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Kawahara T, Nawa N, Murakami K, Tanaka T, Ohseto H, Takahashi I, Narita A, Obara T, Ishikuro M, Orui M, Noda A, Shinoda G, Nagata Y, Nagaie S, Ogishima S, Sugawara J, Kure S, Kinoshita K, Hozawa A, Fuse N, Tamiya G, Bennett WL, Taub MA, Surkan PJ, Kuriyama S, Fujiwara T. Genetic effects on gestational diabetes mellitus and their interactions with environmental factors among Japanese women. J Hum Genet 2025; 70:265-273. [PMID: 40119124 DOI: 10.1038/s10038-025-01330-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2024] [Accepted: 02/28/2025] [Indexed: 03/24/2025]
Abstract
Gestational diabetes mellitus (GDM) is common in Japanese women, posing serious risks to mothers and offspring. This study investigated the influence of maternal genotypes on the risk of GDM and examined how these genotypes modify the effects of psychological and dietary factors during pregnancy. We analyzed data from 20,399 women in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort. Utilizing two customized SNP arrays for the Japanese population (Affymetrix Axiom Japonica Array v2 and NEO), we performed a meta-analysis to combine the datasets. Gene-environment interactions were assessed by modeling interaction terms between genome-wide significant single nucleotide polymorphisms (SNPs) and psychological and dietary factors. Our analysis identified two SNP variants, rs7643571 (p = 9.14 × 10-9) and rs140353742 (p = 1.24 × 10-8), located in an intron of the MDFIC2 gene, as being associated with an increased risk of GDM. Additionally, although there were suggestive patterns for interactions between these SNPs and both dietary factors (e.g., carbohydrate and fruit intake) and psychological distress, none of the interaction terms remained significant after Bonferroni correction (p < 0.05/8). While nominal significance was observed in some models (e.g., psychological distress, p = 0.04), the data did not provide robust evidence of effect modification on GDM risk once adjusted for multiple comparisons. These findings reveal novel genetic associations with GDM in Japanese women and highlight the importance of gene-environment interactions in its etiology. Given that previous genome-wide association studies (GWAS) on GDM have primarily focused on Western populations, our study provides new insights by examining an Asian population using a population-specific array.
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Affiliation(s)
- Tomoki Kawahara
- Department of Public Health, Institute of Science Tokyo, Tokyo, Japan
- Department of Clinical Information Applied Sciences, Institute of Science Tokyo, Tokyo, Japan
| | - Nobutoshi Nawa
- Department of Public Health, Institute of Science Tokyo, Tokyo, Japan.
| | - Keiko Murakami
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Toshihiro Tanaka
- Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan
- Bioresource Research Center, Institute of Science Tokyo, Tokyo, Japan
| | - Hisashi Ohseto
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Ippei Takahashi
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Akira Narita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Taku Obara
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Mami Ishikuro
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Masatsugu Orui
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Aoi Noda
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Genki Shinoda
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Yuki Nagata
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Satoshi Nagaie
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Junichi Sugawara
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Shigeo Kure
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
| | - Wendy L Bennett
- Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21287, USA
| | - Margaret A Taub
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Pamela J Surkan
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Miyagi, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Takeo Fujiwara
- Department of Public Health, Institute of Science Tokyo, Tokyo, Japan
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
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Hatzikotoulas K, Southam L, Stefansdottir L, Boer CG, McDonald ML, Pett JP, Park YC, Tuerlings M, Mulders R, Barysenka A, Arruda AL, Tragante V, Rocco A, Bittner N, Chen S, Horn S, Srinivasasainagendra V, To K, Katsoula G, Kreitmaier P, Tenghe AMM, Gilly A, Arbeeva L, Chen LG, de Pins AM, Dochtermann D, Henkel C, Höijer J, Ito S, Lind PA, Lukusa-Sawalena B, Minn AKK, Mola-Caminal M, Narita A, Nguyen C, Reimann E, Silberstein MD, Skogholt AH, Tiwari HK, Yau MS, Yue M, Zhao W, Zhou JJ, Alexiadis G, Banasik K, Brunak S, Campbell A, Cheung JTS, Dowsett J, Faquih T, Faul JD, Fei L, Fenstad AM, Funayama T, Gabrielsen ME, Gocho C, Gromov K, Hansen T, Hudjashov G, Ingvarsson T, Johnson JS, Jonsson H, Kakehi S, Karjalainen J, Kasbohm E, Lemmelä S, Lin K, Liu X, Loef M, Mangino M, McCartney D, Millwood IY, Richman J, Roberts MB, Ryan KA, Samartzis D, Shivakumar M, Skou ST, Sugimoto S, Suzuki K, Takuwa H, Teder-Laving M, Thomas L, Tomizuka K, Turman C, Weiss S, Wu TT, Zengini E, Zhang Y, Ferreira MAR, Babis G, Baras A, Barker T, Carey DJ, Cheah KSE, Chen Z, Cheung JPY, Daly M, de Mutsert R, Eaton CB, Erikstrup C, Furnes ON, Golightly YM, Gudbjartsson DF, Hailer NP, Hayward C, Hochberg MC, Homuth G, Huckins LM, Hveem K, Ikegawa S, Ishijima M, Isomura M, Jones M, Kang JH, Kardia SLR, Kloppenburg M, Kraft P, Kumahashi N, Kuwata S, Lee MTM, Lee PH, Lerner R, Li L, Lietman SA, Lotta L, Lupton MK, Mägi R, Martin NG, McAlindon TE, Medland SE, Michaëlsson K, Mitchell BD, Mook-Kanamori DO, Morris AP, Nabika T, Nagami F, Nelson AE, Ostrowski SR, Palotie A, Pedersen OB, Rosendaal FR, Sakurai-Yageta M, Schmidt CO, Sham PC, Singh JA, Smelser DT, Smith JA, Song YQ, Sørensen E, Tamiya G, Tamura Y, Terao C, Thorleifsson G, Troelsen A, Tsezou A, Uchio Y, Uitterlinden AG, Ullum H, Valdes AM, van Heel DA, Walters RG, Weir DR, Wilkinson JM, Winsvold BS, Yamamoto M, Zwart JA, Stefansson K, Meulenbelt I, Teichmann SA, van Meurs JBJ, Styrkarsdottir U, Zeggini E. Translational genomics of osteoarthritis in 1,962,069 individuals. Nature 2025:10.1038/s41586-025-08771-z. [PMID: 40205036 DOI: 10.1038/s41586-025-08771-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Accepted: 02/11/2025] [Indexed: 04/11/2025]
Abstract
Osteoarthritis is the third most rapidly growing health condition associated with disability, after dementia and diabetes1. By 2050, the total number of patients with osteoarthritis is estimated to reach 1 billion worldwide2. As no disease-modifying treatments exist for osteoarthritis, a better understanding of disease aetiopathology is urgently needed. Here we perform a genome-wide association study meta-analyses across up to 489,975 cases and 1,472,094 controls, establishing 962 independent associations, 513 of which have not been previously reported. Using single-cell multiomics data, we identify signal enrichment in embryonic skeletal development pathways. We integrate orthogonal lines of evidence, including transcriptome, proteome and epigenome profiles of primary joint tissues, and implicate 700 effector genes. Within these, we find rare coding-variant burden associations with effect sizes that are consistently higher than common frequency variant associations. We highlight eight biological processes in which we find convergent involvement of multiple effector genes, including the circadian clock, glial-cell-related processes and pathways with an established role in osteoarthritis (TGFβ, FGF, WNT, BMP and retinoic acid signalling, and extracellular matrix organization). We find that 10% of the effector genes express a protein that is the target of approved drugs, offering repurposing opportunities, which can accelerate translation.
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Affiliation(s)
- Konstantinos Hatzikotoulas
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | | | - Cindy G Boer
- Department of Internal Medicine, Erasmus MC Medical Center, Rotterdam, The Netherlands
| | - Merry-Lynn McDonald
- Birmingham Veterans Affairs Healthcare System (BVAHS), Birmingham, AL, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
- Department of Epidemiology, School of Public Health, UAB, Birmingham, AL, USA
- Department of Genetics, School of Medicine, UAB, Birmingham, AL, USA
| | - J Patrick Pett
- Wellcome Sanger Institute, Cellular Genetics Programme, Wellcome Genome Campus, Cambridge, UK
| | - Young-Chan Park
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Margo Tuerlings
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Rick Mulders
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Andrei Barysenka
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ana Luiza Arruda
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | | | - Alison Rocco
- Birmingham Veterans Affairs Healthcare System (BVAHS), Birmingham, AL, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Norbert Bittner
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Shibo Chen
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Horn
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Vinodh Srinivasasainagendra
- Birmingham Veterans Affairs Healthcare System (BVAHS), Birmingham, AL, USA
- Department of Biostatistics, School of Public Health, UAB, Birmingham, AL, USA
| | - Ken To
- Wellcome Sanger Institute, Cellular Genetics Programme, Wellcome Genome Campus, Cambridge, UK
- Cambridge Stem Cell Institute, University of Cambridge, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Surgery, University of Cambridge, Cambridge, UK
| | - Georgia Katsoula
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Peter Kreitmaier
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Amabel M M Tenghe
- Centre for Genetic Epidemiology, Institute for Clinical Epidemiology and Applied Biometry, University of Tubingen, Tübingen, Germany
| | | | - Liubov Arbeeva
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lane G Chen
- Department of Psychiatry, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | | | - Daniel Dochtermann
- Birmingham Veterans Affairs Healthcare System (BVAHS), Birmingham, AL, USA
| | - Cecilie Henkel
- Clinical Orthopaedic Research Hvidovre (CORH), Department of Orthopaedic Surgery, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Jonas Höijer
- Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Shuji Ito
- Department of Orthopedic Surgery, Shimane University Faculty of Medicine, Izumo, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Penelope A Lind
- Psychiatric Genetics, Brain and Mental Health Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | | | - Aye Ko Ko Minn
- Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Marina Mola-Caminal
- Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Akira Narita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Chelsea Nguyen
- Birmingham Veterans Affairs Healthcare System (BVAHS), Birmingham, AL, USA
| | - Ene Reimann
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Micah D Silberstein
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anne-Heidi Skogholt
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, UAB, Birmingham, AL, USA
| | - Michelle S Yau
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, Boston, MA, USA
| | - Ming Yue
- School of Biomedical Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jin J Zhou
- Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - George Alexiadis
- 1st Department of Orthopaedics, KAT General Hospital, Athens, Greece
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Joseph Dowsett
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Tariq Faquih
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Lijiang Fei
- Wellcome Sanger Institute, Cellular Genetics Programme, Wellcome Genome Campus, Cambridge, UK
- Cambridge Stem Cell Institute, University of Cambridge, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
| | - Anne Marie Fenstad
- The Norwegian Arthroplasty Register, Department of Orthopaedic Surgery, Haukeland University Hospital, Bergen, Norway
| | | | - Maiken E Gabrielsen
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Chinatsu Gocho
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Kirill Gromov
- Clinical Orthopaedic Research Hvidovre (CORH), Department of Orthopaedic Surgery, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Thomas Hansen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet - Glostrup, Glostrup, Denmark
| | - Georgi Hudjashov
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Thorvaldur Ingvarsson
- Department of Orthopedic Surgery, Akureyri Hospital, Akureyri, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jessica S Johnson
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Helgi Jonsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Medicine, Landspitali The National University Hospital of Iceland, Reykjavik, Iceland
| | - Saori Kakehi
- Department of Metabolism & Endocrinology, Sportology Center, Juntendo University Graduate School of Medicine, Juntendo University, Tokyo, Japan
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Elisa Kasbohm
- Institute for Community Medicine, SHIP-KEF, University Medicine Greifswald, Greifswald, Germany
| | - Susanna Lemmelä
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Marieke Loef
- Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Daniel McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, UK
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Joshua Richman
- Birmingham Veterans Affairs Healthcare System (BVAHS), Birmingham, AL, USA
- Department of Surgery, School of Medicine, UAB, Birmingham, AL, USA
| | - Mary B Roberts
- Center for Primary Care & Prevention, Brown University, Pawtucket, RI, USA
| | - Kathleen A Ryan
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Dino Samartzis
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Hong Kong SAR, China
- Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | - Manu Shivakumar
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Søren T Skou
- Research Unit for Musculoskeletal Function and Physiotherapy, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
- The Research and Implementation Unit PROgrez, Department of Physiotherapy and Occupational Therapy, Næstved-Slagelse-Ringsted Hospitals, Slagelse, Denmark
| | - Sachiyo Sugimoto
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Ken Suzuki
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Hiroshi Takuwa
- Department of Orthopedic Surgery, Shimane University Faculty of Medicine, Izumo, Japan
| | - Maris Teder-Laving
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Laurent Thomas
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Stefan Weiss
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Tian T Wu
- Department of Psychiatry, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Eleni Zengini
- 4th Psychiatric Department, Dromokaiteio Psychiatric Hospital, Haidari, Athens, Greece
| | - Yanfei Zhang
- Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | | | - George Babis
- 2nd Department of Orthopaedics, National and Kapodistrian University of Athens, Medical School, 'Konstantopouleio' Hospital, Athens, Greece
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Tyler Barker
- Sports Medicine Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA
- Intermountain Healthcare, Precision Genomics, Salt Lake City, UT, USA
- Department of Orthopaedics, University of Utah, Salt Lake City, UT, USA
| | - David J Carey
- Department of Genomic Health, Geisinger, Danville, PA, USA
| | - Kathryn S E Cheah
- School of Biomedical Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jason Pui-Yin Cheung
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Hong Kong SAR, China
| | - Mark Daly
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Charles B Eaton
- Center for Primary Care & Prevention, Brown University, Pawtucket, RI, USA
- Department of Family Medicine, Warren Alpert Medical School of Brown University, Providence, RI, USA
- Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Ove Nord Furnes
- The Norwegian Arthroplasty Register, Department of Orthopaedic Surgery, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Yvonne M Golightly
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- University of Nebraska Medical Center, Omaha, NE, USA
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Nils P Hailer
- Orthopedics, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Caroline Hayward
- MRC Human Genetics Unit IGC, University of Edinburgh, Edinburgh, UK
| | - Marc C Hochberg
- Department of Epidemiology and Public Health, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Georg Homuth
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Laura M Huckins
- Department of Psychiatry, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Kristian Hveem
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences, Tokyo, Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Muneaki Ishijima
- Department of Medicine for Orthopaedics and Motor Organ, Sportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Minoru Isomura
- Faculty of Human Sciences, Shimane University, Matsue, Japan
| | | | - Jae H Kang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Margreet Kloppenburg
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Nobuyuki Kumahashi
- Department of Orthopedic Surgery, Matsue Red Cross Hospital, Matsue, Japan
| | - Suguru Kuwata
- Department of Orthopedic Surgery, Shimane University Faculty of Medicine, Izumo, Japan
| | | | - Phil H Lee
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, USA
| | - Robin Lerner
- Blizard Institute, Queen Mary University of London, London, UK
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | | | - Luca Lotta
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Michelle K Lupton
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- Neurogenetics and Dementia, Brain and Mental Health Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Nicholas G Martin
- Genetic Epidemiology, Brain and Mental Health Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Timothy E McAlindon
- Division of Rheumatology, Allergy, & Immunology, Tufts Medical Center, Boston, MA, USA
| | - Sarah E Medland
- Psychiatric Genetics, Brain and Mental Health Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Karl Michaëlsson
- Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Andrew P Morris
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
| | - Toru Nabika
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan
| | - Fuji Nagami
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Amanda E Nelson
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sisse Rye Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Ole Birger Pedersen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital - Køge, Køge, Denmark
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Carsten Oliver Schmidt
- Institute for Community Medicine, SHIP-KEF, University Medicine Greifswald, Greifswald, Germany
| | - Pak Chung Sham
- Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Jasvinder A Singh
- Birmingham Veterans Affairs Healthcare System (BVAHS), Birmingham, AL, USA
- Department of Epidemiology, School of Public Health, UAB, Birmingham, AL, USA
- Division of Rheumatology and Clinical Immunology, Department of Medicine at the School of Medicine, UAB, Birmingham, AL, USA
- Medicine Service, Michale E. DeBakey VA Medical Center, Houston, TX, USA
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | | | - Jennifer A Smith
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - You-Qiang Song
- School of Biomedical Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Gen Tamiya
- Tohoku University Graduate School of Medicine, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Statistical Genetics Team, Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan
| | - Yoshifumi Tamura
- Department of Metabolism & Endocrinology, Sportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | | | - Anders Troelsen
- Clinical Academic Group: Research OsteoArthritis Denmark (CAG ROAD), Department of Orthopaedic Surgery, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Aspasia Tsezou
- Laboratory of Cytogenetics and Molecular Genetics, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Yuji Uchio
- Department of Orthopedic Surgery, Shimane University Faculty of Medicine, Izumo, Japan
| | - A G Uitterlinden
- Department of Internal Medicine, Erasmus MC Medical Center, Rotterdam, The Netherlands
| | | | - Ana M Valdes
- Faculty of Medicine & Health Sciences, School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - J Mark Wilkinson
- School of Medicine and Population Health, The University of Sheffield, Sheffield, UK
| | - Bendik S Winsvold
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Masayuki Yamamoto
- Tohoku University Graduate School of Medicine, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - John-Anker Zwart
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital and University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Kari Stefansson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Ingrid Meulenbelt
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sarah A Teichmann
- Department of Medicine & Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus MC Medical Center, Rotterdam, The Netherlands
| | | | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- TUM School of Medicine and Health, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany.
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3
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Lee DSM, Cardone KM, Zhang DY, Tsao NL, Abramowitz S, Sharma P, DePaolo JS, Conery M, Aragam KG, Biddinger K, Dilitikas O, Hoffman-Andrews L, Judy RL, Khan A, Kullo IJ, Puckelwartz MJ, Reza N, Satterfield BA, Singhal P, Arany Z, Cappola TP, Carruth ED, Day SM, Do R, Haggerty CM, Joseph J, McNally EM, Nadkarni G, Owens AT, Rader DJ, Ritchie MD, Sun YV, Voight BF, Levin MG, Damrauer SM. Common-variant and rare-variant genetic architecture of heart failure across the allele-frequency spectrum. Nat Genet 2025:10.1038/s41588-025-02140-2. [PMID: 40195560 DOI: 10.1038/s41588-025-02140-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 02/21/2025] [Indexed: 04/09/2025]
Abstract
Heart failure is a complex trait, influenced by environmental and genetic factors, affecting over 30 million individuals worldwide. Here we report common-variant and rare-variant association studies of all-cause heart failure and examine how different classes of genetic variation impact its heritability. We identify 176 common-variant risk loci at genome-wide significance in 2,358,556 individuals and cluster these signals into five broad modules based on pleiotropic associations with anthropomorphic traits/obesity, blood pressure/renal function, atherosclerosis/lipids, immune activity and arrhythmias. In parallel, we uncover exome-wide significant associations for heart failure and rare predicted loss-of-function variants in TTN, MYBPC3, FLNC and BAG3 using exome sequencing of 376,334 individuals. We find that total burden heritability of rare coding variants is highly concentrated in a small set of Mendelian cardiomyopathy genes, while common-variant heritability is diffusely spread throughout the genome. Finally, we show that common-variant background modifies heart failure risk among carriers of rare pathogenic truncating variants in TTN. Together, these findings discern genetic links between dysregulated metabolism and heart failure and highlight a polygenic component to heart failure not captured by current clinical genetic testing.
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Affiliation(s)
- David S M Lee
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Kathleen M Cardone
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - David Y Zhang
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Noah L Tsao
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sarah Abramowitz
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Pranav Sharma
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John S DePaolo
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mitchell Conery
- Genomics and Computational Biology Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Krishna G Aragam
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kiran Biddinger
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ozan Dilitikas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Lily Hoffman-Andrews
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Renae L Judy
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York City, NY, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Megan J Puckelwartz
- Department of Pharmacology, Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Nosheen Reza
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Pankhuri Singhal
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Zoltan Arany
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Thomas P Cappola
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Eric D Carruth
- Department of Genomic Health, Geisinger, Danville, PA, USA
| | - Sharlene M Day
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Mount Sinai Icahn School of Medicine, New York City, NY, USA
- BioMe Phenomics Center, Mount Sinai Icahn School of Medicine, New York City, NY, USA
- Department of Genetics and Genomic Sciences, Mount Sinai Icahn School of Medicine, New York City, NY, USA
| | | | - Jacob Joseph
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA
| | - Elizabeth M McNally
- Center for Genetic Medicine, Bluhm Cardiovascular Institute, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Girish Nadkarni
- Division of Nephrology, Department of Medicine, Mount Sinai Icahn School of Medicine, New York City, NY, USA
| | - Anjali T Owens
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel J Rader
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Translational Medicine and Human Genetics, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yan V Sun
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Benjamin F Voight
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Michael G Levin
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
| | - Scott M Damrauer
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Cardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
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4
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Ilboudo Y, Brosseau N, Lo KS, Belhaj H, Moutereau S, Marshall K, Reid M, Kutlar A, Ashley-Koch AE, Telen MJ, Joly P, Galactéros F, Bartolucci P, Lettre G. A replication study of novel fetal hemoglobin-associated genetic variants in sickle cell disease-only cohorts. Hum Mol Genet 2025; 34:699-710. [PMID: 39886999 PMCID: PMC11973897 DOI: 10.1093/hmg/ddaf015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2024] [Revised: 12/18/2024] [Accepted: 01/23/2024] [Indexed: 02/01/2025] Open
Abstract
Sickle cell disease (SCD) is the most common monogenic disease in the world and is caused by mutations in the β-globin gene (HBB). Notably, SCD is characterized by extreme clinical heterogeneity. Inter-individual variation in fetal hemoglobin (HbF) levels strongly contributes to this patient-to-patient variability, with high HbF levels associated with decreased morbidity and mortality. Genetic association studies have identified and replicated HbF levels-associated variants at three loci: BCL11A, HBS1L-MYB, and HBB. In SCD patients, genetic variation at these three loci accounts for ~ 50% of HbF heritability. Genome-wide association studies (GWAS) in non-anemic and SCD patients of multiple ancestries have identified 20 new HbF-associated variants. However, these genetic associations have yet to be replicated in independent SCD cohorts. Here, we validated the association between HbF levels and variants at five of these new loci (ASB3, BACH2, PFAS, ZBTB7A, and KLF1) in up to 3740 SCD patients. By combining CRISPR inhibition and single-cell transcriptomics, we also showed that sequences near non-coding genetic variants at BACH2 (rs4707609) and KLF1 (rs2242514, rs10404876) can control the production of the β-globin genes in erythroid HUDEP-2 cells. Finally, we analyzed whole-exome sequence data from 1354 SCD patients but could not identify rare genetic variants of large effect on HbF levels. Together, our results confirm five new HbF-associated loci that can be functionally studied to develop new strategies to induce HbF expression in SCD patients.
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Affiliation(s)
- Yann Ilboudo
- Montreal Heart Institute, 5000 Bélanger Street, Montréal, Québec, H1T 1C8, Canada
- Department of Medicine, Université de Montréal, 2900 Boul. Édouard-Montpetit, Montréal, Québec, H3T 1J4, Canada
| | - Nicolas Brosseau
- Montreal Heart Institute, 5000 Bélanger Street, Montréal, Québec, H1T 1C8, Canada
- Department of Medicine, Université de Montréal, 2900 Boul. Édouard-Montpetit, Montréal, Québec, H3T 1J4, Canada
| | - Ken Sin Lo
- Montreal Heart Institute, 5000 Bélanger Street, Montréal, Québec, H1T 1C8, Canada
- Department of Medicine, Université de Montréal, 2900 Boul. Édouard-Montpetit, Montréal, Québec, H3T 1J4, Canada
| | - Hicham Belhaj
- Montreal Heart Institute, 5000 Bélanger Street, Montréal, Québec, H1T 1C8, Canada
- Department of Medicine, Université de Montréal, 2900 Boul. Édouard-Montpetit, Montréal, Québec, H3T 1J4, Canada
| | - Stéphane Moutereau
- Red Blood Cell Laboratory, Department of Biochemistry-Pharmacology, Hôpital Universitaire Henri Mondor, Assistance Publique-Hôpitaux de Paris (AP-HP), Université Paris Est, IMRB - U955 - Équipe no 2, Créteil, France
| | - Kwesi Marshall
- Tropical Metabolism Research Unit (TMRU), Caribbean Institute for Health Research (CAIHR), University of the West Indies, Mona, Kingston 7, Jamaica
| | - Marvin Reid
- Graduate Studies and Research, University of the West Indies, Mona, Kingston 7, Jamaica
| | - Abdullah Kutlar
- Center for Blood Disorders, Augusta University, Augusta, Georgia 30912, USA
| | - Allison E Ashley-Koch
- Department of Medicine, Duke University Medical Center, Durham, NC 27707, USA
- Duke Molecular Physiology Institute, Duke University Medical Center, 300 North Duke Street, Durham, NC 27701, USA
| | - Marilyn J Telen
- Duke Comprehensive Sickle Cell Center and Division of Hematology, Department of Medicine, Duke University, Durham, NC 27710, USA
| | - Philippe Joly
- Unité Fonctionnelle 34445 ‘Biochimie des Pathologies Érythrocytaires’, Laboratoire de Biochimie et Biologie Moléculaire Grand-Est, Groupement Hospitalier Est, Hospices Civils de Lyon, Bron, France
- Laboratoire Inter-Universitaire de Biologie de la Motricité (LIBM) EA7424, Equipe ‘Biologie Vasculaire et du Globule Rouge’, Université Claude Bernard Lyon 1, Comité d’Universités et d’Établissements (COMUE), Lyon, France
| | - Frédéric Galactéros
- Red Cell Genetic Disease Unit, Hôpital Henri-Mondor, Assistance Publique-Hôpitaux de Paris (AP-HP), Université Paris Est, IMRB - U955 - Équipe no 2, Créteil, France
| | - Pablo Bartolucci
- Red Cell Genetic Disease Unit, Hôpital Henri-Mondor, Assistance Publique-Hôpitaux de Paris (AP-HP), Université Paris Est, IMRB - U955 - Équipe no 2, Créteil, France
| | - Guillaume Lettre
- Montreal Heart Institute, 5000 Bélanger Street, Montréal, Québec, H1T 1C8, Canada
- Department of Medicine, Université de Montréal, 2900 Boul. Édouard-Montpetit, Montréal, Québec, H3T 1J4, Canada
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5
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Elgaeva EE, Zorkoltseva IV, Nostaeva AV, Verzun DA, Tiys ES, Timoshchuk AN, Kirichenko AV, Svishcheva GR, Freidin MB, Williams FMK, Suri P, Aulchenko YS, Axenovich TI, Tsepilov YA. Decomposing the genetic background of chronic back pain. Hum Mol Genet 2025; 34:711-725. [PMID: 39895344 DOI: 10.1093/hmg/ddae195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 10/09/2024] [Accepted: 12/16/2024] [Indexed: 02/04/2025] Open
Abstract
Chronic back pain (CBP) is a disabling condition with a lifetime prevalence of 40% and a substantial socioeconomic burden. Because of the high heterogeneity of CBP, subphenotyping may help to improve prediction and support personalized treatment of CBP. To investigate CBP subphenotypes, we decomposed its genetic background into a shared one common to other chronic pain conditions (back, neck, hip, knee, stomach, and head pain) and unshared genetic background specific to CBP. We identified and replicated 18 genes with shared impact across different chronic pain conditions and two genes that were specific for CBP. Among people with CBP, we demonstrated that polygenic risk scores accounting for the shared and unshared genetic backgrounds of CBP may underpin different CBP subphenotypes. These subphenotypes are characterized by varying genetic predisposition to diverse medical conditions and interventions such as diabetes mellitus, myocardial infarction, diagnostic endoscopic procedures, and surgery involving muscles, bones, and joints.
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Affiliation(s)
- Elizaveta E Elgaeva
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
- Novosibirsk State University, 1, Pirogova str., 630090, Novosibirsk, Russia
| | - Irina V Zorkoltseva
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
| | - Arina V Nostaeva
- Novosibirsk State University, 1, Pirogova str., 630090, Novosibirsk, Russia
| | - Dmitrii A Verzun
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
- Novosibirsk State University, 1, Pirogova str., 630090, Novosibirsk, Russia
| | - Evgeny S Tiys
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
| | - Anna N Timoshchuk
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, 27, building 1, Lomonosovsky ave., 119991, Moscow, Russia
- Moscow Institute of Physics and Technology, 9, Institutsky lane, 141700, Dolgoprudny, Russia
| | - Anatoliy V Kirichenko
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
| | - Gulnara R Svishcheva
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
- Vavilov Institute of General Genetics, RAS, 3, Gubkin str., 119991, Moscow, Russia
| | - Maxim B Freidin
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, Westminster Bridge Rd., SE1 7EH, London, UK
| | - Frances M K Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, Westminster Bridge Rd., SE1 7EH, London, UK
| | - Pradeep Suri
- Department of Rehabilitation Medicine, University of Washington, 325, Ninth ave., WA 98104, Seattle, USA
- VA Puget Sound Health Care System, 1660, South Columbian Way, WA 98108, Seattle, USA
| | - Yurii S Aulchenko
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
- PolyOmica, 61, Het Vlaggeschip, 5237 PA, 's-Hertogenbosch, The Netherlands
| | - Tatiana I Axenovich
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
| | - Yakov A Tsepilov
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
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6
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Nagarajan P, Winkler TW, Bentley AR, Miller CL, Kraja AT, Schwander K, Lee S, Wang W, Brown MR, Morrison JL, Giri A, O'Connell JR, Bartz TM, de Las Fuentes L, Gudmundsdottir V, Guo X, Harris SE, Huang Z, Kals M, Kho M, Lefevre C, Luan J, Lyytikäinen LP, Mangino M, Milaneschi Y, Palmer ND, Rao V, Rauramaa R, Shen B, Stadler S, Sun Q, Tang J, Thériault S, van der Graaf A, van der Most PJ, Wang Y, Weiss S, Westerman KE, Yang Q, Yasuharu T, Zhao W, Zhu W, Altschul D, Ansari MAY, Anugu P, Argoty-Pantoja AD, Arzt M, Aschard H, Attia JR, Bazzanno L, Breyer MA, Brody JA, Cade BE, Chen HH, Chen YDI, Chen Z, de Vries PS, Dimitrov LM, Do A, Du J, Dupont CT, Edwards TL, Evans MK, Faquih T, Felix SB, Fisher-Hoch SP, Floyd JS, Graff M, Gu C, Gu D, Hairston KG, Hanley AJ, Heid IM, Heikkinen S, Highland HM, Hood MM, Kähönen M, Karvonen-Gutierrez CA, Kawaguchi T, Kazuya S, Kelly TN, Komulainen P, Levy D, Lin HJ, Liu PY, Marques-Vidal P, McCormick JB, Mei H, Meigs JB, Menni C, Nam K, Nolte IM, Pacheco NL, Petty LE, Polikowsky HG, Province MA, Psaty BM, Raffield LM, Raitakari OT, Rich SS, Riha RL, Risch L, Risch M, Ruiz-Narvaez EA, Scott RJ, Sitlani CM, Smith JA, Sofer T, Teder-Laving M, Völker U, Vollenweider P, Wang G, Willems van Dijk K, Wilson OD, Xia R, Yao J, Young KL, Zhang R, Zhu X, Below JE, Böger CA, Conen D, Cox SR, Dörr M, Feitosa MF, Fox ER, Franceschini N, Gharib SA, Gudnason V, Harlow SD, He J, Holliday EG, Kutalik Z, Lakka TA, Lawlor DA, Lee S, Lehtimäki T, Li C, Liu CT, Mägi R, Matsuda F, Morrison AC, Penninx BW, Peyser PA, Rotter JI, Snieder H, Spector TD, Wagenknecht LE, Wareham NJ, Zonderman AB, North KE, Fornage M, Hung AM, Manning AK, Gauderman J, Chen H, Munroe PB, Rao DC, van Heemst D, Redline S, Noordam R, Wang H. A large-scale genome-wide study of gene-sleep duration interactions for blood pressure in 811,405 individuals from diverse populations. Mol Psychiatry 2025:10.1038/s41380-025-02954-w. [PMID: 40181193 DOI: 10.1038/s41380-025-02954-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 03/11/2025] [Indexed: 04/05/2025]
Abstract
Although both short and long sleep duration are associated with elevated hypertension risk, our understanding of their interplay with biological pathways governing blood pressure remains limited. To address this, we carried out genome-wide cross-population gene-by-short-sleep and long-sleep duration interaction analyses for three blood pressure traits (systolic, diastolic, and pulse pressure) in 811,405 individuals from diverse population groups. We discovered 22 novel gene-sleep duration interaction loci for blood pressure, mapped to 23 genes. Investigating these genes' functional implications shed light on neurological, thyroidal, bone metabolism, and hematopoietic pathways that necessitate future investigation for blood pressure management that caters to sleep health lifestyle. Non-overlap between short sleep (12) and long sleep (10) interactions underscores the plausible nature of distinct influences of both sleep duration extremes in cardiovascular health. Several of our loci are specific towards a particular population background or sex, emphasizing the importance of addressing heterogeneity entangled in gene-environment interactions, when considering precision medicine design approaches for blood pressure management.
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Affiliation(s)
- Pavithra Nagarajan
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Clint L Miller
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Aldi T Kraja
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Karen Schwander
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Songmi Lee
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX, USA
| | - Wenyi Wang
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - John L Morrison
- Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Ayush Giri
- Division of Quantitative and Clinical Sciences, Department of Obstetrics & Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626), Department of Veterans Affairs, Nashville, TN, USA
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Lisa de Las Fuentes
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, Department of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Sarah E Harris
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Zhijie Huang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Mart Kals
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Minjung Kho
- Graduate School of Data Science, Seoul National University, Seoul, South Korea
| | - Christophe Lefevre
- Department of Data Sciences, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere, Finland
| | - Massimo Mangino
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
- National Heart & Lung Institute, Cardiovascular Genomics and Precision Medicine, Imperial College London, London, UK
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam UMC/Vrije universiteit, Amsterdam, Netherlands
- GGZ inGeest, Amsterdam, Netherlands
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Varun Rao
- Division of Nephrology, Department of Medicine, University of Illinois Chicago, Chicago, IL, USA
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Botong Shen
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Stefan Stadler
- Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jingxian Tang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Sébastien Thériault
- Department of Molecular Biology, Medical Biochemistry and Pathology, Université Laval, Quebec City, QC, Canada
| | - Adriaan van der Graaf
- Statistical Genetics Group, Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Yujie Wang
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Stefan Weiss
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Kenneth E Westerman
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA
| | - Qian Yang
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tabara Yasuharu
- Graduate School of Public Health, Shizuoka Graduate University of Public Health, Shizuoka, Japan
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Wanying Zhu
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Drew Altschul
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
- School of Psychology, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Md Abu Yusuf Ansari
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Pramod Anugu
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Anna D Argoty-Pantoja
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Michael Arzt
- Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
| | - Hugues Aschard
- Department of Computational Biology, F-75015 Paris, France Institut Pasteur, Université Paris Cité, Paris, France
- Department of Epidemiology, Harvard TH School of Public Health, Boston, MA, USA
| | - John R Attia
- School of Medicine and Public Health, College of Health Medicine and Wellbeing, University of Newcastle, New Lambton Heights, NSW, Australia
| | - Lydia Bazzanno
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Max A Breyer
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Hung-Hsin Chen
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Zekai Chen
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Latchezar M Dimitrov
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Anh Do
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Jiawen Du
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Charles T Dupont
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Todd L Edwards
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626), Department of Veterans Affairs, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Tariq Faquih
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Stephan B Felix
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Susan P Fisher-Hoch
- School of Public Health, The University of Texas Health Science Center at Houston (UTHealth), Brownsville, TX, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Mariaelisa Graff
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Charles Gu
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Dongfeng Gu
- Shenzhen Key Laboratory of Cardiovascular Health and Precision Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Kristen G Hairston
- Department of Endocrinology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Anthony J Hanley
- Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Sami Heikkinen
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Heather M Highland
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michelle M Hood
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere, Finland
| | | | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Setoh Kazuya
- Graduate School of Public Health, Shizuoka Graduate University of Public Health, Shizuoka, Japan
| | - Tanika N Kelly
- Division of Nephrology, Department of Medicine, University of Illinois Chicago, Chicago, IL, USA
| | | | - Daniel Levy
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences, Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Peter Y Liu
- The Institute for Translational Genomics and Population Sciences, Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Joseph B McCormick
- School of Public Health, The University of Texas Health Science Center at Houston (UTHealth), Brownsville, TX, USA
| | - Hao Mei
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - James B Meigs
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Cristina Menni
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Kisung Nam
- Graduate School of Data Science, Seoul National University, Seoul, South Korea
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Natasha L Pacheco
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Lauren E Petty
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Hannah G Polikowsky
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, and Department of Clinical Physiology and Nuclear Medicine, University of Turku, and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Stephen S Rich
- Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA
| | - Renata L Riha
- Department of Sleep Medicine, The University of Edinburgh, Edinburgh, UK
| | - Lorenz Risch
- Faculty of Medical Sciences, Institute for Laboratory Medicine, Private University in the Principality of Liechtenstein, Vaduz, Liechtenstein
- Center of Laboratory Medicine, Institute of Clinical Chemistry, University of Bern and Inselspital, Bern, Switzerland
| | - Martin Risch
- Central Laboratory, Cantonal Hospital Graubünden, Chur, Switzerland
- Medical Laboratory, Dr. Risch Anstalt, Vaduz, Liechtenstein
| | | | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, College of Health Medicine and Wellbeing, University of Newcastle, New Lambton Heights, NSW, Australia
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer A Smith
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- CardioVascular Institute (CVI), Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Maris Teder-Laving
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Uwe Völker
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Guanchao Wang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden, Netherlands
| | - Otis D Wilson
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626), Department of Veterans Affairs, Nashville, TN, USA
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Rui Xia
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kristin L Young
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ruiyuan Zhang
- Department of Epidemiology, O'Donnell School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Jennifer E Below
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Carsten A Böger
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology and Rheumatology, Kliniken Südostbayern, Traunstein, Germany
- KfH Kidney Centre Traunstein, Traunstein, Germany
| | - David Conen
- Population Health Research Institute, Medicine, McMaster University, Hamilton, ON, Canada
| | - Simon R Cox
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Ervin R Fox
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Nora Franceschini
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sina A Gharib
- Pulmonary, Critical Care and Sleep Medicine, Medicine, University of Washington, Seattle, WA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, Department of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Sioban D Harlow
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jiang He
- Department of Epidemiology, O'Donnell School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Elizabeth G Holliday
- School of Medicine and Public Health, College of Health Medicine and Wellbeing, University of Newcastle, New Lambton Heights, NSW, Australia
| | - Zoltan Kutalik
- Statistical Genetics Group, Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Timo A Lakka
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Seunggeun Lee
- Graduate School of Data Science, Seoul National University, Seoul, South Korea
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere, Finland
| | - Changwei Li
- Department of Epidemiology, O'Donnell School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Brenda Wjh Penninx
- Department of Psychiatry, Amsterdam UMC/Vrije universiteit, Amsterdam, Netherlands
- GGZ inGeest, Amsterdam, Netherlands
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Tim D Spector
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Lynne E Wagenknecht
- Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Kari E North
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX, USA
- Human Genetics Center, Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Adriana M Hung
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626), Department of Veterans Affairs, Nashville, TN, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Alisa K Manning
- Clinical and Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Metabolism Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James Gauderman
- Division of Biostatistics, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Patricia B Munroe
- Clinical Pharmacology and Precision Medicine, Queen Mary University of London, London, UK
| | - Dabeeru C Rao
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, Netherlands
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, Netherlands
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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7
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Nair JM, Chauhan G, Prasad G, Chakraborty S, Bandesh K, Giri AK, Marwaha RK, Basu A, Tandon N, Bharadwaj D. Novel genetic associations with childhood adipocytokines in Indian adolescents. Cytokine 2025; 190:156935. [PMID: 40187068 DOI: 10.1016/j.cyto.2025.156935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2025] [Revised: 03/05/2025] [Accepted: 03/28/2025] [Indexed: 04/07/2025]
Abstract
Adipocytokines, including leptin, adiponectin, and resistin, are key mediators linking adiposity, insulin resistance, and inflammation. We present the first genome-wide association study (GWAS; N = 5258) and exome-wide association study (ExWAS; N = 4578) on leptin, adiponectin, and resistin in South Asian population. We identified novel associations in genes ZNF467, and LEPREL2 for leptin; ZNF467, LEPREL2, CRLF3, ZNF732, SOX30, XIRP1, ATP8B3, SPATA2L, TMCO4, TLN2, ABCA12, and SHB for adiponectin; and D2HGDH for resistin. Additionally, we confirmed known associations of FTO, MC4R, and HOXB3 with leptin and ADIPOQ with adiponectin. Notably, ADIPOQ variants were consistently significant across GWAS, ExWAS, and gene-based analyses, reinforcing their central role in regulating adiponectin levels. Most of these novel associations identified were population-specific, highlighting the importance of studying diverse populations to uncover unique genetic signals. After adjusting for BMI, the associations with adiponectin and resistin remained significant, whereas most associations for leptin weakened in both effect size and significance. Functional annotation revealed that the identified variants were enriched for expression in adipose tissue, the brain (cerebellar hemisphere and cerebral cortex), and the pituitary gland. These variants act as eQTLs and splice-QTLs in adipose, brain, and pancreas, suggesting cross-tissue regulatory mechanisms. ExWAS further implicated rare variant burden in genes such as LONP1, ZNF335, and TTC16 for adiponectin and resistin. These findings enhance our understanding of adipocytokine biology, emphasises the need for population-specific genetic research, and lays foundation for future functional studies.
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Affiliation(s)
- Janaki M Nair
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India
| | - Ganesh Chauhan
- CSIR-Institute of Genomics and Integrative Biology, Delhi 110025, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Gauri Prasad
- CSIR-Institute of Genomics and Integrative Biology, Delhi 110025, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Shraddha Chakraborty
- CSIR-Institute of Genomics and Integrative Biology, Delhi 110025, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Khushdeep Bandesh
- CSIR-Institute of Genomics and Integrative Biology, Delhi 110025, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Anil K Giri
- CSIR-Institute of Genomics and Integrative Biology, Delhi 110025, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Raman K Marwaha
- Scientific Advisor and Consultant Endocrinologist, International Life Sciences Institute (ILSI), India
| | - Analabha Basu
- National Institute of Biomedical Genomics, Kalyani 741251, West Bengal, India
| | - Nikhil Tandon
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi 110029, India.
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India.
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8
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Xie Y, Fu J, Liu L, Wang X, Liu F, Liang M, Liu H, Qin W, Yu C. Genetic and neural mechanisms shared by schizophrenia and depression. Mol Psychiatry 2025:10.1038/s41380-025-02975-5. [PMID: 40175520 DOI: 10.1038/s41380-025-02975-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2024] [Revised: 03/04/2025] [Accepted: 03/21/2025] [Indexed: 04/04/2025]
Abstract
Schizophrenia (SCZ) and depression are two prevalent mental disorders characterized by comorbidity and overlapping symptoms, yet the underlying genetic and neural mechanisms remain largely elusive. Here, we investigated the genetic variants and neuroimaging changes shared by SCZ and depression in Europeans and then extended our investigation to cross-ancestry (Europeans and East Asians) populations. Using conditional and conjunctional analyses, we found 213 genetic variants shared by SCZ and depression in Europeans, of which 82.6% were replicated in the cross-ancestry population. The shared risk variants exhibited a higher degree of deleteriousness than random and were enriched for synapse-related functions, among which fewer than 3% of shared variants showed horizontal pleiotropy between the two disorders. Mendelian randomization analyses indicated reciprocal causal effects between SCZ and depression. Using multiple trait genetic colocalization analyses, we pinpointed 13 volume phenotypes shared by SCZ and depression. Particularly noteworthy were the shared volume reductions in the left insula and planum polare, which were validated through large-scale meta-analyses of previous studies and independent neuroimaging datasets of first-episode drug-naïve patients. These findings suggest that the shared genetic risk variants, synapse dysfunction, and brain structural changes may underlie the comorbidity and symptom overlap between SCZ and depression.
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Affiliation(s)
- Yingying Xie
- Department of Radiology & Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology & State Key Laboratory of Experimental Hematology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jilian Fu
- Department of Radiology & Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology & State Key Laboratory of Experimental Hematology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Liping Liu
- The First Psychiatric Hospital of Harbin, Harbin, 150056, China
| | - Xijin Wang
- The First Psychiatric Hospital of Harbin, Harbin, 150056, China
| | - Feng Liu
- Department of Radiology & Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology & State Key Laboratory of Experimental Hematology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Meng Liang
- School of Medical Imaging, Tianjin Medical University, Tianjin, 300203, China
| | - Hesheng Liu
- Division of Brain Sciences, Changping Laboratory, Beijing, 102206, China.
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China.
| | - Wen Qin
- Department of Radiology & Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology & State Key Laboratory of Experimental Hematology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Chunshui Yu
- Department of Radiology & Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology & State Key Laboratory of Experimental Hematology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- School of Medical Imaging, Tianjin Medical University, Tianjin, 300203, China.
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9
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Hernández CF, Villaman C, Leu C, Lal D, Mata I, Klein AD, Pérez-Palma E. Polygenic score analysis identifies distinct genetic risk profiles in Alzheimer's disease comorbidities. Sci Rep 2025; 15:11407. [PMID: 40181078 PMCID: PMC11968852 DOI: 10.1038/s41598-025-95755-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Accepted: 03/24/2025] [Indexed: 04/05/2025] Open
Abstract
Alzheimer's disease (AD) is usually accompanied by comorbidities such as type 2 diabetes (T2D), epilepsy, major depressive disorder (MDD), and migraine headaches (MH) that can significantly affect patient management and progression. As AD, these comorbidities have their own cumulative common genetic risk component that can be explored in a single individual through polygenic scores. Utilizing data from the UK Biobank, we investigated the correlation between polygenic scores (PGS) for these comorbidities and their actual presentation in AD patients. We show that individuals with higher PGS values showed an elevated risk of developing T2D (OR 2.1, p = 1.07 × 10-11) and epilepsy (OR 1.5, p = 0.0176). High T2D-PGS is also associated with an earlier AD onset in individuals at high genetic risk for AD (AD-PGS). In contrast, no significant genetic associations were found for MDD and MH. Our findings show distinct common genetic risk factors for T2D and epilepsy carried by AD patients that are associated with increased prevalence and earlier disease onset. These results highlight the contribution of common genetic variation to the broader clinical landscape of AD and will contribute to future tailored patient management strategies for individuals at high genetic risk.
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Affiliation(s)
- Carlos F Hernández
- Universidad del Desarrollo, Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, 7610658, Santiago, Chile
| | - Camilo Villaman
- Universidad del Desarrollo, Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, 7610658, Santiago, Chile
| | - Costin Leu
- Center for Neurogenetics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Dennis Lal
- Center for Neurogenetics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Cologne Center for Genomics (CCG), Medical Faculty of the University of Cologne, 50923, Köln, Germany
| | - Ignacio Mata
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Andrés D Klein
- Universidad del Desarrollo, Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, 7610658, Santiago, Chile
| | - Eduardo Pérez-Palma
- Universidad del Desarrollo, Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, 7610658, Santiago, Chile.
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10
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Zhong Y, So MT, Ma Z, Zhang D, Wang Y, Xiong Z, Fadista J, Song YQ, Cheah KSE, Alves MM, Borrego S, Ceccherini I, Pakarinen MP, Feenstra B, Lui VCH, Garcia-Barcelo MM, Sham PC, Tam PKH, Tang CSM. Multi-ancestry genome-wide association meta-analysis identifies novel associations and informs genetic risk prediction for Hirschsprung disease. EBioMedicine 2025; 115:105680. [PMID: 40184909 DOI: 10.1016/j.ebiom.2025.105680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 03/13/2025] [Accepted: 03/18/2025] [Indexed: 04/07/2025] Open
Abstract
BACKGROUND Hirschsprung disease (HSCR) is a rare, congenital disease characterized by the absence of enteric ganglia in the hindgut. Common genetic variation contributes substantially to the heritability of the disease yet only three HSCR-associated loci were identified from genome-wide association studies (GWAS) thus far. METHODS We performed the largest multi-ancestry meta-analysis of GWAS to date, totalling 1250 HSCR cases and 7140 controls. Prioritized candidate genes were further characterized using single-cell transcriptomic data of developing human and mouse gut for their roles in development of enteric nervous system (ENS). Functional characterisation using human cells and zebrafish models was performed. Global and ancestry-matched polygenic risk score (PRS) models were derived and evaluated for predicting risk of HSCR. FINDINGS We identified four HSCR-susceptibility loci, with three loci (JAG1, HAND2 and ZNF25) reaching genome-wide significance and one putative locus (UNC5C) prioritized by functional relevance. Spatiotemporal analysis revealed hotspots of gene dysregulation during ENS development. Functional analyses further demonstrated that knockdown of the candidate genes impaired cell migration and zebrafish knockouts displayed abnormal ENS development. We also demonstrated comparable performance for a PRS model derived from multi-ancestry meta-analysis to those of ancestry-matched PRS models, supporting its potential clinical application in risk prediction of HSCR across populations. INTERPRETATION Overall, the meta-analysis implicated novel genes, pathways and spatiotemporal developmental hotspots in the genetic aetiology of HSCR. Development of a PRS universally applicable irrespective of ancestries may leverage its clinical utility in risk prediction. FUNDING The full list of funding bodies can be found in the Acknowledgements section.
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Affiliation(s)
- Yuanxin Zhong
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Man-Ting So
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Zuyi Ma
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Detao Zhang
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Yanbing Wang
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Zewei Xiong
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - João Fadista
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - You-Qiang Song
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Kathryn Song-Eng Cheah
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Maria M Alves
- Department of Clinical Genetics, Erasmus University Medical Centre, Sophia Children's Hospital, Rotterdam, the Netherlands
| | - Salud Borrego
- Department of Genetics, Reproduction and Fetal Medicine, Institute of Biomedicine of Seville (IBIS), University Hospital Virgen del Rocio/CSIC/University of Seville, Seville, Spain; Centre for Biomedical Network Research on Rare Diseases (CIBERER), Seville, Spain
| | | | - Mikko P Pakarinen
- Section of Pediatric Surgery, Helsinki University Hospital and University of Helsinki, Finland; Pediatric Liver and Gut Research Group, University of Helsinki, Finland
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark; Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Vincent Chi-Hang Lui
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China; Dr Li Dak-Sum Research Centre, The University of Hong Kong - Karolinska Institutet Collaboration in Regenerative Medicine, Hong Kong Special Administrative Region of China
| | - Maria-Merce Garcia-Barcelo
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Pak Chung Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China.
| | - Paul Kwong-Hang Tam
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China; Faculty of Medicine, Macau University of Science and Technology, Macao, China.
| | - Clara Sze-Man Tang
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China; Dr Li Dak-Sum Research Centre, The University of Hong Kong - Karolinska Institutet Collaboration in Regenerative Medicine, Hong Kong Special Administrative Region of China.
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11
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Yang L, He W, Zhu Y, Lv Y, Li Y, Zhang Q, Liu Y, Zhang Z, Wang T, Wei H, Cao X, Cui Y, Zhang B, Chen W, He H, Wang X, Chen D, Liu C, Shi C, Liu X, Xu Q, Yuan Q, Yu X, Qian H, Li X, Zhang B, Zhang H, Leng Y, Zhang Z, Dai X, Guo M, Jia J, Qian Q, Shang L. GWAS meta-analysis using a graph-based pan-genome enhanced gene mining efficiency for agronomic traits in rice. Nat Commun 2025; 16:3171. [PMID: 40180959 PMCID: PMC11968974 DOI: 10.1038/s41467-025-58081-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 03/06/2025] [Indexed: 04/05/2025] Open
Abstract
Genome-wide association studies (GWASs) encounter limitations from population structure and sample size, restricting their efficacy. Though meta-analysis mitigates these issues, its application in rice research remains limited. Here, we report a large-scale meta-analysis of six independent GWAS experiments in rice to mine genes for key agronomic traits. By integrating a rice pan-genome graph to identify structural variants, we obtained 6,604,898 SNP and 42,879 PAV variants for the six panels (7765 accessions). Meta-analysis significantly improved quantitative trait loci (QTLs) detection and hidden heritability by up to 43 and 37.88%, respectively. Among 156 QTLs identified for six agronomic traits, 116 were exclusively detected through meta-analysis, highlighting its superior resolution. Two novel QTLs governing grain width and length were functionally validated through CRISPR/Cas9, confirming their candidate genes. Our findings underscore the utility and potential advantages of this pan-genome-based meta-GWAS approach, providing a scalable model for efficiently gene mining from diverse rice germplasms.
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Affiliation(s)
- Longbo Yang
- College of Agriculture, Shanxi Agricultural University, Shanxi, 030801, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Wenchuang He
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Yiwang Zhu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Yang Lv
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Yilin Li
- College of Agriculture, Shanxi Agricultural University, Shanxi, 030801, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Qianqian Zhang
- College of Agriculture, Shanxi Agricultural University, Shanxi, 030801, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Yifan Liu
- College of Agriculture, Shanxi Agricultural University, Shanxi, 030801, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Zhiyuan Zhang
- College of Agriculture, Shanxi Agricultural University, Shanxi, 030801, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Tianyi Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Hua Wei
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Xinglan Cao
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Yan Cui
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Bin Zhang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Wu Chen
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Huiying He
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Xianmeng Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Dandan Chen
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Congcong Liu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Chuanlin Shi
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Xiangpei Liu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Qiang Xu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Qiaoling Yuan
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Xiaoman Yu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Hongge Qian
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Xiaoxia Li
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Bintao Zhang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Hong Zhang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Yue Leng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Zhipeng Zhang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Xiaofan Dai
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Mingliang Guo
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Juqing Jia
- College of Agriculture, Shanxi Agricultural University, Shanxi, 030801, China
| | - Qian Qian
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China.
- Yazhouwan Laboratory, No. 8 Huanjin Road, Yazhou District, Sanya City, Hainan Province, 572024, China.
- Academician Workstation, National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China.
| | - Lianguang Shang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
- Yazhouwan Laboratory, No. 8 Huanjin Road, Yazhou District, Sanya City, Hainan Province, 572024, China.
- Academician Workstation, National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China.
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12
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Hu Y, Haessler J, Lundin JI, Darst BF, Whitsel EA, Grove M, Guan W, Xia R, Szeto M, Raffield LM, Ratliff S, Wang Y, Wang X, Fohner AE, Lynch MT, Patel YM, Lani Park S, Xu H, Mitchell BD, Bis JC, Sotoodehnia N, Brody JA, Psaty BM, Peloso GM, Tsai MY, Rich SS, Rotter JI, Smith JA, Kardia SLR, Reiner AP, Lange L, Fornage M, Pankow JS, Graff M, North KE, Kooperberg C, Peters U. Methylome-wide association analyses of lipids and modifying effects of behavioral factors in diverse race and ethnicity participants. Clin Epigenetics 2025; 17:54. [PMID: 40176173 PMCID: PMC11967142 DOI: 10.1186/s13148-025-01859-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2024] [Accepted: 03/11/2025] [Indexed: 04/04/2025] Open
Abstract
Circulating lipid concentrations are clinically associated with cardiometabolic diseases. The phenotypic variance explained by identified genetic variants remains limited, highlighting the importance of searching for additional factors beyond genetic sequence variants. DNA methylation has been linked to lipid concentrations in previous studies, although most of the studies harbored moderate sample sizes and exhibited underrepresentation of non-European ancestry populations. In addition, knowledge of nongenetic factors on lipid profiles is extremely limited. In the Population Architecture Using Genomics and Epidemiology (PAGE) Study, we performed methylome-wide association analysis on 9,561 participants from diverse race and ethnicity backgrounds for HDL-c, LDL-c, TC, and TG levels, and also tested interactions between smoking or alcohol intake and methylation in their association with lipid levels. We identified novel CpG sites at 16 loci (P < 1.18E-7) with successful replication on 3,215 participants. One additional novel locus was identified in the self-reported White participants (P = 4.66E-8). Although no additional CpG sites were identified in the genome-wide interaction analysis, 13 reported CpG sites showed significant heterogeneous association across smoking or alcohol intake strata. By mapping novel and reported CpG sites to genes, we identified enriched pathways directly linked to lipid metabolism as well as ones spanning various biological functions. These findings provide new insights into the regulation of lipid concentrations.
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Grants
- N01HC95160 NHLBI NIH HHS
- 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, 75N92021D00005, and S10OD028685 NIH HHS
- 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1TR001881, DK063491, HL148610, and R01HL105756 NHLBI NIH HHS
- R01 HL087652 NHLBI NIH HHS
- UL1 TR000040 NCATS NIH HHS
- HHSN268201800010I NHLBI NIH HHS
- N01HC85081 NHLBI NIH HHS
- R01 HL103612 NHLBI NIH HHS
- 75N92020D00002 NHLBI NIH HHS
- 75N92021D00002 NHLBI NIH HHS
- HHSN268201500003C NHLBI NIH HHS
- U01HG007397 NHGRI NIH HHS
- HHSN268201800012C NHLBI NIH HHS
- 75N92020D00005 NHLBI NIH HHS
- 75N92021D00005 WHI NIH HHS
- U01HL054457, RC1HL100185, R01HL087660, R01HL119443, R01HL133221 NHLBI NIH HHS
- 75N92022D00001 NIH HHS
- N01HC95163 NHLBI NIH HHS
- U01 HL080295 NHLBI NIH HHS
- UL1 TR001079 NCATS NIH HHS
- DK063491 National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center
- HHSN268201800014I NHLBI NIH HHS
- U01CA164973 NCI NIH HHS
- U01 HL130114 NHLBI NIH HHS
- R01 HL087660 NHLBI NIH HHS
- HHSN268200800007C NHLBI NIH HHS
- S10 OD028685 NIH HHS
- 75N92020D00001 NHLBI NIH HHS
- N01HC95169 NHLBI NIH HHS
- N01HC95164 NHLBI NIH HHS
- UL1 TR000124 NCATS NIH HHS
- N01HC55222 NHLBI NIH HHS
- HHSN268201800014C NHLBI NIH HHS
- N01HC95162 NHLBI NIH HHS
- N01HC85086 NHLBI NIH HHS
- 75N92020D00003 NHLBI NIH HHS
- R01 HL119443 NHLBI NIH HHS
- R01 HL105756 NHLBI NIH HHS
- N01HC95168 NHLBI NIH HHS
- K08 HL116640 NHLBI NIH HHS
- 75N92021D00001 NHLBI NIH HHS
- P30 DK063491 NIDDK NIH HHS
- RC1 HL100185 NHLBI NIH HHS
- HHSN268201200036C NHLBI NIH HHS
- HHSN268201800001C NHLBI NIH HHS
- HHSN268201800013I NIMHD NIH HHS
- UL1TR000124 NCATS NIH HHS
- U01 HL054457 NHLBI NIH HHS
- N01HC95165 NHLBI NIH HHS
- N01HC95159 NHLBI NIH HHS
- HHSN268201800012I NHLBI NIH HHS
- 75N92021D00003 WHI NIH HHS
- N01HC95161 NHLBI NIH HHS
- UL1 TR001420 NCATS NIH HHS
- 75N92020D00004 NHLBI NIH HHS
- HHSN268201800011C NHLBI NIH HHS
- 75N92020D00007 NHLBI NIH HHS
- R01AG023629 NIA NIH HHS
- HHSN268201800013I, HHSN268201800014I, HHSN268201800015I, HHSN268201800010I, HHSN268201800011I, and HHSN268201800012I NIMHD NIH HHS
- HHSN268201500003I NHLBI NIH HHS
- R01HL105756, HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, R01AG023629, 75N92021D00006, U01HL080295, U01HL130114, K08HL116640, R01HL087652, R01HL092111, R01HL103612, R01HL111089, R01HL116747 and R01HL120393 NHLBI NIH HHS
- R01 HL133221 NHLBI NIH HHS
- 75N92021D00006 NHLBI NIH HHS
- R01HG010297 NHGRI NIH HHS
- N01HC85082 NHLBI NIH HHS
- N01HC95167 NHLBI NIH HHS
- N01HC85083 NHLBI NIH HHS
- HHSN268201800015I NHLBI NIH HHS
- 75N92020D00006 NHLBI NIH HHS
- N01HC85079 NHLBI NIH HHS
- N01HC95166 NHLBI NIH HHS
- R01 AG023629 NIA NIH HHS
- UL1 TR001881 NCATS NIH HHS
- HHSN268201800011I NHLBI NIH HHS
- N01HC85080 NHLBI NIH HHS
- R01 HG010297 NHGRI NIH HHS
- U01 CA164973 NCI NIH HHS
- 75N92021D00004 WHI NIH HHS
- R01 HL111089 NHLBI NIH HHS
- R01 HL116747 NHLBI NIH HHS
- R01 HL092111 NHLBI NIH HHS
- National Institutes of Health
- National Human Genome Research Institute
- National Institute on Minority Health and Health Disparities
- National Heart, Lung, and Blood Institute
- National Institute on Aging
- National Center for Advancing Translational Sciences
- National Cancer Institute
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Affiliation(s)
- Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jessica I Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Burcu F Darst
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Eric A Whitsel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Megan Grove
- School of Public Health, Human Genetics Center, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Weihua Guan
- Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Rui Xia
- McGovern Medical School, The Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Mindy Szeto
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Scott Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yuxuan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Xuzhi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Alison E Fohner
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Megan T Lynch
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yesha M Patel
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - S Lani Park
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Huichun Xu
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Leslie Lange
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Myriam Fornage
- School of Public Health, Human Genetics Center, University of Texas Health Sciences Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
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13
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Kim JP, Jung SH, Jang B, Cho M, Song M, Kim J, Kim B, Lee H, Shin D, Lee EH, Jang H, Kim BH, Ham H, Kim D, Raj T, Cruchaga C, Kim HJ, Na DL, Seo SW, Won HH. Cross-ancestry genome-wide association study identifies implications of SORL1 in cerebral beta-amyloid deposition. Nat Commun 2025; 16:3150. [PMID: 40175353 PMCID: PMC11965558 DOI: 10.1038/s41467-025-57751-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Accepted: 02/27/2025] [Indexed: 04/04/2025] Open
Abstract
GWAS of Alzheimer's disease have been predominantly based on European ancestry cohorts with clinically diagnosed patients. Increasing the ancestral diversity of GWAS and focusing on imaging brain biomarkers for Alzheimer's disease may lead to the identification of new genetic loci. Here, we perform a GWAS on cerebral β-amyloid deposition measured by PET imaging in 3,885 East Asians and a cross-ancestry GWAS meta-analysis with data from 11,816 European participants. Our GWAS analysis replicates known loci (APOE4, CR1, and FERMT2) and identifies a novel locus near SORL1 that is significantly associated with β-amyloid deposition. Single-nucleus expression analysis shows that SORL1 is differentially expressed according to β-amyloid positivity in microglia. Our joint association analysis using the SORL1 lead variant (rs76490923) and the APOE4 allele demonstrates that the risk of β-amyloid deposition is reduced by up to 43.5% in APOE4 non-carriers and up to 55.6% in APOE4 carriers, according to the allelic dosage of the rs76490923 T allele. Our findings suggest that SORL1 may play an important role in the pathogenesis of Alzheimer's disease, particularly in relation to β-amyloid deposition.
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Affiliation(s)
- Jun Pyo Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Sang-Hyuk Jung
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
- Department of Medical Informatics, Kangwon National University College of Medicine, Chuncheon, Republic of Korea
| | - Beomjin Jang
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Minyoung Cho
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
| | - Minku Song
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
| | - Jaeyoung Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
| | - Beomsu Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
| | - Hyunwoo Lee
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Daeun Shin
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Eun Hye Lee
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Bo-Hyun Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Hongki Ham
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Dokyoon Kim
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Towfique Raj
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, USA
- Knight Alzheimer's Disease Research Center, Washington University, St. Louis, MO, USA
- Hope Center for Neurologic Diseases, Washington University, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Hee Jin Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Duk L Na
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Sang Won Seo
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.
| | - Hong-Hee Won
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea.
- Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea.
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14
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Huang Y, Syed MG, Chen R, Li C, Shang X, Wang W, Zhang X, Zhang X, Tang S, Liu J, Liu S, Srinivasan S, Hu Y, Mookiah MRK, Wang H, Trucco E, Yu H, Palmer C, Zhu Z, Doney ASF, He M. Genomic determinants of biological age estimated by deep learning applied to retinal images. GeroScience 2025; 47:2613-2629. [PMID: 39775603 DOI: 10.1007/s11357-024-01481-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Accepted: 12/14/2024] [Indexed: 01/11/2025] Open
Abstract
With the development of deep learning (DL) techniques, there has been a successful application of this approach to determine biological age from latent information contained in retinal images. Retinal age gap (RAG) defined as the difference between chronological age and predicted retinal age has been established previously to predict the age-related disease. In this study, we performed discovery genome-wide association analysis (GWAS) on the RAG using the 31,271 UK Biobank participants and replicated our findings in 8034 GoDARTS participants. The genetic correlation between RAGs predicted from the two cohorts was 0.67 (P = 0.021). After meta-analysis, we found 13 RAG loci which might be related to retinal vessel density and other aging processes. The SNP-wide heritability (h2) of RAG was 0.15. Meanwhile, by performing Mendelian randomization analysis, we found that glycated hemoglobin, inflammation hemocytes, and anemia might be associated with accelerated retinal aging. Our study explored the biological implications and molecular-level mechanism of RAG, which might enable causal inference of the aging process as well as provide potential pharmaceutical intervention targets for further treatment.
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Affiliation(s)
- Yu Huang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK
| | - Mohammad Ghouse Syed
- VAMPIRE Project, Computer Vision and Image Processing Group, School of Science and Engineering (Computing), University of Dundee, Dundee, DD1 9SY, UK
| | - Ruiye Chen
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Cong Li
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Wei Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Xueli Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Xiayin Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Shulin Tang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Jing Liu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Shunming Liu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Sundar Srinivasan
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK
| | - Yijun Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Muthu Rama Krishnan Mookiah
- VAMPIRE Project, Computer Vision and Image Processing Group, School of Science and Engineering (Computing), University of Dundee, Dundee, DD1 9SY, UK
| | - Huan Wang
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK
| | - Emanuele Trucco
- VAMPIRE Project, Computer Vision and Image Processing Group, School of Science and Engineering (Computing), University of Dundee, Dundee, DD1 9SY, UK
| | - Honghua Yu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Colin Palmer
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK
| | - Zhuoting Zhu
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia.
| | - Alexander S F Doney
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
| | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia.
- School of Optometry, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.
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15
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Strom NI, Halvorsen MW, Grove J, Ásbjörnsdóttir B, Luðvígsson P, Thorarensen Ó, de Schipper E, Bäckmann J, Andrén P, Tian C, Als TD, Nissen JB, Meier SM, Bybjerg-Grauholm J, Hougaard DM, Werge T, Børglum AD, Hinds DA, Rück C, Mataix-Cols D, Stefánsson H, Stefansson K, Crowley JJ, Mattheisen M. Genome-Wide Association Study Meta-Analysis of 9619 Cases With Tic Disorders. Biol Psychiatry 2025; 97:743-752. [PMID: 39389409 DOI: 10.1016/j.biopsych.2024.07.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 06/11/2024] [Accepted: 07/05/2024] [Indexed: 10/12/2024]
Abstract
BACKGROUND Despite the significant personal and societal burden of tic disorders (TDs), treatment outcomes remain modest, necessitating a deeper understanding of their etiology. Family history is the biggest known risk factor, and identifying risk genes could accelerate progress in the field. METHODS Expanding upon previous sample size limitations, we added 4800 new TD cases and 971,560 controls and conducted a genome-wide association study (GWAS) meta-analysis with 9619 cases and 981,048 controls of European ancestry. We attempted to replicate the results in an independent deCODE genetics GWAS (885 TD cases and 310,367 controls). To characterize GWAS findings, we conducted several post-GWAS gene-based and enrichment analyses. RESULTS A genome-wide significant hit (rs79244681, p = 2.27 × 10-8) within MCHR2-AS1 was identified, although it was not replicated. Post-GWAS analyses revealed a 13.8% single nucleotide polymorphism heritability and 3 significant genes: BCL11B, NDFIP2, and RBM26. Common variant risk for TD was enriched within genes preferentially expressed in the cortico-striato-thalamo-cortical circuit (including the putamen, caudate, nucleus accumbens, and Brodmann area 9) and 5 brain cell types (excitatory and inhibitory telencephalon neurons, inhibitory diencephalon and mesencephalon neurons, and hindbrain and medium spiny neurons). TD polygenic risk was enriched within loss-of-function intolerant genes (p = .0017) and high-confidence neurodevelopmental disorder genes (p = .0108). Of 112 genetic correlations, 43 were statistically significant, showing high positive correlations with most psychiatric disorders. Of the 2 single nucleotide polymorphisms previously associated with TDs, one (rs2453763) replicated in an independent subsample of our GWAS (p = .00018). CONCLUSIONS This GWAS was still underpowered to identify high-confidence, replicable loci, but the results suggest imminent discovery of common genetic variants for TDs.
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Affiliation(s)
- Nora I Strom
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany; Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, Germany; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden; Department of Biomedicine, Aarhus University, Aarhus, Denmark.
| | - Matthew W Halvorsen
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Jakob Grove
- Department of Biomedicine, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark; Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | | | - Pétur Luðvígsson
- Department of Pediatrics, Landspitali University Hospital, Reykjavik, Iceland
| | - Ólafur Thorarensen
- Department of Pediatrics, Landspitali University Hospital, Reykjavik, Iceland
| | - Elles de Schipper
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden
| | - Julia Bäckmann
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden
| | - Per Andrén
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden
| | - Chao Tian
- 23andMe, Inc., Sunnyvale, California
| | - Thomas Damm Als
- Department of Biomedicine, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Judith Becker Nissen
- Department of Child and Adolescent Psychiatry, Aarhus University Hospital, Aarhus, Denmark; Institute of Clinical Medicine, Institute of Health, Aarhus University, Aarhus, Denmark
| | - Sandra M Meier
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Jonas Bybjerg-Grauholm
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Thomas Werge
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark; GLOBE Institute, Center for GeoGenetics, University of Copenhagen, Copenhagen, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | | | - Christian Rück
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden
| | - David Mataix-Cols
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden
| | | | | | - James J Crowley
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Region Stockholm, Sweden; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Manuel Mattheisen
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, Germany; Department of Community Health and Epidemiology & Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
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16
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Dilliott AA, Costanzo MC, Bandres-Ciga S, Blauwendraat C, Casey B, Hoang Q, Iwaki H, Jang D, Kim JJ, Leonard HL, Levine KS, Makarious M, Nguyen TT, Rouleau GA, Singleton AB, Smadbeck P, Solle J, Vitale D, Nalls M, Flannick J, Burtt NP, Farhan SMK. The Neurodegenerative Disease Knowledge Portal: Propelling Discovery Through the Sharing of Neurodegenerative Disease Genomic Resources. Neurol Genet 2025; 11:e200246. [PMID: 39996130 PMCID: PMC11849525 DOI: 10.1212/nxg.0000000000200246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Accepted: 01/02/2025] [Indexed: 02/26/2025]
Abstract
Although large-scale genetic association studies have proven useful for the delineation of neurodegenerative disease processes, we still lack a full understanding of the pathologic mechanisms of these diseases, resulting in few appropriate treatment options and diagnostic challenges. To mitigate these gaps, the Neurodegenerative Disease Knowledge Portal (NDKP) was created as an open-science initiative with the aim to aggregate, enable analysis, and display all available genomic datasets of neurodegenerative disease, while protecting the integrity and confidentiality of the underlying datasets. The portal contains 218 genomic datasets, including genotyping and sequencing studies, of individuals across 10 different phenotypic groups, including neurologic conditions such as Alzheimer disease, amyotrophic lateral sclerosis, Lewy body dementia, and Parkinson disease. In addition to securely hosting large genomic datasets, the NDKP provides accessible workflows and tools to effectively use the datasets and assist in the facilitation of customized genomic analyses. Here, we summarize the genomic datasets currently included within the portal, the bioinformatics processing of the datasets, and the variety of phenotypes captured. We also present example use cases of the various user interfaces and integrated analytic tools to demonstrate their extensive utility in enabling the extraction of high-quality results at the source, for both genomics experts and those in other disciplines. Overall, the NDKP promotes open science and collaboration, maximizing the potential for discovery from the large-scale datasets researchers and consortia are expending immense resources to produce and resulting in reproducible conclusions to improve diagnostic and therapeutic care for patients with neurodegenerative disease.
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Affiliation(s)
- Allison A Dilliott
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montreal, Quebec, Canada
| | - Maria C Costanzo
- Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- Laboratory of Neurogenetics, NIH, Bethesda, MD
| | - Cornelis Blauwendraat
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- Laboratory of Neurogenetics, NIH, Bethesda, MD
| | - Bradford Casey
- Michael J. Fox Foundation for Parkinson's Research, New York, NY
| | - Quy Hoang
- Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA
| | - Hirotaka Iwaki
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- DataTecnica LLC, Washington, DC
| | - Dongkeun Jang
- Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA
| | - Jonggeol Jeffrey Kim
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- Laboratory of Neurogenetics, NIH, Bethesda, MD
| | - Hampton L Leonard
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- DataTecnica LLC, Washington, DC
| | - Kristin S Levine
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- DataTecnica LLC, Washington, DC
| | - Mary Makarious
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- Laboratory of Neurogenetics, NIH, Bethesda, MD
| | - Trang T Nguyen
- Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA
| | - Guy A Rouleau
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Andrew B Singleton
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- Laboratory of Neurogenetics, NIH, Bethesda, MD
| | - Patrick Smadbeck
- Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA
| | - J Solle
- Michael J. Fox Foundation for Parkinson's Research, New York, NY
| | - Dan Vitale
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- DataTecnica LLC, Washington, DC
| | - Mike Nalls
- Center for Alzheimer's and Related Dementias, NIH, Bethesda, MD
- Laboratory of Neurogenetics, NIH, Bethesda, MD
- DataTecnica LLC, Washington, DC
| | - Jason Flannick
- Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Pediatrics, Boston Children's Hospital, Boston, MA; and
- Department of Pediatrics, Harvard Medical School, Boston, MA
| | - Noël P Burtt
- Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA
| | - Sali M K Farhan
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
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17
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Shan Y, Hu H, Chu Y. Cross-ancestry genome-wide association study identifies new susceptibility genes for preeclampsia. BMC Pregnancy Childbirth 2025; 25:379. [PMID: 40170147 PMCID: PMC11959822 DOI: 10.1186/s12884-025-07534-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2025] [Accepted: 03/26/2025] [Indexed: 04/03/2025] Open
Abstract
BACKGROUND Preeclampsia (PE) is a heterogeneous, multi-organ pregnancy disorder that poses a significant health burden globally, with its pathogenesis remaining unclear. This study aimed to identify novel susceptibility genes for PE through a cross-ancestry genome-wide association study (GWAS). METHODS We performed meta-analysis to summarize the PE GWAS data from the United Kingdom, Finland, and Japan. Subsequently, the multi-ancestry sum of the single-effects model was used to perform cross-ancestry fine-mapping. The functional mapping and annotation (FUMA)-expression quantitative trait loci (eQTL) mapping method, transcriptome-wide association study (TWAS)- functional summary-based imputation (FUSION) method, genome-wide complex trait analysis (GCTA)-multivariate set-based association test (mBAT)-combo method, and polygenic priority score (PoPS) method were employed to screen for candidate genes. We utilized biomarker expression level imputation using summary-level statistics (BLISS), based on summary-level protein quantitative trait loci (pQTL) data, to conduct a multi-ancestry proteome-wide association study (PWAS) analysis, followed by candidate drug prediction. RESULTS Six novel susceptibility genes associated with PE risk were identified: NPPA, SWAP70, NPR3, FGF5, REPIN1, and ACAA1. High expression of the NPPA and SWAP70 and low expression of the remaining genes were associated with a reduced risk of PE. Furthermore, we identified drugs that target NPPA, NPR3, and REPIN1. CONCLUSIONS Our study identified NPPA, SWAP70, NPR3, FGF5, REPIN1, and ACAA1 as novel genes whose predicted expression was linked to the risk of PE, offering new insights into the genetic framework of this condition.
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Affiliation(s)
- Yuping Shan
- Department of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hong Hu
- Clinical Medicine, Nantong University, Nantong, China
| | - Yijing Chu
- Department of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China.
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Kiltschewskij DJ, Reay WR, Cairns MJ. Schizophrenia is associated with altered DNA methylation variance. Mol Psychiatry 2025; 30:1383-1395. [PMID: 39271751 PMCID: PMC11919772 DOI: 10.1038/s41380-024-02749-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 09/02/2024] [Accepted: 09/04/2024] [Indexed: 09/15/2024]
Abstract
Varying combinations of genetic and environmental risk factors are thought to underpin phenotypic heterogeneity between individuals in psychiatric conditions such as schizophrenia. While epigenome-wide association studies in schizophrenia have identified extensive alteration of mean DNA methylation levels, less is known about the location and impact of DNA methylation variance, which could contribute to phenotypic and treatment response heterogeneity. To explore this question, we conducted the largest meta-analysis of blood DNA methylation variance in schizophrenia to date, leveraging three cohorts comprising 1036 individuals with schizophrenia and 954 non-psychiatric controls. Surprisingly, only a small proportion (0.1%) of the 213 variably methylated positions (VMPs) associated with schizophrenia (Benjamini-Hochberg FDR < 0.05) were shared with differentially methylated positions (DMPs; sites with mean changes between cases and controls). These blood-derived VMPs were found to be overrepresented in genes previously associated with schizophrenia and amongst brain-enriched genes, with evidence of concordant changes at VMPs in the cerebellum, hippocampus, prefrontal cortex, or striatum. Epigenetic covariance was also observed with respect to clinically significant metrics including age of onset, cognitive deficits, and symptom severity. We also uncovered a significant VMP in individuals with first-episode psychosis (n = 644) from additional cohorts and a non-psychiatric comparison group (n = 633). Collectively, these findings suggest schizophrenia is associated with significant changes in DNA methylation variance, which may contribute to individual-to-individual heterogeneity.
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Affiliation(s)
- Dylan J Kiltschewskij
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Precision Medicine Program, Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - William R Reay
- Menzies Institute for Medical Research, Hobart, TAS, Australia
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia.
- Precision Medicine Program, Hunter Medical Research Institute, New Lambton, NSW, Australia.
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19
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Du S, Chen J, Li J, Qian W, Wu S, Peng Q, Liu Y, Pan T, Li Y, Hadi SS, Tan J, Yuan Z, Wang J, Tang K, Wang Z, Wen Y, Dong X, Zhou W, Ruiz-Linares A, Shi Y, Jin L, Liu F, Zhang M, Wang S. A multi-ancestry GWAS meta-analysis of facial features and its application in predicting archaic human features. J Genet Genomics 2025; 52:513-524. [PMID: 39002897 DOI: 10.1016/j.jgg.2024.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 07/06/2024] [Accepted: 07/06/2024] [Indexed: 07/15/2024]
Abstract
Facial morphology, a complex trait influenced by genetics, holds great significance in evolutionary research. However, due to limited fossil evidence, the facial characteristics of Neanderthals and Denisovans have remained largely unknown. In this study, we conduct a large-scale multi-ethnic meta-analysis of the genome-wide association study (GWAS), including 9674 East Asians and 10,115 Europeans, quantitatively assessing 78 facial traits using 3D facial images. We identify 71 genomic loci associated with facial features, including 21 novel loci. We develop a facial polygenic score (FPS) that enables the prediction of facial features based on genetic information. Interestingly, the distribution of FPSs among populations from diverse continental groups exhibits relevant correlations with observed facial features. Furthermore, we apply the FPS to predict the facial traits of seven Neanderthals and one Denisovan using ancient DNA and align predictions with the fossil records. Our results suggest that Neanderthals and Denisovans likely share similar facial features, such as a wider but shorter nose and a wider endocanthion distance. The decreased mouth width is characterized specifically in Denisovans. The integration of genomic data and facial trait analysis provides valuable insights into the evolutionary history and adaptive changes in human facial morphology.
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Affiliation(s)
- Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jieyi Chen
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Jiarui Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Wei Qian
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Sijie Wu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yu Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ting Pan
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yi Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Sibte Syed Hadi
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 11452, Kingdom of Saudi Arabia
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China
| | - Jiucun Wang
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai 200438, China
| | - Kun Tang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhuo Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yanqin Wen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Xinran Dong
- Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Wenhao Zhou
- Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China; Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510623, China
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China; Aix-Marseille Université, CNRS, EFS, ADES, Marseille 13005, France; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Li Jin
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai 200438, China
| | - Fan Liu
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 11452, Kingdom of Saudi Arabia; Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, 3015 CN Rotterdam, the Netherlands
| | - Manfei Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China.
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China.
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20
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Noguchi E, Morii W, Kitazawa H, Hirota T, Sonehara K, Masuko H, Okada Y, Hizawa N. A genome-wide meta-analysis reveals shared and population-specific variants for allergic sensitization. J Allergy Clin Immunol 2025; 155:1321-1332. [PMID: 39644933 DOI: 10.1016/j.jaci.2024.11.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 11/12/2024] [Accepted: 11/13/2024] [Indexed: 12/09/2024]
Abstract
BACKGROUND Allergic diseases are major causes of morbidity in both developed and developing countries and represent a global burden on health care systems. Allergic sensitization is defined as the production of IgE specific to common environmental allergens and is an important indicator in the assessment of allergic diseases. OBJECTIVE We sought to clarify the genetic basis of allergic sensitization. METHODS We performed a genome-wide association study (GWAS) of allergic sensitization in the Japanese population followed by a cross-ancestry meta-analysis with a European population including 20,492 cases and 23,342 controls for Japanese and 8,246 cases and 16,786 controls for Europeans. We also performed a polysensitization GWAS of a Japanese population including 4,923 cases and 17,009 controls. RESULTS Allergic sensitization GWAS identified 18 susceptibility loci for Japanese only and 23 loci for the cross-ancestry population, among which 4 loci were novel. Polysensitization GWAS identified 8 significant loci. Expression quantitative trait locus colocalization analysis revealed polysensitization GWAS significant variants affecting both the phenotype and the expression of the CD28, LPP, and LRCC32 genes. Cross-population genetic correlation analysis of allergic sensitization suggested that heterogeneity exists in allergic sensitization between Europeans and Japanese, indicating that more genetic heterogeneity may exist in allergic sensitization than allergic diseases. CONCLUSIONS Our investigation provides new insights into the molecular mechanism of allergic sensitization that could enhance current understanding of allergy and allergic diseases.
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Affiliation(s)
- Emiko Noguchi
- Department of Medical Genetics, Institute of Medicine, University of Tsukuba, Tsukuba, Japan.
| | - Wataru Morii
- Department of Medical Genetics, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Haruna Kitazawa
- Department of Pulmonary Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Tomomitsu Hirota
- Division of Molecular Genetics, Jikei University School of Medicine, Research Center for Medical Science, Tokyo, Japan
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Hironori Masuko
- Department of Pulmonary Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan; Premium Research Institute for Human Metaverse Medicine, Osaka University, Suita, Japan; Laboratory of Statistical Immunology, Immunology Frontier Research Center, Osaka University, Suita, Japan
| | - Nobuyuki Hizawa
- Department of Pulmonary Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
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21
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Hayman MME, Jones W, Aman A, Ward J, Anderson J, Lyall DM, Pell JP, Sattar N, Welsh P, Strawbridge RJ. Association of GLP1R locus with mental ill-health endophenotypes and cardiometabolic traits: A trans-ancestry study in UK Biobank. Diabetes Obes Metab 2025; 27:1845-1858. [PMID: 39838854 PMCID: PMC11885074 DOI: 10.1111/dom.16178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2024] [Revised: 12/18/2024] [Accepted: 12/27/2024] [Indexed: 01/23/2025]
Abstract
AIMS Glucagon-like peptide 1 receptor agonists (GLP1RA), used to treat type 2 diabetes and obesity, have been associated with off-target behavioural effects. We systematically assessed genetic variation in the GLP1R locus for impact on mental ill-health (MIH) and cardiometabolic phenotypes across diverse populations within UK Biobank. MATERIALS AND METHODS All genetic variants with minor allele frequency >1% in the GLP1R locus were investigated for associations with MIH phenotypes and cardiometabolic phenotypes. Linear or Logistic regression analyses (adjusted for age, sex, population structure and genotyping chip) were conducted separately in unrelated individuals of self-reported white British (N = 408 774), white European (N = 50 314), South Asian (N = 7667), multiple-ancestry groups (N = 10 437) or African-Caribbean (N = 7641) subsets. All ancestries were subsequently combined in an inverse variance-weighted fixed effects meta-analysis. Bonferroni correction for multiple testing was applied (for number of independent genetic variants). RESULTS Associations were identified between GLP1R variants and body mass index (BMI), blood pressure and type 2 diabetes in all ancestries. All ancestries except South Asian had significant MIH associations (mood instability: rs111265626-G, odds ratio [OR] 0.851 [confidence interval, CI 0.79-0.92], risk-taking behaviour: rs75408972-T, OR 1.05 [CI 1.03-1.08] or chronic pain: rs9296280-C, OR 0.645 [CI 0.54-0.78]). The trans-ancestry meta-analysis showed mainly consistent effect sizes and directions for metabolic traits, but discordant directions MIH associations. Only signals for chronic pain, stroke and BMI influenced expression of GLP1R. CONCLUSIONS GLP1R variants have consistent cardiometabolic effects across ancestries, but effects on MIH phenotypes are more varied. Any observed behavioural changes with GLP1RA are likely not acting directly through GLP1R.
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Affiliation(s)
- Madeleine M. E. Hayman
- School of Cardiovascular and Metabolic HealthUniversity of GlasgowGlasgowUK
- School of Health and WellbeingUniversity of GlasgowGlasgowUK
- Deanery of Molecular, Genetic and Population Health SciencesUniversity of EdinburghEdinburghUK
| | - Waneisha Jones
- School of Health and WellbeingUniversity of GlasgowGlasgowUK
| | - Alisha Aman
- College of Medical, Veterinary, and Life Sciences, Graduate SchoolUniversity of GlasgowGlasgowUK
| | - Joey Ward
- School of Health and WellbeingUniversity of GlasgowGlasgowUK
| | - Jana Anderson
- School of Health and WellbeingUniversity of GlasgowGlasgowUK
| | - Donald M. Lyall
- School of Health and WellbeingUniversity of GlasgowGlasgowUK
| | - Jill P. Pell
- School of Health and WellbeingUniversity of GlasgowGlasgowUK
| | - Naveed Sattar
- School of Cardiovascular and Metabolic HealthUniversity of GlasgowGlasgowUK
| | - Paul Welsh
- School of Cardiovascular and Metabolic HealthUniversity of GlasgowGlasgowUK
| | - Rona J. Strawbridge
- School of Health and WellbeingUniversity of GlasgowGlasgowUK
- Cardiovascular Medicine Unit, Department of Medicine SolnaKarolinska InstituteStockholmSweden
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22
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Nair JM, Chauhan G, Prasad G, Bandesh K, Giri AK, Chakraborty S, Marwaha RK, Mathur S, Choudhury D, Tandon N, Basu A, Bharadwaj D. Mapping the landscape of childhood obesity: genomic insights and socioeconomic status in Indian school-going children. Obesity (Silver Spring) 2025; 33:754-765. [PMID: 40000390 DOI: 10.1002/oby.24248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2024] [Revised: 11/19/2024] [Accepted: 12/20/2024] [Indexed: 02/27/2025]
Abstract
OBJECTIVE Childhood obesity (OB) is influenced by complex gene-environmental interaction. While genetics of adult OB have been extensively studied, polygenic childhood OB in non-European populations is still underexplored. Furthermore, in a developing nation such as India, how the environmental component strongly modulated by the socioeconomic status (SES) shapes the genetic susceptibility is crucial to understand. METHODS A two-staged genome-wide association study (GWAS; N = 5673) and an independent exome-wide association study (ExWAS; N = 4963) were performed using a generalized linear model assuming additive effect to identify the common and rare genetic variants respectively associated with childhood OB. Rare-variant burden testing was also performed. We used the gene expression profiles and regulatory data from public databases to explain the novel associations. The implications of SES as a potential modifier of genetic susceptibility were evaluated. RESULTS GWAS identified novel associations in TCF7L2, IMMP2L, IPMK, CDC5L, SNTG1, and MX1, whereas ExWAS uncovered CNTN4, COQ4, TNFRSF10D, FLG-AS1, and BMP3. Both GWAS and ExWAS validated known associations in FTO and MC4R. Furthermore, rare-variant testing highlighted the role of 101 genes. We also observed that SES can modulate the inherent susceptibility to OB. CONCLUSIONS Our study identified genetic variants associated with childhood OB and highlighted the gene-environmental interaction in childhood OB.
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Affiliation(s)
- Janaki M Nair
- School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Ganesh Chauhan
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Gauri Prasad
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Khushdeep Bandesh
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Anil K Giri
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Shraddha Chakraborty
- Council of Scientific and Industrial Research (CSIR)-Institute of Genomics and Integrative Biology, Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Raman K Marwaha
- International Life Sciences Institute (ILSI), New Delhi, India
| | - Sandeep Mathur
- Department of Endocrinology, SMS Medical College and Hospital, Jaipur, India
| | | | - Nikhil Tandon
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India
| | - Analabha Basu
- Biotechnology Research Innovation Council-National Institute of Biomedical Genomics, Kalyani, India
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Neylan CJ, Levin MG, Hartmann K, Beigel K, Khodursky S, DePaolo JS, Abramowitz S, Furth EE, Heuckeroth RO, Damrauer SM, Maguire LH. Genome-wide association meta-analysis identifies 126 novel loci for diverticular disease and implicates connective tissue and colonic motility. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.03.27.25324777. [PMID: 40196262 PMCID: PMC11974943 DOI: 10.1101/2025.03.27.25324777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/09/2025]
Abstract
Diverticular disease is a common and morbid complex phenotype influenced by both innate and environmental risk factors. We performed the largest genome-wide association study meta-analysis for diverticular disease, identifying 126 novel loci. Employing multiple downstream analytic strategies, including tissue and pathway enrichment, statistical fine-mapping, allele-specific expression, protein quantitative trait loci and drug-target investigations, and linkage disequilibrium score regression, we prioritized causal genes and produced several lines of evidence linking diverticular disease to connective tissue biology and colonic motility. We substantiated these findings by integrating single-cell RNA sequencing data, showing that prioritized diverticular disease-associated genes are enriched for expression in colonic smooth muscle, fibroblasts, and interstitial cells of Cajal. In quantitative analysis of surgical specimens, we found a substantial reduction in the density of elastin present in the sigmoid colon in severe diverticulitis.
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24
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Megat S, Marques C, Hernán-Godoy M, Sellier C, Stuart-Lopez G, Dirrig-Grosch S, Gorin C, Brunet A, Fischer M, Keime C, Kessler P, Mendoza-Parra MA, Zwamborn RAJ, Veldink JH, Scholz SW, Ferrucci L, Ludolph A, Traynor B, Chio A, Dupuis L, Rouaux C. CREB3 gain of function variants protect against ALS. Nat Commun 2025; 16:2942. [PMID: 40140376 PMCID: PMC11947196 DOI: 10.1038/s41467-025-58098-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 03/12/2025] [Indexed: 03/28/2025] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly evolving neurodegenerative disease arising from the loss of glutamatergic corticospinal neurons (CSN) and cholinergic motoneurons (MN). Here, we performed comparative cross-species transcriptomics of CSN using published snRNA-seq data from the motor cortex of ALS and control postmortem tissues, and performed longitudinal RNA-seq on CSN purified from male Sod1G86R mice. We report that CSN undergo ER stress and altered mRNA translation, and identify the transcription factor CREB3 and its regulatory network as a resilience marker of ALS, not only amongst vulnerable neuronal populations, but across all neuronal populations as well as other cell types. Using genetic and epidemiologic analyses we further identify the rare variant CREB3R119G (rs11538707) as a positive disease modifier in ALS. Through gain of function, CREB3R119G decreases the risk of developing ALS and the motor progression rate of ALS patients.
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Affiliation(s)
- Salim Megat
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France.
| | - Christine Marques
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Marina Hernán-Godoy
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Chantal Sellier
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Geoffrey Stuart-Lopez
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Sylvie Dirrig-Grosch
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Charlotte Gorin
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Aurore Brunet
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Mathieu Fischer
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Céline Keime
- Université de Strasbourg, Inserm UMR-S 1258, CNRS UMR-S 7104, Institut de Génétique, Biologie Moléculaire et Cellulaire, Illkirch-Graffenstaden, France
| | - Pascal Kessler
- Université de Strasbourg, Inserm UMS 38, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Marco Antonio Mendoza-Parra
- UMR 8030 Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, University of Evry-val-d'Essonne, University Paris-Saclay, Evry, France
| | - Ramona A J Zwamborn
- Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Jan H Veldink
- Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Luigi Ferrucci
- Intramural Research Program of the National Institute on Aging, NIH, Baltimore, MD, USA
| | | | - Bryan Traynor
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Therapeutic Development Branch, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA
| | - Adriano Chio
- ALS Center "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy
| | - Luc Dupuis
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France
| | - Caroline Rouaux
- Université de Strasbourg, Inserm, Strasbourg Translational Neuroscience and Psychiatry, Inserm UMR-S 1329, Centre de Recherche en Biomédecine de Strasbourg, Strasbourg, France.
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25
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Puerta R, de Rojas I, García-González P, Olivé C, Sotolongo-Grau O, García-Sánchez A, García-Gutiérrez F, Montrreal L, Tartari JP, Sanabria Á, Pytel V, Lage C, Quintela I, Aguilera N, Rodriguez-Rodriguez E, Alarcón-Martín E, Orellana A, Pastor P, Pérez-Tur J, Piñol-Ripoll G, López de Munain A, García-Alberca JM, Royo JL, Bullido MJ, Álvarez V, Real LM, Corbatón Anchuelo A, Gómez-Garre D, Martínez Larrad MT, Franco-Macías E, Mir P, Medina M, Sánchez-Valle R, Dols-Icardo O, Sáez ME, Carracedo Á, Tárraga L, Alegret M, Valero S, Marquié M, Boada M, Sánchez Juan P, Cavazos JE, Cabrera-Socorro A, Cano A, Ruiz A. Linking genomic and proteomic signatures to brain amyloid burden: insights from GR@ACE/DEGESCO. Funct Integr Genomics 2025; 25:73. [PMID: 40133566 PMCID: PMC11937198 DOI: 10.1007/s10142-025-01581-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2024] [Revised: 03/12/2025] [Accepted: 03/13/2025] [Indexed: 03/27/2025]
Abstract
Alzheimer's disease (AD) is a complex disease with a strong genetic component, yet many genetic risk factors remain unknown. We combined genome-wide association studies (GWAS) on amyloid endophenotypes measured in cerebrospinal fluid (CSF) and positron emission tomography (PET) as surrogates of amyloid pathology, which may provide insights into the underlying biology of the disease. We performed a meta-GWAS of CSF Aβ42 and PET measures combining six independent cohorts (n = 2,076). Given the opposite beta direction of Aβ phenotypes in CSF and PET measures, only genetic signals showing opposite directions were considered for analysis (n = 376,599). We explored the amyloidosis signature in the CSF proteome using SOMAscan proteomics (ACE cohort, n = 1,008), connected it with GWAS loci modulating amyloidosis and performed an enrichment analysis of overlapping hits. Finally, we compared our results with a large meta-analysis using publicly available datasets in CSF (n = 13,409) and PET (n = 13,116). After filtering the meta-GWAS, we observed genome-wide significance in the rs429358-APOE locus and annotated nine suggestive hits. We replicated the APOE loci using the large CSF-PET meta-GWAS, identifying multiple AD-associated genes including the novel GADL1 locus. Additionally, we found 1,387 FDR-significant SOMAscan proteins associated with CSF Aβ42 levels. The overlap among GWAS loci and proteins associated with amyloid burden was minimal (n = 35). The enrichment analysis revealed mechanisms connecting amyloidosis with the plasma membrane's anchored component, synapse physiology and mental disorders that were replicated in the large CSF-PET meta-analysis. Combining CSF and PET amyloid GWAS with CSF proteome analyses may effectively elucidate causative molecular mechanisms behind amyloid mobilization and AD physiopathology.
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Affiliation(s)
- Raquel Puerta
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Doctorate in Biotechnology, Facultat de Farmàcia i Ciències de l'Alimentació, Universitat de Barcelona, Avda. Diagonal 643, 08028, Barcelona, Spain
| | - Itziar de Rojas
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Pablo García-González
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Clàudia Olivé
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Oscar Sotolongo-Grau
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Ainhoa García-Sánchez
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Fernando García-Gutiérrez
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Laura Montrreal
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Juan Pablo Tartari
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Ángela Sanabria
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Vanesa Pytel
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Carmen Lage
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Marqués de Valdecilla University Hospital- IDIVAL-Universidad de Cantabria, Santander, Spain
| | - Inés Quintela
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Nuria Aguilera
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Eloy Rodriguez-Rodriguez
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Marqués de Valdecilla University Hospital- IDIVAL-Universidad de Cantabria, Santander, Spain
| | - Emilio Alarcón-Martín
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Adelina Orellana
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Pau Pastor
- Unit of Neurodegenerative Diseases, Department of Neurology, University Hospital Germans Trias I Pujol, Badalona, Barcelona, Spain
- The Germans Trias I Pujol Research Institute (IGTP), Badalona, Barcelona, Spain
| | - Jordi Pérez-Tur
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Unitat de Genètica Molecular, Institut de Biomedicina de València-CSIC, Valencia, Spain
- Unidad Mixta de Neurologia Genètica, Instituto de Investigación Sanitaria La Fe, Valencia, Spain
| | - Gerard Piñol-Ripoll
- Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Lleida, Spain
- Institut de Recerca Biomedica de Lleida (IRBLLeida), Lleida, Spain
| | - Adolfo López de Munain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Neurology, Hospital Universitario Donostia, San Sebastian, Spain
- Department of Neurosciences. Faculty of Medicine and Nursery, University of the Basque Country, San Sebastián, Spain
- Neurosciences Area, Instituto Biodonostia, San Sebastian, Spain
| | - Jose María García-Alberca
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Alzheimer Research Center & Memory Clinic, Andalusian Institute for Neuroscience, Málaga, Spain
| | - Jose Luís Royo
- Departamento de Especialidades Quirúrgicas, Bioquímica E Inmunología. School of Medicine, University of Malaga, Málaga, Spain
| | - María J Bullido
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Centro de Biología Molecular Severo Ochoa (UAM-CSIC), Madrid, Spain
- Instituto de Investigación Sanitaria 'Hospital La Paz' (IdIPaz), Madrid, Spain
- Universidad Autónoma de Madrid, Madrid, Spain
| | - Victoria Álvarez
- Laboratorio de Genética, Hospital Universitario Central de Asturias, Oviedo, Spain
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Luis Miguel Real
- Instituto de Biomedicina de Sevilla/Hospital Universitario Virgen de Valme/CSIC/Dpto de Bioquímica Médica, Biología Molecular e Inmunología/Universidad de Sevilla, Sevilla, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Arturo Corbatón Anchuelo
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Hospital Clínico San Carlos, Madrid, Spain
| | - Dulcenombre Gómez-Garre
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Hospital Clínico San Carlos, Madrid, Spain
- Laboratorio de Riesgo Cardiovascular y Microbiota, Hospital Clínico San Carlos; Departamento de Fisiología, Facultad de Medicina, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Biomedical Research Networking Center in Cardiovascular Diseases (CIBERCV), Madrid, Spain
| | - María Teresa Martínez Larrad
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Hospital Clínico San Carlos, Madrid, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
| | - Emilio Franco-Macías
- Dementia Unit, Department of Neurology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBiS), Seville, Spain
| | - Pablo Mir
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología. Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Miguel Medina
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Raquel Sánchez-Valle
- Alzheimer'S Disease and Other Cognitive Disorders Unit. Service of Neurology. Hospital Clínic of Barcelona. Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Oriol Dols-Icardo
- Department of Neurology, Sant Pau Memory Unit, Sant Pau Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Ángel Carracedo
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Fundación Pública Galega de Medicina Xenómica- CIBERER-IDIS, Santiago de Compostela, Spain
| | - Lluís Tárraga
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Montse Alegret
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Sergi Valero
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Marta Marquié
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Mercè Boada
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Pascual Sánchez Juan
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Reina Sofia Alzheimer Centre, CIEN Foundation, ISCIII, Madrid, Spain
| | - Jose Enrique Cavazos
- South Texas Alzheimer's Disease Research Center, San Antonio, TX, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
| | - Alfredo Cabrera-Socorro
- Neuroscience Therapeutic Area, Janssen Research & Development, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - Amanda Cano
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Agustín Ruiz
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, C/ Marquès de Sentmenat, 57, 08029, Barcelona, Spain.
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain.
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA.
- Department of Microbiology, Immunology and Molecular Genetics. Long School of Medicine, University of Texas Health Science Center, San Antonio, TX, USA.
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26
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Meuwissen T, Boerner V. Multitrait genome-wide association best linear unbiased prediction of genetic values. Genet Sel Evol 2025; 57:15. [PMID: 40119282 PMCID: PMC11927129 DOI: 10.1186/s12711-025-00964-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2024] [Accepted: 03/06/2025] [Indexed: 03/24/2025] Open
Abstract
BACKGROUND The GWABLUP (Genome-Wide Association based Best Linear Unbiased Prediction) approach used GWA analysis results to differentially weigh the SNPs in genomic prediction, and was found to improve the reliabilities of genomic predictions. However, the proposed multitrait GWABLUP method assumed that the SNP weights were the same across the traits. Here we extended and validated the multitrait GWABLUP method towards using trait specific SNP weights. RESULTS In a 3-trait dairy data set, multitrait GWAS estimates of SNP effects and their standard errors were translated into trait specific likelihood ratios for the SNPs having trait effects, and posterior probabilities using the GWABLUP approach. This produced trait specific prior (co)variance matrices for each SNP, which were applied in a SNP-BLUP model for genomic predictions, implemented in the APEX linear model suite. In a validation population, the trait specific SNP weights resulted in more reliable predictions for all three traits. Especially, for somatic cell count, which was hardly related to the other traits, the use of the same weights across all traits was harming genomic predictions. The use of trait specific SNP weights overcame this problem. CONCLUSIONS In multitrait GWABLUP analyses of ~ 30,000 reference population cows, trait specific SNP weights resulted in up to 13% more reliable genomic predictions than unweighted SNP-BLUP, and improved genomic predictions for all three studied traits.
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Affiliation(s)
- Theo Meuwissen
- Faculty of Life Sciences, Norwegian University of Life Sciences, 1432, Ås, Norway.
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27
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Prizment A, Standafer A, Qu C, Beutel KM, Wang S, Huang WY, Lindblom A, Pearlman R, Van Guelpen B, Wolk A, Buchanan DD, Grant RC, Schmit SL, Platz EA, Joshu CE, Couper DJ, Peters U, Starr TK, Scott P, Pankratz N. Functional variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene are associated with increased risk of colorectal cancer. Hum Mol Genet 2025; 34:617-625. [PMID: 39825500 PMCID: PMC11924186 DOI: 10.1093/hmg/ddaf007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2024] [Revised: 12/17/2024] [Accepted: 01/14/2025] [Indexed: 01/20/2025] Open
Abstract
BACKGROUND Individuals with cystic fibrosis (CF; a recessive disorder) have an increased risk of colorectal cancer (CRC). Evidence suggests individuals with a single CFTR variant may also have increased CRC risk. METHODS Using population-based studies (GECCO, CORECT, CCFR, and ARIC; 53 785 CRC cases and 58 010 controls), we tested for an association between the most common CFTR variant (Phe508del) and CRC risk. For replication, we used whole exome sequencing data from UK Biobank (UKB; 5126 cases and 20 504 controls matched 4:1 based on genetic distance, age, and sex), and extended our analyses to all other heterozygous CFTR variants annotated as CF-causing. RESULTS In our meta-analysis of GECCO-CORECT-CCFR-ARIC, the odds ratio (OR) for CRC risk associated with Phe508del was 1.11 (P = 0.010). In our UKB replication, the OR for CRC risk associated with Phe508del was 1.28 (P = 0.002). The sequencing data from UKB also revealed an association between the presence of any other single CF-causing variant (excluding Phe508del) and CRC risk (OR = 1.33; P = 0.030). When stratifying CFTR variants by functional class, class I variants (no protein produced) had a stronger association (OR = 1.77; p = 0.002), while class II variants (misfolding and retention of the protein in the endoplasmic reticulum) other than Phe508del (OR = 1.75; p = 0.107) had similar effect size as Phe508del, and variants in classes III-VI had non-significant ORs less than 1.0 and/or were not present in cases. CONCLUSIONS CF-causing heterozygous variants, especially class I variants, are associated with a modest but statistically significant increased CRC risk. More research is needed to explain the biology underlying these associations.
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Affiliation(s)
- Anna Prizment
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
- Masonic Cancer Center, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Abby Standafer
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98019, USA
| | - Kathleen M Beutel
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Shuo Wang
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, MSC 9776, Bethesda, MD, 20892, USA
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, K1 Molekylär medicin och kirurgi, K1 MMK Klinisk genetik, 171 76 Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Eugeniavägen 3, 171 64 Solna, Sweden
| | - Rachel Pearlman
- Department of Internal Medicine, Division of Human Genetics, The Ohio State University Comprehensive Cancer Center, 2012 Kenny Rd, Columbus, OH, 43221, USA
| | - Bethany Van Guelpen
- Department of Radiation Sciences, Oncology Unit, 27C, Målpunkt QC11, NUS, Norrlands universitetssjukhus, Umeå University, 901 85 Umeå, Sweden
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, C6 Institutet för miljömedicin, C6 CVD-NUT-EPI Wolk, 171 77 Stockholm, Sweden
| | - Daniel D Buchanan
- Department of Clinical Pathology, University of Melbourne Center for Cancer Research, University of Melbourne, 305 Grattan Street, Melbourne, Victoria, 3010, Australia
| | - Robert C Grant
- UHN-Princess Margaret Cancer Centre, University of Toronto, 7-811 700 University Ave, Toronto, Ontario, M5G 1X6, Canada
| | - Stephanie L Schmit
- Genomic Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, Mail Code NE50, Cleveland, OH, 44195, USA
- Population and Cancer Prevention Program, Case Comprehensive Cancer Center, 10900 Euclid Ave, Cleveland, OH, 44106, USA
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street, Baltimore, MD, 21205, USA
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, 615 N Wolfe Street, Baltimore, MD, 21205, USA
| | - Corinne E Joshu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street, Baltimore, MD, 21205, USA
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, 615 N Wolfe Street, Baltimore, MD, 21205, USA
| | - David J Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill, 123 W Franklin Street, Suite 450, CB #8030, Chapel Hill, NC, 27516, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, 98019, USA
| | - Timothy K Starr
- Masonic Cancer Center, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
- Department of Obstetrics and Gynecology, Medical School, University of Minnesota, 515 Delaware St SE, Minneapolis, MN, 55455, USA
| | - Patricia Scott
- Masonic Cancer Center, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
- Department of Biomedical Sciences, University of Minnesota Medical School Duluth, 1035 University Drive, Duluth, MN, 55812, USA
| | - Nathan Pankratz
- Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN, 55455, USA
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Lin C, Xia M, Dai Y, Huang Q, Sun Z, Zhang G, Luo R, Peng Q, Li J, Wang X, Lin H, Gao X, Tang H, Shen X, Wang S, Jin L, Hao X, Zheng Y. Cross-ancestry analyses of Chinese and European populations reveal insights into the genetic architecture and disease implication of metabolites. CELL GENOMICS 2025:100810. [PMID: 40118068 DOI: 10.1016/j.xgen.2025.100810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Revised: 01/22/2025] [Accepted: 02/17/2025] [Indexed: 03/23/2025]
Abstract
Differential susceptibilities to various diseases and corresponding metabolite variations have been documented across diverse ethnic populations, but the genetic determinants of these disparities remain unclear. Here, we performed large-scale genome-wide association studies of 171 directly quantifiable metabolites from a nuclear magnetic resonance-based metabolomics platform in 10,792 Han Chinese individuals. We identified 15 variant-metabolite associations, eight of which were successfully replicated in an independent Chinese population (n = 4,480). By cross-ancestry meta-analysis integrating 213,397 European individuals from the UK Biobank, we identified 228 additional variant-metabolite associations and improved fine-mapping precision. Moreover, two-sample Mendelian randomization analyses revealed evidence that genetically predicted levels of triglycerides in high-density lipoprotein were associated with a higher risk of coronary artery disease and that of glycine with a lower risk of heart failure in both ancestries. These findings enhance our understanding of the shared and specific genetic architecture of metabolites as well as their roles in complex diseases across populations.
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Affiliation(s)
- Chenhao Lin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China; College of Food Science, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China
| | - Mingfeng Xia
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yuxiang Dai
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Qingxia Huang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Zhonghan Sun
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Guoqing Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; National Genomics Data Center& Bio-Med Big Data Center, University of Chinese Academy of Sciences, Chinese Academy of Science, Shanghai 200031, China
| | - Ruijin Luo
- Shanghai Southgene Technology Co., Ltd., Shanghai 201203, China
| | - Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jinxi Li
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Xiaofeng Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China; Fudan University-the People's Hospital of Rugao Joint Research Institute of Longevity and Aging, Rugao, Jiangsu 226500, China
| | - Huandong Lin
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xin Gao
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Xia Shen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China; Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, Guangdong 511400, China
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China.
| | - Xingjie Hao
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
| | - Yan Zheng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Center for Evolutionary Biology, and School of Life Sciences, Fudan University, Shanghai 200433, China; Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
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29
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Mori Y, van Dijk EHC, Miyake M, Hosoda Y, den Hollander AI, Yzer S, Miki A, Chen LJ, Ahn J, Takahashi A, Morino K, Nakao SY, Hoyng CB, Ng DSC, Cen LP, Chen H, Ng TK, Pang CP, Joo K, Sato T, Sakata Y, Tajima A, Tabara Y, Park KH, Matsuda F, Yamashiro K, Honda S, Nagasaki M, Boon CJF, Tsujikawa A. Genome-wide association and multi-omics analyses provide insights into the disease mechanisms of central serous chorioretinopathy. Sci Rep 2025; 15:9158. [PMID: 40097481 PMCID: PMC11914043 DOI: 10.1038/s41598-025-92210-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 02/26/2025] [Indexed: 03/19/2025] Open
Abstract
Central serous chorioretinopathy (CSC) is a major cause of vision loss, especially in middle-aged men, and its chronic subtype can lead to legal blindness. Despite its clinical importance, the underlying mechanisms of CSC need further clarification. In this study, we conducted a meta-analysis of three genome-wide association studies (GWASs) for CSC consisting of 8811 Asians and Caucasians, followed by replication in an additional 4338 Asians. We identified four genome-wide hits, including a novel hit (rs12960630 at LINC01924-CDH7, Pmeta = 2.97 × 10-9). A phenome-wide association study for rs12960630 showed a positive correlation between its CSC risk allele with plasma cortisol concentration. Expression/splicing quantitative trait loci (QTL) analyses showed an association of all these hits with the expression and/or splicing of genes in genital organs, which may explain the sex differences in CSC. Protein QTL also suggested the protein-level contribution of the complement factor H pathway to CSC pathogenesis.
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Affiliation(s)
- Yuki Mori
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Elon H C van Dijk
- Department of Ophthalmology, Leiden University Medical Center, Leiden, The Netherlands
| | - Masahiro Miyake
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan.
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
| | | | | | - Suzanne Yzer
- Department of Ophthalmology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Akiko Miki
- Division of Ophthalmology, Department of Surgery, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Li Jia Chen
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Jeeyun Ahn
- Seoul National University, College of Medicine, Seoul, Korea
- SMG-SNU Boramae Medical Center, Seoul, Korea
| | - Ayako Takahashi
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
| | - Kazuya Morino
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Shin-Ya Nakao
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Carel B Hoyng
- Department of Ophthalmology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Danny S C Ng
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Ling-Ping Cen
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
| | - Haoyu Chen
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
| | - Tsz Kin Ng
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
| | - Chi Pui Pang
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
| | - Kwangsic Joo
- Seoul National University, College of Medicine, Seoul, Korea
- Seoul National University Bundang Hospital, Seongnam, Korea
| | - Takehiro Sato
- Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Yasuhiko Sakata
- Department of Clinical Medicine and Development, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Atsushi Tajima
- Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Graduate School of Public Health, Shizuoka Graduate University of Public Health, Shizuoka, Japan
| | - Kyu Hyung Park
- Seoul National University, College of Medicine, Seoul, Korea
- Seoul National University Hospital, Seoul, Korea
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kenji Yamashiro
- Department of Ophthalmology and Visual Science, Kochi Medical School, Kochi University, Nankoku, Japan
| | - Shigeru Honda
- Department of Ophthalmology and Visual Sciences, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Masao Nagasaki
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
| | - Camiel J F Boon
- Department of Ophthalmology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Ophthalmology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Akitaka Tsujikawa
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Shogoin-kawahara, Sakyo, Kyoto, 606-8507, Japan
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30
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Lim J, Vujkovic M, Levin MG, Lorenz K, Voight BF, Zhang DY, Dudek MF, Pahl MC, Pippin JA, Su C, Manduchi E, Wells AD, Grant SF, Abramowitz S, Damrauer SM, Mukherjee S, Yang G, Kaplan DE, Rader DJ. Trans-ancestry genome-wide association meta-analysis of gallstone disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.03.16.25324077. [PMID: 40166541 PMCID: PMC11957090 DOI: 10.1101/2025.03.16.25324077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
Gallstone disease is a highly prevalent and costly gastrointestinal disease. Yet, genetic variation in susceptibility to gallstone disease and its implication in metabolic regulatory pathways remain to be explored. We report a trans-ancestry genome-wide association meta-analysis of gallstone disease including 88,063 cases and 1,490,087 controls in the UK Biobank, FinnGen, Biobank Japan, and Million Veteran Program. We identified 91 (37 novel) risk loci across the meta-analysis and found replication in statistically compelling signals in the All of Us Research Program. A polygenic risk score constructed from trans-ancestry lead variants was positively associated with liver chemistry and alpha-1-antitrypsin deficiency and negatively associated with total cholesterol and low-density lipoprotein levels among trans-ancestry and European ancestry groups in the Penn Medicine BioBank. Cross-trait colocalization analysis between risk loci and 44 liver, metabolic, renal, and inflammatory traits yielded 350 significant colocalizations as well as 97 significant colocalizations and 65 prioritized genes from expression quantitative trait loci from eight tissues. These findings broaden our understanding of the genetic architecture of gallstone disease.
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Affiliation(s)
- Junghyun Lim
- Division of Gastroenterology and Hepatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
- Division of Translational Medicine and Human Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Marijana Vujkovic
- Division of Translational Medicine and Human Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Michael G. Levin
- Division of Cardiovascular Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Kim Lorenz
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - David Y. Zhang
- Division of Translational Medicine and Human Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Max F. Dudek
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Chun Su
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Elisabetta Manduchi
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Endocrinology and Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Sarah Abramowitz
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Scott M. Damrauer
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Samiran Mukherjee
- Division of Gastroenterology and Hepatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Guoyi Yang
- Division of Translational Medicine and Human Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - David E. Kaplan
- Division of Gastroenterology and Hepatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | - Daniel J. Rader
- Division of Translational Medicine and Human Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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31
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Özkaraca Mİ, Agung M, Navarro P, Tenesa A. Divide and conquer approach for genome-wide association studies. Genetics 2025:iyaf019. [PMID: 40080676 DOI: 10.1093/genetics/iyaf019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Accepted: 01/18/2025] [Indexed: 03/15/2025] Open
Abstract
Genome-wide association studies (GWAS) are computationally intensive, requiring significant time and resources with computational complexity scaling at least linearly with sample size. Here, we present an accurate and resource-efficient pipeline for GWAS that mitigates the impact of sample size on computational demands. Our approach involves (1) randomly partitioning the cohort into equally sized sub-cohorts, (2) conducting independent GWAS within each sub-cohort, and (3) integrating the results using a novel meta-analysis technique that accounts for population structure and other confounders between sub-cohorts. Importantly, we demonstrate through simulations and real-data examples in humans that our approach effectively manages analyzing related individuals, a critical factor in real datasets, while controlling for inflated effect sizes, a phenomenon known as winner's curse. We show that our method achieves the same discovery levels as standard approaches but with significantly reduced computational costs. Additionally, it is well-suited for incremental GWAS as new samples are added over time. Our implementation within a bioinformatics workflow management system enhances reproducibility and scalability.
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Affiliation(s)
- Mustafa İsmail Özkaraca
- The Roslin Institute, The University of Edinburgh, Edinburgh EH25 9RG, UK
- The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Mulya Agung
- The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Pau Navarro
- The Roslin Institute, The University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Albert Tenesa
- The Roslin Institute, The University of Edinburgh, Edinburgh EH25 9RG, UK
- The Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh EH4 2XU, UK
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32
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Dias JA, Chen T, Xing H, Wang X, Rodriguez AA, Madduri RK, Kraft P, Zhang H. Evaluating Multi-Ancestry Genome-Wide Association Methods: Statistical Power, Population Structure, and Practical Implications. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.03.11.25323772. [PMID: 40162269 PMCID: PMC11952640 DOI: 10.1101/2025.03.11.25323772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
The increasing availability of diverse biobanks has enabled multi-ancestry genome-wide association studies (GWAS), enhancing the discovery of genetic variants across traits and diseases. However, the choice of an optimal method remains debated due to challenges in statistical power differences across ancestral groups and approaches to account for population structure. Two primary strategies exist: (1) Pooled analysis, which combines individuals from all genetic backgrounds into a single dataset while adjusting for population stratification using principal components, increasing the sample size and statistical power but requiring careful control of population stratification. (2) Meta-analysis, which performs ancestry-group-specific GWAS and subsequently combines summary statistics, potentially capturing fine-scale population structure, but facing limitations in handling admixed individuals. Using large-scale simulations with varying sample sizes and ancestry compositions, we compare these methods alongside real data analyses of eight continuous and five binary traits from the UK Biobank ( N ≈ 324,000 ) and All of Us Research Program ( N ≈ 207,000 ). Our results demonstrate that pooled analysis generally exhibits better statistical power while effectively adjusting for population stratification. We further present a theoretical framework linking power differences to allele frequency variations across populations. These findings, validated across both biobanks, highlight pooled analysis as a robust and scalable strategy for multi-ancestry GWAS, improving genetic discovery while maintaining rigorous population structure control.
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Affiliation(s)
- Julie-Alexia Dias
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Tony Chen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Hua Xing
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Instituters of Health, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Rockville, MD, USA
| | - Xiaoyu Wang
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Instituters of Health, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Rockville, MD, USA
| | - Alex A. Rodriguez
- Data Science and Learning division, Argonne National Laboratory, Lemont, IL, USA
| | - Ravi K. Madduri
- Data Science and Learning division, Argonne National Laboratory, Lemont, IL, USA
| | - Peter Kraft
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Instituters of Health, Bethesda, MD, USA
| | - Haoyu Zhang
- Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Instituters of Health, Bethesda, MD, USA
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33
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Yuan S, Chen J, Geng J, Zhao SS, Yarmolinsky J, Arkema EV, Abramowitz S, Levin MG, Tsilidis KK, Burgess S, Damrauer SM, Larsson SC. GWAS identifies genetic loci, lifestyle factors and circulating biomarkers that are risk factors for sarcoidosis. Nat Commun 2025; 16:2481. [PMID: 40075078 PMCID: PMC11903676 DOI: 10.1038/s41467-025-57829-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 03/03/2025] [Indexed: 03/14/2025] Open
Abstract
Sarcoidosis is a complex inflammatory disease with a strong genetic component. Here, we perform a genome-wide association study in 9755 sarcoidosis cases to identify risk loci and map associated genes. We then use transcriptome-wide association studies and enrichment analyses to explore pathways involved in sarcoidosis and use Mendelian randomization to examine associations with modifiable factors and circulating biomarkers. We identify 28 genomic loci associated with sarcoidosis, with the C1orf141-IL23R locus showing the largest effect size. We observe gene expression patterns related to sarcoidosis in the spleen, whole blood, and lung, and highlight 75 tissue-specific genes through transcriptome-wide association studies. Furthermore, we use enrichment analysis to establish key roles for T cell activation, leukocyte adhesion, and cytokine production in sarcoidosis. Additionally, we find associations between sarcoidosis and genetically predicted body mass index, interleukin-23 receptor, and eight circulating proteins.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
| | - Jie Chen
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Jiawei Geng
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Sizheng Steven Zhao
- Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Science, School of Biological Sciences, Faculty of Biological Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - James Yarmolinsky
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Elizabeth V Arkema
- Department of Medicine Solna, Clinical Epidemiology Division, Karolinska Institutet, Stockholm, Sweden
| | - Sarah Abramowitz
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Michael G Levin
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kostas K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Scott M Damrauer
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
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34
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Sonehara K, Uwamino Y, Saiki R, Takeshita M, Namba S, Uno S, Nakanishi T, Nishimura T, Naito T, Sato G, Kanai M, Liu A, Uchida S, Kurafuji T, Tanabe A, Arai T, Ohno A, Shibata A, Tanaka S, Wakui M, Kashimura S, Tomi C, Hara A, Yoshikawa S, Gotanda K, Misawa K, Tanaka H, Azekawa S, Wang QS, Edahiro R, Shirai Y, Yamamoto K, Nagao G, Suzuki T, Kiyoshi M, Ishii-Watabe A, Higashiue S, Kobayashi S, Yamaguchi H, Okazaki Y, Matsumoto N, Masumoto A, Koga H, Kanai A, Oda Y, Suzuki Y, Matsuda K, Kitagawa Y, Koike R, Kimura A, Kumanogoh A, Yoshimura A, Imoto S, Miyano S, Kanai T, Fukunaga K, Hasegawa N, Murata M, Matsushita H, Ogawa S, Okada Y, Namkoong H. Germline variants and mosaic chromosomal alterations affect COVID-19 vaccine immunogenicity. CELL GENOMICS 2025; 5:100783. [PMID: 40043710 PMCID: PMC11960526 DOI: 10.1016/j.xgen.2025.100783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 11/27/2024] [Accepted: 02/06/2025] [Indexed: 03/15/2025]
Abstract
Vaccine immunogenicity is influenced by the vaccinee's genetic background. Here, we perform a genome-wide association study of vaccine-induced SARS-CoV-2-specific immunoglobulin G (IgG) antibody titers and T cell immune responses in 1,559 mRNA-1273 and 537 BNT162b2 vaccinees of Japanese ancestry. SARS-CoV-2-specific antibody titers are associated with the immunoglobulin heavy chain (IGH) and major histocompatibility complex (MHC) locus, and T cell responses are associated with MHC. The lead variants at IGH contain a population-specific missense variant (rs1043109-C; p.Leu192Val) in the immunoglobulin heavy constant gamma 1 gene (IGHG1), with a strong decreasing effect (β = -0.54). Antibody-titer-associated variants modulate circulating immune regulatory proteins (e.g., LILRB4 and FCRL6). Age-related hematopoietic expanded mosaic chromosomal alterations (mCAs) affecting MHC and IGH also impair antibody production. MHC-/IGH-affecting mCAs confer infectious and immune disease risk, including sepsis and Graves' disease. Impacts of expanded mosaic loss of chromosomes X/Y on these phenotypes were examined. Altogether, both germline and somatic mutations contribute to adaptive immunity functions.
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Affiliation(s)
- Kyuto Sonehara
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoshifumi Uwamino
- Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan.
| | - Ryunosuke Saiki
- Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan
| | - Masaru Takeshita
- Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Shinichi Namba
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shunsuke Uno
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan
| | - Tomoko Nakanishi
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Japan Society for the Promotion of Science, Tokyo, Japan
| | - Tomoyasu Nishimura
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan; Keio University Health Center, Shinjuku-ku, Tokyo, Japan
| | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Go Sato
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Department of Gastroenterological Surgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland; Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Aoxing Liu
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sho Uchida
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan
| | | | - Akiko Tanabe
- Clinical Laboratory, Keio University Hospital, Tokyo, Japan
| | - Tomoko Arai
- Clinical Laboratory, Keio University Hospital, Tokyo, Japan
| | - Akemi Ohno
- Clinical Laboratory, Keio University Hospital, Tokyo, Japan
| | - Ayako Shibata
- Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Shiho Tanaka
- Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Masatoshi Wakui
- Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Shoko Kashimura
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan
| | - Chiharu Tomi
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan
| | - Akemi Hara
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan
| | - Shiori Yoshikawa
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan
| | - Keiko Gotanda
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan
| | - Kana Misawa
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan; Division of Pharmacodynamics, Keio University Faculty of Pharmacy, Tokyo, Japan
| | - Hiromu Tanaka
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Shuhei Azekawa
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Qingbo S Wang
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Ryuya Edahiro
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Yuya Shirai
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan; Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
| | - Kenichi Yamamoto
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan; Division of Health Science, Osaka University Graduate School of Medicine, Suita, Japan
| | - Genta Nagao
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Takuo Suzuki
- Division of Biological Chemistry and Biologicals, National Institute of Health Sciences, Kanagawa, Japan
| | - Masato Kiyoshi
- Division of Biological Chemistry and Biologicals, National Institute of Health Sciences, Kanagawa, Japan
| | - Akiko Ishii-Watabe
- Division of Biological Chemistry and Biologicals, National Institute of Health Sciences, Kanagawa, Japan
| | | | | | | | - Yasushi Okazaki
- Diagnostics and Therapeutics of Intractable Diseases, Intractable Disease Research Center, Graduate School of Medicine, Juntendo University, Tokyo, Japan
| | - Naoyuki Matsumoto
- Diagnostics and Therapeutics of Intractable Diseases, Intractable Disease Research Center, Graduate School of Medicine, Juntendo University, Tokyo, Japan
| | | | | | - Akinori Kanai
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Yoshiya Oda
- Department of Lipidomics, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan
| | - Yutaka Suzuki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yuko Kitagawa
- Department of Surgery, Keio University School of Medicine, Tokyo, Japan
| | - Ryuji Koike
- Health Science Research and Development Center (HeRD), Tokyo Medical and Dental University, Tokyo, Japan
| | - Akinori Kimura
- Institute of Research, Tokyo Medical and Dental University, Tokyo, Japan
| | - Atsushi Kumanogoh
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan; Department of Immunopathology, Immunology Frontier Research Center, Osaka University, Suita, Japan
| | - Akihiko Yoshimura
- Department of Microbiology and Immunology, Keio University School of Medicine, Tokyo, Japan
| | - Seiya Imoto
- Division of Health Medical Intelligence, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Satoru Miyano
- M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Takanori Kanai
- Division of Gastroenterology and Hepatology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Koichi Fukunaga
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Naoki Hasegawa
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan
| | - Mitsuru Murata
- Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan; Research Center of Clinical Medicine, International University of Health and Welfare, Tokyo, Japan
| | - Hiromichi Matsushita
- Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Seishi Ogawa
- Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan; Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan; Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institute, Stockholm, Sweden
| | - Yukinori Okada
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan; Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan.
| | - Ho Namkoong
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
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Chen R, Petrazzini BO, Duffy Á, Rocheleau G, Jordan D, Bansal M, Do R. Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease. Genome Biol 2025; 26:50. [PMID: 40065360 PMCID: PMC11892324 DOI: 10.1186/s13059-025-03518-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Accepted: 02/26/2025] [Indexed: 03/14/2025] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have identified common variants associated with metabolic dysfunction-associated steatotic liver disease (MASLD). However, rare coding variant studies have been limited by phenotyping challenges and small sample sizes. We test associations of rare and ultra-rare coding variants with proton density fat fraction (PDFF) and MASLD case-control status in 736,010 participants of diverse ancestries from the UK Biobank, All of Us, and BioMe and performed a trans-ancestral meta-analysis. We then developed models to accurately predict PDFF and MASLD status in the UK Biobank and tested associations with these predicted phenotypes to increase statistical power. RESULTS The trans-ancestral meta-analysis with PDFF and MASLD case-control status identifies two single variants and two gene-level associations in APOB, CDH5, MYCBP2, and XAB2. Association testing with predicted phenotypes, which replicates more known genetic variants from GWAS than true phenotypes, identifies 16 single variants and 11 gene-level associations implicating 23 additional genes. Two variants were polymorphic only among African ancestry participants and several associations showed significant heterogeneity in ancestry and sex-stratified analyses. In total, we identified 27 genes, of which 3 are monogenic causes of steatosis (APOB, G6PC1, PPARG), 4 were previously associated with MASLD (APOB, APOC3, INSR, PPARG), and 23 had supporting clinical, experimental, and/or genetic evidence. CONCLUSIONS Our results suggest that trans-ancestral association analyses can identify ancestry-specific rare and ultra-rare coding variants in MASLD pathogenesis. Furthermore, we demonstrate the utility of machine learning in genetic investigations of difficult-to-phenotype diseases in trans-ancestral biobanks.
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Affiliation(s)
- Robert Chen
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ben Omega Petrazzini
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Áine Duffy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ghislain Rocheleau
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel Jordan
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Meena Bansal
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Kim J, Williams A, Noh H, Jasper EA, Jones SH, Jaworski JA, Shuey MM, Ruiz-Narváez EA, Wise LA, Palmer JR, Connolly J, Keaton JM, Denny JC, Khan A, Abbass MA, Rasmussen-Torvik LJ, Kottyan LC, Madhivanan P, Krupp K, Wei WQ, Edwards TL, Velez Edwards DR, Hellwege JN. Genome-wide meta-analysis identifies novel risk loci for uterine fibroids within and across multiple ancestry groups. Nat Commun 2025; 16:2273. [PMID: 40050615 PMCID: PMC11885530 DOI: 10.1038/s41467-025-57483-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 02/12/2025] [Indexed: 03/09/2025] Open
Abstract
Uterine leiomyomata or fibroids are highly heritable, common, and benign tumors of the uterus with poorly understood etiology. Previous GWAS have reported 72 associated genes but included limited numbers of non-European individuals. Here, we identify 11 novel genes associated with fibroids across multi-ancestry and ancestry-stratified GWAS analyses. We replicate a known fibroid GWAS gene in African ancestry individuals and estimate the SNP-based heritability of fibroids in African ancestry populations as 15.9%. Using genetically predicted gene expression and colocalization analyses, we identify 46 novel genes associated with fibroids. These genes are significantly enriched in cancer, cell death and survival, reproductive system disease, and cellular growth and proliferation networks. We also find that increased predicted expression of HEATR3 in uterine tissue is associated with fibroids across ancestry strata. Overall, we report genetic variants associated with fibroids coupled with functional and gene pathway enrichment analyses.
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Affiliation(s)
- Jeewoo Kim
- Division of Quantitative and Clinical Sciences, Department of Obstetrics & Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
- Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Ariel Williams
- Center for Precision Health Research, National Human Genome Research Institute, National Institute of Health, Bethesda, MD, USA
| | - Hannah Noh
- Tufts University Medical School Graduate Programs, Boston, MA, USA
- Medicine, Health and Society, Vanderbilt University, Nashville, TN, USA
| | - Elizabeth A Jasper
- Division of Quantitative and Clinical Sciences, Department of Obstetrics & Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sarah H Jones
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA
| | - James A Jaworski
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Megan M Shuey
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Edward A Ruiz-Narváez
- Department of Nutritional Sciences University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Lauren A Wise
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Julie R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA, USA
| | - John Connolly
- Center for Applied Genomics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jacob M Keaton
- Center for Precision Health Research, National Human Genome Research Institute, National Institute of Health, Bethesda, MD, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Joshua C Denny
- Center for Precision Health Research, National Human Genome Research Institute, National Institute of Health, Bethesda, MD, USA
- All of Us Research Program, Office of the Director, National Institutes of Health, Bethesda, MD, USA
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Mohammad A Abbass
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Leah C Kottyan
- Center for Autoimmune Genomics and Etiology, Department of Pediatrics, Cincinnati Children's Hospital, University of Cincinnati, Cincinnati, OH, USA
| | - Purnima Madhivanan
- University of Arizona Comprehensive Cancer Center, Tucson, AZ, USA
- Department of Health Promotion Sciences, Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
- Public Health Research Institute of India, Mysuru, India
- Department of Medicine, College of Medicine, University of Arizona, Tucson, AZ, USA
| | - Karl Krupp
- University of Arizona Comprehensive Cancer Center, Tucson, AZ, USA
- Public Health Research Institute of India, Mysuru, India
- Public Health Practice, Policy, & Translational Research Department, Mel & Enid Zuckerman College of Public Health, Phoenix, AZ, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Digna R Velez Edwards
- Division of Quantitative and Clinical Sciences, Department of Obstetrics & Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
- Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
- Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Jacklyn N Hellwege
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA.
- Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA.
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Xu X, Xu L, Lang Z, Sun G, Pan J, Li X, Bian Z, Wu X. Identification of potential susceptibility loci for non-small cell lung cancer through whole genome sequencing in circadian rhythm genes. Sci Rep 2025; 15:7825. [PMID: 40050692 PMCID: PMC11885630 DOI: 10.1038/s41598-025-92083-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Accepted: 02/25/2025] [Indexed: 03/09/2025] Open
Abstract
Lung cancer is a malignant tumor with a high morbidity and mortality rate worldwide, causing an increasing disease burden. Of these, the most common type is non-small cell lung cancer (NSCLC), which accounts for 80-85% of all lung cancer cases. Genetic research is crucial for continuously discovering susceptibility genes related to lung cancer for in-depth study. The role of genetic predisposition in the development of NSCLC, particularly within circadian rhythm pathways known to govern various physiological processes, is increasingly acknowledged. Yet, the association between genetic variants of circadian rhythm-related genes and NSCLC susceptibility among Chinese populations is not fully understood. This study carried out a two-phase (discovery and validation stages) research design to identify genetic variants associated with NSCLC risk within the circadian rhythm pathway. We employed extensive whole-genome sequencing (WGS) for 1,104 NSCLC cases and 9,635 controls. FastGWA-GLMM was used for single-locus risk association analysis of NSCLC, and we screened candidate SNPs in the validation set that comprised 4,444 cases and 174,282 controls from the Biobank Japan Project (BBJ). Furthermore, GCTA-COJO conditional analysis was utilized to confirm SNPs related to NSCLC risk. Finally, potential genetic variations that may regulate gene expression were explored in GTEx and QTLbase. RNA sequencing data were utilized for transcriptomic verification. Our study identified eight candidate SNPs associated with NSCLC susceptibility within the circadian rhythm pathway that met the requirement with P < 0.05 in both the discovery and validation populations. After conditional analysis, five of these SNPs remained. The A allele of CUL1 rs78524436 (ORmeta = 1.18, 95%CI: 1.09-1.29, Pmeta = 7.99e-5) and the A allele of TEF rs9611588 (ORmeta = 1.06, 95%CI: 1.02-1.10, Pmeta = 1.28e-3) were associated with an increased risk of NSCLC. The A allele of FBXL21 rs2069868 (ORmeta = 0.86, 95%CI: 0.80-0.96, Pmeta = 4.78e-4), the T allele of CSNK1D rs147316973 (ORmeta = 0.76, 95%CI: 0.65-0.88, Pmeta = 5.93e-4), and the A allele of RORA rs1589701 (ORmeta = 0.94, 95%CI: 0.91-0.98, Pmeta = 3.40e-3) were associated with a lower risk of NSCLC, separately. The eQTL results revealed an association between RORA rs1589701 and TEF rs9611588 with the expression levels of RORA and TEF, respectively. Transcriptome data indicated that RORA and TEF showed lower expression levels in tumor tissues compared to normal tissues (P < 0.001). Moreover, poorer survival was observed in patients with lower RORA and TEF expressions (log-rank P < 0.05). Our findings spotlight potential susceptibility loci within circadian rhythm pathway genes that modulate NSCLC carcinogenesis, which enriches the understanding of the genetic susceptibility of NSCLC in the Chinese population and provides a more solid basis for exploring the biological mechanism of circadian rhythm genes in NSCLC.
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Affiliation(s)
- Xiaohang Xu
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Zhejiang Key Laboratory of Intelligent Preventive Medicine, Hangzhou, 310058, China
| | - Luopiao Xu
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Zhejiang Key Laboratory of Intelligent Preventive Medicine, Hangzhou, 310058, China
| | - Zeyong Lang
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Gege Sun
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Junlong Pan
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Xue Li
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Zhejiang Key Laboratory of Intelligent Preventive Medicine, Hangzhou, 310058, China
| | - Zilong Bian
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Xifeng Wu
- Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Zhejiang Key Laboratory of Intelligent Preventive Medicine, Hangzhou, 310058, China.
- National Institute for Data Science in Health and Medicine, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
- School of Medicine and Health Science, George Washington University, Washington, DC, USA.
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Yang L, Sadler MC, Altman RB. Genetic association studies using disease liabilities from deep neural networks. Am J Hum Genet 2025; 112:675-692. [PMID: 39986278 PMCID: PMC11948217 DOI: 10.1016/j.ajhg.2025.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Revised: 01/23/2025] [Accepted: 01/24/2025] [Indexed: 02/24/2025] Open
Abstract
The case-control study is a widely used method for investigating the genetic underpinnings of binary traits. However, long-term, prospective cohort studies often grapple with absent or evolving health-related outcomes. Here, we propose two methods, liability and meta, for conducting genome-wide association studies (GWASs) that leverage disease liabilities calculated from deep patient phenotyping. Analyzing 38 common traits in ∼300,000 UK Biobank participants, we identified an increased number of loci in comparison to the number identified by the conventional case-control approach, and there were high replication rates in larger external GWASs. Further analyses confirmed the disease specificity of the genetic architecture; the meta method demonstrated higher robustness when phenotypes were imputed with low accuracy. Additionally, polygenic risk scores based on disease liabilities more effectively predicted newly diagnosed cases in the 2022 dataset, which were controls in the earlier 2019 dataset. Our findings demonstrate that integrating high-dimensional phenotypic data into deep neural networks enhances genetic association studies while capturing disease-relevant genetic architecture.
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Affiliation(s)
- Lu Yang
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Department of Computer Science, Stanford University, Stanford, CA 94305, USA.
| | - Marie C Sadler
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; University Center for Primary Care and Public Health, 1010 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Russ B Altman
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Computer Science, Stanford University, Stanford, CA 94305, USA
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39
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Bovo S, Ribani A, Fanelli F, Galimberti G, Martelli PL, Trevisi P, Bertolini F, Bolner M, Casadio R, Dall'Olio S, Gallo M, Luise D, Mazzoni G, Schiavo G, Taurisano V, Zambonelli P, Bosi P, Pagotto U, Fontanesi L. Merging metabolomics and genomics provides a catalog of genetic factors that influence molecular phenotypes in pigs linking relevant metabolic pathways. Genet Sel Evol 2025; 57:11. [PMID: 40050712 PMCID: PMC11887101 DOI: 10.1186/s12711-025-00960-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Accepted: 02/18/2025] [Indexed: 03/09/2025] Open
Abstract
BACKGROUND Metabolomics opens novel avenues to study the basic biological mechanisms underlying complex traits, starting from characterization of metabolites. Metabolites and their levels in a biofluid represent simple molecular phenotypes (metabotypes) that are direct products of enzyme activities and relate to all metabolic pathways, including catabolism and anabolism of nutrients. In this study, we demonstrated the utility of merging metabolomics and genomics in pigs to uncover a large list of genetic factors that influence mammalian metabolism. RESULTS We obtained targeted characterization of the plasma metabolome of more than 1300 pigs from two populations of Large White and Duroc pig breeds. The metabolomic profiles of these pigs were used to identify genetically influenced metabolites by estimating the heritability of the level of 188 metabolites. Then, combining breed-specific genome-wide association studies of single metabolites and their ratios and across breed meta-analyses, we identified a total of 97 metabolite quantitative trait loci (mQTL), associated with 126 metabolites. Using these results, we constructed a human-pig comparative catalog of genetic factors influencing the metabolomic profile. Whole genome resequencing data identified several putative causative mutations for these mQTL. Additionally, based on a major mQTL for kynurenine level, we designed a nutrigenetic study feeding piglets that carried different genotypes at the candidate gene kynurenine 3-monooxygenase (KMO) varying levels of tryptophan and demonstrated the effect of this genetic factor on the kynurenine pathway. Furthermore, we used metabolomic profiles of Large White and Duroc pigs to reconstruct metabolic pathways using Gaussian Graphical Models, which included perturbation of the identified mQTL. CONCLUSIONS This study has provided the first catalog of genetic factors affecting molecular phenotypes that describe the pig blood metabolome, with links to important metabolic pathways, opening novel avenues to merge genetics and nutrition in this livestock species. The obtained results are relevant for basic and applied biology and to evaluate the pig as a biomedical model. Genetically influenced metabolites can be further exploited in nutrigenetic approaches in pigs. The described molecular phenotypes can be useful to dissect complex traits and design novel feeding, breeding and selection programs in pigs.
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Affiliation(s)
- Samuele Bovo
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy.
| | - Anisa Ribani
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Flaminia Fanelli
- Endocrinology Research Group, Center for Applied Biomedical Research, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
- Division of Endocrinology and Prevention and Care of Diabetes, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Policlinico di Sant'Orsola, Bologna, Italy
| | - Giuliano Galimberti
- Department of Statistical Sciences "Paolo Fortunati", University of Bologna, Bologna, Italy
| | - Pier Luigi Martelli
- Biocomputing Group, Department of Pharmacology and Biotechnology, University of Bologna, Bologna, Italy
| | - Paolo Trevisi
- Laboratory on Animal Nutrition and Feeding for Livestock Sustainability and Resilience, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Francesca Bertolini
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Matteo Bolner
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Rita Casadio
- Biocomputing Group, Department of Pharmacology and Biotechnology, University of Bologna, Bologna, Italy
| | - Stefania Dall'Olio
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | | | - Diana Luise
- Laboratory on Animal Nutrition and Feeding for Livestock Sustainability and Resilience, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Gianluca Mazzoni
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Giuseppina Schiavo
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Valeria Taurisano
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Paolo Zambonelli
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Paolo Bosi
- Laboratory on Animal Nutrition and Feeding for Livestock Sustainability and Resilience, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Uberto Pagotto
- Endocrinology Research Group, Center for Applied Biomedical Research, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
- Division of Endocrinology and Prevention and Care of Diabetes, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Policlinico di Sant'Orsola, Bologna, Italy
| | - Luca Fontanesi
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy.
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Jung HU, Jung H, Baek EJ, Kang JO, Kwon SY, You J, Lim JE, Oh B. Assessment of polygenic risk score performance in East Asian populations for ten common diseases. Commun Biol 2025; 8:374. [PMID: 40045046 PMCID: PMC11882803 DOI: 10.1038/s42003-025-07767-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Accepted: 02/18/2025] [Indexed: 03/09/2025] Open
Abstract
Polygenic risk score (PRS) uses genetic variants to assess disease susceptibility. While PRS performance is well-studied in Europeans, its accuracy in East Asians is less explored. This study evaluated PRSs for ten diseases in the Health Examinees (HEXA) cohort (n = 55,870) in Korea. Single-population PRSs were constructed using PRS-CS, LDpred2, and Lassosum based on East Asian GWAS summary statistics (sample sizes: 51,442-341,204), while cross-population PRSs were developed using PRS-CSx and CT-SLEB by integrating European and East Asian GWAS data. PRS-CS consistently outperformed other single-population methods across key metrics, including the likelihood ratio test (LRT), odds ratio per standard deviation (perSD OR), net reclassification improvement (NRI), and area under the curve (AUC). Cross-population PRSs further improved predictive performance, with average increases of 1.08-fold (LRT), 1.07-fold (perSD OR), and 1.15-fold (NRI) across seven diseases with statistical significance, and a 1.01-fold improvement in AUC. Differences in R² between single- and cross-population PRSs were statistically significant for five diseases, showing an average increase of 1.13%. Cross-population PRSs achieved 87.8% of the predictive performance observed in European PRSs. These findings highlight the benefits of integrating European GWAS data while underscoring the need for larger East Asian datasets to improve prediction accuracy.
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Affiliation(s)
- Hae-Un Jung
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea
| | - Hyein Jung
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea
| | | | - Ji-One Kang
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Shin Young Kwon
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea
| | | | - Ji Eun Lim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea.
| | - Bermseok Oh
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
- Mendel Inc, Seoul, Republic of Korea.
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea.
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41
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Toikumo S, Davis C, Jinwala Z, Khan Y, Jennings M, Davis L, Sanchez-Roige S, Kember RL, Kranzler HR. Gene discovery and pleiotropic architecture of Chronic Pain in a Genome-wide Association Study of >1.2 million Individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.02.28.25323112. [PMID: 40093235 PMCID: PMC11908286 DOI: 10.1101/2025.02.28.25323112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 03/19/2025]
Abstract
Chronic pain is highly prevalent worldwide, and genome-wide association studies (GWAS) have identified a growing number of chronic pain loci. To further elucidate its genetic architecture, we leveraged data from 1,235,695 European ancestry individuals across three biobanks. In a meta-analytic GWAS, we identified 343 independent loci for chronic pain, 92 of which were new. Sex-specific meta-analyses revealed 115 independent loci (12 of which were new) for males (N = 583,066) and 12 loci (two of which were new) for females (N = 241,266). Multi-omics gene prioritization analyses highlighted 490 genes associated with chronic pain through their effects on brain- and blood-specific regulation. Loci associated with increased risk for chronic pain were also associated with increased risk for multiple other traits, with Mendelian randomization analyses showing that chronic pain was causally associated with psychiatric disorders, substance use disorders, and C-reactive protein levels. Chronic pain variants also exhibited pleiotropic associations with cortical area brain structures. This study expands our knowledge of the genetics of chronic pain and its pathogenesis, highlighting the importance of its pleiotropy with multiple disorders and elucidating its multi-omic pathophysiology.
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Affiliation(s)
- Sylvanus Toikumo
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104, USA
- Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, 3535 Market Street, Philadelphia, PA 19104
| | - Christal Davis
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104, USA
- Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, 3535 Market Street, Philadelphia, PA 19104
| | - Zeal Jinwala
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104, USA
- Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, 3535 Market Street, Philadelphia, PA 19104
| | - Yousef Khan
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104, USA
- Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, 3535 Market Street, Philadelphia, PA 19104
| | - Mariela Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Lea Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Rachel L. Kember
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104, USA
- Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, 3535 Market Street, Philadelphia, PA 19104
| | - Henry R. Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA 19104, USA
- Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, 3535 Market Street, Philadelphia, PA 19104
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42
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Singh A, Alarcon C, Nutescu EA, O'Brien TJ, Tuck M, Gong L, Klein TE, Meltzer DO, Johnson JA, Cavallari LH, Perera MA. Local ancestry informed GWAS of warfarin dose requirement in African Americans identifies a novel CYP2C19 splice QTL. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.03.03.25323247. [PMID: 40093246 PMCID: PMC11908343 DOI: 10.1101/2025.03.03.25323247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 03/19/2025]
Abstract
African Americans (AAs) are underrepresented in pharmacogenomics which has led to a significant gap in knowledge. AAs are admixed and can inherit specific loci from either their African or European ancestor, known as local ancestry (LA). A previous study in AAs identified single nucleotide polymorphisms (SNPs) located in the CYP2C cluster that are associated with warfarin dose. However, LA was not considered in this study. An IWPC cohort (N=340) was used to determine the LA-adjusted association with warfarin dose. Ancestry-specific GWAS's were conducted with TRACTOR and ancestry tracts were meta-analyzed using METAL. We replicated top associations in the independent ACCOuNT cohort of AAs (N=309) and validated associations in a warfarin pharmacokinetic study in AAs. To elucidate functional roles of top associations, we performed short-read RNA-sequencing from AA hepatocytes carrying each genotype for expression of CYP2C9 and CYP2C19. We identified 6 novel genome-wide significant SNPs (P<5E-8) in the CYP2C locus (lead SNP, rs7906871 (P=3.14E-8)). These associations were replicated (P≤2.76E-5) and validated with a pharmacokinetic association for S-Warfarin concentration in plasma (P=0.048). rs7906871 explains 6.0% of the variability in warfarin dose in AAs. Multivariate regression including rs7906871, previously associated SNPs, clinical and demographic factors explain 37% of dose variability, greater than previously reported studies in AAs. RNA-seq data in AA hepatocytes identified a significant alternate exon inclusion event between exons 6 and 7 in CYP2C19 for carriers of rs7906871. In conclusion, we have found and replicated a novel CYP2C variant associated with warfarin dose requirement and potential functional consequences to CYP2C19.
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Affiliation(s)
- Anmol Singh
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Cristina Alarcon
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Edith A Nutescu
- Department of Pharmacy Practice, University of Illinois Chicago College of Pharmacy, Chicago, IL
| | - Travis J O'Brien
- Departments of Pharmacology and Physiology, George Washington University, Washington DC
| | | | - Li Gong
- Department of Biomedical Data Science, Stanford University, Stanford, CA
| | - Teri E Klein
- Departments of Biomedical Data Science, Medicine and Genetics, Stanford University, Stanford, CA
| | - David O Meltzer
- Section of Hospital Medicine, Department of Medicine, University of Chicago, Chicago IL
| | - Julie A Johnson
- Departments of Internal Medicine and Pharmaceutics & Pharmacology, Colleges of Medicine and Pharmacy, Clinical and Translational Science Institute, The Ohio State University, Columbus, OH
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL
| | - Minoli A Perera
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, IL
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43
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Henry A, Mo X, Finan C, Chaffin MD, Speed D, Issa H, Denaxas S, Ware JS, Zheng SL, Malarstig A, Gratton J, Bond I, Roselli C, Miller D, Chopade S, Schmidt AF, Abner E, Adams L, Andersson C, Aragam KG, Ärnlöv J, Asselin G, Raja AA, Backman JD, Bartz TM, Biddinger KJ, Biggs ML, Bloom HL, Boersma E, Brandimarto J, Brown MR, Brunak S, Bruun MT, Buckbinder L, Bundgaard H, Carey DJ, Chasman DI, Chen X, Cook JP, Czuba T, de Denus S, Dehghan A, Delgado GE, Doney AS, Dörr M, Dowsett J, Dudley SC, Engström G, Erikstrup C, Esko T, Farber-Eger EH, Felix SB, Finer S, Ford I, Ghanbari M, Ghasemi S, Ghouse J, Giedraitis V, Giulianini F, Gottdiener JS, Gross S, Guðbjartsson DF, Gui H, Gutmann R, Hägg S, Haggerty CM, Hedman ÅK, Helgadottir A, Hemingway H, Hillege H, Hyde CL, Aagaard Jensen B, Jukema JW, Kardys I, Karra R, Kavousi M, Kizer JR, Kleber ME, Køber L, Koekemoer A, Kuchenbaecker K, Lai YP, Lanfear D, Langenberg C, Lin H, Lind L, Lindgren CM, Liu PP, London B, Lowery BD, Luan J, Lubitz SA, Magnusson P, Margulies KB, Marston NA, Martin H, März W, Melander O, Mordi IR, Morley MP, Morris AP, Morrison AC, Morton L, Nagle MW, Nelson CP, Niessner A, Niiranen T, Noordam R, Nowak C, O'Donoghue ML, Ostrowski SR, Owens AT, Palmer CNA, Paré G, Pedersen OB, Perola M, Pigeyre M, Psaty BM, Rice KM, Ridker PM, Romaine SPR, Rotter JI, Ruff CT, Sabatine MS, Sallah N, Salomaa V, Sattar N, Shalaby AA, Shekhar A, Smelser DT, Smith NL, Sørensen E, Srinivasan S, Stefansson K, Sveinbjörnsson G, Svensson P, Tammesoo ML, Tardif JC, Teder-Laving M, Teumer A, Thorgeirsson G, Thorsteinsdottir U, Torp-Pedersen C, Tragante V, Trompet S, Uitterlinden AG, Ullum H, van der Harst P, van Heel D, van Setten J, van Vugt M, Veluchamy A, Verschuuren M, Verweij N, Vissing CR, Völker U, Voors AA, Wallentin L, Wang Y, Weeke PE, Wiggins KL, Williams LK, Yang Y, Yu B, Zannad F, Zheng C, Asselbergs FW, Cappola TP, Dubé MP, Dunn ME, Lang CC, Samani NJ, Shah S, Vasan RS, Smith JG, Holm H, Shah S, Ellinor PT, Hingorani AD, Wells Q, Lumbers RT. Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes. Nat Genet 2025:10.1038/s41588-024-02064-3. [PMID: 40038546 DOI: 10.1038/s41588-024-02064-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 12/17/2024] [Indexed: 03/06/2025]
Abstract
Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment.
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Affiliation(s)
- Albert Henry
- Institute of Cardiovascular Science, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
| | - Xiaodong Mo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Chris Finan
- Institute of Cardiovascular Science, University College London, London, UK
| | - Mark D Chaffin
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Doug Speed
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Hanane Issa
- Institute of Health Informatics, University College London, London, UK
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
- British Heart Foundation Data Science Centre, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - James S Ware
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- National Heart & Lung Institute, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
- Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK
- Hammersmith Hospital, Imperial College Hospitals NHS Trust, London, UK
| | - Sean L Zheng
- National Heart & Lung Institute, Imperial College London, London, UK
- Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK
| | - Anders Malarstig
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden
- Pfizer Worldwide Research & Development, Cambridge, MA, USA
| | - Jasmine Gratton
- Institute of Cardiovascular Science, University College London, London, UK
| | - Isabelle Bond
- Institute of Cardiovascular Science, University College London, London, UK
| | - Carolina Roselli
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - David Miller
- Division of Biosciences, University College London, London, UK
| | - Sandesh Chopade
- Institute of Cardiovascular Science, University College London, London, UK
| | - A Floriaan Schmidt
- Institute of Cardiovascular Science, University College London, London, UK
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Erik Abner
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Charlotte Andersson
- Department of Cardiology, Herlev Gentofte Hospital, Herlev, Denmark
- National Heart, Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
| | - Krishna G Aragam
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Johan Ärnlöv
- Department of Neurobiology, Care Sciences and Society/Section of Family Medicine and Primary Care, Karolinska Institutet, Stockholm, Sweden
- School of Health and Social Sciences, Dalarna University, Falun, Sweden
| | | | - Anna Axelsson Raja
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Joshua D Backman
- Analytical Genetics, Regeneron Genetics Center, Tarrytown, NY, USA
| | - Traci M Bartz
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Kiran J Biddinger
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Mary L Biggs
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Heather L Bloom
- Department of Medicine, Division of Cardiology, Emory University Medical Center, Atlanta, GA, USA
| | - Eric Boersma
- Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jeffrey Brandimarto
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael R Brown
- Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas School of Public Health, Houston, TX, USA
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mie Topholm Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
| | | | - Henning Bundgaard
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - David J Carey
- Department of Molecular and Functional Genomics, Geisinger, Danville, PA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Xing Chen
- Pfizer Worldwide Research & Development, Cambridge, MA, USA
| | - James P Cook
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Tomasz Czuba
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg University and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Simon de Denus
- Montreal Heart Institute, Montreal, Quebec, Canada
- Faculty of Pharmacy, Université de Montréal, Montreal, Quebec, Canada
| | - Abbas Dehghan
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Graciela E Delgado
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Alexander S Doney
- Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Joseph Dowsett
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Samuel C Dudley
- Department of Medicine, Cardiovascular Division, University of Minnesota, Minneapolis, MN, USA
| | - Gunnar Engström
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Deparment of Clinical Medicine, Health, Aarhus University, Aarhus, Denmark
| | - Tõnu Esko
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Eric H Farber-Eger
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephan B Felix
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Sarah Finer
- Centre for Primary Care and Public Health, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Ian Ford
- Robertson Center for Biostatistics, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Sahar Ghasemi
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Jonas Ghouse
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - John S Gottdiener
- Department of Medicine, Division of Cardiology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Stefan Gross
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Daníel F Guðbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Hongsheng Gui
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA
| | - Rebecca Gutmann
- Division of Cardiovascular Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - Åsa K Hedman
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden
| | | | - Harry Hemingway
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
| | - Hans Hillege
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Craig L Hyde
- Pfizer Worldwide Research & Development, Cambridge, MA, USA
| | | | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, LUMC, Leiden, the Netherlands
| | - Isabella Kardys
- Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ravi Karra
- Department of Medicine, Division of Cardiology, Duke University Medical Center, Durham, NC, USA
- Department of Pathology, Duke University Medical Center, Durham, NC, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jorge R Kizer
- Cardiology Section, San Francisco Veterans Affairs Health System, and Departments of Medicine, Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Lars Køber
- Department of Cardiology, Nordsjaellands Hospital, Copenhagen, Denmark
| | - Andrea Koekemoer
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Karoline Kuchenbaecker
- Division of Psychiatry, University College London, London, UK
- UCL Genetics Institute, University College London, London, UK
| | - Yi-Pin Lai
- Pfizer Worldwide Research & Development, Cambridge, MA, USA
| | - David Lanfear
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA
- Heart and Vascular Institute, Henry Ford Hospital, Detroit, MI, USA
| | - Claudia Langenberg
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, Berlin, Germany
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Honghuang Lin
- National Heart, Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Cecilia M Lindgren
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Peter P Liu
- University of Ottawa Heart Institute, Ottawa, Ontario, Canada
- Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Barry London
- Division of Cardiovascular Medicine and Abboud Cardiovascular Research Center, University of Iowa, Iowa City, IA, USA
| | - Brandon D Lowery
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Steven A Lubitz
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Patrik Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kenneth B Margulies
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicholas A Marston
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA, USA
| | - Hilary Martin
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, University of Heidelberg, Heidelberg, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
- Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany
| | - Olle Melander
- Department of Internal Medicine, Clinical Sciences, Lund University and Skåne University Hospital, Malmö, Sweden
| | - Ify R Mordi
- Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
| | - Michael P Morley
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Alanna C Morrison
- Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas School of Public Health, Houston, TX, USA
| | - Lori Morton
- Cardiovascular Research, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Alexander Niessner
- Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, Vienna, Austria
| | - Teemu Niiranen
- Department of Medicine, Turku University Hospital and University of Turku, Turku, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Christoph Nowak
- Department of Neurobiology, Care Sciences and Society/Section of Family Medicine and Primary Care, Karolinska Institutet, Stockholm, Sweden
| | - Michelle L O'Donoghue
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA, USA
| | - Sisse Rye Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anjali T Owens
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Colin N A Palmer
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
| | - Guillaume Paré
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton, Ontario, Canada
| | - Ole Birger Pedersen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, Finland
| | - Marie Pigeyre
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Simon P R Romaine
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA, USA
- Departments of Pediatrics and Medicine, Harbor-UCLA Medical Center, Torrance, CA, USA
- Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Christian T Ruff
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA, USA
| | - Marc S Sabatine
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA, USA
| | - Neneh Sallah
- Institute of Health Informatics, University College London, London, UK
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Naveed Sattar
- BHF Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
| | - Alaa A Shalaby
- Department of Medicine, Division of Cardiology, University of Pittsburgh Medical Center and VA Pittsburgh HCS, Pittsburgh, PA, USA
| | - Akshay Shekhar
- Cardiovascular Research, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Diane T Smelser
- Department of Molecular and Functional Genomics, Geisinger, Danville, PA, USA
| | - Nicholas L Smith
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Veterans Affairs Office of Research & Development, Seattle Epidemiologic Research and Information Center, Seattle, WA, USA
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Sundararajan Srinivasan
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Department of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Per Svensson
- Department of Cardiology, Söderjukhuset, Stockholm, Sweden
- Department of Clinical Science and Education-Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Mari-Liis Tammesoo
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jean-Claude Tardif
- Montreal Heart Institute, Montreal, Quebec, Canada
- Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Maris Teder-Laving
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Alexander Teumer
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Guðmundur Thorgeirsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Department of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Internal Medicine, Division of Cardiology, National University Hospital of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Department of Medicine, University of Iceland, Reykjavik, Iceland
| | | | | | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Andre G Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
| | - David van Heel
- Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, London, UK
| | - Jessica van Setten
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Marion van Vugt
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Abirami Veluchamy
- Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
| | - Monique Verschuuren
- Department Life Course and Health, Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Christoffer Rasmus Vissing
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Adriaan A Voors
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Lars Wallentin
- Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Peter E Weeke
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Kerri L Wiggins
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - L Keoki Williams
- Center for Individualized and Genomic Medicine Research, Department of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA
| | - Yifan Yang
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas School of Public Health, Houston, TX, USA
| | - Faiez Zannad
- Université de Lorraine, CHU de Nancy, Inserm and INI-CRCT (F-CRIN), Institut Lorrain du Coeur et des Vaisseaux, Vandoeuvre Lès Nancy, France
| | - Chaoqun Zheng
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Folkert W Asselbergs
- Institute of Health Informatics, University College London, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Thomas P Cappola
- Penn Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marie-Pierre Dubé
- Montreal Heart Institute, Montreal, Quebec, Canada
- Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Michael E Dunn
- Cardiovascular Research, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Chim C Lang
- Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Svati Shah
- Department of Medicine, Division of Cardiology, Duke University Medical Center, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
- Duke Molecular Physiology Institute, Durham, NC, USA
| | - Ramachandran S Vasan
- National Heart, Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA
- Sections of Cardiology, Preventive Medicine and Epidemiology, Department of Medicine, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - J Gustav Smith
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg University and Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
- Wallenberg Center for Molecular Medicine and Lund University Diabetes Center, Lund University, Lund, Sweden
| | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Sonia Shah
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Patrick T Ellinor
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiac Arrhythmia Service and Cardiovascular Research Center, Massachusetts General Hospital, Cambridge, MA, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, University College London, London, UK
| | - Quinn Wells
- Division of Cardiovascular Medicine, Vanderbilt University, Nashville, TN, USA
| | - R Thomas Lumbers
- Institute of Health Informatics, University College London, London, UK.
- Health Data Research UK, London, UK.
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK.
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Larsson SC, Chen J, Ruan X, Li X, Yuan S. Genome-wide association study and Mendelian randomization analyses reveal insights into bladder cancer etiology. JNCI Cancer Spectr 2025; 9:pkaf014. [PMID: 39898788 PMCID: PMC11950924 DOI: 10.1093/jncics/pkaf014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Revised: 12/05/2024] [Accepted: 01/21/2025] [Indexed: 02/04/2025] Open
Abstract
BACKGROUND The causes of bladder cancer are not completely understood. Our objective was to identify blood proteins and modifiable causal risk factors for bladder cancer by combining genome-wide association study (GWAS) and Mendelian randomization (MR) analyses. METHODS We first performed a GWAS meta-analysis of 6984 bladder cancer case patients and 708 432 control individuals from 3 European databases. Next, we conducted 2-sample MR and colocalization analyses using data from the present GWAS and published GWAS meta-analyses on plasma proteins and modifiable factors. RESULTS Genome-wide association study meta-analysis uncovered 17 bladder cancer susceptibility loci, of which 3 loci were novel. Genes were enriched in pathways related to the metabolic and catabolic processes of xenobiotics and cellular detoxification. Proteome-wide MR analysis based on cis-acting genetic variants revealed that higher plasma levels of glutathione S-transferases were strongly associated with a reduced risk of bladder cancer. There is strong evidence of colocalization between GSTM1 and bladder cancer. Finally, multivariable MR analyses of suspected risk factors for bladder cancer revealed independent causal associations between smoking and adiposity, particularly abdominal obesity, and risk of bladder cancer. CONCLUSIONS Findings from this large-scale GWAS and multivariable MR analyses highlight the key role of detoxification processes, particularly glutathione S-transferase 1, as well as smoking and abdominal obesity in bladder cancer etiology.
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Affiliation(s)
- Susanna C Larsson
- Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jie Chen
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xixian Ruan
- Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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Dominy J, Bai J, Koch C, Zaman Khan M, Khalid S, Chung JH, Panditrao M, Liu L, Zhang Q, Jahanzaib M, Mian MR, Liaqat MB, Raza SS, Sultana R, Jalal A, Saeed MH, Abbas S, Memon FR, Ishaq M, Saleheen K, Rasheed A, Gurtan A, Saleheen D. Human CD33 deficiency is associated with mild alteration of circulating white blood cell counts. PLoS Genet 2025; 21:e1011600. [PMID: 40043053 PMCID: PMC11927914 DOI: 10.1371/journal.pgen.1011600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Revised: 03/21/2025] [Accepted: 01/29/2025] [Indexed: 03/22/2025] Open
Abstract
The single pass transmembrane protein CD33 is enriched in phagocytic and hematopoietic cell types, such as monocytes. CD33 is thought to be associated with immune cell function, susceptibility to Alzheimer's disease, and rare leukemias. Antagonism or genetic ablation of CD33 has been proposed to treat Alzheimer's disease, hematological cancers, and as a selection mechanism for enriching genetically altered blood cells. To understand the impact of chronic CD33 loss or ablation, we describe individuals who we confirmed to be missing CD33 due to germline loss of function variants. Through PheWAS-based approaches using existing whole exome biobanks and bespoke phenotyping using recall-by-genotype (RBG) studies, we show that CD33 loss of function alters circulating white blood cell counts and distributions, albeit mildly and with no overt clinical pathology. These findings indicate that chronic CD33 antagonism/ablation is likely to be safe in humans.
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Affiliation(s)
- John Dominy
- Biomedical Research at Novartis, Cambridge, Massachusetts, United States of America
| | - Jirong Bai
- Biomedical Research at Novartis, Cambridge, Massachusetts, United States of America
| | - Christopher Koch
- Biomedical Research at Novartis, Cambridge, Massachusetts, United States of America
| | | | - Shareef Khalid
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Jonathan H Chung
- Biomedical Research at Novartis, Cambridge, Massachusetts, United States of America
| | - Madhura Panditrao
- Biomedical Research at Novartis, Cambridge, Massachusetts, United States of America
| | - Lulu Liu
- Biomedical Research at Novartis, Cambridge, Massachusetts, United States of America
| | - Qi Zhang
- Biomedical Research at Novartis, Cambridge, Massachusetts, United States of America
| | | | | | | | | | - Riffat Sultana
- Karachi Institute of Heart Diseases, Karachi, Sindh, Pakistan
| | - Anjum Jalal
- Punjab Institute of Cardiology, Lahore, Punjab, Pakistan
| | | | - Shahid Abbas
- Faisalabad Institute of Cardiology, Faisalabad, Punjab, Pakistan
| | | | - Mohammad Ishaq
- Karachi Institute of Heart Diseases, Karachi, Sindh, Pakistan
| | - Kashif Saleheen
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | - Asif Rasheed
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | - Allan Gurtan
- Biomedical Research at Novartis, Cambridge, Massachusetts, United States of America
| | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Cardiology, Columbia University Irving Medical Center, New York, New York, United States of America
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Acharya V, Fan K, Snitz BE, Ganguli M, DeKosky ST, Lopez OL, Feingold E, Kamboh MI. Sex-stratified genome-wide meta-analysis identifies novel loci for cognitive decline in older adults. Alzheimers Dement 2025; 21:e14461. [PMID: 40042063 PMCID: PMC11880917 DOI: 10.1002/alz.14461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 09/30/2024] [Accepted: 11/13/2024] [Indexed: 03/09/2025]
Abstract
INTRODUCTION Many complex traits and diseases show sex-specific biases in clinical presentation and prevalence. METHODS To understand sex-specific genetic architecture of cognitive decline across five cognitive domains (attention, memory, executive function, language, and visuospatial function) and global cognitive function, we performed sex-stratified genome-wide meta-analysis in 3021 older adults aged ≥ 65 years (female = 1545, male = 1476) from three prospective cohorts. Gene-based and gene-set enrichment analyses were conducted for each cognitive trait. RESULTS We identified a novel genome-wide significant (GWS) intergenic locus for decline of memory in males near RPS23P3 on chromosome 4 (rs6851574: minor allele frequency [MAF] = 0.39, Pmale = 4.10E-08, βmale = 0.19; Pinteraction = 3.76E-04). We also identified a subthreshold GWS locus for decline of executive function on chromosome 12 in females near the NDUFA12 gene, involved in oxidative phosphorylation (rs11107823: MAF = 0.12, Pfemale = 9.35E-08, βfemale = 0.28; Pinteraction = 7.42E-06). DISCUSSION Sex-aware genetic studies can help in the identification of novel genetic loci and enhance sex-specific understanding of cognitive decline. HIGHLIGHTS Our genome-wide meta-analysis of single variants identified two new genetic associations, one in males and one in females. The novel male association was observed with the decline of memory in the intergenic region near the RPS23P3 gene on chromosome 4. This intergenic region has previously been implicated in several brain and cognition related traits, including anatomical brain aging, brain shape, and educational attainment. The novel female-specific association was observed with decline in executive function on chromosome 12 near the NDUFA12 gene, which is involved in oxidative phosphorylation. Sex-stratified analyses offer sex-specific understanding of biological pathways involved in cognitive aging.
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Affiliation(s)
- Vibha Acharya
- Department of Human GeneticsUniversity of Pittsburgh School of Public HealthPittsburghPennsylvaniaUSA
| | - Kang‐Hsien Fan
- Department of Human GeneticsUniversity of Pittsburgh School of Public HealthPittsburghPennsylvaniaUSA
| | - Beth E. Snitz
- Department of NeurologySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Mary Ganguli
- Department of NeurologySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of EpidemiologyUniversity of Pittsburgh School of Public HealthPittsburghPennsylvaniaUSA
| | - Steven T. DeKosky
- McKnight Brain Institute and Department of NeurologyCollege of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Oscar L. Lopez
- Department of NeurologySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Eleanor Feingold
- Department of Human GeneticsUniversity of Pittsburgh School of Public HealthPittsburghPennsylvaniaUSA
| | - M. Ilyas Kamboh
- Department of Human GeneticsUniversity of Pittsburgh School of Public HealthPittsburghPennsylvaniaUSA
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of EpidemiologyUniversity of Pittsburgh School of Public HealthPittsburghPennsylvaniaUSA
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Aguzzoli Heberle B, Fox KL, Lobraico Libermann L, Ronchetti Martins Xavier S, Tarnowski Dallarosa G, Carolina Santos R, Fardo DW, Wendt Viola T, Ebbert MTW. Systematic review and meta-analysis of bulk RNAseq studies in human Alzheimer's disease brain tissue. Alzheimers Dement 2025; 21:e70025. [PMID: 40042520 PMCID: PMC11881636 DOI: 10.1002/alz.70025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2024] [Revised: 01/28/2025] [Accepted: 01/29/2025] [Indexed: 03/09/2025]
Abstract
We systematically reviewed and meta-analyzed bulk RNA sequencing (RNAseq) studies comparing Alzheimer's disease (AD) patients to controls in human brain tissue. We searched PubMed, Web of Science, and Scopus for human brain bulk RNAseq studies, excluding re-analyses and studies limited to small RNAs or gene panels. We developed 10 criteria for quality assessment and performed a meta-analysis on three high-quality datasets. Of 3266 records, 24 qualified for the systematic review, and one study with three datasets qualified for the meta-analysis. The meta-analysis identified 571 differentially expressed genes (DEGs) in the temporal lobe and 189 in the frontal lobe, including CLU and GFAP. Pathway analysis suggested reactivation of developmental processes in the adult AD brain. Limited data availability constrained the meta-analysis. These findings underscore the need for rigorous methods in AD transcriptomic research to better identify transcriptomic changes and advance biomarker and therapeutic development. This review is registered in PROSPERO (CRD42023466522). HIGHLIGHTS Comprehensive review: Conducted the first systematic review and meta-analysis of bulk RNA sequencing (RNAseq) studies comparing Alzheimer's disease (AD) patients with non-demented controls using primary human brain tissue. KEY FINDINGS Identified 571 differentially expressed genes (DEGs) in the temporal lobe and 189 in the frontal lobe of patients with AD, revealing potential therapeutic targets. Pathway discovery: Highlighted key overlapping pathways such as "tube morphogenesis" and "neuroactive ligand-receptor interaction" that may play critical roles in AD. QUALITY ASSESSMENT Emphasized the importance of methodological rigor in transcriptomic studies, including quality assessment tools to guide future research in AD. STUDY LIMITATION Acknowledged limited access to complete data tables and lack of diversity in existing datasets, which constrained some of the analysis.
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Affiliation(s)
- Bernardo Aguzzoli Heberle
- Sanders‐Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Kristin L. Fox
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Division of Laboratory Animal ResourcesUniversity of KentuckyLexingtonKentuckyUSA
| | - Lucas Lobraico Libermann
- School of MedicineBrain Institute of Rio Grande do SulPontifical Catholic University of Rio Grande do Sul (PUCRS)Porto AlegreRio Grande do SulBrazil
| | | | - Guilherme Tarnowski Dallarosa
- School of MedicineBrain Institute of Rio Grande do SulPontifical Catholic University of Rio Grande do Sul (PUCRS)Porto AlegreRio Grande do SulBrazil
| | - Rhaná Carolina Santos
- School of MedicineUniversity of the Sinos Valley (UNISINOS)São LeopoldoRio Grande do SulBrazil
| | - David W. Fardo
- Sanders‐Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Department of BiostatisticsUniversity of KentuckyLexingtonKentuckyUSA
| | - Thiago Wendt Viola
- School of MedicineBrain Institute of Rio Grande do SulPontifical Catholic University of Rio Grande do Sul (PUCRS)Porto AlegreRio Grande do SulBrazil
| | - Mark T. W. Ebbert
- Sanders‐Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Division of Biomedical Informatics, Internal Medicine, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
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Cheng B, Wen Y, Wei W, Cheng S, Pan C, Meng P, Liu L, Yang X, Liu H, Jia Y, Zhang F. Polygenic enrichment analysis in multi-omics levels identifies cell/tissue specific associations with schizophrenia based on single-cell RNA sequencing data. Schizophr Res 2025; 277:93-101. [PMID: 40036903 DOI: 10.1016/j.schres.2025.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 01/24/2025] [Accepted: 02/22/2025] [Indexed: 03/06/2025]
Abstract
OBJECTIVE Understanding the specific cellular origin and tissue heterogeneity in schizophrenia is critically important for exploring the disease etiology. This study aims to investigate these aspects by performing multiple analyses based on omics data. METHOD We performed single-cell disease relevance score (scDRS) algorithm to link brain single-cell RNA sequencing (scRNA-seq) with schizophrenia risk across multi-omics scales at single-cell resolution. This approach identified cell types with overexpression of schizophrenia-related genes implicated by multi-omics panels (ATAC-seq, RNA-seq, TWAS, and GWAS). Schizophrenia-related genes from these multi-omics panels were extracted and combined with scRNA-seq data to calculate scDRS. Subsequently, the cell-type vs. disease association and tissue heterogeneity were assessed using scDRS for each omics panel. RESULTS We identified two novel cell subpopulations in the brain that differentially express SCUBE3 (59 cells, 7.0 %) and FN1 (21 cells, 2.5 %). At the individual cell level, schizophrenia-associated cell subpopulations included microglial cell associated with ATAC-seq panel (Passociation = 0.002, Pheterogeneity = 0.009) and deep layer neuron suggestively associated with GWAS panel (Passociation = 0.033, Pheterogeneity = 0.017). At the brain tissue level, microglial cell was significantly associated with cortical plate in ATAC-seq panel (Passociation = 0.002, Pheterogeneity = 0.011). Gene level analysis identified several genes associated with schizophrenia across multi-omics panels. CONCLUSIONS Our study outlines the signature of cell subpopulations, brain regions, and disease risk genes in schizophrenia at single-cell resolution across multi-omics scales. These findings provide a reference for future precision medicine approaches targeting specific cell types and brain regions in schizophrenia.
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Affiliation(s)
- Bolun Cheng
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Yan Wen
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Wenming Wei
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Shiqiang Cheng
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Chuyu Pan
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Peilin Meng
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Li Liu
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Xuena Yang
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Huan Liu
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China
| | - Yumeng Jia
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China.
| | - Feng Zhang
- NHC Key Laboratory of Environment and Endemic Diseases (Xi'an Jiaotong University), Xi'an 710061, China; Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University), Ministry of Education, Xi'an 710061, China; Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, 710061, China.
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Wonkam A, Esoh K, Levine RM, Ngo Bitoungui VJ, Mnika K, Nimmagadda N, Dempsey EAD, Nkya S, Sangeda RZ, Nembaware V, Morrice J, Osman F, Beer MA, Makani J, Mulder N, Lettre G, Steinberg MH, Latanich R, Casella JF, Drehmer D, Arking DE, Chimusa ER, Yen JS, Newby GA, Antonarakis SE. FLT1 and other candidate fetal haemoglobin modifying loci in sickle cell disease in African ancestries. Nat Commun 2025; 16:2092. [PMID: 40025045 PMCID: PMC11873275 DOI: 10.1038/s41467-025-57413-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/20/2025] [Indexed: 03/04/2025] Open
Abstract
Known fetal haemoglobin (HbF)-modulating loci explain 10-24% variation of HbF level in Africans with Sickle Cell Disease (SCD), compared to 50% among Europeans. Here, we report fourteen candidate loci from a genome-wide association study (GWAS) of HbF level in patients with SCD from Cameroon, Tanzania, and the United States of America. We present results of cell-based experiments for FLT1 candidate, demonstrating expression in early haematopoiesis and a possible involvement in hypoxia associated HbF induction. Our study employed genotyping arrays that capture a broad range of African and non-African genetic variation and replicated known loci (BCL11A and HBS1L-MYB). We estimated the heritability of HbF level in SCD at 94%, higher than estimated in unselected Europeans, and suggesting a robust capture of HbF-associated loci by these arrays. Our approach, which involved genotype imputation against six reference haplotype panels and association analysis with each of the panels, proved superior over selecting a best-performing panel, evidenced by a substantial proportion of panel-specific (up to 18%) and a low proportion of shared (28%) imputed variants across the panels.
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Affiliation(s)
- Ambroise Wonkam
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
| | - Kevin Esoh
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Rachel M Levine
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | | | - Khuthala Mnika
- Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Nikitha Nimmagadda
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Erin A D Dempsey
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Siana Nkya
- Department of Biochemistry and Molecular Biology, Muhimbili University of Health and Allied Sciences, Dar Es Salaam, Tanzania
| | - Raphael Z Sangeda
- Department of Pharmaceutical Microbiology, Muhimbili University of Health and Allied Sciences, Dar Es Salaam, Tanzania
| | - Victoria Nembaware
- Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Jack Morrice
- Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Fujr Osman
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael A Beer
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Julie Makani
- Sickle Cell Programme, Department of Haematology and Blood Transfusion, Muhimbili University of Health & Allied Sciences (MUHAS), Dar Es Salaam, Tanzania
- SickleInAfrica Clinical Coordinating Center, Muhimbili University of Health & Allied Sciences (MUHAS), Dar Es Salaam, Tanzania
- Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, UK
| | - Nicola Mulder
- Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, CIDRI-Africa Wellcome Trust Centre, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Guillaume Lettre
- Montreal Heart Institute, Université de Montréal, Montreal, QC, Canada
| | - Martin H Steinberg
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Rachel Latanich
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James F Casella
- Department of Pediatrics, Division of Hematology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daiana Drehmer
- Armstrong Oxygen Biology Research Center, Institute for Cell Engineering, and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dan E Arking
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Emile R Chimusa
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle, Tyne and Wear, UK
| | - Jonathan S Yen
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Gregory A Newby
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA
| | - Stylianos E Antonarakis
- Department of Genetic Medicine, Faculty of Medicine, University of Geneva, Geneva, Switzerland
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50
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Wen S, Kuri-Morales P, Hu F, Nag A, Tachmazidou I, Deevi SVV, Taiy H, Smith KR, Loesch DP, Burren OS, Dhindsa RS, Wasilewski S, Alegre-Díaz J, Berumen J, Emberson J, Torres JM, Collins R, Carss K, Wang Q, Petrovski S, Tapia-Conyer R, Fabre MA, Harper AR, Vassiliou GS, Mitchell J. Comparative analysis of the Mexico City Prospective Study and the UK Biobank identifies ancestry-specific effects on clonal hematopoiesis. Nat Genet 2025; 57:572-582. [PMID: 39948438 PMCID: PMC11906367 DOI: 10.1038/s41588-025-02085-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 01/09/2025] [Indexed: 03/15/2025]
Abstract
The impact of genetic ancestry on the development of clonal hematopoiesis (CH) remains largely unexplored. Here, we compared CH in 136,401 participants from the Mexico City Prospective Study (MCPS) to 416,118 individuals from the UK Biobank (UKB) and observed CH to be significantly less common in MCPS compared to UKB (adjusted odds ratio = 0.59, 95% confidence interval (CI) = [0.57, 0.61], P = 7.31 × 10-185). Among MCPS participants, CH frequency was positively correlated with the percentage of European ancestry (adjusted beta = 0.84, 95% CI = [0.66, 1.03], P = 7.35 × 10-19). Genome-wide and exome-wide association analyses in MCPS identified ancestry-specific variants in the TCL1B locus with opposing effects on DNMT3A-CH versus non-DNMT3A-CH. Meta-analysis of MCPS and UKB identified five novel loci associated with CH, including polymorphisms at PARP11/CCND2, MEIS1 and MYCN. Our CH study, the largest in a non-European population to date, demonstrates the power of cross-ancestry comparisons to derive novel insights into CH pathogenesis.
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Affiliation(s)
- Sean Wen
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
- Department of Haematology, Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Pablo Kuri-Morales
- Instituto Tecnológico y de Estudios Superiores de Monterrey, Monterrey, Mexico
| | - Fengyuan Hu
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Abhishek Nag
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ioanna Tachmazidou
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Sri V V Deevi
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Haeyam Taiy
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Katherine R Smith
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Douglas P Loesch
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Oliver S Burren
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ryan S Dhindsa
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Sebastian Wasilewski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Jesus Alegre-Díaz
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Ciudad de México, Mexico
| | - Jaime Berumen
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Ciudad de México, Mexico
| | - Jonathan Emberson
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jason M Torres
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Keren Carss
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Quanli Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Roberto Tapia-Conyer
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Ciudad de México, Mexico
| | - Margarete A Fabre
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
- Department of Haematology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Andrew R Harper
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
- Clinical Development, Research and Early Development, Respiratory and Immunology (R&I), BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - George S Vassiliou
- Department of Haematology, Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
- Department of Haematology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
| | - Jonathan Mitchell
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
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