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Wong ZQ, Deng L, Cengnata A, Abdul Rahman T, Mohd Ismail A, Hong Lim RL, Xu S, Hoh BP. Expression quantitative trait loci (eQTL): from population genetics to precision medicine. J Genet Genomics 2025; 52:449-459. [PMID: 39986349 DOI: 10.1016/j.jgg.2025.02.003] [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: 11/11/2024] [Revised: 02/11/2025] [Accepted: 02/12/2025] [Indexed: 02/24/2025]
Abstract
Evidence has shown that differential transcriptomic profiles among human populations from diverse ancestries, supporting the role of genetic architecture in regulating gene expression alongside environmental stimuli. Genetic variants that regulate gene expression, known as expression quantitative trait loci (eQTL), are primarily shaped by human migration history and evolutionary forces, likewise, regulation of gene expression in principle could have been influenced by these events. Therefore, a comprehensive understanding of how human evolution impacts eQTL offers important insights into how phenotypic diversity is shaped. Recent studies, however, suggest that eQTL is enriched in genes that are selectively constrained. Whether eQTL is minimally affected by selective pressures remains an open question and requires comprehensive investigations. In addition, such studies are primarily dominated by the major populations of European ancestry, leaving many marginalized populations underrepresented. These observations indicate there exists a fundamental knowledge gap in the role of genomics variation on phenotypic diversity, which potentially hinders precision medicine. This article aims to revisit the abundance of eQTL across diverse populations and provide an overview of their impact from the population and evolutionary genetics perspective, subsequently discuss their influence on phenomics, as well as challenges and opportunities in the applications to precision medicine.
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Affiliation(s)
- Zhi Qi Wong
- Faculty of Applied Sciences, UCSI University, Kuala Lumpur 56000, Malaysia
| | - Lian Deng
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Alvin Cengnata
- Faculty of Applied Sciences, UCSI University, Kuala Lumpur 56000, Malaysia
| | - Thuhairah Abdul Rahman
- Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, 47000, Malaysia
| | - Aletza Mohd Ismail
- Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, 47000, Malaysia
| | - Renee Lay Hong Lim
- Faculty of Applied Sciences, UCSI University, Kuala Lumpur 56000, Malaysia
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China; Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200433, China; Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai 200433, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, Jiangsu 221008, China; Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan 450001, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Boon-Peng Hoh
- Division of Applied Biomedical Sciences and Biotechnology, School of Health Sciences, IMU University, Kuala Lumpur 57000, Malaysia.
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2
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He J, Perera D, Wen W, Ping J, Li Q, Lyu L, Chen Z, Shu X, Long J, Cai Q, Shu XO, Yin Z, Zheng W, Long Q, Guo X. Enhancing disease risk gene discovery by integrating transcription factor-linked trans-variants into transcriptome-wide association analyses. Nucleic Acids Res 2025; 53:gkae1035. [PMID: 39535029 PMCID: PMC11724290 DOI: 10.1093/nar/gkae1035] [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: 06/26/2024] [Revised: 10/14/2024] [Accepted: 10/21/2024] [Indexed: 11/16/2024] Open
Abstract
Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data. However, trans-variants for predicting gene expression remain largely unexplored. Here, we introduce transTF-TWAS, which incorporates transcription factor (TF)-linked trans-variants to enhance model building for TF downstream target genes. Using data from the Genotype-Tissue Expression project, we predict gene expression and alternative splicing and applied these prediction models to large GWAS datasets for breast, prostate, lung cancers and other diseases. We demonstrate that transTF-TWAS outperforms other existing TWAS approaches in both constructing gene expression prediction models and identifying disease-associated genes, as shown by simulations and real data analysis. Our transTF-TWAS approach significantly contributes to the discovery of disease risk genes. Findings from this study shed new light on several genetically driven key TF regulators and their associated TF-gene regulatory networks underlying disease susceptibility.
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Affiliation(s)
- Jingni He
- Department of Biochemistry & Molecular Biology, University of Calgary, HMRB 231, 3330 Hospital Drive NW, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, The Alfred Centre, Level 6, 99 Commercial Road, Melbourne, VIC 3004, Australia
| | - Deshan Perera
- Department of Biochemistry & Molecular Biology, University of Calgary, HMRB 231, 3330 Hospital Drive NW, Calgary, AB T2N 4N1, Canada
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Qing Li
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Linshuoshuo Lyu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Zhishan Chen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Xiang Shu
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 633 3rd Ave, 3rd Floor, New York, NY, 10017, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Zhijun Yin
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
| | - Quan Long
- Department of Biochemistry & Molecular Biology, University of Calgary, HMRB 231, 3330 Hospital Drive NW, Calgary, AB T2N 4N1, Canada
- Department of Medical Genetics, University of Calgary, 3330 Hospital Drive NW, Calgary, AB T2N 4N2, Canada
- Department of Mathematics & Statistics, University of Calgary, Mathematical Sciences 476, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Heritage Medical Research Building, 3330 Hospital Dr. NW, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute, University of Calgary, Health Research Innovation Centre, 3330 Hospital Drive NW, Calgary, Alberta, T2N 4N1, Canada
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, 2525 West End Ave, Nashville, TN 37203, USA
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3
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Mishra P, Barrera TS, Grieshop K, Agrawal AF. Cis-regulatory Variation in Relation to Sex and Sexual Dimorphism in Drosophila melanogaster. Genome Biol Evol 2024; 16:evae234. [PMID: 39613311 DOI: 10.1093/gbe/evae234] [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] [Accepted: 10/11/2024] [Indexed: 12/01/2024] Open
Abstract
Much of sexual dimorphism is likely due to sex-biased gene expression, which results from differential regulation of a genome that is largely shared between males and females. Here, we use allele-specific expression to explore cis-regulatory variation in Drosophila melanogaster in relation to sex. We develop a Bayesian framework to infer the transcriptome-wide joint distribution of cis-regulatory effects across the sexes. We also examine patterns of cis-regulatory variation with respect to two other levels of variation in sexual dimorphism: (i) across genes that vary in their degree of sex-biased expression and (ii) among tissues that vary in their degree of dimorphism (e.g. relatively low dimorphism in heads vs. high dimorphism in gonads). We uncover evidence of widespread cis-regulatory variation in all tissues examined, with female-biased genes being especially enriched for this variation. A sizeable proportion of cis-regulatory variation is inferred to have sex-specific effects, with sex-dependent cis effects being much more frequent in gonads than in heads. Finally, we find some genes where 1 allele contributes to more than 50% of a gene's expression in heterozygous males but <50% of its expression in heterozygous females. Such variants could provide a mechanism for sex-specific dominance reversals, a phenomenon important for sexually antagonistic balancing selection. However, tissue differences in allelic imbalance are approximately as frequent as sex differences, perhaps suggesting that sexual conflict may not be particularly unique in shaping patterns of expression variation.
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Affiliation(s)
- Prashastha Mishra
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada M5S 3B2
| | - Tania S Barrera
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada M5S 3B2
| | - Karl Grieshop
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada M5S 3B2
- Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, Stockholm SE-10691, Sweden
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
| | - Aneil F Agrawal
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada M5S 3B2
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Wang J, Zhang Z, Lu Z, Mancuso N, Gazal S. Genes with differential expression across ancestries are enriched in ancestry-specific disease effects likely due to gene-by-environment interactions. Am J Hum Genet 2024; 111:2117-2128. [PMID: 39191255 PMCID: PMC11480800 DOI: 10.1016/j.ajhg.2024.07.021] [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: 12/21/2023] [Revised: 07/26/2024] [Accepted: 07/30/2024] [Indexed: 08/29/2024] Open
Abstract
Multi-ancestry genome-wide association studies (GWASs) have highlighted the existence of variants with ancestry-specific effect sizes. Understanding where and why these ancestry-specific effects occur is fundamental to understanding the genetic basis of human diseases and complex traits. Here, we characterized genes differentially expressed across ancestries (ancDE genes) at the cell-type level by leveraging single-cell RNA-sequencing data in peripheral blood mononuclear cells for 21 individuals with East Asian (EAS) ancestry and 23 individuals with European (EUR) ancestry (172,385 cells); then, we tested whether variants surrounding those genes were enriched in disease variants with ancestry-specific effect sizes by leveraging ancestry-matched GWASs of 31 diseases and complex traits (average n ∼ 90,000 and ∼ 267,000 in EAS and EUR, respectively). We observed that ancDE genes tended to be cell-type specific and enriched in genes interacting with the environment and in variants with ancestry-specific disease effect sizes, which suggests cell-type-specific, gene-by-environment interactions shared between regulatory and disease architectures. Finally, we illustrated how different environments might have led to ancestry-specific myeloid cell leukemia 1 (MCL1) expression in B cells and ancestry-specific allele effect sizes in lymphocyte count GWASs for variants surrounding MCL1. Our results imply that large single-cell and GWAS datasets from diverse ancestries are required to improve our understanding of human diseases.
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Affiliation(s)
- Juehan Wang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Zixuan Zhang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Zeyun Lu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Nicholas Mancuso
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Steven Gazal
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
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5
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Sarnowski C, Ma J, Nguyen NQH, Hoogeveen RC, Ballantyne CM, Coresh J, Morrison AC, Chatterjee N, Boerwinkle E, Yu B. Ancestrally diverse genome-wide association analysis highlights ancestry-specific differences in genetic regulation of plasma protein levels. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.27.24314500. [PMID: 39399032 PMCID: PMC11469718 DOI: 10.1101/2024.09.27.24314500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
Fully characterizing the genetic architecture of circulating proteins in multi-ancestry populations provides an unprecedented opportunity to gain insights into the etiology of complex diseases. We characterized and contrasted the genetic associations of plasma proteomes in 9,455 participants of European and African (19.8%) ancestry from the Atherosclerosis Risk in Communities Study. Of 4,651 proteins, 1,408 and 2,565 proteins had protein-quantitative trait loci (pQTLs) identified in African and European ancestry respectively, and twelve unreported potentially causal protein-disease relationships were identified. Shared pQTLs across the two ancestries were detected in 1,113 aptamer-region pairs pQTLs, where 53 of them were not previously reported (all trans pQTLs). Sixteen unique protein-cardiovascular trait pairs were colocalized in both European and African ancestry with the same candidate causal variants. Our systematic cross-ancestry comparison provided a reliable set of pQTLs, highlighted the shared and distinct genetic architecture of proteome in two ancestries, and demonstrated possible biological mechanisms underlying complex diseases.
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Affiliation(s)
- Chloé Sarnowski
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
| | - Jianzhong Ma
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
| | - Ngoc Quynh H. Nguyen
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
| | - Ron C Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, TX
| | | | - Josef Coresh
- Optimal Aging Institute, New York University Grossman School of Medicine, New York, NY
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Alanna C Morrison
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Eric Boerwinkle
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Bing Yu
- Department of Epidemiology, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX
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6
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Wen J, Sun Q, Huang L, Zhou L, Doyle MF, Ekunwe L, Durda P, Olson NC, Reiner AP, Li Y, Raffield LM. Gene expression and splicing QTL analysis of blood cells in African American participants from the Jackson Heart Study. Genetics 2024; 228:iyae098. [PMID: 39056362 PMCID: PMC11373511 DOI: 10.1093/genetics/iyae098] [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: 05/07/2024] [Accepted: 06/05/2024] [Indexed: 07/28/2024] Open
Abstract
Most gene expression and alternative splicing quantitative trait loci (eQTL/sQTL) studies have been biased toward European ancestry individuals. Here, we performed eQTL and sQTL analyses using TOPMed whole-genome sequencing-derived genotype data and RNA-sequencing data from stored peripheral blood mononuclear cells in 1,012 African American participants from the Jackson Heart Study (JHS). At a false discovery rate of 5%, we identified 17,630 unique eQTL credible sets covering 16,538 unique genes; and 24,525 unique sQTL credible sets covering 9,605 unique genes, with lead QTL at P < 5e-8. About 24% of independent eQTLs and independent sQTLs with a minor allele frequency > 1% in JHS were rare (minor allele frequency < 0.1%), and therefore unlikely to be detected, in European ancestry individuals. Finally, we created an open database, which is freely available online, allowing fast query and bulk download of our QTL results.
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Affiliation(s)
- Jia Wen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Le Huang
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lingbo Zhou
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Margaret F Doyle
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA
| | - Lynette Ekunwe
- Department of Medicine, University of MS Medical Center (UMMC), Jackson, MS 39213, USA
| | - Peter Durda
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA
| | - Nels C Olson
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research, Seattle, WA 98109, USA
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
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Taylor DJ, Chhetri SB, Tassia MG, Biddanda A, Yan SM, Wojcik GL, Battle A, McCoy RC. Sources of gene expression variation in a globally diverse human cohort. Nature 2024; 632:122-130. [PMID: 39020179 PMCID: PMC11291278 DOI: 10.1038/s41586-024-07708-2] [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: 11/07/2023] [Accepted: 06/12/2024] [Indexed: 07/19/2024]
Abstract
Genetic variation that influences gene expression and splicing is a key source of phenotypic diversity1-5. Although invaluable, studies investigating these links in humans have been strongly biased towards participants of European ancestries, which constrains generalizability and hinders evolutionary research. Here to address these limitations, we developed MAGE, an open-access RNA sequencing dataset of lymphoblastoid cell lines from 731 individuals from the 1000 Genomes Project6, spread across 5 continental groups and 26 populations. Most variation in gene expression (92%) and splicing (95%) was distributed within versus between populations, which mirrored the variation in DNA sequence. We mapped associations between genetic variants and expression and splicing of nearby genes (cis-expression quantitative trait loci (eQTLs) and cis-splicing QTLs (sQTLs), respectively). We identified more than 15,000 putatively causal eQTLs and more than 16,000 putatively causal sQTLs that are enriched for relevant epigenomic signatures. These include 1,310 eQTLs and 1,657 sQTLs that are largely private to underrepresented populations. Our data further indicate that the magnitude and direction of causal eQTL effects are highly consistent across populations. Moreover, the apparent 'population-specific' effects observed in previous studies were largely driven by low resolution or additional independent eQTLs of the same genes that were not detected. Together, our study expands our understanding of human gene expression diversity and provides an inclusive resource for studying the evolution and function of human genomes.
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Affiliation(s)
- Dylan J Taylor
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Surya B Chhetri
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Michael G Tassia
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Arjun Biddanda
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Stephanie M Yan
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Genevieve L Wojcik
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA.
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He J, Perera D, Wen W, Ping J, Li Q, Lyu L, Chen Z, Shu X, Long J, Cai Q, Shu XO, Zheng W, Long Q, Guo X. Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.10.23295443. [PMID: 37873299 PMCID: PMC10593059 DOI: 10.1101/2023.10.10.23295443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data. However, trans-located variants for predicting gene expression remain largely unexplored. Here, we introduce transTF-TWAS, which incorporates transcription factor (TF)-linked trans-located variants to enhance model building. Using data from the Genotype-Tissue Expression project, we predict gene expression and alternative splicing and applied these models to large GWAS datasets for breast, prostate, and lung cancers. We demonstrate that transTF-TWAS outperforms other existing TWAS approaches in both constructing gene prediction models and identifying disease-associated genes, as evidenced by simulations and real data analysis. Our transTF-TWAS approach significantly contributes to the discovery of disease risk genes. Findings from this study have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.
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9
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Choi J, Lee SM, Norwitz ER, Kim JH, Jung YM, Park CW, Jun JK, Lee D, Jin Y, Kim S, Cha B, Park JS, Kim JI. Placental expression quantitative trait loci in an East Asian population. HGG ADVANCES 2024; 5:100276. [PMID: 38310352 PMCID: PMC10883826 DOI: 10.1016/j.xhgg.2024.100276] [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: 08/11/2023] [Revised: 01/29/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024] Open
Abstract
Expression quantitative trait loci (eQTL) analysis measures the contribution of genetic variation in gene expression on complex traits. Although this methodology has been used to examine gene regulation in numerous human tissues, eQTL research in solid tissues is relatively lacking. We conducted eQTL analysis on placentas collected from an East Asian population in an effort to identify gene regulatory mechanisms in this tissue. Placentas (n = 102) were collected at the time of cesarean delivery. mRNA was extracted, sequenced with NGS, and compared with matched maternal and fetal DNA arrays performed using maternal and neonatal cord blood. Linear regression modeling was performed using tensorQTL. Fine-mapping along with epigenomic annotation was used to select putative functional variants. We identified 2,703 coding genes that contained at least one eQTL with statistical significance (false discovery rate <0.05). After fine-mapping, we found 108 previously unreported eQTL variants with posterior inclusion probability >0.1. Of these, 19% were located in genomic regions with evidence from public placental epigenome suggesting that they may be functionally relevant. For example, variant rs28379289 located in the placenta-specific regulatory region changes the binding affinity of transcription factor leading to higher expression of LGALS3, which is known to affect placental function. This study expands the knowledge base of regulatory elements within the human placenta and identifies 108 previously unreported placenta eQTL signals, which are listed in our publicly available GMI eQTL database. Further studies are needed to identify and characterize genetic regulatory mechanisms that affect placental function in normal pregnancy and placenta-related diseases.
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Affiliation(s)
- Jaeyong Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Seung Mi Lee
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | | | - Ji Hoi Kim
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Young Mi Jung
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Chan-Wook Park
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Jong Kwan Jun
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea
| | - Dakyung Lee
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Yongjoon Jin
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Sookyung Kim
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Bukyoung Cha
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Joong Shin Park
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea.
| | - Jong-Il Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea.
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10
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George SHL, Medina-Rivera A, Idaghdour Y, Lappalainen T, Gallego Romero I. Increasing diversity of functional genetics studies to advance biological discovery and human health. Am J Hum Genet 2023; 110:1996-2002. [PMID: 37995684 PMCID: PMC10716434 DOI: 10.1016/j.ajhg.2023.10.012] [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: 05/22/2023] [Revised: 10/25/2023] [Accepted: 10/25/2023] [Indexed: 11/25/2023] Open
Abstract
In this perspective we discuss the current lack of genetic and environmental diversity in functional genomics datasets. There is a well-described Eurocentric bias in genetic and functional genomic research that has a clear impact on the benefit this research can bring to underrepresented populations. Current research focused on genetic variant-to-function experiments aims to identify molecular QTLs, but the lack of data from genetically diverse individuals has limited analyses to mostly populations of European ancestry. Although some efforts have been established to increase diversity in functional genomic studies, much remains to be done to consistently generate data for underrepresented populations from now on. We discuss the major barriers for this continuity and suggest actionable insights, aiming to empower research and researchers from underserved populations.
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Affiliation(s)
- Sophia H L George
- Department of Obstetrics, Gynecology and Reproductive Sciences, Miller School of Medicine, University of Miami, Miami, FL, USA; Sylvester Comprehensive Cancer Center, Miami, FL, USA.
| | - Alejandra Medina-Rivera
- Laboratorio Internacional de Investigación Sobre El Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Youssef Idaghdour
- Program in Biology, Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, UAE; Public Health Research Center, New York University Abu Dhabi, Abu Dhabi, UAE; Center for Genomics and Systems Biology, New York University Abu Dhabi, Abu Dhabi, UAE
| | - Tuuli Lappalainen
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden; New York Genome Center, New York, NY, USA.
| | - Irene Gallego Romero
- Melbourne Integrative Genomics and School of BioSciences, University of Melbourne, Parkville, VIC, Australia; Center for Genomics, Evolution and Medicine, Institute of Genomics, University of Tartu, Tartu, Estonia
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11
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Abraham LN, Croll D. Genome-wide expression QTL mapping reveals the highly dynamic regulatory landscape of a major wheat pathogen. BMC Biol 2023; 21:263. [PMID: 37981685 PMCID: PMC10658818 DOI: 10.1186/s12915-023-01763-3] [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: 07/17/2023] [Accepted: 11/07/2023] [Indexed: 11/21/2023] Open
Abstract
BACKGROUND In agricultural ecosystems, outbreaks of diseases are frequent and pose a significant threat to food security. A successful pathogen undergoes a complex and well-timed sequence of regulatory changes to avoid detection by the host immune system; hence, well-tuned gene regulation is essential for survival. However, the extent to which the regulatory polymorphisms in a pathogen population provide an adaptive advantage is poorly understood. RESULTS We used Zymoseptoria tritici, one of the most important pathogens of wheat, to generate a genome-wide map of regulatory polymorphism governing gene expression. We investigated genome-wide transcription levels of 146 strains grown under nutrient starvation and performed expression quantitative trait loci (eQTL) mapping. We identified cis-eQTLs for 65.3% of all genes and the majority of all eQTL loci are within 2kb upstream and downstream of the transcription start site (TSS). We also show that polymorphism in different gene elements contributes disproportionally to gene expression variation. Investigating regulatory polymorphism in gene categories, we found an enrichment of regulatory variants for genes predicted to be important for fungal pathogenesis but with comparatively low effect size, suggesting a separate layer of gene regulation involving epigenetics. We also show that previously reported trait-associated SNPs in pathogen populations are frequently cis-regulatory variants of neighboring genes with implications for the trait architecture. CONCLUSIONS Overall, our study provides extensive evidence that single populations segregate large-scale regulatory variation and are likely to fuel rapid adaptation to resistant hosts and environmental change.
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Affiliation(s)
- Leen Nanchira Abraham
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, 2000, Neuchâtel, Switzerland
- Present address: Institute of Plant Sciences, University of Cologne, Cologne, Germany
| | - Daniel Croll
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, 2000, Neuchâtel, Switzerland.
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12
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Wang J, Gazal S. Ancestry-specific regulatory and disease architectures are likely due to cell-type-specific gene-by-environment interactions. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.20.23297214. [PMID: 37905038 PMCID: PMC10615008 DOI: 10.1101/2023.10.20.23297214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Multi-ancestry genome-wide association studies (GWAS) have highlighted the existence of variants with ancestry-specific effect sizes. Understanding where and why these ancestry-specific effects occur is fundamental to understanding the genetic basis of human diseases and complex traits. Here, we characterized genes differentially expressed across ancestries (ancDE genes) at the cell-type level by leveraging single-cell RNA-seq data in peripheral blood mononuclear cells for 21 individuals with East Asian (EAS) ancestry and 23 individuals with European (EUR) ancestry (172K cells); then, we tested if variants surrounding those genes were enriched in disease variants with ancestry-specific effect sizes by leveraging ancestry-matched GWAS of 31 diseases and complex traits (average N = 90K and 267K in EAS and EUR, respectively). We observed that ancDE genes tend to be cell-type-specific, to be enriched in genes interacting with the environment, and in variants with ancestry-specific disease effect sizes, suggesting the impact of shared cell-type-specific gene-by-environment (GxE) interactions between regulatory and disease architectures. Finally, we illustrated how GxE interactions might have led to ancestry-specific MCL1 expression in B cells, and ancestry-specific allele effect sizes in lymphocyte count GWAS for variants surrounding MCL1. Our results imply that large single-cell and GWAS datasets in diverse populations are required to improve our understanding on the effect of genetic variants on human diseases.
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Affiliation(s)
- Juehan Wang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Steven Gazal
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
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13
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Li X, Shen A, Zhao Y, Xia J. Mendelian Randomization Using the Druggable Genome Reveals Genetically Supported Drug Targets for Psychiatric Disorders. Schizophr Bull 2023; 49:1305-1315. [PMID: 37418754 PMCID: PMC10483453 DOI: 10.1093/schbul/sbad100] [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] [Indexed: 07/09/2023]
Abstract
BACKGROUND AND HYPOTHESIS Psychiatric disorders impose a huge health and economic burden on modern society. However, there is currently no proven completely effective treatment available, partly owing to the inefficiency of drug target identification and validation. We aim to identify therapeutic targets relevant to psychiatric disorders by conducting Mendelian randomization (MR) analysis. STUDY DESIGN We performed genome-wide MR analysis by integrating expression quantitative trait loci (eQTL) of 4479 actionable genes that encode druggable proteins and genetic summary statistics from genome-wide association studies of psychiatric disorders. After conducting colocalization analysis on the brain MR findings, we employed protein quantitative trait loci (pQTL) data as genetic proposed instruments for intersecting the colocalized genes to provide further genetic evidence. STUDY RESULTS By performing MR and colocalization analysis with eQTL genetic instruments, we obtained 31 promising drug targets for psychiatric disorders, including 21 significant genes for schizophrenia, 7 for bipolar disorder, 2 for depression, 1 for attention deficit and hyperactivity (ADHD) and none for autism spectrum disorder. Combining MR results using pQTL genetic instruments, we finally proposed 8 drug-targeting genes supported by the strongest MR evidence, including gene ACE, BTN3A3, HAPLN4, MAPK3 and NEK4 for schizophrenia, gene NEK4 and HAPLN4 for bipolar disorder, and gene TIE1 for ADHD. CONCLUSIONS Our findings with genetic support were more likely to be to succeed in clinical trials. In addition, our study prioritizes approved drug targets for the development of new therapies and provides critical drug reuse opportunities for psychiatric disorders.
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Affiliation(s)
- Xiaoyan Li
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
| | - Aotian Shen
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
| | - Yiran Zhao
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
| | - Junfeng Xia
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China
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14
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Sugolov A, Emmenegger E, Paterson AD, Sun L. Statistical Learning of Large-Scale Genetic Data: How to Run a Genome-Wide Association Study of Gene-Expression Data Using the 1000 Genomes Project Data. STATISTICS IN BIOSCIENCES 2023; 16:250-264. [PMID: 38495080 PMCID: PMC10940486 DOI: 10.1007/s12561-023-09375-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 04/07/2023] [Accepted: 05/22/2023] [Indexed: 03/19/2024]
Abstract
Teaching statistics through engaging applications to contemporary large-scale datasets is essential to attracting students to the field. To this end, we developed a hands-on, week-long workshop for senior high-school or junior undergraduate students, without prior knowledge in statistical genetics but with some basic knowledge in data science, to conduct their own genome-wide association study (GWAS). The GWAS was performed for open source gene expression data, using publicly available human genetics data. Assisted by a detailed instruction manual, students were able to obtain ∼ 1.4 million p-values from a real scientific study, within several days. This early motivation kept students engaged in learning the theories that support their results, including regression, data visualization, results interpretation, and large-scale multiple hypothesis testing. To further their learning motivation by emphasizing the personal connection to this type of data analysis, students were encouraged to make short presentations about how GWAS has provided insights into the genetic basis of diseases that are present in their friends or families. The appended open source, step-by-step instruction manual includes descriptions of the datasets used, the software needed, and results from the workshop. Additionally, scripts used in the workshop are archived on Github and Zenodo to further enhance reproducible research and training.
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Affiliation(s)
- Anton Sugolov
- Department of Mathematics,Faculty of Arts and Sciences, University of Toronto, Toronto, Canada
| | - Eric Emmenegger
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada
| | - Andrew D. Paterson
- Program in Genetics & Genome Biology The Hospital for Sick Children, University of Toronto, Toronto, ON Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Lei Sun
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Department of Statistical Sciences, Faculty of Arts and Sciences, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
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15
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Qiao J, Wu Y, Zhang S, Xu Y, Zhang J, Zeng P, Wang T. Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes. BMC Genomics 2023; 24:324. [PMID: 37312035 DOI: 10.1186/s12864-023-09425-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 06/01/2023] [Indexed: 06/15/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear. RESULTS By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection. CONCLUSIONS Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.
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Affiliation(s)
- Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuxuan Wu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yue Xu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Jinhui Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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16
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Zhang J, Zhang S, Qiao J, Wang T, Zeng P. Similarity and diversity of genetic architecture for complex traits between East Asian and European populations. BMC Genomics 2023; 24:314. [PMID: 37308816 DOI: 10.1186/s12864-023-09434-x] [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: 01/18/2023] [Accepted: 06/07/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Genome-wide association studies have detected a large number of single-nucleotide polymorphisms (SNPs) associated with complex traits in diverse ancestral groups. However, the trans-ethnic similarity and diversity of genetic architecture is not well understood currently. RESULTS By leveraging summary statistics of 37 traits from East Asian (Nmax=254,373) or European (Nmax=693,529) populations, we first evaluated the trans-ethnic genetic correlation (ρg) and found substantial evidence of shared genetic overlap underlying these traits between the two populations, with [Formula: see text] ranging from 0.53 (se = 0.11) for adult-onset asthma to 0.98 (se = 0.17) for hemoglobin A1c. However, 88.9% of the genetic correlation estimates were significantly less than one, indicating potential heterogeneity in genetic effect across populations. We next identified common associated SNPs using the conjunction conditional false discovery rate method and observed 21.7% of trait-associated SNPs can be identified simultaneously in both populations. Among these shared associated SNPs, 20.8% showed heterogeneous influence on traits between the two ancestral populations. Moreover, we demonstrated that population-common associated SNPs often exhibited more consistent linkage disequilibrium and allele frequency pattern across ancestral groups compared to population-specific or null ones. We also revealed population-specific associated SNPs were much likely to undergo natural selection compared to population-common associated SNPs. CONCLUSIONS Our study provides an in-depth understanding of similarity and diversity regarding genetic architecture for complex traits across diverse populations, and can assist in trans-ethnic association analysis, genetic risk prediction, and causal variant fine mapping.
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Affiliation(s)
- Jinhui Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China
| | - Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China.
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China.
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China.
- Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China.
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17
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Wen J, Sun Q, Huang L, Zhou L, Doyle MF, Ekunwe L, Olson NC, Reiner AP, Li Y, Raffield LM. Gene Expression and Splicing QTL Analysis of Blood Cells in African American Participants from the Jackson Heart Study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.26.538455. [PMID: 37163084 PMCID: PMC10168308 DOI: 10.1101/2023.04.26.538455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Most gene expression and alternative splicing quantitative trait loci (eQTL/sQTL) studies have been biased toward European ancestry individuals. Here, we performed eQTL and sQTL analysis using TOPMed whole genome sequencing-derived genotype data and RNA sequencing data from stored peripheral blood mononuclear cells in 1,012 African American participants from the Jackson Heart Study (JHS). At a false discovery rate (FDR) of 5%, we identified 4,798,604 significant eQTL-gene pairs, covering 16,538 unique genes; and 5,921,368 sQTL-gene-cluster pairs, covering 9,605 unique genes. About 31% of detected eQTL and sQTL variants with a minor allele frequency (MAF) > 1% in JHS were rare (MAF < 0.1%), and therefore unlikely to be detected, in European ancestry individuals. We also generated 17,630 eQTL credible sets and 24,525 sQTL credible sets for genes (gene-clusters) with lead QTL p < 5e-8. Finally, we created an open database, which is freely available online, allowing fast query and bulk download of our QTL results.
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18
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Knutson KA, Pan W. MATS: a novel multi-ancestry transcriptome-wide association study to account for heterogeneity in the effects of cis-regulated gene expression on complex traits. Hum Mol Genet 2023; 32:1237-1251. [PMID: 36179104 PMCID: PMC10077507 DOI: 10.1093/hmg/ddac247] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 09/16/2022] [Accepted: 09/28/2022] [Indexed: 01/16/2023] Open
Abstract
The Transcriptome-Wide Association Study (TWAS) is a widely used approach which integrates gene expression and Genome Wide Association Study (GWAS) data to study the role of cis-regulated gene expression (GEx) in complex traits. However, the genetic architecture of GEx varies across populations, and recent findings point to possible ancestral heterogeneity in the effects of GEx on complex traits, which may be amplified in TWAS by modeling GEx as a function of cis-eQTLs. Here, we present a novel extension to TWAS to account for heterogeneity in the effects of cis-regulated GEx which are correlated with ancestry. Our proposed Multi-Ancestry TwaS (MATS) framework jointly analyzes samples from multiple populations and distinguishes between shared, ancestry-specific and/or subject-specific expression-trait associations. As such, MATS amplifies power to detect shared GEx associations over ancestry-stratified TWAS through increased sample sizes, and facilitates the detection of genes with subgroup-specific associations which may be masked by standard TWAS. Our simulations highlight the improved Type-I error conservation and power of MATS compared with competing approaches. Our real data applications to Alzheimer's disease (AD) case-control genotypes from the Alzheimer's Disease Sequencing Project (ADSP) and continuous phenotypes from the UK Biobank (UKBB) identify a number of unique gene-trait associations which were not discovered through standard and/or ancestry-stratified TWAS. Ultimately, these findings promote MATS as a powerful method for detecting and estimating significant gene expression effects on complex traits within multi-ancestry cohorts and corroborates the mounting evidence for inter-population heterogeneity in gene-trait associations.
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Affiliation(s)
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
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19
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Grandt CL, Brackmann LK, Foraita R, Schwarz H, Hummel-Bartenschlager W, Hankeln T, Kraemer C, Zahnreich S, Drees P, Mirsch J, Spix C, Blettner M, Schmidberger H, Binder H, Hess M, Galetzka D, Marini F, Poplawski A, Marron M. Gene expression variability in long-term survivors of childhood cancer and cancer-free controls in response to ionizing irradiation. Mol Med 2023; 29:41. [PMID: 36997855 PMCID: PMC10061869 DOI: 10.1186/s10020-023-00629-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/20/2023] [Indexed: 04/01/2023] Open
Abstract
BACKGROUND Differential expression analysis is usually adjusted for variation. However, most studies that examined the expression variability (EV) have used computations affected by low expression levels and did not examine healthy tissue. This study aims to calculate and characterize an unbiased EV in primary fibroblasts of childhood cancer survivors and cancer-free controls (N0) in response to ionizing radiation. METHODS Human skin fibroblasts of 52 donors with a first primary neoplasm in childhood (N1), 52 donors with at least one second primary neoplasm (N2 +), as well as 52 N0 were obtained from the KiKme case-control study and exposed to a high (2 Gray) and a low dose (0.05 Gray) of X-rays and sham- irradiation (0 Gray). Genes were then classified as hypo-, non-, or hyper-variable per donor group and radiation treatment, and then examined for over-represented functional signatures. RESULTS We found 22 genes with considerable EV differences between donor groups, of which 11 genes were associated with response to ionizing radiation, stress, and DNA repair. The largest number of genes exclusive to one donor group and variability classification combination were all detected in N0: hypo-variable genes after 0 Gray (n = 49), 0.05 Gray (n = 41), and 2 Gray (n = 38), as well as hyper-variable genes after any dose (n = 43). While after 2 Gray positive regulation of cell cycle was hypo-variable in N0, (regulation of) fibroblast proliferation was over-represented in hyper-variable genes of N1 and N2+. In N2+, 30 genes were uniquely classified as hyper-variable after the low dose and were associated with the ERK1/ERK2 cascade. For N1, no exclusive gene sets with functions related to the radiation response were detected in our data. CONCLUSION N2+ showed high degrees of variability in pathways for the cell fate decision after genotoxic insults that may lead to the transfer and multiplication of DNA-damage via proliferation, where apoptosis and removal of the damaged genome would have been appropriate. Such a deficiency could potentially lead to a higher vulnerability towards side effects of exposure to high doses of ionizing radiation, but following low-dose applications employed in diagnostics, as well.
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Affiliation(s)
- Caine Lucas Grandt
- Leibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstr. 30, 28359, Bremen, Germany.
- Faculty of Human and Health Sciences, University of Bremen, Bremen, Germany.
| | - Lara Kim Brackmann
- Leibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstr. 30, 28359, Bremen, Germany
| | - Ronja Foraita
- Leibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstr. 30, 28359, Bremen, Germany
| | - Heike Schwarz
- Leibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstr. 30, 28359, Bremen, Germany
| | | | - Thomas Hankeln
- Institute of Organismic and Molecular Evolution, Molecular Genetics and Genome Analysis, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Christiane Kraemer
- Institute of Organismic and Molecular Evolution, Molecular Genetics and Genome Analysis, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sebastian Zahnreich
- Department of Radiation Oncology and Radiation Therapy, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Philipp Drees
- Department of Orthopaedics and Traumatology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Johanna Mirsch
- Radiation Biology and DNA Repair, Technical University of Darmstadt, Darmstadt, Germany
| | - Claudia Spix
- Division of Childhood Cancer Epidemiology, German Childhood Cancer Registry, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Maria Blettner
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), Center of the Johannes, University Medical, Gutenberg University, Mainz, Germany
| | - Heinz Schmidberger
- Department of Radiation Oncology and Radiation Therapy, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Harald Binder
- Institute of Medical Biometry and Statistics, University Medical Center, Freiburg, Germany
| | - Moritz Hess
- Institute of Medical Biometry and Statistics, University Medical Center, Freiburg, Germany
| | - Danuta Galetzka
- Department of Radiation Oncology and Radiation Therapy, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Federico Marini
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), Center of the Johannes, University Medical, Gutenberg University, Mainz, Germany
| | - Alicia Poplawski
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), Center of the Johannes, University Medical, Gutenberg University, Mainz, Germany
| | - Manuela Marron
- Leibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstr. 30, 28359, Bremen, Germany
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Kelly DE, Ramdas S, Ma R, Rawlings-Goss RA, Grant GR, Ranciaro A, Hirbo JB, Beggs W, Yeager M, Chanock S, Nyambo TB, Omar SA, Woldemeskel D, Belay G, Li H, Brown CD, Tishkoff SA. The genetic and evolutionary basis of gene expression variation in East Africans. Genome Biol 2023; 24:35. [PMID: 36829244 PMCID: PMC9951478 DOI: 10.1186/s13059-023-02874-4] [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: 03/03/2022] [Accepted: 02/13/2023] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND Mapping of quantitative trait loci (QTL) associated with molecular phenotypes is a powerful approach for identifying the genes and molecular mechanisms underlying human traits and diseases, though most studies have focused on individuals of European descent. While important progress has been made to study a greater diversity of human populations, many groups remain unstudied, particularly among indigenous populations within Africa. To better understand the genetics of gene regulation in East Africans, we perform expression and splicing QTL mapping in whole blood from a cohort of 162 diverse Africans from Ethiopia and Tanzania. We assess replication of these QTLs in cohorts of predominantly European ancestry and identify candidate genes under selection in human populations. RESULTS We find the gene regulatory architecture of African and non-African populations is broadly shared, though there is a considerable amount of variation at individual loci across populations. Comparing our analyses to an equivalently sized cohort of European Americans, we find that QTL mapping in Africans improves the detection of expression QTLs and fine-mapping of causal variation. Integrating our QTL scans with signatures of natural selection, we find several genes related to immunity and metabolism that are highly differentiated between Africans and non-Africans, as well as a gene associated with pigmentation. CONCLUSION Extending QTL mapping studies beyond European ancestry, particularly to diverse indigenous populations, is vital for a complete understanding of the genetic architecture of human traits and can reveal novel functional variation underlying human traits and disease.
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Affiliation(s)
- Derek E Kelly
- Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA
- Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Shweta Ramdas
- Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Rong Ma
- Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | - Jibril B Hirbo
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - William Beggs
- Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Meredith Yeager
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Stephen Chanock
- Division of Cancer Epidemiology and Genetics, National Institutes of Health, Rockville, MD, USA
| | - Thomas B Nyambo
- Department of Biochemistry, Kampala International University in Tanzania, Dar Es Salaam, Tanzania
| | - Sabah A Omar
- Center for Biotechnology Research and Development, Kenya Medical Research Institute, Nairobi, Kenya
| | - Dawit Woldemeskel
- Microbial Cellular and Molecular Biology Department, Addis Ababa University, Addis Ababa, Ethiopia
| | - Gurja Belay
- Microbial Cellular and Molecular Biology Department, Addis Ababa University, Addis Ababa, Ethiopia
| | - Hongzhe Li
- Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher D Brown
- Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA
- Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah A Tishkoff
- Genetics, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Biology, University of Pennsylvania, Philadelphia, USA.
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21
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Hansson O, Kumar A, Janelidze S, Stomrud E, Insel PS, Blennow K, Zetterberg H, Fauman E, Hedman ÅK, Nagle MW, Whelan CD, Baird D, Mälarstig A, Mattsson‐Carlgren N. The genetic regulation of protein expression in cerebrospinal fluid. EMBO Mol Med 2023; 15:e16359. [PMID: 36504281 PMCID: PMC9832827 DOI: 10.15252/emmm.202216359] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 11/12/2022] [Accepted: 11/14/2022] [Indexed: 12/14/2022] Open
Abstract
Studies of the genetic regulation of cerebrospinal fluid (CSF) proteins may reveal pathways for treatment of neurological diseases. 398 proteins in CSF were measured in 1,591 participants from the BioFINDER study. Protein quantitative trait loci (pQTL) were identified as associations between genetic variants and proteins, with 176 pQTLs for 145 CSF proteins (P < 1.25 × 10-10 , 117 cis-pQTLs and 59 trans-pQTLs). Ventricular volume (measured with brain magnetic resonance imaging) was a confounder for several pQTLs. pQTLs for CSF and plasma proteins were overall correlated, but CSF-specific pQTLs were also observed. Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP-10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease. CSF levels of GRN, MMP-10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively. These findings point to pathways to be explored for novel therapies. The novel finding that ventricular volume confounded pQTLs has implications for design of future studies of the genetic regulation of the CSF proteome.
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Affiliation(s)
- Oskar Hansson
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
- Memory ClinicSkåne University Hospital, Lund UniversityLundSweden
| | - Atul Kumar
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
- Memory ClinicSkåne University Hospital, Lund UniversityLundSweden
| | - Philip S Insel
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
- Department of Psychiatry and Behavioral SciencesUniversity of California, San FranciscoSan FranciscoCAUSA
| | - Kaj Blennow
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska AcademyUniversity of GothenburgMölndalSweden
| | - Henrik Zetterberg
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska AcademyUniversity of GothenburgMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Eric Fauman
- Internal Medicine Research UnitPfizer Worldwide Research, Development and MedicalCambridgeMAUSA
| | - Åsa K Hedman
- Pfizer Worldwide Research, Development and MedicalStockholmSweden
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Michael W Nagle
- Neurogenomics, Genetics‐Guided Dementia DiscoveryEisai, IncCambridgeMAUSA
| | | | - Denis Baird
- Department of Neurology, Skåne University HospitalLund UniversityLundSweden
| | - Anders Mälarstig
- Pfizer Worldwide Research, Development and MedicalStockholmSweden
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Niklas Mattsson‐Carlgren
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
- Department of Neurology, Skåne University HospitalLund UniversityLundSweden
- Wallenberg Center for Molecular MedicineLund UniversityLundSweden
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22
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Liu S, Won H, Clarke D, Matoba N, Khullar S, Mu Y, Wang D, Gerstein M. Illuminating links between cis-regulators and trans-acting variants in the human prefrontal cortex. Genome Med 2022; 14:133. [PMID: 36424644 PMCID: PMC9685876 DOI: 10.1186/s13073-022-01133-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 10/25/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Neuropsychiatric disorders afflict a large portion of the global population and constitute a significant source of disability worldwide. Although Genome-wide Association Studies (GWAS) have identified many disorder-associated variants, the underlying regulatory mechanisms linking them to disorders remain elusive, especially those involving distant genomic elements. Expression quantitative trait loci (eQTLs) constitute a powerful means of providing this missing link. However, most eQTL studies in human brains have focused exclusively on cis-eQTLs, which link variants to nearby genes (i.e., those within 1 Mb of a variant). A complete understanding of disease etiology requires a clearer understanding of trans-regulatory mechanisms, which, in turn, entails a detailed analysis of the relationships between variants and expression changes in distant genes. METHODS By leveraging large datasets from the PsychENCODE consortium, we conducted a genome-wide survey of trans-eQTLs in the human dorsolateral prefrontal cortex. We also performed colocalization and mediation analyses to identify mediators in trans-regulation and use trans-eQTLs to link GWAS loci to schizophrenia risk genes. RESULTS We identified ~80,000 candidate trans-eQTLs (at FDR<0.25) that influence the expression of ~10K target genes (i.e., "trans-eGenes"). We found that many variants associated with these candidate trans-eQTLs overlap with known cis-eQTLs. Moreover, for >60% of these variants (by colocalization), the cis-eQTL's target gene acts as a mediator for the trans-eQTL SNP's effect on the trans-eGene, highlighting examples of cis-mediation as essential for trans-regulation. Furthermore, many of these colocalized variants fall into a discernable pattern wherein cis-eQTL's target is a transcription factor or RNA-binding protein, which, in turn, targets the gene associated with the candidate trans-eQTL. Finally, we show that trans-regulatory mechanisms provide valuable insights into psychiatric disorders: beyond what had been possible using only cis-eQTLs, we link an additional 23 GWAS loci and 90 risk genes (using colocalization between candidate trans-eQTLs and schizophrenia GWAS loci). CONCLUSIONS We demonstrate that the transcriptional architecture of the human brain is orchestrated by both cis- and trans-regulatory variants and found that trans-eQTLs provide insights into brain-disease biology.
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Affiliation(s)
- Shuang Liu
- Waisman Center, University of Wisconsin - Madison, Madison, WI, 53705, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.,Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Declan Clarke
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Nana Matoba
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.,Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Saniya Khullar
- Waisman Center, University of Wisconsin - Madison, Madison, WI, 53705, USA.,Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, WI, 53706, USA
| | - Yudi Mu
- Department of Statistics, University of Wisconsin - Madison, Madison, WI, 53706, USA
| | - Daifeng Wang
- Waisman Center, University of Wisconsin - Madison, Madison, WI, 53705, USA. .,Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, WI, 53706, USA. .,Department of Computer Sciences, University of Wisconsin - Madison, Madison, WI, 53706, USA.
| | - Mark Gerstein
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA. .,Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA. .,Department of Computer Science, Yale University, New Haven, CT, 06520, USA. .,Department of Statistics and Data Science, Yale University, New Haven, CT, 06520, USA.
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23
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Zhang Y, Zhang CY, Li SW, Yuan J, Xu L, Wei YJ, Zhou F, Wang JY, Huo JH, Wang L, Feng LM, Kang CY, Yang JZ. A functional population-specific variant rs77416373 in the Ca V2.1 gene is associated with antidepressant treatment response in Han Chinese subjects with major depressive disorder. Asian J Psychiatr 2022; 77:103272. [PMID: 36181755 DOI: 10.1016/j.ajp.2022.103272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 08/30/2022] [Accepted: 09/23/2022] [Indexed: 11/29/2022]
Affiliation(s)
- Yan Zhang
- Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Chu-Yi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Shi-Wu Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Jing Yuan
- Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Li Xu
- Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Yu-Jun Wei
- Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Fang Zhou
- Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Jun-Yang Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Jin-Hua Huo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Lu Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Li-Mei Feng
- Department of Pharmacy, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Chuan-Yuan Kang
- Department of Psychosomatic Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
| | - Jian-Zhong Yang
- Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
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24
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Qiao J, Shao Z, Wu Y, Zeng P, Wang T. Detecting associated genes for complex traits shared across East Asian and European populations under the framework of composite null hypothesis testing. Lab Invest 2022; 20:424. [PMID: 36138484 PMCID: PMC9503281 DOI: 10.1186/s12967-022-03637-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 09/12/2022] [Indexed: 11/21/2022]
Abstract
Background Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking. Methods By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement. Results Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones. Conclusion Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03637-8.
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Affiliation(s)
- Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Zhonghe Shao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuxuan Wu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. .,Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. .,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. .,Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. .,Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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25
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Lee S, Yang HK, Lee HJ, Park DJ, Kong SH, Park SK. Systematic review of gastric cancer-associated genetic variants, gene-based meta-analysis, and gene-level functional analysis to identify candidate genes for drug development. Front Genet 2022; 13:928783. [PMID: 36081994 PMCID: PMC9446437 DOI: 10.3389/fgene.2022.928783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/25/2022] [Indexed: 12/05/2022] Open
Abstract
Objective: Despite being a powerful tool to identify novel variants, genome-wide association studies (GWAS) are not sufficient to explain the biological function of variants. In this study, we aimed to elucidate at the gene level the biological mechanisms involved in gastric cancer (GC) development and to identify candidate drug target genes. Materials and methods: We conducted a systematic review for GWAS on GC following the PRISMA guidelines. Single nucleotide polymorphism (SNP)-level meta-analysis and gene-based analysis (GBA) were performed to identify SNPs and genes significantly associated with GC. Expression quantitative trait loci (eQTL), disease network, pathway enrichment, gene ontology, gene-drug, and chemical interaction analyses were conducted to elucidate the function of the genes identified by GBA. Results: A review of GWAS on GC identified 226 SNPs located in 91 genes. In the comprehensive GBA, 44 genes associated with GC were identified, among which 12 genes (THBS3, GBAP1, KRTCAP2, TRIM46, HCN3, MUC1, DAP3, EFNA1, MTX1, PRKAA1, PSCA, and ABO) were eQTL. Using disease network and pathway analyses, we identified that PRKAA, THBS3, and EFNA1 were significantly associated with the PI3K-Alt-mTOR-signaling pathway, which is involved in various oncogenic processes, and that MUC1 acts as a regulator in both the PI3K-Alt-mTOR and P53 signaling pathways. Furthermore, RPKAA1 had the highest number of interactions with drugs and chemicals. Conclusion: Our study suggests that PRKAA1, a gene in the PI3K-Alt-mTOR-signaling pathway, could be a potential target gene for drug development associated with GC in the future. Systematic Review Registration: website, identifier registration number.
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Affiliation(s)
- Sangjun Lee
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, South Korea
| | - Han-Kwang Yang
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea
| | - Hyuk-Joon Lee
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea
| | - Do Joong Park
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea
| | - Seong-Ho Kong
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea
| | - Sue K. Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea
- Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, South Korea
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26
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Topouza DG, Choi J, Nesdoly S, Tarnouskaya A, Nicol CJB, Duan QL. Novel MicroRNA-Regulated Transcript Networks Are Associated with Chemotherapy Response in Ovarian Cancer. Int J Mol Sci 2022; 23:ijms23094875. [PMID: 35563265 PMCID: PMC9101651 DOI: 10.3390/ijms23094875] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/25/2022] [Accepted: 04/26/2022] [Indexed: 11/16/2022] Open
Abstract
High-grade serous ovarian cancer (HGSOC) is a highly lethal gynecologic cancer, in part due to resistance to platinum-based chemotherapy reported among 20% of patients. This study aims to generate novel hypotheses of the biological mechanisms underlying chemotherapy resistance, which remain poorly understood. Differential expression analyses of mRNA- and microRNA-sequencing data from HGSOC patients of The Cancer Genome Atlas identified 21 microRNAs associated with angiogenesis and 196 mRNAs enriched for adaptive immunity and translation. Coexpression network analysis identified three microRNA networks associated with chemotherapy response enriched for lipoprotein transport and oncogenic pathways, as well as two mRNA networks enriched for ubiquitination and lipid metabolism. These network modules were replicated in two independent ovarian cancer cohorts. Moreover, integrative analyses of the mRNA/microRNA sequencing and single-nucleotide polymorphisms (SNPs) revealed potential regulation of significant mRNA transcripts by microRNAs and SNPs (expression quantitative trait loci). Thus, we report novel transcriptional networks and biological pathways associated with resistance to platinum-based chemotherapy in HGSOC patients. These results expand our understanding of the effector networks and regulators of chemotherapy response, which will help to improve the management of ovarian cancer.
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Affiliation(s)
- Danai G. Topouza
- Department of Biomedical and Molecular Sciences, Queen’s University, 18 Stuart St., Kingston, ON K7L 3N6, Canada; (D.G.T.); (J.C.); (C.J.B.N.)
| | - Jihoon Choi
- Department of Biomedical and Molecular Sciences, Queen’s University, 18 Stuart St., Kingston, ON K7L 3N6, Canada; (D.G.T.); (J.C.); (C.J.B.N.)
| | - Sean Nesdoly
- School of Computing, Queen’s University, 21-25 Union St., Kingston, ON K7L 2N8, Canada; (S.N.); (A.T.)
| | - Anastasiya Tarnouskaya
- School of Computing, Queen’s University, 21-25 Union St., Kingston, ON K7L 2N8, Canada; (S.N.); (A.T.)
| | - Christopher J. B. Nicol
- Department of Biomedical and Molecular Sciences, Queen’s University, 18 Stuart St., Kingston, ON K7L 3N6, Canada; (D.G.T.); (J.C.); (C.J.B.N.)
- Department of Pathology and Molecular Medicine, Queen’s University, 88 Stuart St., Kingston, ON K7L 3N6, Canada
- Division of Cancer Biology and Genetics, Queen’s University Cancer Research Institute, Queen’s University, 10 Stuart St., Kingston, ON K7L 3N6, Canada
| | - Qing Ling Duan
- Department of Biomedical and Molecular Sciences, Queen’s University, 18 Stuart St., Kingston, ON K7L 3N6, Canada; (D.G.T.); (J.C.); (C.J.B.N.)
- School of Computing, Queen’s University, 21-25 Union St., Kingston, ON K7L 2N8, Canada; (S.N.); (A.T.)
- Correspondence:
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27
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A high-throughput real-time PCR tissue-of-origin test to distinguish blood from lymphoblastoid cell line DNA for (epi)genomic studies. Sci Rep 2022; 12:4684. [PMID: 35304543 PMCID: PMC8933453 DOI: 10.1038/s41598-022-08663-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/09/2022] [Indexed: 12/13/2022] Open
Abstract
Lymphoblastoid cell lines (LCLs) derive from blood infected in vitro by Epstein–Barr virus and were used in several genetic, transcriptomic and epigenomic studies. Although few changes were shown between LCL and blood genotypes (SNPs) validating their use in genetics, more were highlighted for other genomic features and/or in their transcriptome and epigenome. This could render them less appropriate for these studies, notably when blood DNA could still be available. Here we developed a simple, high-throughput and cost-effective real-time PCR approach allowing to distinguish blood from LCL DNA samples based on the presence of EBV relative load and rearranged T-cell receptors γ and β. Our approach was able to achieve 98.5% sensitivity and 100% specificity on DNA of known origin (458 blood and 316 LCL DNA). It was further applied to 1957 DNA samples from the CEPH Aging cohort comprising DNA of uncertain origin, identifying 784 blood and 1016 LCL DNA. A subset of these DNA was further analyzed with an epigenetic clock indicating that DNA extracted from blood should be preferred to LCL for DNA methylation-based age prediction analysis. Our approach could thereby be a powerful tool to ascertain the origin of DNA in old collections prior to (epi)genomic studies.
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28
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Abell NS, DeGorter MK, Gloudemans MJ, Greenwald E, Smith KS, He Z, Montgomery SB. Multiple causal variants underlie genetic associations in humans. Science 2022; 375:1247-1254. [PMID: 35298243 PMCID: PMC9725108 DOI: 10.1126/science.abj5117] [Citation(s) in RCA: 99] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Associations between genetic variation and traits are often in noncoding regions with strong linkage disequilibrium (LD), where a single causal variant is assumed to underlie the association. We applied a massively parallel reporter assay (MPRA) to functionally evaluate genetic variants in high, local LD for independent cis-expression quantitative trait loci (eQTL). We found that 17.7% of eQTLs exhibit more than one major allelic effect in tight LD. The detected regulatory variants were highly and specifically enriched for activating chromatin structures and allelic transcription factor binding. Integration of MPRA profiles with eQTL/complex trait colocalizations across 114 human traits and diseases identified causal variant sets demonstrating how genetic association signals can manifest through multiple, tightly linked causal variants.
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Affiliation(s)
- Nathan S. Abell
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Marianne K. DeGorter
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | | | - Emily Greenwald
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Kevin S. Smith
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Stephen B. Montgomery
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, 94305, USA
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29
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Lee M, Lindo J, Rilling JK. Exploring gene-culture coevolution in humans by inferring neuroendophenotypes: A case study of the oxytocin receptor gene and cultural tightness. GENES, BRAIN, AND BEHAVIOR 2022; 21:e12783. [PMID: 35044077 PMCID: PMC8917075 DOI: 10.1111/gbb.12783] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 10/25/2021] [Accepted: 11/15/2021] [Indexed: 01/17/2023]
Abstract
The gene-culture coevolution (GCC) framework has gained increasing prominence in the social and biological sciences. While most studies on human GCC concern the evolution of low-level physiological traits, attempts have also been made to apply GCC to complex human traits, including social behavior and cognition. One major methodological challenge in this endeavor is to reconstruct a specific biological pathway between the implicated genes and their distal phenotypes. Here, we introduce a novel approach that combines data on population genetics and expression quantitative trait loci to infer the specific intermediate phenotypes of genes in the brain. We suggest that such "neuroendophenotypes" will provide more detailed mechanistic insights into the GCC process. We present a case study where we explored a GCC dynamics between the oxytocin receptor gene (OXTR) and cultural tightness-looseness. By combining data from the 1000 Genomes project and the Gene-Tissue-Expression project (GTEx), we estimated and compared OXTR expression in 10 brain regions across five human superpopulations. We found that OXTR expression in the anterior cingulate cortex (ACC) was highly variable across populations, and this variation correlated with cultural tightness and socio-ecological threats worldwide. The mediation models also suggested possible GCC dynamics where the increased OXTR expression in the ACC mediates or emerges from the tight culture and higher socio-ecological threats. Formal selection scans further confirmed that OXTR alleles linked to enhanced receptor expression in the ACC underwent positive selection in East Asian countries with tighter social norms. We discuss the implications of our method in human GCC research.
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Affiliation(s)
- Minwoo Lee
- Department of Anthropology, Emory UniversityAtlantaGeorgiaUSA
| | - John Lindo
- Department of Anthropology, Emory UniversityAtlantaGeorgiaUSA
| | - James K. Rilling
- Department of Anthropology, Emory UniversityAtlantaGeorgiaUSA,Department of Psychiatry and Behavioral Science, Emory UniversityAtlantaGeorgiaUSA,Center for Behavioral Neuroscience, Emory UniversityAtlantaGeorgiaUSA,Yerkes National Primate Research Center, Emory UniversityAtlantaGeorgiaUSA,Center for Translational Social Neuroscience, Emory UniversityAtlantaGeorgiaUSA
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Quiver MH, Lachance J. Adaptive eQTLs reveal the evolutionary impacts of pleiotropy and tissue-specificity while contributing to health and disease. HGG ADVANCES 2022; 3:100083. [PMID: 35047867 PMCID: PMC8756519 DOI: 10.1016/j.xhgg.2021.100083] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 12/21/2021] [Indexed: 11/24/2022] Open
Abstract
Large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans, and many of these regulatory variants have large allele frequency differences between populations. Here, we conducted genome-wide scans of selection to identify adaptive eQTLs (i.e., eQTLs with large population branch statistics). We then tested if tissue pleiotropy affects whether eQTLs are more or less likely to be adaptive and identified tissues that have been key targets of positive selection during the last 100,000 years. Top adaptive eQTL outliers include rs1043809, rs66899053, and rs2814778 (a SNP that is associated with malaria resistance). We found that effect sizes of eQTLs were negatively correlated with population branch statistics and that adaptive eQTLs affect two-thirds as many tissues as do non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results imply that pleiotropy inhibits adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we found that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for signatures of positive selection. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. Scans of selections also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that eQTLs have played an important role in recent human evolution.
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Affiliation(s)
- Melanie H Quiver
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
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31
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Natri HM, Hudjashov G, Jacobs G, Kusuma P, Saag L, Darusallam CC, Metspalu M, Sudoyo H, Cox MP, Gallego Romero I, Banovich NE. Genetic architecture of gene regulation in Indonesian populations identifies QTLs associated with global and local ancestries. Am J Hum Genet 2022; 109:50-65. [PMID: 34919805 PMCID: PMC8764200 DOI: 10.1016/j.ajhg.2021.11.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 11/16/2021] [Indexed: 02/07/2023] Open
Abstract
Lack of diversity in human genomics limits our understanding of the genetic underpinnings of complex traits, hinders precision medicine, and contributes to health disparities. To map genetic effects on gene regulation in the underrepresented Indonesian population, we have integrated genotype, gene expression, and CpG methylation data from 115 participants across three island populations that capture the major sources of genomic diversity in the region. In a comparison with European datasets, we identify eQTLs shared between Indonesia and Europe as well as population-specific eQTLs that exhibit differences in allele frequencies and/or overall expression levels between populations. By combining local ancestry and archaic introgression inference with eQTLs and methylQTLs, we identify regulatory loci driven by modern Papuan ancestry as well as introgressed Denisovan and Neanderthal variation. GWAS colocalization connects QTLs detected here to hematological traits, and further comparison with European datasets reflects the poor overall transferability of GWAS statistics across diverse populations. Our findings illustrate how population-specific genetic architecture, local ancestry, and archaic introgression drive variation in gene regulation across genetically distinct and in admixed populations and highlight the need for performing association studies on non-European populations.
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Affiliation(s)
- Heini M Natri
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA; The Translational Genomics Research Institute, Phoenix, AZ 85004, USA
| | - Georgi Hudjashov
- Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North 4410, New Zealand; Centre for Genomics, Evolution and Medicine, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Guy Jacobs
- Leverhulme Centre for Human Evolutionary Studies, Department of Archaeology, University of Cambridge, Cambridge CB2 1QH, UK; Complexity Institute, Nanyang Technological University, Singapore, 637460
| | - Pradiptajati Kusuma
- Complexity Institute, Nanyang Technological University, Singapore, 637460; Laboratory of Genome Diversity and Disease, Eijkman Institute for Molecular Biology, Jakarta 10430, Indonesia
| | - Lauri Saag
- Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Chelzie Crenna Darusallam
- Laboratory of Genome Diversity and Disease, Eijkman Institute for Molecular Biology, Jakarta 10430, Indonesia
| | - Mait Metspalu
- Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Herawati Sudoyo
- Laboratory of Genome Diversity and Disease, Eijkman Institute for Molecular Biology, Jakarta 10430, Indonesia
| | - Murray P Cox
- Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North 4410, New Zealand
| | - Irene Gallego Romero
- Centre for Genomics, Evolution and Medicine, Institute of Genomics, University of Tartu, Tartu 51010, Estonia; Melbourne Integrative Genomics, University of Melbourne, Parkville, VIC 3010, Australia; School of BioSciences, University of Melbourne, Parkville, VIC 3010, Australia; Centre for Stem Cell Systems, University of Melbourne, Parkville, VIC 3010, Australia
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32
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Elorbany R, Popp JM, Rhodes K, Strober BJ, Barr K, Qi G, Gilad Y, Battle A. Single-cell sequencing reveals lineage-specific dynamic genetic regulation of gene expression during human cardiomyocyte differentiation. PLoS Genet 2022; 18:e1009666. [PMID: 35061661 PMCID: PMC8809621 DOI: 10.1371/journal.pgen.1009666] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 02/02/2022] [Accepted: 12/21/2021] [Indexed: 12/13/2022] Open
Abstract
Dynamic and temporally specific gene regulatory changes may underlie unexplained genetic associations with complex disease. During a dynamic process such as cellular differentiation, the overall cell type composition of a tissue (or an in vitro culture) and the gene regulatory profile of each cell can both experience significant changes over time. To identify these dynamic effects in high resolution, we collected single-cell RNA-sequencing data over a differentiation time course from induced pluripotent stem cells to cardiomyocytes, sampled at 7 unique time points in 19 human cell lines. We employed a flexible approach to map dynamic eQTLs whose effects vary significantly over the course of bifurcating differentiation trajectories, including many whose effects are specific to one of these two lineages. Our study design allowed us to distinguish true dynamic eQTLs affecting a specific cell lineage from expression changes driven by potentially non-genetic differences between cell lines such as cell composition. Additionally, we used the cell type profiles learned from single-cell data to deconvolve and re-analyze data from matched bulk RNA-seq samples. Using this approach, we were able to identify a large number of novel dynamic eQTLs in single cell data while also attributing dynamic effects in bulk to a particular lineage. Overall, we found that using single cell data to uncover dynamic eQTLs can provide new insight into the gene regulatory changes that occur among heterogeneous cell types during cardiomyocyte differentiation.
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Affiliation(s)
- Reem Elorbany
- Interdisciplinary Scientist Training Program, University of Chicago, Chicago, Illinois, United States of America
| | - Joshua M. Popp
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Katherine Rhodes
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Benjamin J. Strober
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Kenneth Barr
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Guanghao Qi
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Yoav Gilad
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Department of Medicine, University of Chicago, Chicago, Illinois, United States of America
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, United States of America
- Department of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
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33
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McHenry ML, Benchek P, Malone L, Nsereko M, Mayanja-Kizza H, Boom WH, Williams SM, Hawn TR, Stein CM. Resistance to TST/IGRA conversion in Uganda: Heritability and Genome-Wide Association Study. EBioMedicine 2021; 74:103727. [PMID: 34871961 PMCID: PMC8652006 DOI: 10.1016/j.ebiom.2021.103727] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 11/17/2021] [Accepted: 11/17/2021] [Indexed: 11/09/2022] Open
Abstract
Background Pulmonary tuberculosis (TB) is one of the most deadly pathogens on earth. However, the majority of people have resistance to active disease. Further, some individuals, termed resisters (RSTRs), do not develop traditional latent tuberculosis (LTBI). The RSTR phenotype is important for understanding pathogenesis and preventing TB. The host genetic underpinnings of RSTR are largely understudied. Methods In a cohort of 908 Ugandan subjects with genome-wide data on single nucleotide polymorphisms, we assessed the heritability of the RSTR phenotype and other TB phenotypes using restricted maximum likelihood estimation (REML). We then used a subset of 263 RSTR and LTBI subjects with high quality phenotyping and long-term follow-up to identify DNA variants genome-wide associated with the RSTR phenotype relative to LTBI subjects in a case-control GWAS design and annotated and enriched these variants to better understand their role in TB pathogenesis. Results The heritability of the TB outcomes was very high, at 55% for TB vs. LTBI and 50.4% for RSTR vs. LTBI among HIV- subjects, controlling for age and sex. We identified 27 loci associated with the RSTR phenotype (P<5e-05) and our annotation and enrichment analyses suggest an important regulatory role for many of them. Interpretation The heritability results show that the genetic contribution to variation in TB outcomes is very high and our GWAS results highlight variants that may play an important role in resistance to infection as well as TB pathogenesis as a whole.
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Affiliation(s)
- Michael L McHenry
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Penelope Benchek
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - LaShaunda Malone
- Department of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Mary Nsereko
- Department of Medicine, School of Medicine, Makerere University, Kampala, Uganda
| | | | - W Henry Boom
- Department of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Scott M Williams
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Thomas R Hawn
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Catherine M Stein
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA; Department of Medicine, Case Western Reserve University, Cleveland, OH, USA
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34
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Zhang Q, He Y, Xu H, Li L, Guo Y, Zhang J, Cheng L, Yu H, Dai Y, Yang Q, Yang Z, Li C, Zhang S, Zhu S, Luo B, Gao Y. Modulation of STIM1 by a risk insertion/deletion polymorphism underlying genetics susceptibility to sudden cardiac death originated from coronary artery disease. Forensic Sci Int 2021; 328:111010. [PMID: 34592581 DOI: 10.1016/j.forsciint.2021.111010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/17/2021] [Indexed: 12/29/2022]
Abstract
Stromal interaction molecule 1 (STIM1), as a dynamic calcium signal transducer and key regulator of cardiomyocyte Ca2+ homeostasis, has been implicated in various pathological processes related to sudden cardiac death originated from coronary artery disease (SCD-CAD). In this study, we performed a systematic variant screening on promoter region of STIM1 to filter potential functional genetic variations. Based on the screening results, a 5-bp insertion/deletion (indel) polymorphism (rs3061890) in promoter region of STIM1 was selected as the candidate variant. We investigated the association of rs3061890 with SCD-CAD susceptibility in Chinese Han populations. The homozygote del/del genotype significantly increased risk for SCD-CAD as compared with the ins/ins genotype (odds ratio, 2.86 [95% confidence interval, 1.69-4.29]; P = 2.3 × 10-5). Compared with the common allele, the 5-bp deletion risk allele exhibited lower transcriptional capacity in luciferase assays. Intriguingly, genotype-phenotype correlation studies using human myocardium tissue samples revealed that the expression of STIM1 was associated with the genotype of rs3061890. Computational prediction combined with electrophoretic mobility shift (EMSA) and chromatin immunoprecipitation (ChIP) assays provided convincing evidence for stronger binding affinity of ELF1 (E74 like ETS transcription factor 1) with the deletion allele promoter. Taken together, our findings implied an allele-specific mechanism of regulating the transcription of STIM1 via ELF1, which contribute to SCD-CAD susceptibility. rs3061890 may thus considered as a candidate genetic marker for SCD-CAD prediction and prevention.
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Affiliation(s)
- Qing Zhang
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.
| | - Yan He
- Department of Epidemiology, Medical College of Soochow University, Suzhou, China.
| | - Hongfei Xu
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.
| | - Lijuan Li
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.
| | - Yadong Guo
- Department of Forensic Sciences, School of Basic Medical Sciences, Central South University, Changsha, China.
| | - Jianhua Zhang
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, Shanghai, China.
| | - Lei Cheng
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Huan Yu
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.
| | - Yunda Dai
- Department of Forensic Pathology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
| | - Qi Yang
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.
| | - Zhenzhen Yang
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.
| | - Chengtao Li
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, Shanghai, China.
| | - Suhua Zhang
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, Shanghai, China.
| | - Shaohua Zhu
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.
| | - Bin Luo
- Department of Forensic Pathology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
| | - Yuzhen Gao
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.
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35
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Isshiki M, Naka I, Kimura R, Nishida N, Furusawa T, Natsuhara K, Yamauchi T, Nakazawa M, Ishida T, Inaoka T, Matsumura Y, Ohtsuka R, Ohashi J. Admixture with indigenous people helps local adaptation: admixture-enabled selection in Polynesians. BMC Ecol Evol 2021; 21:179. [PMID: 34551727 PMCID: PMC8456657 DOI: 10.1186/s12862-021-01900-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 08/25/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Homo sapiens have experienced admixture many times in the last few thousand years. To examine how admixture affects local adaptation, we investigated genomes of modern Polynesians, who are shaped through admixture between Austronesian-speaking people from Southeast Asia (Asian-related ancestors) and indigenous people in Near Oceania (Papuan-related ancestors). METHODS In this study local ancestry was estimated across the genome in Polynesians (23 Tongan subjects) to find the candidate regions of admixture-enabled selection contributed by Papuan-related ancestors. RESULTS The mean proportion of Papuan-related ancestry across the Polynesian genome was estimated as 24.6% (SD = 8.63%), and two genomic regions, the extended major histocompatibility complex (xMHC) region on chromosome 6 and the ATP-binding cassette transporter sub-family C member 11 (ABCC11) gene on chromosome 16, showed proportions of Papuan-related ancestry more than 5 SD greater than the mean (> 67.8%). The coalescent simulation under the assumption of selective neutrality suggested that such signals of Papuan-related ancestry enrichment were caused by positive selection after admixture (false discovery rate = 0.045). The ABCC11 harbors a nonsynonymous SNP, rs17822931, which affects apocrine secretory cell function. The approximate Bayesian computation indicated that, in Polynesian ancestors, a strong positive selection (s = 0.0217) acted on the ancestral allele of rs17822931 derived from Papuan-related ancestors. CONCLUSIONS Our results suggest that admixture with Papuan-related ancestors contributed to the rapid local adaptation of Polynesian ancestors. Considering frequent admixture events in human evolution history, the acceleration of local adaptation through admixture should be a common event in humans.
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Affiliation(s)
- Mariko Isshiki
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, 113-0033 Japan
| | - Izumi Naka
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, 113-0033 Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara, 903-0125 Japan
| | - Nao Nishida
- Genome Medical Science Project, Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Chiba, 272-8516 Japan
| | - Takuro Furusawa
- Graduate School of Asian and African Area Studies, Kyoto University, Kyoto, 606-8501 Japan
| | - Kazumi Natsuhara
- Department of International Health and Nursing, Faculty of Nursing, Toho University, Tokyo, 143-0015 Japan
| | - Taro Yamauchi
- Faculty of Health Sciences, Hokkaido University, Sapporo, 060-0812 Japan
| | - Minato Nakazawa
- Graduate School of Health Sciences, Kobe University, Kobe, 654-0142 Japan
| | - Takafumi Ishida
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, 113-0033 Japan
| | - Tsukasa Inaoka
- Department of Human Ecology, Faculty of Agriculture, Saga University, Saga, 840-8502 Japan
| | - Yasuhiro Matsumura
- Faculty of Health and Nutrition, Bunkyo University, Chigasaki, 253-8550 Japan
| | | | - Jun Ohashi
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, 113-0033 Japan
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Zhen Q, Zhang Y, Yu Y, Yang H, Zhang T, Li X, Mo X, Li B, Wu J, Liang Y, Ge H, Xu Q, Chen W, Qian W, Xu H, Chen G, Bai B, Zhang J, Lu Y, Chen S, Zhang H, Zhang Y, Chen X, Li X, Jin X, Lin X, Yong L, Fang M, Zhao J, Lu Y, Wu S, Jiang D, Shi J, Cao H, Qiu Y, Li S, Kang X, Shen J, Ma H, Sun S, Fan Y, Chen W, Bai M, Jiang Q, Li W, Lv C, Li S, Chen M, Li F, Li Y, Sun L. Three Novel Structural Variations at MHC and IL12B Predisposing to Psoriasis. Br J Dermatol 2021; 186:307-317. [PMID: 34498260 DOI: 10.1111/bjd.20752] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/07/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Structural variations (SVs, defined as DNA variants ≥50 bp) have been associated with various complex human diseases. However, research to screen the whole genome for SVs predisposing to psoriasis is still lacking. OBJECTIVES This study aimed to investigate the association of SVs and psoriasis. METHODS We performed a genome-wide screen on SVs using an imputation method on 5 independent cohorts with 45,386 subjects from the Chinese Han population. Fine mapping analysis, genetic interaction analysis and RNA expression analysis were conducted to explore the mechanism of SVs. RESULTS We obtained 4,535 SVs in total and identified 2 novel deletions (esv3608550, OR=2.73, P<2.00×10-308 ; esv3608542, OR=0.47, P=7.40×10-28 ) at 6q21.33 (MHC), 1 novel Alu element insertion (esv3607339, OR=1.22, P=1.18×10-35 ) at 5q33.3 (IL12B), and confirmed 1 previously reported deletion (esv3587563, OR=1.30, P=9.52×10-60 ) at 1q21.2 (LCE) for psoriasis. Fine mapping analysis including SNPs and small Insertions/Deletions (InDels) revealed that esv3608550 and esv3608542 were independently associated with psoriasis, and a novel independent SNP (rs9378188, OR=1.65, P=3.46×10-38 ) was identified at 6q21.33. By genetic interaction analysis and RNA expression analysis, we speculate that the association of 2 deletions at 6q21.33 with psoriasis might relate to their influence on the expression of HLA-C. CONCLUSIONS Our study constructed the most comprehensive SV map for psoriasis thus far and enriched the genetic architecture and pathogenesis of psoriasis as well as highlighted the nonnegligible impact of SVs on complex diseases.
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Affiliation(s)
- Q Zhen
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - Y Zhang
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Y Yu
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - H Yang
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - T Zhang
- Department of Biology, University of Copenhagen, Ole MaalØes Vej 5, 2200, Copenhagen, Denmark
| | - X Li
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - X Mo
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - B Li
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,The Comprehensive Lab, College of Basic, Anhui Medical University
| | - J Wu
- Department of Dermatology, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University
| | - Y Liang
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - H Ge
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - Q Xu
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - W Chen
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - W Qian
- Institute of Dermalology, Guangzhou Medical University, Guangzhou, 510095, China
| | - H Xu
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - G Chen
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - B Bai
- Department of Dermatology at No.2 Hospital, Harbin Medical University, Harbin, Heilongjiang, 150001, China
| | - J Zhang
- Department of Dermatology, The 195 Hospital of Chinese People's Liberation Army, Xianning, Hubei, 437100, China
| | - Y Lu
- Dermatology Department of the First Affiliated Hospital, Nanjng Medical University, Nanjing, Jiangsu, 210029, China
| | - S Chen
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - H Zhang
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - Y Zhang
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - X Chen
- Department of Dermatology at Chengdu Second People's Hospital, Sichuan, Chengdu, 610017, China
| | - X Li
- Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437, China
| | - X Jin
- School of Medicine, South China University of Technology, Guangzhou, 510006, Guangdong, China
| | - X Lin
- Department of Neurology and Institute of Neurology, The First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, China
| | - L Yong
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
| | - M Fang
- Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture, Fisheries College, Jimei University, Xiamen, Fujian, 361021, China
| | - J Zhao
- Department of Dermatology, People's Hospital of Xinjiang Uygur Autonomous Region, Xinjiang, Urumqi, 830001, China
| | - Y Lu
- Department of Dermatology at Chengdu Second People's Hospital, Sichuan, Chengdu, 610017, China
| | - S Wu
- Urology Institute of Shenzhen University, The Luohu Affiliated Hospital of Shenzhen University
| | - D Jiang
- Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture, Fisheries College, Jimei University, Xiamen, Fujian, 361021, China
| | - J Shi
- Department of Dermatology at the Second Affiliated Hospital, Baotou Medical College, University Of Science and Technology Of The Inner Mongolia, Baotou, Inner Mongolia, 014030, China
| | - H Cao
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Y Qiu
- Department of Dermatology, Jining No. 1 People's Hospital, Shandong, 272011, China
| | - S Li
- Department of Dermatology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
| | - X Kang
- Department of Dermatology, People's Hospital of Xinjiang Uygur Autonomous Region, Xinjiang, Urumqi, 830001, China
| | - J Shen
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - H Ma
- Department of Dematology, the 2rd Hospital of Xi'an Jiaotong University. Xi'an, Shanxi, 710004, China
| | - S Sun
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Y Fan
- Department of Dermatology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
| | - W Chen
- Department of Neurology and Institute of Neurology, The First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, China
| | - M Bai
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Q Jiang
- Donggang Center Hospital, Dandong, Liaoning, 118300
| | - W Li
- Collaborative Innovation Center for Birth Defect Research and Transformation of Shandong Province, Jining Medical University, Jining, Shandong, 272067, China
| | - C Lv
- Dalian Dermatosis Hospital, Dalian, Liaoning, 116021, China
| | - S Li
- Department of Dermatology at No, Hospital of Jilin University, Changchun, Jilin, 130021, China
| | - M Chen
- Dermatology Hospital, Peking Union Medical College
| | - F Li
- Department of Dermatology, The Second Hospital of Jilin University, Changchun, 130041, China
| | - Y Li
- Department of Dermatology, The 195 Hospital of Chinese People's Liberation Army, Xianning, Hubei, 437100, China
| | - L Sun
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, China.,Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, China, 230032.,Anhui Provincial Institute of Translational Medicine, Hefei, 230032, China
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37
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Wang Z, Fan X, Shen Y, Pagadala MS, Signer R, Cygan KJ, Fairbrother WG, Carter H, Chung WK, Huang KL. Non-cancer-related pathogenic germline variants and expression consequences in ten-thousand cancer genomes. Genome Med 2021; 13:147. [PMID: 34503567 PMCID: PMC8431938 DOI: 10.1186/s13073-021-00964-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 08/30/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND DNA sequencing is increasingly incorporated into the routine care of cancer patients, many of whom also carry inherited, moderate/high-penetrance variants associated with other diseases. Yet, the prevalence and consequence of such variants remain unclear. METHODS We analyzed the germline genomes of 10,389 adult cancer cases in the TCGA cohort, identifying pathogenic/likely pathogenic variants in autosomal-dominant genes, autosomal-recessive genes, and 59 medically actionable genes curated by the American College of Molecular Genetics (i.e., the ACMG 59 genes). We also analyzed variant- and gene-level expression consequences in carriers. RESULTS The affected genes exhibited varying pan-ancestry and population-specific patterns, and overall, the European population showed the highest frequency of pathogenic/likely pathogenic variants. We further identified genes showing expression consequence supporting variant functionality, including altered gene expression, allelic specific expression, and mis-splicing determined by a massively parallel splicing assay. CONCLUSIONS Our results demonstrate that expression-altering variants are found in a substantial fraction of cases and illustrate the yield of genomic risk assessments for a wide range of diseases across diverse populations.
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Affiliation(s)
- Zishan Wang
- Department of Genetics and Genomic Sciences, Center for Transformative Disease Modeling, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Xiao Fan
- Departments of Pediatrics and Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Yufeng Shen
- Departments of Systems Biology and DBMI, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Meghana S Pagadala
- Department of Medicine, University of California San Diego, 9500 Gilman, San Diego, CA, 92093, USA
| | - Rebecca Signer
- Department of Genetics and Genomic Sciences, Center for Transformative Disease Modeling, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kamil J Cygan
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - William G Fairbrother
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Hannah Carter
- Department of Medicine, University of California San Diego, 9500 Gilman, San Diego, CA, 92093, USA
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
| | - Kuan-Lin Huang
- Department of Genetics and Genomic Sciences, Center for Transformative Disease Modeling, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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38
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Franceschini N, Morris AP. Genetics of kidney traits in worldwide populations: the Continental Origins and Genetic Epidemiology Network (COGENT) Kidney Consortium. Kidney Int 2021; 98:35-41. [PMID: 32571486 DOI: 10.1016/j.kint.2020.02.036] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 02/14/2020] [Accepted: 02/28/2020] [Indexed: 10/24/2022]
Affiliation(s)
- Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA.
| | - Andrew P Morris
- Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
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39
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Zhang Q, Yu H, Yang Z, Li L, He Y, Zhu S, Li C, Zhang S, Luo B, Gao Y. A Functional Indel Polymorphism Within MIR155HG Is Associated With Sudden Cardiac Death Risk in a Chinese Population. Front Cardiovasc Med 2021; 8:671168. [PMID: 34136547 PMCID: PMC8200405 DOI: 10.3389/fcvm.2021.671168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 04/29/2021] [Indexed: 11/17/2022] Open
Abstract
Sudden cardiac death (SCD) is a devastating complication of multiple disease processes and has gradually became a major public health issue. miR-155 is one of the best characterized miRNAs and plays a critical role in several physiological and pathological process, including cardiovascular diseases. In this study, we systematically screened the whole region of miR-155 host gene (MIR155HG) and identified a 4-bp insertion/deletion variant (rs72014506) residing in the intron region of MIR155HG as the candidate polymorphism. The association of rs72014506 with SCD susceptibility was evaluated using 166 SCD cases and 830 healthy controls in a Chinese population. Logistic regression analysis suggested that the homozygote del/del genotype significantly decreased the risk of SCD [odds ratio (OR) = 0.29; 95% confidence interval (CI) = 0.12–0.74; Ptrend = 0.0004]. Further genotype–expression association study using human myocardium tissue samples suggested that the deletion allele was intimately linked to lower the expression of both MIR155HG and mature miR155. Luciferase activity assay also revealed that the deletion allele of rs72014506 inhibited gene transcriptional activity. Finally, we performed electrophoretic mobility shift assay and verified the preferential binding affinity of the deletion allele with POU2F1 (POU domain class 2 transcription factor 1). Collectively, we have successfully identified a SCD risk conferring polymorphism in the MIR155HG gene and a likely biological mechanism for the decreased risk of SCD associated with the deletion allele. This novel variant may thus serve as a potential genetic marker for SCD diagnosis and prevention in natural populations, if validated by further studies with a larger sample size.
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Affiliation(s)
- Qing Zhang
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Huan Yu
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Zhenzhen Yang
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Lijuan Li
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Yan He
- Department of Epidemiology, Medical College of Soochow University, Suzhou, China
| | - Shaohua Zhu
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Chengtao Li
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, Shanghai, China
| | - Suhua Zhang
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, Shanghai, China
| | - Bin Luo
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Yuzhen Gao
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
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40
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Li X, Su X, Liu J, Li H, Li M, Li W, Luo XJ. Transcriptome-wide association study identifies new susceptibility genes and pathways for depression. Transl Psychiatry 2021; 11:306. [PMID: 34021117 PMCID: PMC8140098 DOI: 10.1038/s41398-021-01411-w] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Revised: 04/22/2021] [Accepted: 04/30/2021] [Indexed: 12/11/2022] Open
Abstract
Depression is the most prevalent mental disorder with substantial morbidity and mortality. Although genome-wide association studies (GWASs) have identified multiple risk variants for depression, due to the complicated gene regulatory mechanisms and complexity of linkage disequilibrium (LD), the biological mechanisms by which the risk variants exert their effects on depression remain largely unknown. Here, we perform a transcriptome-wide association study (TWAS) of depression by integrating GWAS summary statistics from 807,553 individuals (246,363 depression cases and 561,190 controls) and summary-level gene-expression data (from the dorsolateral prefrontal cortex (DLPFC) of 1003 individuals). We identified 53 transcriptome-wide significant (TWS) risk genes for depression, of which 23 genes were not implicated in risk loci of the original GWAS. Seven out of 53 risk genes (B3GALTL, FADS1, TCTEX1D1, XPNPEP3, ZMAT2, ZNF501 and ZNF502) showed TWS associations with depression in two independent brain expression quantitative loci (eQTL) datasets, suggesting that these genes may represent promising candidates. We further conducted conditional analyses and identified the potential risk genes that driven the TWAS association signal in each locus. Finally, pathway enrichment analysis revealed biologically pathways relevant to depression. Our study identified new depression risk genes whose expression dysregulation may play a role in depression. More importantly, we translated the GWAS associations into risk genes and relevant pathways. Further mechanistic study and functional characterization of the TWS depression risk genes will facilitate the diagnostics and therapeutics for depression.
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Affiliation(s)
- Xiaoyan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, 230601, Hefei, Anhui, China
| | - Xi Su
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, China
| | - Jiewei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
| | - Huijuan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China
| | - Wenqiang Li
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China.
- Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, China.
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China.
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, 650204, Kunming, Yunnan, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, 650204, Kunming, China.
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Characterization of intermediate-sized insertions using whole-genome sequencing data and analysis of their functional impact on gene expression. Hum Genet 2021; 140:1201-1216. [PMID: 33978893 DOI: 10.1007/s00439-021-02291-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 05/04/2021] [Indexed: 10/21/2022]
Abstract
Intermediate-sized insertions are one of the structural variants contributing to genome diversity. However, due to technical difficulties in identifying them, their importance in disease pathogenicity and gene expression regulation remains unclear. We used whole-genome sequencing data of 174 Japanese samples to characterize intermediate-sized insertions using a highly-accurate insertion calling method (IMSindel software and joint-call recovery) and obtained a catalogue of 4254 insertions. We constructed an imputation panel comprising of insertions and SNVs from all samples, and conducted imputation of intermediate-sized insertions for 82 publicly-available Japanese samples. Positive Predictive Value of imputation, evaluated using Nanopore long-read sequencing data, was 97%. Subsequent eQTL analysis predicted 128 (~ 3.0%) insertions as causative for gene expression level changes. Enrichment analysis of causal insertions for genome regulatory elements showed significant associations with CTCF-binding sites, super-enhancers, and promoters. Among 17 causal insertions found in the same causal set with GWAS hits, there were insertions associated with changes in expression of cancer-related genes such as BRCA1, ZNF222, and ABCB10. Analysis of insertions sequences revealed that 461 insertions were short tandem duplications frequently found in early-replicating regions of genome. Furthermore, comparison of functional importance of intermediate-sized insertions with that of intermediate-sized deletions detected in the same sample set in our previous study showed that insertions were more frequent in genic regions, and proportion of functional candidates was smaller in insertions. Here, we characterize a high-confidence set of intermediate-sized insertions and indicate their importance in gene expression regulation. Our results emphasize the importance of considering intermediate-sized insertions in trait association studies.
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42
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Bakhtiari M, Park J, Ding YC, Shleizer-Burko S, Neuhausen SL, Halldórsson BV, Stefánsson K, Gymrek M, Bafna V. Variable number tandem repeats mediate the expression of proximal genes. Nat Commun 2021; 12:2075. [PMID: 33824302 PMCID: PMC8024321 DOI: 10.1038/s41467-021-22206-z] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 02/17/2021] [Indexed: 12/12/2022] Open
Abstract
Variable number tandem repeats (VNTRs) account for significant genetic variation in many organisms. In humans, VNTRs have been implicated in both Mendelian and complex disorders, but are largely ignored by genomic pipelines due to the complexity of genotyping and the computational expense. We describe adVNTR-NN, a method that uses shallow neural networks to genotype a VNTR in 18 seconds on 55X whole genome data, while maintaining high accuracy. We use adVNTR-NN to genotype 10,264 VNTRs in 652 GTEx individuals. Associating VNTR length with gene expression in 46 tissues, we identify 163 "eVNTRs". Of the 22 eVNTRs in blood where independent data is available, 21 (95%) are replicated in terms of significance and direction of association. 49% of the eVNTR loci show a strong and likely causal impact on the expression of genes and 80% have maximum effect size at least 0.3. The impacted genes are involved in diseases including Alzheimer's, obesity and familial cancers, highlighting the importance of VNTRs for understanding the genetic basis of complex diseases.
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Affiliation(s)
- Mehrdad Bakhtiari
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Jonghun Park
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Yuan-Chun Ding
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | | | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | | | | | - Melissa Gymrek
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Vineet Bafna
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA.
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43
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Wang JY, Li XY, Li HJ, Liu JW, Yao YG, Li M, Xiao X, Luo XJ. Integrative Analyses Followed by Functional Characterization Reveal TMEM180 as a Schizophrenia Risk Gene. Schizophr Bull 2021; 47:1364-1374. [PMID: 33768244 PMCID: PMC8379544 DOI: 10.1093/schbul/sbab032] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Recent large-scale integrative analyses (including Transcriptome-Wide Association Study [TWAS] and Summary-data-based Mendelian Randomization [SMR]) have identified multiple genes whose cis-regulated expression changes may confer risk of schizophrenia. Nevertheless, expression quantitative trait loci (eQTL) data and genome-wide associations used for integrative analyses were mainly from populations of European ancestry, resulting in potential missing of pivotal biological insights in other continental populations due to population heterogeneity. Here we conducted TWAS and SMR integrative analyses using blood eQTL (from 162 subjects) and GWAS data (22 778 cases and 35 362 controls) of schizophrenia in East Asian (EAS) populations. Both TWAS (P = 2.89 × 10-14) and SMR (P = 6.04 × 10-5) analyses showed that decreased TMEM180 mRNA expression was significantly associated with risk of schizophrenia. We further found that TMEM180 was significantly down-regulated in the peripheral blood of schizophrenia cases compared with controls (P = 8.63 × 10-4 in EAS sample), and its expression was also significantly lower in the brain tissues of schizophrenia cases compared with controls (P = 1.87 × 10-5 in European sample from PsychENCODE). Functional explorations suggested that Tmem180 knockdown affected neurodevelopment, ie, proliferation and differentiation of neural stem cells. RNA sequencing showed that pathways regulated by Tmem180 were significantly enriched in brain development and synaptic transmission. In conclusion, our study provides convergent lines of evidence for the involvement of TMEM180 in schizophrenia, and highlights the potential and importance of resource integration and sharing at this big data era in bio-medical research.
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Affiliation(s)
- Jun-Yang Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
| | - Xiao-Yan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
| | - Hui-Juan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
| | - Jie-Wei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Yong-Gang Yao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,CAS Center for Excellence in Brain Science, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,CAS Center for Excellence in Brain Science, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China,To whom correspondence should be addressed; Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China; tel: +86-871-68125413, fax: +86-871-68125413, e-mail:
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Tsai YC, Huang CY, Hsueh YM, Fan YC, Fong YC, Huang SP, Geng JH, Chen LC, Lu TL, Bao BY. Genetic variants in MAPK10 modify renal cell carcinoma susceptibility and clinical outcomes. Life Sci 2021; 275:119396. [PMID: 33774030 DOI: 10.1016/j.lfs.2021.119396] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 03/08/2021] [Accepted: 03/20/2021] [Indexed: 12/09/2022]
Abstract
AIMS The mitogen-activated protein kinase (MAPK) cascades integrate various upstream signals to regulate many cellular functions, including proliferation, differentiation, and survival. Dysregulation of these pathways has been implicated in the occurrence and progression of a variety of cancers. MAIN METHODS This study aimed to assess the association of 192 single nucleotide polymorphisms in 22 MAPK cascade genes with renal cell carcinoma (RCC) risk and survival in 312 patients and 318 controls. KEY FINDINGS After multiple testing correction and multivariate analysis, the minor T allele of MAPK10 rs12648265 remained associated with a lower risk of RCC (adjusted odds ratio 0.64, 95% confidence interval 0.50-0.82, P = 0.000426) and metastasis (adjusted hazard ratio 0.50, 95% confidence interval 0.30-0.82, P = 0.006). Presence of the rs12648265 T allele demonstrated a trend towards being associated with increased MAPK10 expression, and meta-analysis of four RCC datasets indicated that high MAPK10 expression is associated with a favourable prognosis. Furthermore, activation of MAPK10 by the potent agonist anisomycin inhibited RCC cell growth in vitro, suggesting an involvement of MAPK10 in RCC progression. SIGNIFICANCE In conclusion, MAPK10 may be a meaningful biomarker and a potential therapeutic target in RCC.
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Affiliation(s)
- Yuan-Chin Tsai
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan; Ph.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 110, Taiwan
| | - Chao-Yuan Huang
- Department of Urology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei 100, Taiwan
| | - Yu-Mei Hsueh
- Department of Family Medicine, Wan Fang Hospital, Taipei Medical University, Taipei 116, Taiwan; Department of Public Health, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
| | - Yu-Ching Fan
- Ph.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 110, Taiwan
| | - Yu-Cin Fong
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan
| | - Shu-Pin Huang
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan; Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan; Department of Urology, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan; Center for Cancer Research, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Jiun-Hung Geng
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan; Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan; Department of Urology, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung 812, Taiwan
| | - Lih-Chyang Chen
- Department of Medicine, Mackay Medical College, New Taipei City 252, Taiwan
| | - Te-Ling Lu
- Department of Pharmacy, China Medical University, Taichung 406, Taiwan
| | - Bo-Ying Bao
- Department of Pharmacy, China Medical University, Taichung 406, Taiwan; Sex Hormone Research Center, China Medical University Hospital, Taichung 404, Taiwan; Department of Nursing, Asia University, Taichung 413, Taiwan.
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45
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Kassam I, Tan S, Gan FF, Saw WY, Tan LWL, Moong DKN, Soong R, Teo YY, Loh M. Genome-wide identification of cis DNA methylation quantitative trait loci in three Southeast Asian Populations. Hum Mol Genet 2021; 30:603-618. [PMID: 33547791 DOI: 10.1093/hmg/ddab038] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 01/25/2021] [Accepted: 01/28/2021] [Indexed: 12/12/2022] Open
Abstract
DNA methylation (DNAm) is an epigenetic modification that acts to regulate gene transcription, is essential for cellular processes and plays an important role in complex traits and disease. Variation in DNAm levels is influenced by both genetic and environmental factors. Several studies have examined the extent to which common genetic variation influences DNAm (i.e. mQTLs), however, an improved understanding of mQTLs across diverse human populations is needed to increase their utility in integrative genomic studies in order to further our understanding of complex trait and disease biology. Here, we systematically examine cis-mQTLs in three Southeast Asian populations in the Singapore Integrative Omics (iOmics) Study, comprised of Chinese (n = 93), Indians (n = 83) and Malays (n = 78). A total of 24 851 cis-mQTL probes were associated with at least one SNP in meta- and ethnicity-specific analyses at a stringent significance level. These cis-mQTL probes show significant differences in local SNP heritability between the ethnicities, enrichment in functionally relevant regions using data from the Roadmap Epigenomics Mapping Consortium and are associated with nearby genes and complex traits due to pleiotropy. Importantly, DNAm prediction performance and the replication of cis-mQTLs both within iOmics and between two independent mQTL studies in European and Bangladeshi individuals is best when the genetic distance between the ethnicities is small, with differences in cis-mQTLs likely due to differences in allele frequency and linkage disequilibrium. This study highlights the importance of, and opportunities from, extending investigation of the genetic control of DNAm to Southeast Asian populations.
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Affiliation(s)
- Irfahan Kassam
- Life Sciences Institute, National University of Singapore, Singapore 117456.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Sili Tan
- KK Research Centre, KK Women's and Children's Hospital, Singapore 229899
| | - Fei Fei Gan
- Department of NUH Tissue Repository, National University Health System, Singapore 119228
| | - Woei-Yuh Saw
- Baker Heart and Diabetes Institute, Melbourne Victoria, Australia 3004
| | - Linda Wei-Lin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Don Kyin Nwe Moong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Richie Soong
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599
| | - Yik-Ying Teo
- Life Sciences Institute, National University of Singapore, Singapore 117456.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232.,Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom W2 1PG.,Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research (ASTAR), Singapore 138648
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46
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Blencowe M, Ahn IS, Saleem Z, Luk H, Cely I, Mäkinen VP, Zhao Y, Yang X. Gene networks and pathways for plasma lipid traits via multitissue multiomics systems analysis. J Lipid Res 2021; 62:100019. [PMID: 33561811 PMCID: PMC7873371 DOI: 10.1194/jlr.ra120000713] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 12/04/2020] [Accepted: 12/23/2020] [Indexed: 12/13/2022] Open
Abstract
Genome-wide association studies (GWASs) have implicated ∼380 genetic loci for plasma lipid regulation. However, these loci only explain 17-27% of the trait variance, and a comprehensive understanding of the molecular mechanisms has not been achieved. In this study, we utilized an integrative genomics approach leveraging diverse genomic data from human populations to investigate whether genetic variants associated with various plasma lipid traits, namely, total cholesterol, high and low density lipoprotein cholesterol (HDL and LDL), and triglycerides, from GWASs were concentrated on specific parts of tissue-specific gene regulatory networks. In addition to the expected lipid metabolism pathways, gene subnetworks involved in "interferon signaling," "autoimmune/immune activation," "visual transduction," and "protein catabolism" were significantly associated with all lipid traits. In addition, we detected trait-specific subnetworks, including cadherin-associated subnetworks for LDL; glutathione metabolism for HDL; valine, leucine, and isoleucine biosynthesis for total cholesterol; and insulin signaling and complement pathways for triglyceride. Finally, by using gene-gene relations revealed by tissue-specific gene regulatory networks, we detected both known (e.g., APOH, APOA4, and ABCA1) and novel (e.g., F2 in adipose tissue) key regulator genes in these lipid-associated subnetworks. Knockdown of the F2 gene (coagulation factor II, thrombin) in 3T3-L1 and C3H10T1/2 adipocytes altered gene expression of Abcb11, Apoa5, Apof, Fabp1, Lipc, and Cd36; reduced intracellular adipocyte lipid content; and increased extracellular lipid content, supporting a link between adipose thrombin and lipid regulation. Our results shed light on the complex mechanisms underlying lipid metabolism and highlight potential novel targets for lipid regulation and lipid-associated diseases.
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Affiliation(s)
- Montgomery Blencowe
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA; Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - In Sook Ahn
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Zara Saleem
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Helen Luk
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ingrid Cely
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ville-Petteri Mäkinen
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA; South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Yuqi Zhao
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA; Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA; Interdepartmental Program of Bioinformatics, University of California, Los Angeles, Los Angeles, CA, USA.
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47
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Population-Matched Transcriptome Prediction Increases TWAS Discovery and Replication Rate. iScience 2020; 23:101850. [PMID: 33313492 PMCID: PMC7721644 DOI: 10.1016/j.isci.2020.101850] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 11/12/2020] [Accepted: 11/18/2020] [Indexed: 12/11/2022] Open
Abstract
Most genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) focus on European populations; however, these results cannot always be accurately applied to non-European populations due to genetic architecture differences. Using GWAS summary statistics in the Population Architecture using Genomics and Epidemiology study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we perform TWAS to determine gene-trait associations. We compared results using three transcriptome prediction models derived from Multi-Ethnic Study of Atherosclerosis populations: the African American and Hispanic/Latino (AFHI) model, the European (EUR) model, and the African American, Hispanic/Latino, and European (ALL) model. We identified 240 unique significant trait-associated genes. We found more significant, colocalized genes that replicate in larger cohorts when applying the AFHI model than the EUR or ALL model. Thus, TWAS with population-matched transcriptome models have more power for discovery and replication, demonstrating the need for more transcriptome studies in diverse populations.
TWAS mechanistically extends GWAS findings in diverse populations Population-matched transcriptome models detect more replicable associations Colocalization shows GWAS variants likely act through gene expression regulation More GWAS and transcriptome modeling in diverse populations are needed
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48
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Lee YG, Lee JY, Kim J, Kim YJ. Insertion variants missing in the human reference genome are widespread among human populations. BMC Biol 2020; 18:167. [PMID: 33187521 PMCID: PMC7666470 DOI: 10.1186/s12915-020-00894-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 10/09/2020] [Indexed: 01/07/2023] Open
Abstract
Background Structural variants comprise diverse genomic arrangements including deletions, insertions, inversions, and translocations, which can generally be detected in humans through sequence comparison to the reference genome. Among structural variants, insertions are the least frequently identified variants, mainly due to ascertainment bias in the reference genome, lack of previous sequence knowledge, and low complexity of typical insertion sequences. Though recent developments in long-read sequencing deliver promise in annotating individual non-reference insertions, population-level catalogues on non-reference insertion variants have not been identified and the possible functional roles of these hidden variants remain elusive. Results To detect non-reference insertion variants, we developed a pipeline, InserTag, which generates non-reference contigs by local de novo assembly and then infers the full-sequence of insertion variants by tracing contigs from non-human primates and other human genome assemblies. Application of the pipeline to data from 2535 individuals of the 1000 Genomes Project helped identify 1696 non-reference insertion variants and re-classify the variants as retention of ancestral sequences or novel sequence insertions based on the ancestral state. Genotyping of the variants showed that individuals had, on average, 0.92-Mbp sequences missing from the reference genome, 92% of the variants were common (allele frequency > 5%) among human populations, and more than half of the variants were major alleles. Among human populations, African populations were the most divergent and had the most non-reference sequences, which was attributed to the greater prevalence of high-frequency insertion variants. The subsets of insertion variants were in high linkage disequilibrium with phenotype-associated SNPs and showed signals of recent continent-specific selection. Conclusions Non-reference insertion variants represent an important type of genetic variation in the human population, and our developed pipeline, InserTag, provides the frameworks for the detection and genotyping of non-reference sequences missing from human populations. Supplementary information Supplementary information accompanies this paper at 10.1186/s12915-020-00894-1.
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Affiliation(s)
- Young-Gun Lee
- Department of Integrated Omics for Biomedical Science, WCU Graduate School, Yonsei University, Seoul, Republic of Korea
| | - Jin-Young Lee
- Department of Biochemistry, College of Life Science and Technology, Yonsei University, Seoul, Republic of Korea
| | - Junhyong Kim
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Young-Joon Kim
- Department of Integrated Omics for Biomedical Science, WCU Graduate School, Yonsei University, Seoul, Republic of Korea. .,Department of Biochemistry, College of Life Science and Technology, Yonsei University, Seoul, Republic of Korea.
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49
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Yang Z, Zhang Q, Yu H, Li L, He Y, Zhu S, Li C, Zhang S, Luo B, Gao Y. A Novel COX10 Deletion Polymorphism as a Susceptibility Factor for Sudden Cardiac Death Risk in Chinese Populations. DNA Cell Biol 2020; 40:10-17. [PMID: 33180568 DOI: 10.1089/dna.2020.6086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Identifying common genetic variations that are related to sudden cardiac death (SCD) is crucial since it can facilitate the diagnosis and risk stratification of SCD. It has been reported that COX10 mutations might be related with SCD. In this study, we performed a systematic variant screening on the COX10 to filter potential functional genetic variations. Based on the screening results, an insertion/deletion polymorphism (rs397763766) in 3'untranslated regions of COX10 was selected as the candidate variant. We conducted a case-control study to investigate the association between rs397763766 and SCD susceptibility in Chinese populations. Logistic regression analysis showed that the deletion allele of rs397763766 was associated with an increased risk for SCD (odds ratio = 1.61, 95% confidence interval = 1.25-2.07, p = 1.87 × 10-4) susceptibility than insertion allele. Further genotype-phenotype analysis using human cardiac tissue samples suggested that COX10 expression level in genotypes containing deletion allele was higher than that in ins/ins genotype. The results were further reinforced by RNA sequencing data from 1000 Genomes Project. Luciferase activity assay indicated that COX10 expression could be regulated by rs397763766 through interfering binding with miR-15b, thus conferring risk of SCD. In conclusion, the novel rs397763766 polymorphism might be a potential marker for molecular diagnosis and genetic counseling of SCD.
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Affiliation(s)
- Zhenzhen Yang
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China.,Institute of Forensic Sciences, Henan University of Economics and Law, Zhengzhou, China
| | - Qing Zhang
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Huan Yu
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Lijuan Li
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Yan He
- Department of Epidemiology, Medical College of Soochow University, Suzhou, China
| | - Shaohua Zhu
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Chengtao Li
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, Shanghai, China
| | - Suhua Zhang
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, Shanghai, China
| | - Bin Luo
- Department of Forensic Pathology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Yuzhen Gao
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
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50
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Owen KA, Price A, Ainsworth H, Aidukaitis BN, Bachali P, Catalina MD, Dittman JM, Howard TD, Kingsmore KM, Labonte AC, Marion MC, Robl RD, Zimmerman KD, Langefeld CD, Grammer AC, Lipsky PE. Analysis of Trans-Ancestral SLE Risk Loci Identifies Unique Biologic Networks and Drug Targets in African and European Ancestries. Am J Hum Genet 2020; 107:864-881. [PMID: 33031749 PMCID: PMC7675009 DOI: 10.1016/j.ajhg.2020.09.007] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 09/16/2020] [Indexed: 12/11/2022] Open
Abstract
Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder with a prominent genetic component. Individuals of African ancestry (AA) experience the disease more severely and with an increased co-morbidity burden compared to European ancestry (EA) populations. We hypothesize that the disparities in disease prevalence, activity, and response to standard medications between AA and EA populations is partially conferred by genomic influences on biological pathways. To address this, we applied a comprehensive approach to identify all genes predicted from SNP-associated risk loci detected with the Immunochip. By combining genes predicted via eQTL analysis, as well as those predicted from base-pair changes in intergenic enhancer sites, coding-region variants, and SNP-gene proximity, we were able to identify 1,731 potential ancestry-specific and trans-ancestry genetic drivers of SLE. Gene associations were linked to upstream and downstream regulators using connectivity mapping, and predicted biological pathways were mined for candidate drug targets. Examination of trans-ancestral pathways reflect the well-defined role for interferons in SLE and revealed pathways associated with tissue repair and remodeling. EA-dominant genetic drivers were more often associated with innate immune and myeloid cell function pathways, whereas AA-dominant pathways mirror clinical findings in AA subjects, suggesting disease progression is driven by aberrant B cell activity accompanied by ER stress and metabolic dysfunction. Finally, potential ancestry-specific and non-specific drug candidates were identified. The integration of all SLE SNP-predicted genes into functional pathways revealed critical molecular pathways representative of each population, underscoring the influence of ancestry on disease mechanism and also providing key insight for therapeutic selection.
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MESH Headings
- B-Lymphocytes/immunology
- B-Lymphocytes/pathology
- Black People
- Bortezomib/therapeutic use
- DNA, Intergenic/genetics
- DNA, Intergenic/immunology
- Enhancer Elements, Genetic
- Gene Expression
- Gene Ontology
- Gene Regulatory Networks
- Genetic Predisposition to Disease
- Genome, Human
- Genome-Wide Association Study
- Heterocyclic Compounds/therapeutic use
- Humans
- Interferons/genetics
- Interferons/immunology
- Isoquinolines/therapeutic use
- Lactams
- Lupus Erythematosus, Systemic/drug therapy
- Lupus Erythematosus, Systemic/ethnology
- Lupus Erythematosus, Systemic/genetics
- Lupus Erythematosus, Systemic/immunology
- Molecular Sequence Annotation
- Polymorphism, Single Nucleotide
- Protein Array Analysis
- Quantitative Trait Loci
- Quantitative Trait, Heritable
- White People
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Affiliation(s)
| | - Andrew Price
- AMPEL BioSolutions LLC, Charlottesville, VA 22902, USA
| | | | | | | | | | | | | | | | | | | | - Robert D Robl
- AMPEL BioSolutions LLC, Charlottesville, VA 22902, USA
| | - Kip D Zimmerman
- Wake Forest School of Medicine, Winston-Salem, NC 27109, USA
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