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Taşkoparan Ş, Altınay C, Barbaros Özer H. Recent updates of probiotic dairy-based beverages. Food Funct 2025; 16:1656-1669. [PMID: 39962909 DOI: 10.1039/d4fo06322h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2025]
Abstract
There is a rapid paradigm shift in the food consumption habits of consumers globally. The interest in healthier, safer, minimally processed and nature-identical foods is the driving force of this paradigm shift. Although the roots of this consumer trend go back further, especially the Covid-19 pandemic has contributed to the acceleration of this process. The effects of probiotics on human health have been known for many years. The commercial success of some probiotic microorganism strains, supported by clinical studies, is also evident. Probiotic microorganisms can be found in commercial products in a wide range of forms including powder, tablets or incorporated into liquid or solid food matrices. Milk and dairy products are suitable vehicles for the delivery of probiotics into the human body. Apart from well-established dairy-based probiotic foods including yogurt and yogurt-type beverages, in recent years some dairy products supplemented or enhanced with postbiotics and paraprobiotics are gaining popularity. The incorporation of next-generation probiotics in probiotic beverage formulations has also attracted the attention of researchers. The current state-of-the art for the utilization of next-generation probiotics, postbiotics and paraprobiotics in dairy-based probiotic beverages is the main focus of this review. Conventional milk-, whey- and buttermilk-based probiotic beverages are also covered.
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Affiliation(s)
- Şevval Taşkoparan
- Ankara University Faculty of Agriculture Department of Dairy Technology, Diskapi, Ankara, Turkey.
| | - Canan Altınay
- Ankara University Faculty of Agriculture Department of Dairy Technology, Diskapi, Ankara, Turkey.
| | - H Barbaros Özer
- Ankara University Faculty of Agriculture Department of Dairy Technology, Diskapi, Ankara, Turkey.
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2
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Mires S, Sommella E, Merciai F, Salviati E, Caponigro V, Basilicata MG, Marini F, Campiglia P, Baquedano M, Dong T, Skerritt C, Eastwood KA, Caputo M. Plasma metabolomic and lipidomic profiles accurately classify mothers of children with congenital heart disease: an observational study. Metabolomics 2024; 20:70. [PMID: 38955892 PMCID: PMC11219374 DOI: 10.1007/s11306-024-02129-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 05/08/2024] [Indexed: 07/04/2024]
Abstract
INTRODUCTION Congenital heart disease (CHD) is the most common congenital anomaly, representing a significant global disease burden. Limitations exist in our understanding of aetiology, diagnostic methodology and screening, with metabolomics offering promise in addressing these. OBJECTIVE To evaluate maternal metabolomics and lipidomics in prediction and risk factor identification for childhood CHD. METHODS We performed an observational study in mothers of children with CHD following pregnancy, using untargeted plasma metabolomics and lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). 190 cases (157 mothers of children with structural CHD (sCHD); 33 mothers of children with genetic CHD (gCHD)) from the children OMACp cohort and 162 controls from the ALSPAC cohort were analysed. CHD diagnoses were stratified by severity and clinical classifications. Univariate, exploratory and supervised chemometric methods were used to identify metabolites and lipids distinguishing cases and controls, alongside predictive modelling. RESULTS 499 metabolites and lipids were annotated and used to build PLS-DA and SO-CovSel-LDA predictive models to accurately distinguish sCHD and control groups. The best performing model had an sCHD test set mean accuracy of 94.74% (sCHD test group sensitivity 93.33%; specificity 96.00%) utilising only 11 analytes. Similar test performances were seen for gCHD. Across best performing models, 37 analytes contributed to performance including amino acids, lipids, and nucleotides. CONCLUSIONS Here, maternal metabolomic and lipidomic analysis has facilitated the development of sensitive risk prediction models classifying mothers of children with CHD. Metabolites and lipids identified offer promise for maternal risk factor profiling, and understanding of CHD pathogenesis in the future.
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Affiliation(s)
- Stuart Mires
- Translational Health Sciences, University of Bristol, Bristol, UK.
- University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.
| | | | | | | | - Vicky Caponigro
- Department of Pharmacy, University of Salerno, Salerno, Italy
| | - Manuela Giovanna Basilicata
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | | | | | - Mai Baquedano
- Translational Health Sciences, University of Bristol, Bristol, UK
| | - Tim Dong
- Translational Health Sciences, University of Bristol, Bristol, UK
| | - Clare Skerritt
- University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Kelly-Ann Eastwood
- Translational Health Sciences, University of Bristol, Bristol, UK
- University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Massimo Caputo
- Translational Health Sciences, University of Bristol, Bristol, UK
- University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
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3
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Heinzmann SS, Waldenberger M, Peters A, Schmitt-Kopplin P. Cluster Analysis Statistical Spectroscopy for the Identification of Metabolites in 1H NMR Metabolomics. Metabolites 2022; 12:metabo12100992. [PMID: 36295894 PMCID: PMC9607017 DOI: 10.3390/metabo12100992] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/14/2022] [Accepted: 10/12/2022] [Indexed: 11/28/2022] Open
Abstract
Metabolite identification in non-targeted NMR-based metabolomics remains a challenge. While many peaks of frequently occurring metabolites are assigned, there is a high number of unknowns in high-resolution NMR spectra, hampering biological conclusions for biomarker analysis. Here, we use a cluster analysis approach to guide peak assignment via statistical correlations, which gives important information on possible structural and/or biological correlations from the NMR spectrum. Unknown peaks that cluster in close proximity to known peaks form hypotheses for their metabolite identities, thus, facilitating metabolite annotation. Subsequently, metabolite identification based on a database search, 2D NMR analysis and standard spiking is performed, whereas without a hypothesis, a full structural elucidation approach would be required. The approach allows a higher identification yield in NMR spectra, especially once pathway-related subclusters are identified.
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Affiliation(s)
- Silke S. Heinzmann
- Research Unit Analytical BioGeoChemistry, Helmholtz Munich, 85764 Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
- Correspondence:
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, 85764 Neuherberg, Germany
- German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, 80336 Munich, Germany
| | - Annette Peters
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
- German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, 80336 Munich, Germany
- Institute of Epidemiology, Helmholtz Munich, 85764 Neuherberg, Germany
- Institute for Medical Information Processing Biometry and Epidemiology (IBE), Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Philippe Schmitt-Kopplin
- Research Unit Analytical BioGeoChemistry, Helmholtz Munich, 85764 Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
- Chair of Analytical Food Chemistry, Technical University of Munich, 85354 Freising, Germany
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Brachem C, Oluwagbemigun K, Langenau J, Weinhold L, Alexy U, Schmid M, Nöthlings U. Exploring the association between habitual food intake and the urine and blood metabolome in adolescents and young adults: a cohort study. Mol Nutr Food Res 2022; 66:e2200023. [PMID: 35785518 DOI: 10.1002/mnfr.202200023] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 05/08/2022] [Indexed: 11/07/2022]
Abstract
SCOPE Habitual diet may be reflected in metabolite profiles that can improve accurate assessment of dietary exposure and further enhance our understanding of their link to health conditions. We aimed to explore the relationship of habitual food intake with blood and urine metabolites in adolescents and young adults. METHODS The study population comprised 228 participants (94 male and 134 female) of the DONALD study. Dietary intake was assessed by yearly repeated 3d-food records. Habitual diet was estimated as the average consumption of 23 food groups in adolescence. Using an untargeted metabolomics approach, we quantified 2638 metabolites in plasma and 1407 metabolites in urine. In each sex, we determined unique diet-metabolite associations using orthogonal projection to latent structures (oPLS) and random forests (RF). RESULTS We observed 6 metabolites in agreement between oPLS and RF in urine, 1 in females (vanillylmandelate to processed/ other meat) and 5 in males (indole-3-acetamide, and N6-methyladenosine to eggs; hippurate, citraconate/glutaconate, and X - 12111 to vegetables). We observed no association in blood in agreement. CONCLUSION We observed a limited reflection of habitual food group intake by single metabolites in urine and not in blood. The explored biomarkers should be confirmed in additional studies. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Christian Brachem
- Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, 53115, Bonn, Germany
| | - Kolade Oluwagbemigun
- Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, 53115, Bonn, Germany
| | - Julia Langenau
- Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, 53115, Bonn, Germany
| | - Leonie Weinhold
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), University Hospital Bonn, 53127, Bonn, Germany
| | - Ute Alexy
- Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, DONALD Study, Heinstück 11, 44225, Dortmund, Germany
| | - Matthias Schmid
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), University Hospital Bonn, 53127, Bonn, Germany
| | - Ute Nöthlings
- Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, 53115, Bonn, Germany.,Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, DONALD Study, Heinstück 11, 44225, Dortmund, Germany
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Dawkins JJ, Allegretti JR, Gibson TE, McClure E, Delaney M, Bry L, Gerber GK. Gut metabolites predict Clostridioides difficile recurrence. MICROBIOME 2022; 10:87. [PMID: 35681218 PMCID: PMC9178838 DOI: 10.1186/s40168-022-01284-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 05/02/2022] [Indexed: 05/10/2023]
Abstract
BACKGROUND Clostridioides difficile infection (CDI) is the most common hospital acquired infection in the USA, with recurrence rates > 15%. Although primary CDI has been extensively linked to gut microbial dysbiosis, less is known about the factors that promote or mitigate recurrence. Moreover, previous studies have not shown that microbial abundances in the gut measured by 16S rRNA amplicon sequencing alone can accurately predict CDI recurrence. RESULTS We conducted a prospective, longitudinal study of 53 non-immunocompromised participants with primary CDI. Stool sample collection began pre-CDI antibiotic treatment at the time of diagnosis, and continued up to 8 weeks post-antibiotic treatment, with weekly or twice weekly collections. Samples were analyzed using (1) 16S rRNA amplicon sequencing, (2) liquid chromatography/mass-spectrometry metabolomics measuring 1387 annotated metabolites, and (3) short-chain fatty acid profiling. The amplicon sequencing data showed significantly delayed recovery of microbial diversity in recurrent participants, and depletion of key anaerobic taxa at multiple time-points, including Clostridium cluster XIVa and IV taxa. The metabolomic data also showed delayed recovery in recurrent participants, and moreover mapped to pathways suggesting distinct functional abnormalities in the microbiome or host, such as decreased microbial deconjugation activity, lowered levels of endocannabinoids, and elevated markers of host cell damage. Further, using predictive statistical/machine learning models, we demonstrated that the metabolomic data, but not the other data sources, can accurately predict future recurrence at 1 week (AUC 0.77 [0.71, 0.86; 95% interval]) and 2 weeks (AUC 0.77 [0.69, 0.85; 95% interval]) post-treatment for primary CDI. CONCLUSIONS The prospective, longitudinal, and multi-omic nature of our CDI recurrence study allowed us to uncover previously unrecognized dynamics in the microbiome and host presaging recurrence, and, in particular, to elucidate changes in the understudied gut metabolome. Moreover, we demonstrated that a small set of metabolites can accurately predict future recurrence. Our findings have implications for development of diagnostic tests and treatments that could ultimately short-circuit the cycle of CDI recurrence, by providing candidate metabolic biomarkers for diagnostics development, as well as offering insights into the complex microbial and metabolic alterations that are protective or permissive for recurrence. Video Abstract.
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Affiliation(s)
- Jennifer J. Dawkins
- Department of Pathology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
- Harvard-MIT Health Sciences & Technology, Harvard Medical School, MIT, Cambridge, MA USA
| | - Jessica R. Allegretti
- Massachusetts Host-Microbiome Center, Boston, MA USA
- Division of Gastroenterology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
| | - Travis E. Gibson
- Department of Pathology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
| | - Emma McClure
- Division of Gastroenterology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
| | - Mary Delaney
- Massachusetts Host-Microbiome Center, Boston, MA USA
| | - Lynn Bry
- Department of Pathology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
- Massachusetts Host-Microbiome Center, Boston, MA USA
| | - Georg K. Gerber
- Department of Pathology, Brigham & Woman’s Hospital, Harvard Medical School, Boston, MA USA
- Harvard-MIT Health Sciences & Technology, Harvard Medical School, MIT, Cambridge, MA USA
- Massachusetts Host-Microbiome Center, Boston, MA USA
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Loo RL, Chan Q, Nicholson JK, Holmes E. Balancing the Equation: A Natural History of Trimethylamine and Trimethylamine- N-oxide. J Proteome Res 2022; 21:560-589. [PMID: 35142516 DOI: 10.1021/acs.jproteome.1c00851] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Trimethylamine (TMA) and its N-oxide (TMAO) are ubiquitous in prokaryote and eukaryote organisms as well as in the environment, reflecting their fundamental importance in evolutionary biology, and their diverse biochemical functions. Both metabolites have multiple biological roles including cell-signaling. Much attention has focused on the significance of serum and urinary TMAO in cardiovascular disease risk, yet this is only one of the many facets of a deeper TMA-TMAO partnership that reflects the significance of these metabolites in multiple biological processes spanning animals, plants, bacteria, and fungi. We report on analytical methods for measuring TMA and TMAO and attempt to critically synthesize and map the global functions of TMA and TMAO in a systems biology framework.
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Affiliation(s)
- Ruey Leng Loo
- Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,The Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Queenie Chan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, United Kingdom.,MRC Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, United Kingdom
| | - Jeremy K Nicholson
- Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,The Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Institute of Global Health Innovation, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, United Kingdom
| | - Elaine Holmes
- Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,The Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Nutrition Research, Department of Metabolism, Nutrition and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, London SW7 2AZ, United Kingdom
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7
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Shibutami E, Takebayashi T. A Scoping Review of the Application of Metabolomics in Nutrition Research: The Literature Survey 2000-2019. Nutrients 2021; 13:3760. [PMID: 34836016 PMCID: PMC8623534 DOI: 10.3390/nu13113760] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 10/19/2021] [Accepted: 10/19/2021] [Indexed: 12/29/2022] Open
Abstract
Nutrimetabolomics is an emerging field in nutrition research, and it is expected to play a significant role in deciphering the interaction between diet and health. Through the development of omics technology over the last two decades, the definition of food and nutrition has changed from sources of energy and major/micro-nutrients to an essential exposure factor that determines health risks. Furthermore, this new approach has enabled nutrition research to identify dietary biomarkers and to deepen the understanding of metabolic dynamics and the impacts on health risks. However, so far, candidate markers identified by metabolomics have not been clinically applied and more efforts should be made to validate those. To help nutrition researchers better understand the potential of its application, this scoping review outlined the historical transition, recent focuses, and future prospects of the new realm, based on trends in the number of human research articles from the early stage of 2000 to the present of 2019 by searching the Medical Literature Analysis and Retrieval System Online (MEDLINE). Among them, objective dietary assessment, metabolic profiling, and health risk prediction were positioned as three of the principal applications. The continued growth will enable nutrimetabolomics research to contribute to personalized nutrition in the future.
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Affiliation(s)
- Eriko Shibutami
- Graduate School of Health Management, Keio University, Kanagawa 252-0883, Japan;
| | - Toru Takebayashi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo 160-8582, Japan
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8
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Sim XY, Ibrahim B, Gam LH. Urinary metabolites of type 2 diabetes rats fed with palm oil-enriched high fat diet. Heliyon 2021; 7:e08075. [PMID: 34632142 PMCID: PMC8487023 DOI: 10.1016/j.heliyon.2021.e08075] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/17/2021] [Accepted: 09/23/2021] [Indexed: 11/25/2022] Open
Abstract
High fat diet (HFD) is one of the risk factors of obesity and diabetes. Recommended diet regimen for diabetes is difficult to abide by especially for HFD as it adds flavour to the taste buds. In this study, palm oil-enriched HFD and normal diet were fed to nicotinamide-induced type 2 diabetes rats, respectively for six weeks. Additionally, metformin, a common drug used to treat diabetes was given to rats under treatment groups. We evaluated the change of urinary metabolites of diabetes rats fed with palm oil-enriched HFD, and also after metformin treatment. Rats were divided into six-groups with different feeding diets, disease condition and with or without metformin treatment. Rats' urine were collected at the end of six weeks feeding program and subjected to 1H-NMR and multivariate data analysis to evaluate their metabolite profiles. At the early phase of diabetes, metabolites changes in diabetic rats were associated with the disease itself. Our data showed that continuous consumption of HFD altered various metabolic pathways of diabetic rats and caused detrimental effects to the rats. On the other hand, metformin treatment combined with normal diet lessened the physiological impacts caused by diabetes condition.
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Affiliation(s)
- Xuan-Yi Sim
- USM-RIKEN International Centre of Aging Science, USM, 11800 Minden, Penang, Malaysia
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia
| | - Baharudin Ibrahim
- Faculty of Pharmacy, Universiti of Malaya, Kuala Lumpur, 50603, Malaysia
| | - Lay-Harn Gam
- USM-RIKEN International Centre of Aging Science, USM, 11800 Minden, Penang, Malaysia
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia
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9
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Penney N, Barton W, Posma JM, Darzi A, Frost G, Cotter PD, Holmes E, Shanahan F, O'Sullivan O, Garcia-Perez I. Investigating the Role of Diet and Exercise in Gut Microbe-Host Cometabolism. mSystems 2020; 5:e00677-20. [PMID: 33262239 PMCID: PMC7716389 DOI: 10.1128/msystems.00677-20] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Accepted: 11/04/2020] [Indexed: 12/22/2022] Open
Abstract
We investigated the individual and combined effects of diet and physical exercise on metabolism and the gut microbiome to establish how these lifestyle factors influence host-microbiome cometabolism. Urinary and fecal samples were collected from athletes and less active controls. Individuals were further classified according to an objective dietary assessment score of adherence to healthy dietary habits according to WHO guidelines, calculated from their proton nuclear magnetic resonance (1H-NMR) urinary profiles. Subsequent models were generated comparing extremes of dietary habits, exercise, and the combined effect of both. Differences in metabolic phenotypes and gut microbiome profiles between the two groups were assessed. Each of the models pertaining to diet healthiness, physical exercise, or a combination of both displayed a metabolic and functional microbial signature, with a significant proportion of the metabolites identified as discriminating between the various pairwise comparisons resulting from gut microbe-host cometabolism. Microbial diversity was associated with a combination of high adherence to healthy dietary habits and exercise and was correlated with a distinct array of microbially derived metabolites, including markers of proteolytic activity. Improved control of dietary confounders, through the use of an objective dietary assessment score, has uncovered further insights into the complex, multifactorial relationship between diet, exercise, the gut microbiome, and metabolism. Furthermore, the observation of higher proteolytic activity associated with higher microbial diversity indicates that increased microbial diversity may confer deleterious as well as beneficial effects on the host.IMPORTANCE Improved control of dietary confounders, through the use of an objective dietary assessment score, has uncovered further insights into the complex, multifactorial relationship between diet, exercise, the gut microbiome, and metabolism. Each of the models pertaining to diet healthiness, physical exercise, or a combination of both, displayed a distinct metabolic and functional microbial signature. A significant proportion of the metabolites identified as discriminating between the various pairwise comparisons result from gut microbe-host cometabolism, and the identified interactions have expanded current knowledge in this area. Furthermore, although increased microbial diversity has previously been linked with health, our observation of higher microbial diversity being associated with increased proteolytic activity indicates that it may confer deleterious as well as beneficial effects on the host.
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Affiliation(s)
- N Penney
- Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - W Barton
- APC Microbiome Ireland, University College Cork, National University of Ireland, Cork, Ireland
- Teagasc Food Research Centre, Moorepark, Co. Cork, Ireland
- Department of Medicine, University College Cork, National University of Ireland, Cork, Ireland
| | - J M Posma
- Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
- Health Data Research UK, London, United Kingdom
| | - A Darzi
- Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - G Frost
- Section for Nutrition Research, Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - P D Cotter
- APC Microbiome Ireland, University College Cork, National University of Ireland, Cork, Ireland
- Teagasc Food Research Centre, Moorepark, Co. Cork, Ireland
| | - E Holmes
- Section for Nutrition Research, Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - F Shanahan
- APC Microbiome Ireland, University College Cork, National University of Ireland, Cork, Ireland
- Department of Medicine, University College Cork, National University of Ireland, Cork, Ireland
| | - O O'Sullivan
- APC Microbiome Ireland, University College Cork, National University of Ireland, Cork, Ireland
- Teagasc Food Research Centre, Moorepark, Co. Cork, Ireland
| | - I Garcia-Perez
- Section for Nutrition Research, Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
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10
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Beckmann M, Wilson T, Lloyd AJ, Torres D, Goios A, Willis ND, Lyons L, Phillips H, Mathers JC, Draper J. Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations-A Perspective. Front Nutr 2020; 7:602515. [PMID: 33344495 PMCID: PMC7745244 DOI: 10.3389/fnut.2020.602515] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 10/29/2020] [Indexed: 12/27/2022] Open
Abstract
Improvement of diet at the population level is a cornerstone of national and international strategies for reducing chronic disease burden. A critical challenge in generating robust data on habitual dietary intake is accurate exposure assessment. Self-reporting instruments (e.g., food frequency questionnaires, dietary recall) are subject to reporting bias and serving size perceptions, while weighed dietary assessments are unfeasible in large-scale studies. However, secondary metabolites derived from individual foods/food groups and present in urine provide an opportunity to develop potential biomarkers of food intake (BFIs). Habitual dietary intake assessment in population surveys using biomarkers presents several challenges, including the need to develop affordable biofluid collection methods, acceptable to participants that allow collection of informative samples. Monitoring diet comprehensively using biomarkers requires analytical methods to quantify the structurally diverse mixture of target biomarkers, at a range of concentrations within urine. The present article provides a perspective on the challenges associated with the development of urine biomarker technology for monitoring diet exposure in free-living individuals with a view to its future deployment in "real world" situations. An observational study (n = 95), as part of a national survey on eating habits, provided an opportunity to explore biomarker measurement in a free-living population. In a second food intervention study (n = 15), individuals consumed a wide range of foods as a series of menus designed specifically to achieve exposure reflecting a diversity of foods commonly consumed in the UK, emulating normal eating patterns. First Morning Void urines were shown to be suitable samples for biomarker measurement. Triple quadrupole mass spectrometry, coupled with liquid chromatography, was used to assess simultaneously the behavior of a panel of 54 potential BFIs. This panel of chemically diverse biomarkers, reporting intake of a wide range of commonly-consumed foods, can be extended successfully as new biomarker leads are discovered. Towards validation, we demonstrate excellent discrimination of eating patterns and quantitative relationships between biomarker concentrations in urine and the intake of several foods. In conclusion, we believe that the integration of information from BFI technology and dietary self-reporting tools will expedite research on the complex interactions between dietary choices and health.
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Affiliation(s)
- Manfred Beckmann
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Thomas Wilson
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Amanda J. Lloyd
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Duarte Torres
- Faculty of Nutrition and Food Sciences, University of Porto, Porto, Portugal
- Epidemiology Research Unit (EPIUnit), Institute of Public Health, University of Porto, Porto, Portugal
| | - Ana Goios
- Faculty of Nutrition and Food Sciences, University of Porto, Porto, Portugal
- Epidemiology Research Unit (EPIUnit), Institute of Public Health, University of Porto, Porto, Portugal
| | - Naomi D. Willis
- Human Nutrition Research Centre, Population Health Sciences Institute, William Leech Building, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - Laura Lyons
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - Helen Phillips
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
| | - John C. Mathers
- Human Nutrition Research Centre, Population Health Sciences Institute, William Leech Building, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - John Draper
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom
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11
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Saenger T, Hübner F, Lindemann V, Ganswind K, Humpf HU. Urinary Biomarkers for Orange Juice Consumption. Mol Nutr Food Res 2020; 65:e2000781. [PMID: 33216459 DOI: 10.1002/mnfr.202000781] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 11/12/2020] [Indexed: 10/23/2022]
Abstract
SCOPE As orange juice belongs to one of the most consumed juices worldwide, a human study is performed to identify urinary biomarkers for the consumption of orange juice in order to differentiate between low, medium, and high intake. METHODS AND RESULTS The 32 study participants abstained from citrus fruits, juices and products thereof, except for one portion of orange juice, for eight days. Throughout the study, spot urine samples are collected and quantitatively analyzed by high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) regarding their content of several potential biomarkers for orange juice intake after enzymatic treatment with β-glucuronidase. Proline betaine is determined as a long-term biomarker: based on its urinary excretion, orange juice consumption is traceable for at least 72 h after intake. Naringenin and hesperetin are identified as qualitative short-term biomarkers. Synephrine sulfate also showed a fast increase and decrease in a semi-quantitative approach. In the case of phloretin, no correlation between orange juice consumption and the urinary concentration is observed. CONCLUSION Proline betaine is the most promising biomarker for orange juice consumption and allows to differentiate between low, medium, and high intake. Hesperetin and naringenin (as well as synephrine) are applicable as supporting biomarkers, whereas phloretin does not represent a reliable biomarker for orange juice consumption.
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Affiliation(s)
- Theresa Saenger
- Institute of Food Chemistry, Westfälische Wilhelms-Universität Münster, Corrensstrasse 45, Münster, 48149, Germany
| | - Florian Hübner
- Institute of Food Chemistry, Westfälische Wilhelms-Universität Münster, Corrensstrasse 45, Münster, 48149, Germany
| | - Viktoria Lindemann
- Institute of Food Chemistry, Westfälische Wilhelms-Universität Münster, Corrensstrasse 45, Münster, 48149, Germany
| | - Kristina Ganswind
- Institute of Food Chemistry, Westfälische Wilhelms-Universität Münster, Corrensstrasse 45, Münster, 48149, Germany
| | - Hans-Ulrich Humpf
- Institute of Food Chemistry, Westfälische Wilhelms-Universität Münster, Corrensstrasse 45, Münster, 48149, Germany
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12
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Mahmoodpoor A, Shamekh A, Sanaie S. Foodomics and COVID-19. Clin Nutr ESPEN 2020; 38:283. [PMID: 32690172 PMCID: PMC7260526 DOI: 10.1016/j.clnesp.2020.05.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 05/08/2020] [Accepted: 05/17/2020] [Indexed: 11/30/2022]
Affiliation(s)
- Ata Mahmoodpoor
- Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Ali Shamekh
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Sarvin Sanaie
- Neurosciences Research Center, Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran.
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13
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Clarke ED, Rollo ME, Pezdirc K, Collins CE, Haslam RL. Urinary biomarkers of dietary intake: a review. Nutr Rev 2020; 78:364-381. [PMID: 31670796 DOI: 10.1093/nutrit/nuz048] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Dietary intakes are commonly assessed by established methods including food frequency questionnaires, food records, or recalls. These self-report methods have limitations impacting validity and reliability. Dietary biomarkers provide objective verification of self-reported food intakes, and represent a rapidly evolving area. This review aims to summarize the urinary biomarkers of individual foods, food groups, dietary patterns, or nutritional supplements that have been evaluated to date. Six electronic databases were searched. Included studies involved healthy populations, were published from 2000, and compared measured dietary intake with urinary markers. The initial search identified 9985 studies; of these, 616 full texts were retrieved and 109 full texts were included. Of the included studies, 67 foods and food components were studied, and 347 unique urinary biomarkers were identified. The most reliable biomarkers identified were whole grains (alkylresorcinols), soy (isoflavones), and sugar (sucrose and fructose). While numerous novel urinary biomarkers have been identified, further validation studies are warranted to verify the accuracy of self-reported intakes and utility within practice.
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Affiliation(s)
- Erin D Clarke
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW, Australia.,Priority Research Centre in Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia
| | - Megan E Rollo
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW, Australia.,Priority Research Centre in Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia
| | - Kristine Pezdirc
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia
| | - Clare E Collins
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW, Australia.,Priority Research Centre in Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia
| | - Rebecca L Haslam
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW, Australia.,Priority Research Centre in Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia
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14
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Hussien AK, Moez PE, Elwakil HS, Elagaan HA. Identification of urinary proteomic profile of patients with chronic allograft nephropathy. ALEXANDRIA JOURNAL OF MEDICINE 2020. [DOI: 10.1080/20905068.2020.1749782] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Affiliation(s)
- Amr K. Hussien
- Internal Medicine, Faculty of Medicine, University of KafrElsheikh, KafrElsheikh, Egypt
| | - Pacint E. Moez
- Clinical and Chemical Pathology, Faculty of Medicine, University of Alexandria, Alexandria, Egypt
| | - Hala S. Elwakil
- Internal Medicine, Faculty of Medicine, University of Alexandria, Alexandria, Egypt
| | - Hayam A. Elagaan
- Internal Medicine, Faculty of Medicine, University of Alexandria, Alexandria, Egypt
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15
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Posma JM, Garcia-Perez I, Frost G, Aljuraiban GS, Chan Q, Van Horn L, Daviglus M, Stamler J, Holmes E, Elliott P, Nicholson JK. Nutriome-metabolome relationships provide insights into dietary intake and metabolism. ACTA ACUST UNITED AC 2020; 1:426-436. [PMID: 32954362 PMCID: PMC7497842 DOI: 10.1038/s43016-020-0093-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Dietary assessment traditionally relies on self-reported data which are often inaccurate and may result in erroneous diet-disease risk associations. We illustrate how urinary metabolic phenotyping can be used as alternative approach for obtaining information on dietary patterns. We used two multi-pass 24-hr dietary recalls, obtained on two occasions on average three weeks apart, paired with two 24-hr urine collections from 1,848 U.S. individuals; 67 nutrients influenced the urinary metabotype measured with 1H-NMR spectroscopy characterized by 46 structurally identified metabolites. We investigated the stability of each metabolite over time and showed that the urinary metabolic profile is more stable within individuals than reported dietary patterns. The 46 metabolites accurately predicted healthy and unhealthy dietary patterns in a free-living U.S. cohort and replicated in an independent U.K. cohort. We mapped these metabolites into a host-microbial metabolic network to identify key pathways and functions. These data can be used in future studies to evaluate how this set of diet-derived, stable, measurable bioanalytical markers are associated with disease risk. This knowledge may give new insights into biological pathways that characterize the shift from a healthy to unhealthy metabolic phenotype and hence give entry points for prevention and intervention strategies.
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Affiliation(s)
- Joram M Posma
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, South Kensington Campus, Imperial College London, SW7 2AZ, U.K.,Health Data Research UK-London, U.K
| | - Isabel Garcia-Perez
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Hammersmith Campus, Imperial College London, W12 0NN, U.K
| | - Gary Frost
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Hammersmith Campus, Imperial College London, W12 0NN, U.K
| | - Ghadeer S Aljuraiban
- The Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia.,Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, St. Mary's Campus, Imperial College London, W2 1PG, U.K
| | - Queenie Chan
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, St. Mary's Campus, Imperial College London, W2 1PG, U.K.,MRC Centre for Environment and Health, School of Public Health, Faculty of Medicine, St. Mary's Campus, Imperial College London, W2 1PG, U.K
| | - Linda Van Horn
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, U.S.A
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL 60612
| | - Jeremiah Stamler
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, U.S.A
| | - Elaine Holmes
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Hammersmith Campus, Imperial College London, W12 0NN, U.K.,UK Dementia Research Institute, Faculty of Medicine, Hammersmith Campus, Imperial College London, W12 0NN, U.K.,Division of Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia.,The Australian National Phenome Center, Harry Perkins Institute, Murdoch University, WA 6150, Australia
| | - Paul Elliott
- Health Data Research UK-London, U.K.,Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, St. Mary's Campus, Imperial College London, W2 1PG, U.K.,MRC Centre for Environment and Health, School of Public Health, Faculty of Medicine, St. Mary's Campus, Imperial College London, W2 1PG, U.K.,UK Dementia Research Institute, Faculty of Medicine, Hammersmith Campus, Imperial College London, W12 0NN, U.K.,National Institute for Health Research Imperial Biomedical Research Centre, St. Mary's Campus, Imperial College London, W2 1PG, U.K.,British Heart Foundation Centre of Research Excellence at Imperial, Imperial College London, W2 1PG, U.K
| | - Jeremy K Nicholson
- Division of Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia.,The Australian National Phenome Center, Harry Perkins Institute, Murdoch University, WA 6150, Australia
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16
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Garcia-Perez I, Posma JM, Chambers ES, Mathers JC, Draper J, Beckmann M, Nicholson JK, Holmes E, Frost G. RETRACTED ARTICLE: Dietary metabotype modelling predicts individual responses to dietary interventions. NATURE FOOD 2020; 1:355-364. [PMID: 37128097 DOI: 10.1038/s43016-020-0092-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 05/06/2020] [Indexed: 12/12/2022]
Abstract
Habitual consumption of poor quality diets is linked directly to risk factors for many non-communicable diseases. This has resulted in the vast majority of countries and the World Health Organization developing policies for healthy eating to reduce the prevalence of non-communicable diseases in the population. However, there is mounting evidence of variability in individual metabolic responses to any dietary intervention. We have developed a method for applying a pipeline for understanding interindividual differences in response to diet, based on coupling data from highly controlled dietary studies with deep metabolic phenotyping. In this feasibility study, we create an individual Dietary Metabotype Score (DMS) that embodies interindividual variability in dietary response and captures consequent dynamic changes in concentrations of urinary metabolites. We find an inverse relationship between the DMS and blood glucose concentration. There is also a relationship between the DMS and urinary metabolic energy loss. Furthermore, we use a metabolic entropy approach to visualize individual and collective responses to dietary interventions. Potentially, the DMS offers a method to target and to enhance dietary response at the individual level, thereby reducing the burden of non-communicable diseases at the population level.
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Affiliation(s)
- Isabel Garcia-Perez
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Joram M Posma
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
- Health Data Research UK-London, London, UK
| | - Edward S Chambers
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - John C Mathers
- Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Newcastle, UK
| | - John Draper
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
| | - Manfred Beckmann
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
| | - Jeremy K Nicholson
- The Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.
| | - Elaine Holmes
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
- The Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.
| | - Gary Frost
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
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17
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Pan S, Hullar MAJ, Lai LA, Peng H, May DH, Noble WS, Raftery D, Navarro SL, Neuhouser ML, Lampe PD, Lampe JW, Chen R. Gut Microbial Protein Expression in Response to Dietary Patterns in a Controlled Feeding Study: A Metaproteomic Approach. Microorganisms 2020; 8:E379. [PMID: 32156071 PMCID: PMC7143255 DOI: 10.3390/microorganisms8030379] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 03/02/2020] [Accepted: 03/04/2020] [Indexed: 12/11/2022] Open
Abstract
Although the gut microbiome has been associated with dietary patterns linked to health, microbial metabolism is not well characterized. This ancillary study was a proof of principle analysis for a novel application of metaproteomics to study microbial protein expression in a controlled dietary intervention. We measured the response of the microbiome to diet in a randomized crossover dietary intervention of a whole-grain, low glycemic load diet (WG) and a refined-grain, high glycemic load diet (RG). Total proteins in stools from 9 participants at the end of each diet period (n = 18) were analyzed by LC MS/MS and proteins were identified using the Human Microbiome Project (HMP) human gut microbiome database and UniProt human protein databases. T-tests, controlling for false discovery rate (FDR) <10%, were used to compare the Gene Ontology (GO) biological processes and bacterial enzymes between the two interventions. Using shotgun proteomics, more than 53,000 unique peptides were identified including microbial (89%) and human peptides (11%). Forty-eight bacterial enzymes were statistically different between the diets, including those implicated in SCFA production and degradation of fatty acids. Enzymes associated with degradation of human mucin were significantly enriched in the RG diet. These results illustrate that the metaproteomic approach is a valuable tool to study the microbial metabolism of diets that may influence host health.
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Affiliation(s)
- Sheng Pan
- Institute of Molecular Medicine, the University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (S.P.); (H.P.)
| | - Meredith A. J. Hullar
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA 98109, USA; (D.R.); (S.L.N.); (M.L.N.); (P.D.L.); (J.W.L.)
| | - Lisa A. Lai
- Department of Medicine, University of Washington, Seattle, WA 98105, USA;
| | - Hong Peng
- Institute of Molecular Medicine, the University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (S.P.); (H.P.)
| | - Damon H. May
- Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA; (D.H.M.)
| | - William S. Noble
- Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA; (D.H.M.)
| | - Daniel Raftery
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA 98109, USA; (D.R.); (S.L.N.); (M.L.N.); (P.D.L.); (J.W.L.)
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA 98109 USA
| | - Sandi L. Navarro
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA 98109, USA; (D.R.); (S.L.N.); (M.L.N.); (P.D.L.); (J.W.L.)
| | - Marian L. Neuhouser
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA 98109, USA; (D.R.); (S.L.N.); (M.L.N.); (P.D.L.); (J.W.L.)
| | - Paul D. Lampe
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA 98109, USA; (D.R.); (S.L.N.); (M.L.N.); (P.D.L.); (J.W.L.)
| | - Johanna W. Lampe
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA 98109, USA; (D.R.); (S.L.N.); (M.L.N.); (P.D.L.); (J.W.L.)
| | - Ru Chen
- Division of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
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18
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Abstract
Diet is an important risk factor for colorectal cancer (CRC), and several dietary constituents implicated in CRC are modified by gut microbial metabolism. Microbial fermentation of dietary fiber produces short-chain fatty acids, e.g., acetate, propionate, and butyrate. Dietary fiber has been shown to reduce colon tumors in animal models, and, in vitro, butyrate influences cellular pathways important to cancer risk. Furthermore, work from our group suggests that the combined effects of butyrate and omega-3 polyunsaturated fatty acids (n-3 PUFA) may enhance the chemopreventive potential of these dietary constituents. We postulate that the relatively low intakes of n-3 PUFA and fiber in Western populations and the failure to address interactions between these dietary components may explain why chemoprotective effects of n-3 PUFA and fermentable fibers have not been detected consistently in prospective cohort studies. In this review, we summarize the evidence outlining the effects of n-3 long-chain PUFA and highly fermentable fiber with respect to alterations in critical pathways important to CRC prevention, particularly intrinsic mitochondrial-mediated programmed cell death resulting from the accumulation of lipid reactive oxygen species (ferroptosis), and epigenetic programming related to lipid catabolism and beta-oxidation-associated genes.
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19
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Cuparencu C, Praticó G, Hemeryck LY, Sri Harsha PSC, Noerman S, Rombouts C, Xi M, Vanhaecke L, Hanhineva K, Brennan L, Dragsted LO. Biomarkers of meat and seafood intake: an extensive literature review. GENES & NUTRITION 2019; 14:35. [PMID: 31908682 PMCID: PMC6937850 DOI: 10.1186/s12263-019-0656-4] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 11/12/2019] [Indexed: 01/16/2023]
Abstract
Meat, including fish and shellfish, represents a valuable constituent of most balanced diets. Consumption of different types of meat and fish has been associated with both beneficial and adverse health effects. While white meats and fish are generally associated with positive health outcomes, red and especially processed meats have been associated with colorectal cancer and other diseases. The contribution of these foods to the development or prevention of chronic diseases is still not fully elucidated. One of the main problems is the difficulty in properly evaluating meat intake, as the existing self-reporting tools for dietary assessment may be imprecise and therefore affected by systematic and random errors. Dietary biomarkers measured in biological fluids have been proposed as possible objective measurements of the actual intake of specific foods and as a support for classical assessment methods. Good biomarkers for meat intake should reflect total dietary intake of meat, independent of source or processing and should be able to differentiate meat consumption from that of other protein-rich foods; alternatively, meat intake biomarkers should be specific to each of the different meat sources (e.g., red vs. white; fish, bird, or mammal) and/or cooking methods. In this paper, we present a systematic investigation of the scientific literature while providing a comprehensive overview of the possible biomarker(s) for the intake of different types of meat, including fish and shellfish, and processed and heated meats according to published guidelines for biomarker reviews (BFIrev). The most promising biomarkers are further validated for their usefulness for dietary assessment by published validation criteria.
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Affiliation(s)
- Cătălina Cuparencu
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Rolighedsvej 30, 1958 Frederiksberg C, Denmark
| | - Giulia Praticó
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Rolighedsvej 30, 1958 Frederiksberg C, Denmark
| | - Lieselot Y. Hemeryck
- Department of Veterinary Public Health & Food Safety, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium
| | - Pedapati S. C. Sri Harsha
- School of Agriculture and Food Science, Institute of Food & Health, University College Dublin, Belfield 4, Dublin, Ireland
| | - Stefania Noerman
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Yliopistonranta 1, 70210 Kuopio, Finland
| | - Caroline Rombouts
- Department of Veterinary Public Health & Food Safety, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium
| | - Muyao Xi
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Rolighedsvej 30, 1958 Frederiksberg C, Denmark
| | - Lynn Vanhaecke
- Department of Veterinary Public Health & Food Safety, Ghent University, Salisburylaan 133, 9820 Merelbeke, Belgium
| | - Kati Hanhineva
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Yliopistonranta 1, 70210 Kuopio, Finland
| | - Lorraine Brennan
- School of Agriculture and Food Science, Institute of Food & Health, University College Dublin, Belfield 4, Dublin, Ireland
| | - Lars O. Dragsted
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Rolighedsvej 30, 1958 Frederiksberg C, Denmark
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20
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Hughes RL, Kable ME, Marco M, Keim NL. The Role of the Gut Microbiome in Predicting Response to Diet and the Development of Precision Nutrition Models. Part II: Results. Adv Nutr 2019; 10:979-998. [PMID: 31225587 PMCID: PMC6855959 DOI: 10.1093/advances/nmz049] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Revised: 03/28/2019] [Accepted: 04/12/2019] [Indexed: 12/17/2022] Open
Abstract
The gut microbiota is increasingly implicated in the health and metabolism of its human host. The host's diet is a major component influencing the composition and function of the gut microbiota, and mounting evidence suggests that the composition and function of the gut microbiota influence the host's metabolic response to diet. This effect of the gut microbiota on personalized dietary response is a growing focus of precision nutrition research and may inform the effort to tailor dietary advice to the individual. Because the gut microbiota has been shown to be malleable to some extent, it may also allow for therapeutic alterations of the gut microbiota in order to alter response to certain dietary components. This article is the second in a 2-part review of the current research in the field of precision nutrition incorporating the gut microbiota into studies investigating interindividual variability in response to diet. Part I reviews the methods used by researchers to design and carry out such studies as well as analyze the results subsequently obtained. Part II reviews the findings of these studies and discusses the gaps in our current knowledge and directions for future research. The studies reviewed provide the current understanding in this field of research and a foundation from which we may build, utilizing and expanding upon the methods and results they present to inform future studies.
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Affiliation(s)
- Riley L Hughes
- Departments of Nutrition, Food Science & Technology, University of California, Davis, CA
| | - Mary E Kable
- Departments of Nutrition, Food Science & Technology, University of California, Davis, CA,Departments of Immunity and Disease Prevention, Obesity and Metabolism, Western Human Nutrition Research Center, Agricultural Research Service, USDA, Davis, CA
| | - Maria Marco
- Food Science & Technology, University of California, Davis, CA
| | - Nancy L Keim
- Departments of Nutrition, Food Science & Technology, University of California, Davis, CA,Obesity and Metabolism, Western Human Nutrition Research Center, Agricultural Research Service, USDA, Davis, CA,Address correspondence to NLK (e-mail: )
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21
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Langenau J, Boeing H, Bergmann MM, Nöthlings U, Oluwagbemigun K. The Association between Alcohol Consumption and Serum Metabolites and the Modifying Effect of Smoking. Nutrients 2019; 11:nu11102331. [PMID: 31581552 PMCID: PMC6836136 DOI: 10.3390/nu11102331] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 09/26/2019] [Accepted: 09/27/2019] [Indexed: 12/24/2022] Open
Abstract
Alcohol consumption is an important lifestyle factor that is associated with several health conditions and a behavioral link with smoking is well established. Metabolic alterations after alcohol consumption have yet to be comprehensively investigated. We studied the association of alcohol consumption with metabolite patterns (MPs) among 2433 individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study, and a potential modification by smoking. Alcohol consumption was self-reported through dietary questionnaires and serum metabolites were measured by a targeted approach. The metabolites were summarized as MPs using the treelet transform analysis (TT). We fitted linear models with alcohol consumption continuously and in five categories. We stratified the continuously modelled alcohol consumption by smoking status. All models were adjusted for potential confounders. Among men, alcohol consumption was positively associated with six MPs and negatively associated with one MP. In women, alcohol consumption was inversely associated with one MP. Heavy consumers differed from other consumers with respect to the "Long and short chain acylcarnitines" MP. Our findings suggest that long and short chain acylcarnitines might play an important role in the adverse effects of heavy alcohol consumption on chronic diseases. The relations seem to depend on gender and smoking status.
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Affiliation(s)
- Julia Langenau
- Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, 53115 Bonn, Germany.
| | - Heiner Boeing
- German Institute of Human Nutrition Potsdam-Rehbrücke, Division of Epidemiology, 14558 Nuthetal, Germany.
| | - Manuela M Bergmann
- German Institute of Human Nutrition Potsdam-Rehbrücke, Division of Epidemiology, 14558 Nuthetal, Germany.
| | - Ute Nöthlings
- Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, 53115 Bonn, Germany.
| | - Kolade Oluwagbemigun
- Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, 53115 Bonn, Germany.
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22
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Affiliation(s)
- H. M. Roager
- Department of Nutrition, Exercise and Sports University of Copenhagen Frederiksberg Denmark
| | - L. O. Dragsted
- Department of Nutrition, Exercise and Sports University of Copenhagen Frederiksberg Denmark
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23
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Cuparencu C, Rinnan Å, Dragsted LO. Combined Markers to Assess Meat Intake-Human Metabolomic Studies of Discovery and Validation. Mol Nutr Food Res 2019; 63:e1900106. [PMID: 31141834 DOI: 10.1002/mnfr.201900106] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 04/05/2019] [Indexed: 01/01/2023]
Abstract
SCOPE Biomarkers of red meat may clarify the relationship between meat intake and health. This paper explores the discovery of biomarkers of intake for three types of meat with varying heme iron content. Candidate biomarkers for red and general meat are further evaluated based on defined validation criteria. METHODS AND RESULTS In a randomized cross-over meal study, healthy volunteers consume a randomized sequence of four test meals: chicken, pork, beef, and a control made of egg white and pea. Fasting and postprandial urine samples are collected to cover 48 h and profiled by untargeted LC-ESI-qTOF-MS metabolomics. The profiles following the meal challenges are explored by univariate and multivariate analyses. Nine red, four white, and eight general meat biomarkers are selected as putative biomarkers, originating from collagen degradation, flavour compounds, and amino acid metabolism. Heme-related metabolites are masked by the chlorophyll content of the control meal. The candidate biomarkers are confirmed in an independent meal study and validated for plausibility, robustness, time-response, and prediction performance. Combinations of biomarkers are more efficient than single markers in predicting meat intake. CONCLUSION New combinations of partially validated biomarkers are proposed to assess terrestrial meat intake and thus help disentangle the effects of meat consumption on human health.
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Affiliation(s)
- Cătălina Cuparencu
- Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, 1958, Frederiksberg, Denmark
| | - Åsmund Rinnan
- Department of Food Science, Faculty of Science, University of Copenhagen, 1958, Frederiksberg, Denmark
| | - Lars O Dragsted
- Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, 1958, Frederiksberg, Denmark
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24
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Urpi-Sarda M, Almanza-Aguilera E, Llorach R, Vázquez-Fresno R, Estruch R, Corella D, Sorli JV, Carmona F, Sanchez-Pla A, Salas-Salvadó J, Andres-Lacueva C. Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants. DIABETES & METABOLISM 2019; 45:167-174. [PMID: 29555466 DOI: 10.1016/j.diabet.2018.02.006] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 01/24/2018] [Accepted: 02/13/2018] [Indexed: 01/20/2023]
Abstract
AIM To characterize the urinary metabolomic fingerprint and multi-metabolite signature associated with type 2 diabetes (T2D), and to classify the population into metabotypes related to T2D. METHODS A metabolomics analysis using the 1H-NMR-based, non-targeted metabolomic approach was conducted to determine the urinary metabolomic fingerprint of T2D compared with non-T2D participants in the PREDIMED trial. The discriminant metabolite fingerprint was subjected to logistic regression analysis and ROC analyses to establish and to assess the multi-metabolite signature of T2D prevalence, respectively. Metabotypes associated with T2D were identified using the k-means algorithm. RESULTS A total of 33 metabolites were significantly different (P<0.05) between T2D and non-T2D participants. The multi-metabolite signature of T2D comprised high levels of methylsuccinate, alanine, dimethylglycine and guanidoacetate, and reduced levels of glutamine, methylguanidine, 3-hydroxymandelate and hippurate, and had a 96.4% AUC, which was higher than the metabolites on their own and glucose. Amino-acid and carbohydrate metabolism were the main metabolic alterations in T2D, and various metabotypes were identified in the studied population. Among T2D participants, those with a metabotype of higher levels of phenylalanine, phenylacetylglutamine, p-cresol and acetoacetate had significantly higher levels of plasma glucose. CONCLUSION The multi-metabolite signature of T2D highlights the altered metabolic fingerprint associated mainly with amino-acid, carbohydrate and microbiota metabolism. Metabotypes identified in this patient population could be related to higher risk of long-term cardiovascular events and therefore require further studies. Metabolomics is a useful tool for elucidating the metabolic complexity and interindividual variation in T2D towards the development of stratified precision nutrition and medicine. Trial registration at www.controlled-trials.com: ISRCTN35739639.
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Affiliation(s)
- M Urpi-Sarda
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain.
| | - E Almanza-Aguilera
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - R Llorach
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - R Vázquez-Fresno
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; Department of Computing Science and Biological Sciences, University of Alberta, Edmonton, Canada
| | - R Estruch
- Department of Internal Medicine, Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Barcelona, Spain; CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
| | - D Corella
- CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain
| | - J V Sorli
- CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain
| | - F Carmona
- Statistics Department, Biology Faculty, University of Barcelona, Barcelona, Spain
| | - A Sanchez-Pla
- Statistics Department, Biology Faculty, University of Barcelona, Barcelona, Spain
| | - J Salas-Salvadó
- CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain; Human Nutrition Unit, Biochemistry and Biotechnology Department. Hospital Universitari de Sant Joan de Reus, Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, Reus, Spain
| | - C Andres-Lacueva
- Biomarkers and Nutrimetabolomic Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain; CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain.
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Abstract
Acute kidney injury (AKI) is a severe and frequent condition in hospitalized patients. Currently, no efficient therapy of AKI is available. Therefore, efforts focus on early prevention and potentially early initiation of renal replacement therapy to improve the outcome in AKI. The detection of AKI in hospitalized patients implies the need for early, accurate, robust, and easily accessible biomarkers of AKI evolution and outcome prediction because only a narrow window exists to implement the earlier-described measures. Even more challenging is the multifactorial origin of AKI and the fact that the changes of molecular expression induced by AKI are difficult to distinguish from those of the diseases associated or causing AKI as shock or sepsis. During the past decade, a considerable number of protein biomarkers for AKI have been described and we expect from recent advances in the field of omics technologies that this number will increase further in the future and be extended to other sorts of biomolecules, such as RNAs, lipids, and metabolites. However, most of these biomarkers are poorly defined by their AKI-associated molecular context. In this review, we describe the state-of-the-art tissue and biofluid proteomic and metabolomic technologies and new bioinformatics approaches for proteomic and metabolomic pathway and molecular interaction analysis. In the second part of the review, we focus on AKI-associated proteomic and metabolomic biomarkers and briefly outline their pathophysiological context in AKI.
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26
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Davies R. The metabolomic quest for a biomarker in chronic kidney disease. Clin Kidney J 2018; 11:694-703. [PMID: 30288265 PMCID: PMC6165760 DOI: 10.1093/ckj/sfy037] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 04/16/2018] [Indexed: 12/15/2022] Open
Abstract
Chronic kidney disease (CKD) is a growing burden on people and on healthcare for which the diagnostics are niether disease-specific nor indicative of progression. Biomarkers are sought to enable clinicians to offer more appropriate patient-centred treatments, which could come to fruition by using a metabolomics approach. This mini-review highlights the current literature of metabolomics and CKD, and suggests additional factors that need to be considered in this quest for a biomarker, namely the diet and the gut microbiome, for more meaningful advances to be made.
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Affiliation(s)
- Robert Davies
- School of Biomedical and Healthcare Sciences, University of Plymouth School of Biological Sciences, Plymouth, UK
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27
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Michielsen CCJR, Almanza-Aguilera E, Brouwer-Brolsma EM, Urpi-Sarda M, Afman LA. Biomarkers of food intake for cocoa and liquorice (products): a systematic review. GENES AND NUTRITION 2018; 13:22. [PMID: 30065791 PMCID: PMC6062926 DOI: 10.1186/s12263-018-0610-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 07/05/2018] [Indexed: 12/20/2022]
Abstract
Background To unravel true links between diet and health, it is important that dietary exposure is accurately measured. Currently, mainly self-reporting methods (e.g. food frequency questionnaires and 24-h recalls) are used to assess food intake in epidemiological studies. However, these traditional instruments are subjective measures and contain well-known biases. Especially, estimating the intake of the group of confectionary products, such as products containing cocoa and liquorice, remains a challenge. The use biomarkers of food intake (BFIs) may provide a more objective measurement. However, an overview of current candidate biomarkers and their validity is missing for both cocoa- and liquorice-containing foods. Objective The purpose of the current study was to (1) identify currently described candidate BFIs for cocoa (products) and liquorice, (2) to evaluate the validity of these identified candidate BFIs and (3) to address further validation and/or identification work to be done. Methods This systematic review was based on a comprehensive literature search of three databases (PubMed, Scopus and ISI web of Science), to identify candidate BFIs. Via a second search step in the Human Metabolome Database (HMDB), the Food Database (FooDB) and Phenol-Explorer, the specificity of the candidate BFIs was evaluated, followed by an evaluation of the validity of the specific candidate BFIs, via pre-defined criteria. Results In total, 37 papers were included for cocoa and 8 papers for liquorice. For cocoa, 164 unique candidate BFIs were obtained, and for liquorice, four were identified in total. Despite the high number of identified BFIs for cocoa, none of the metabolites was specific. Therefore, the validity of these compounds was not further examined. For liquorice intake, 18-glycyrrhetinic acid (18-GA) was found to have the highest assumed validity. Conclusions For cocoa, specific BFIs were missing, mainly because the individual BFIs were also found in foods having a similar composition, such as tea (polyphenols) or coffee (caffeine). However, a combination of individual BFIs might lead to discriminating profiles between cocoa (products) and foods with a similar composition. Therefore, studies directly comparing the consumption of cocoa to these similar products are needed, enabling efforts to find a unique profile per product. For liquorice, we identified 18-GA as a promising BFI; however, important information on its validity is missing; thus, more research is necessary. Our findings indicate a need for more studies to determine acceptable BFIs for both cocoa and liquorice.
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Affiliation(s)
- Charlotte C J R Michielsen
- 1Division of Human Nutrition and Health, Wageningen University and Research Centre, Stippeneng 4, 6708 WE Wageningen, The Netherlands
| | - Enrique Almanza-Aguilera
- 2Department of Nutrition, Food Sciences and Gastronomy, Biomarkers and Nutrimetabolomics Laboratory, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,3CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 08028 Barcelona, Spain
| | - Elske M Brouwer-Brolsma
- 1Division of Human Nutrition and Health, Wageningen University and Research Centre, Stippeneng 4, 6708 WE Wageningen, The Netherlands
| | - Mireia Urpi-Sarda
- 2Department of Nutrition, Food Sciences and Gastronomy, Biomarkers and Nutrimetabolomics Laboratory, XaRTA, INSA-UB, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,3CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 08028 Barcelona, Spain
| | - Lydia A Afman
- 1Division of Human Nutrition and Health, Wageningen University and Research Centre, Stippeneng 4, 6708 WE Wageningen, The Netherlands
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Khodorova NV, Rutledge DN, Oberli M, Mathiron D, Marcelo P, Benamouzig R, Tomé D, Gaudichon C, Pilard S. Urinary Metabolomics Profiles Associated to Bovine Meat Ingestion in Humans. Mol Nutr Food Res 2018; 63:e1700834. [PMID: 29468821 DOI: 10.1002/mnfr.201700834] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 12/21/2017] [Indexed: 01/03/2023]
Abstract
SCOPE The impact of meat consumption on human health is widely examined in nutritional epidemiological studies, especially due to the connection between the consumption of red and processed meat and the risk of colon cancer. Food questionnaires do not assess the exposure to different methods of meat cooking. This study aimed to identify biomarkers of the acute ingestion of bovine meat cooked with two different processes. METHODS AND RESULTS Non-targeted UPLC-MS metabolite profiling was done on urine samples obtained from 24 healthy volunteers before and 8 h after the ingestion of a single meal composed of intrinsically 15 N labelled bovine meat, either cooked at 55 °C for 5 min or at 90 °C for 30 min. A discriminant analysis extension of independent components analysis was applied to the mass spectral data. After meat ingestion, the urinary excretion of 1-methylhistidine, phenylacetylglutamine, and short- and medium-chained acylcarnitines was observed. 15 N labelling was detected in these metabolites, thus confirming their origin from ingested meat. However, no difference was observed in urinary metabolomic profiles according to the meat cooking process used. CONCLUSION Meat ingestion led to the excretion of several nitrogen-containing compounds, but although a metabolic signature was detected for meat ingestion, the impact of the cooking process was not detectable at the level of urinary metabolic signature in our experimental conditions.
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Affiliation(s)
- Nadezda V Khodorova
- UMR Physiologie de la Nutrition et du Comportement Alimentaire, AgroParisTech, Institut National de la Recherche Agronomique, Université Paris Saclay, Paris, France
| | - Douglas N Rutledge
- UMR 1145 Génie Industriel Alimentaire, AgroParisTech, Institut National de la Recherche Agronomique, Université Paris Saclay, Paris, France
| | - Marion Oberli
- UMR Physiologie de la Nutrition et du Comportement Alimentaire, AgroParisTech, Institut National de la Recherche Agronomique, Université Paris Saclay, Paris, France
| | - David Mathiron
- Plateforme Analytique, Université de Picardie Jules Verne, Amiens, France
| | - Paulo Marcelo
- Plateforme Imagerie Cellulaire et Analyse des Protéines, Université de Picardie Jules Verne, Amiens, France
| | - Robert Benamouzig
- UMR Physiologie de la Nutrition et du Comportement Alimentaire, AgroParisTech, Institut National de la Recherche Agronomique, Université Paris Saclay, Paris, France
| | - Daniel Tomé
- UMR Physiologie de la Nutrition et du Comportement Alimentaire, AgroParisTech, Institut National de la Recherche Agronomique, Université Paris Saclay, Paris, France
| | - Claire Gaudichon
- UMR Physiologie de la Nutrition et du Comportement Alimentaire, AgroParisTech, Institut National de la Recherche Agronomique, Université Paris Saclay, Paris, France
| | - Serge Pilard
- Plateforme Analytique, Université de Picardie Jules Verne, Amiens, France
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29
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Gil RB, Ortiz A, Sanchez-Niño MD, Markoska K, Schepers E, Vanholder R, Glorieux G, Schmitt-Kopplin P, Heinzmann SS. Increased urinary osmolyte excretion indicates chronic kidney disease severity and progression rate. Nephrol Dial Transplant 2018; 33:2156-2164. [DOI: 10.1093/ndt/gfy020] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 12/22/2017] [Indexed: 12/14/2022] Open
Affiliation(s)
- Ryan B Gil
- Helmholtz Center Munich, German Research Center for Environment Health, Research Unit Analytical BioGeoChemistry, Neuherberg, Germany
| | | | | | | | - Eva Schepers
- Department of Internal Medicine, Nephrology Division, Ghent University Hospital, Ghent, Belgium
| | - Raymond Vanholder
- Department of Internal Medicine, Nephrology Division, Ghent University Hospital, Ghent, Belgium
| | - Griet Glorieux
- Department of Internal Medicine, Nephrology Division, Ghent University Hospital, Ghent, Belgium
| | - Philippe Schmitt-Kopplin
- Helmholtz Center Munich, German Research Center for Environment Health, Research Unit Analytical BioGeoChemistry, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Technical University Munich, Chair of Analytical Food Chemistry, Freising-Weihenstephan, Germany
| | - Silke S Heinzmann
- Helmholtz Center Munich, German Research Center for Environment Health, Research Unit Analytical BioGeoChemistry, Neuherberg, Germany
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30
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Loo RL, Zou X, Appel LJ, Nicholson JK, Holmes E. Characterization of metabolic responses to healthy diets and association with blood pressure: application to the Optimal Macronutrient Intake Trial for Heart Health (OmniHeart), a randomized controlled study. Am J Clin Nutr 2018; 107:323-334. [PMID: 29506183 DOI: 10.1093/ajcn/nqx072] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 12/13/2017] [Indexed: 01/02/2023] Open
Abstract
Background Interindividual variation in the response to diet is common, but the underlying mechanism for such variation is unclear. Objective The objective of this study was to use a metabolic profiling approach to identify a panel of urinary metabolites representing individuals demonstrating typical (homogeneous) metabolic responses to healthy diets, and subsequently to define the association of these metabolites with improvement of risk factors for cardiovascular diseases (CVDs). Design 24-h urine samples from 158 participants with pre-hypertension and stage 1 hypertension, collected at baseline and following the consumption of a carbohydrate-rich, a protein-rich, and a monounsaturated fat-rich healthy diet (6 wk/diet) in a randomized, crossover study, were analyzed by proton (1H) nuclear magnetic resonance (NMR) spectroscopy. Urinary metabolite profiles were interrogated to identify typical and variable responses to each diet. We quantified the differences in absolute excretion of metabolites, distinguishing between dietary comparisons within the typical response groups, and established their associations with CVD risk factors using linear regression. Results Globally all 3 diets induced a similar pattern of change in the urinary metabolic profiles for the majority of participants (60.1%). Diet-dependent metabolic variation was not significantly associated with total cholesterol or low-density lipoprotein (LDL) cholesterol concentration. However, blood pressure (BP) was found to be significantly associated with 6 urinary metabolites reflecting dietary intake [proline-betaine (inverse), carnitine (direct)], gut microbial co-metabolites [hippurate (direct), 4-cresyl sulfate (inverse), phenylacetylglutamine (inverse)], and tryptophan metabolism [N-methyl-2-pyridone-5-carboxamide (inverse)]. A dampened clinical response was observed in some individuals with variable metabolic responses, which could be attributed to nonadherence to diet (≤25.3%), variation in gut microbiome activity (7.6%), or a combination of both (7.0%). Conclusions These data indicate interindividual variations in BP in response to dietary change and highlight the potential influence of the gut microbiome in mediating this relation. This approach provides a framework for stratification of individuals undergoing dietary management. The original OmniHeart intervention study and the metabolomics study were registered at www.clinicaltrials.gov as NCT00051350 and NCT03369535, respectively.
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Affiliation(s)
- Ruey Leng Loo
- Medway Metabonomics Research Group, Medway School of Pharmacy, Universities of Kent and Greenwich, Chatham Maritime, United Kingdom
| | - Xin Zou
- Medway Metabonomics Research Group, Medway School of Pharmacy, Universities of Kent and Greenwich, Chatham Maritime, United Kingdom.,Ministry of Education Key Laboratory of Systems Biomedicine, Shanghai Centre for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Lawrence J Appel
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD.,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD
| | - Jeremy K Nicholson
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, United Kingdom.,MRC-HPA Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Elaine Holmes
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, United Kingdom.,MRC-HPA Centre for Environment and Health, Imperial College London, London, United Kingdom
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Siopi A, Mougios V. Metabolomics in Human Acute-Exercise Trials: Study Design and Preparation. Methods Mol Biol 2018; 1738:279-287. [PMID: 29654597 DOI: 10.1007/978-1-4939-7643-0_19] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Metabolomics can be of great value in the study of exercise metabolism. However, because of the high intraindividual and interindividual biological variability of the human metabolome, special considerations should be taken into account when designing an acute-exercise metabolomic study. To study different exercise parameters, e.g., different exercise modes, intensities, etc., a crossover study design, where each participant acts as their own control, is preferable to a parallel design, one involving different groups of participants. Moreover, the study should include a no exercise, control trial. Before each trial, participants should follow carefully designed preparatory steps to control for possible confounding factors, i.e., maintain repeatable and constant conditions for all individual trials of the study to minimize variation due to factors other than the one(s) being studied. This chapter focuses on the design of human metabolomic studies, where the intervention is an acute metabolic challenge, such as an exercise bout or a test meal, and presents some basic steps for screening potential participants, performing preliminary tests, preparing for the trial day, and performing the trial.
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Affiliation(s)
- Aikaterina Siopi
- School of Physical Education and Sport Science at Thessaloniki, Aristotle University of Thessaloniki, Thessaloniki, Greece. .,Department of Physical Education and Sport Science at Thermi, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | - Vassilis Mougios
- School of Physical Education and Sport Science at Thessaloniki, Aristotle University of Thessaloniki, Thessaloniki, Greece
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32
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Wang M, Zhang X, Wang Y, Li Y, Chen Y, Zheng H, Ma F, Ma CW, Lu B, Xie Z, Liao Q. Metabonomic strategy for the detection of metabolic effects of probiotics combined with prebiotic supplementation in weaned rats. RSC Adv 2018; 8:5042-5057. [PMID: 35539530 PMCID: PMC9078034 DOI: 10.1039/c7ra12067b] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Accepted: 01/15/2018] [Indexed: 11/21/2022] Open
Abstract
The purpose of this study is to investigate the effects of probiotics combined with prebiotics (PP) supplementation on weaned rat metabolism. A metabonomic strategy employing 1H-NMR spectroscopy and multivariate data analysis was used to examine weaned rat biological responses to PP supplementation. Male Sprague-Dawley rats (post-natal day 21, PD 21) received probiotics (Lactobacillus acidophilus NCFM (L-NCFM) and Bifidobacterium lactis Bi-07 (B-LBi07), 1 : 1, 1.0 × 1011 cfu kg−1) and prebiotics (Lycium barbarum polysaccharides (LBP), Poria cocos polysaccharides (PCPs) and Lentinan, 1 : 1 : 1, 24 g kg−1) via intragastric administration for 28 consecutive days. Urine and feces were collected for analysis. Significant topographical metabolic variations were present in urine and feces. Urinary metabolites upregulated by PP treatment included alanine, N-acetylglycine, glutamine, dimethylamine, phosphorylcholine, ethylene glycol, mannitol, phenylacetylglycine and glycoate, which were related to alanine, aspartate and glutamate metabolism, and choline metabolism. Feces-derived metabolites, including caproate, valerate, butyrate, propionate, lactate, acetate, succinate, methanol, threonine and methionine, were significantly increased, which were related to short-chain fatty acid (SCFA) metabolism and TCA cycle metabolism. These results indicate that dietary PP supplementation can regulate common systemic metabolic processes, including energy metabolism, amino acid metabolism, lipid metabolism, nucleic acid metabolism, and gut microbiota-related metabolism. This study also illuminates the vital role of PP supplementation in regulating the metabolism of weaned rats. Dietary probiotic supplementation is beneficial to the growth of weaned rats by regulating the metabolism.![]()
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Affiliation(s)
- Mengxia Wang
- School of Pharmaceutical Sciences
- Guangzhou University of Chinese Medicine
- Guangzhou
- P. R. China
| | - Xiaojun Zhang
- School of Pharmaceutical Sciences
- Guangzhou University of Chinese Medicine
- Guangzhou
- P. R. China
| | | | - Yuan Li
- School of Pharmaceutical Sciences
- Guangzhou University of Chinese Medicine
- Guangzhou
- P. R. China
| | - Yongxiong Chen
- School of Pharmaceutical Sciences
- Guangzhou University of Chinese Medicine
- Guangzhou
- P. R. China
| | - Haihui Zheng
- School of Pharmaceutical Sciences (Shen Zhen)
- Sun Yat-sen University
- Guangzhou
- P. R. China
| | - Fangli Ma
- Infinitus (China) Company Ltd
- Guangzhou
- China
| | | | - Biyu Lu
- School of Pharmaceutical Sciences
- Guangzhou University of Chinese Medicine
- Guangzhou
- P. R. China
| | - Zhiyong Xie
- School of Pharmaceutical Sciences (Shen Zhen)
- Sun Yat-sen University
- Guangzhou
- P. R. China
| | - Qiongfeng Liao
- School of Pharmaceutical Sciences
- Guangzhou University of Chinese Medicine
- Guangzhou
- P. R. China
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Suárez M, Caimari A, del Bas JM, Arola L. Metabolomics: An emerging tool to evaluate the impact of nutritional and physiological challenges. Trends Analyt Chem 2017. [DOI: 10.1016/j.trac.2017.06.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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Metabotyping for the development of tailored dietary advice solutions in a European population: the Food4Me study. Br J Nutr 2017; 118:561-569. [PMID: 29056103 DOI: 10.1017/s0007114517002069] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.
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Xu J, Zheng X, Cheng KK, Chang X, Shen G, Liu M, Wang Y, Shen J, Zhang Y, He Q, Dong J, Yang Z. NMR-based metabolomics Reveals Alterations of Electro-acupuncture Stimulations on Chronic Atrophic Gastritis Rats. Sci Rep 2017; 7:45580. [PMID: 28358020 PMCID: PMC5372362 DOI: 10.1038/srep45580] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 02/28/2017] [Indexed: 12/15/2022] Open
Abstract
Chronic atrophic gastritis (CAG) is a common gastrointestinal disease which has been considered as precancerous lesions of gastric carcinoma. Previously, electro-acupuncture stimulation has been shown to be effective in ameliorating symptoms of CAG. However the underlying mechanism of this beneficial treatment is yet to be established. In the present study, an integrated histopathological examination along with molecular biological assay, as well as 1H NMR analysis of multiple biological samples (urine, serum, stomach, cortex and medulla) were employed to systematically assess the pathology of CAG and therapeutic effect of electro-acupuncture stimulation at Sibai (ST 2), Liangmen (ST 21), and Zusanli (ST 36) acupoints located in the stomach meridian using a rat model of CAG. The current results showed that CAG caused comprehensive metabolic alterations including the TCA cycle, glycolysis, membrane metabolism and catabolism, gut microbiota-related metabolism. On the other hand, electro-acupuncture treatment was found able to normalize a number of CAG-induced metabolomics changes by alleviating membrane catabolism, restoring function of neurotransmitter in brain and partially reverse the CAG-induced perturbation in gut microbiota metabolism. These findings provided new insights into the biochemistry of CAG and mechanism of the therapeutic effect of electro-acupuncture stimulations.
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Affiliation(s)
- Jingjing Xu
- Department of Electronic Science, and Department of Traditional Chinese Medicine, Xiamen University, Xiamen 361005, China
| | - Xujuan Zheng
- Department of Electronic Science, and Department of Traditional Chinese Medicine, Xiamen University, Xiamen 361005, China
| | - Kian-Kai Cheng
- Department of Bioprocess &Polymer Engineering, Innovative Centre in Agritechnology, University Teknologi Malaysia, Johor 81310, Malaysia
| | - Xiaorong Chang
- College of Acupuncture and Moxibustion, Hunan University of Chinese Medicine, Changsha 410007, China
| | - Guiping Shen
- Department of Electronic Science, and Department of Traditional Chinese Medicine, Xiamen University, Xiamen 361005, China
| | - Mi Liu
- College of Acupuncture and Moxibustion, Hunan University of Chinese Medicine, Changsha 410007, China
| | - Yadong Wang
- Department of Electronic Science, and Department of Traditional Chinese Medicine, Xiamen University, Xiamen 361005, China
| | - Jiacheng Shen
- Department of Electronic Science, and Department of Traditional Chinese Medicine, Xiamen University, Xiamen 361005, China
| | - Yuan Zhang
- College of Acupuncture and Moxibustion, Hunan University of Chinese Medicine, Changsha 410007, China
| | - Qida He
- Department of Electronic Science, and Department of Traditional Chinese Medicine, Xiamen University, Xiamen 361005, China
| | - Jiyang Dong
- Department of Electronic Science, and Department of Traditional Chinese Medicine, Xiamen University, Xiamen 361005, China
| | - Zongbao Yang
- Department of Electronic Science, and Department of Traditional Chinese Medicine, Xiamen University, Xiamen 361005, China
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Hocher B, Adamski J. Metabolomics for clinical use and research in chronic kidney disease. Nat Rev Nephrol 2017; 13:269-284. [PMID: 28262773 DOI: 10.1038/nrneph.2017.30] [Citation(s) in RCA: 232] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Chronic kidney disease (CKD) has a high prevalence in the general population and is associated with high mortality; a need therefore exists for better biomarkers for diagnosis, monitoring of disease progression and therapy stratification. Moreover, very sensitive biomarkers are needed in drug development and clinical research to increase understanding of the efficacy and safety of potential and existing therapies. Metabolomics analyses can identify and quantify all metabolites present in a given sample, covering hundreds to thousands of metabolites. Sample preparation for metabolomics requires a very fast arrest of biochemical processes. Present key technologies for metabolomics are mass spectrometry and proton nuclear magnetic resonance spectroscopy, which require sophisticated biostatistic and bioinformatic data analyses. The use of metabolomics has been instrumental in identifying new biomarkers of CKD such as acylcarnitines, glycerolipids, dimethylarginines and metabolites of tryptophan, the citric acid cycle and the urea cycle. Biomarkers such as c-mannosyl tryptophan and pseudouridine have better performance in CKD stratification than does creatinine. Future challenges in metabolomics analyses are prospective studies and deconvolution of CKD biomarkers from those of other diseases such as metabolic syndrome, diabetes mellitus, inflammatory conditions, stress and cancer.
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Affiliation(s)
- Berthold Hocher
- Department of Basic Medicine, Medical College of Hunan University, 410006 Changsha, China
| | - Jerzy Adamski
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany
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Cheung W, Keski-Rahkonen P, Assi N, Ferrari P, Freisling H, Rinaldi S, Slimani N, Zamora-Ros R, Rundle M, Frost G, Gibbons H, Carr E, Brennan L, Cross AJ, Pala V, Panico S, Sacerdote C, Palli D, Tumino R, Kühn T, Kaaks R, Boeing H, Floegel A, Mancini F, Boutron-Ruault MC, Baglietto L, Trichopoulou A, Naska A, Orfanos P, Scalbert A. A metabolomic study of biomarkers of meat and fish intake. Am J Clin Nutr 2017; 105:600-608. [PMID: 28122782 DOI: 10.3945/ajcn.116.146639] [Citation(s) in RCA: 146] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 12/27/2016] [Indexed: 11/14/2022] Open
Abstract
Background: Meat and fish intakes have been associated with various chronic diseases. The use of specific biomarkers may help to assess meat and fish intake and improve subject classification according to the amount and type of meat or fish consumed.Objective: A metabolomic approach was applied to search for biomarkers of meat and fish intake in a dietary intervention study and in free-living subjects from the European Prospective Investigation into Cancer and Nutrition (EPIC) study.Design: In the dietary intervention study, 4 groups of 10 subjects consumed increasing quantities of chicken, red meat, processed meat, and fish over 3 successive weeks. Twenty-four-hour urine samples were collected during each period and analyzed by high-resolution liquid chromatography-mass spectrometry. Signals characteristic of meat or fish intake were replicated in 50 EPIC subjects for whom a 24-h urine sample and 24-h dietary recall were available and who were selected for their exclusive intake or no intake of any of the 4 same foods.Results: A total of 249 mass spectrometric features showed a positive dose-dependent response to meat or fish intake in the intervention study. Eighteen of these features best predicted intake of the 4 food groups in the EPIC urine samples on the basis of partial receiver operator curve analyses with permutation testing (areas under the curve ranging between 0.61 and 1.0). Of these signals, 8 metabolites were identified. Anserine was found to be specific for chicken intake, whereas trimethylamine-N-oxide showed good specificity for fish. Carnosine and 3 acylcarnitines (acetylcarnitine, propionylcarnitine, and 2-methylbutyrylcarnitine) appeared to be more generic indicators of meat and meat and fish intake, respectively.Conclusion: The meat and fish biomarkers identified in this work may be used to study associations between meat and fish intake and disease risk in epidemiologic studies. This trial was registered at clinicaltrials.gov as NCT01684917.
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Affiliation(s)
- William Cheung
- International Agency for Research on Cancer, Lyon, France
| | | | - Nada Assi
- International Agency for Research on Cancer, Lyon, France
| | - Pietro Ferrari
- International Agency for Research on Cancer, Lyon, France
| | | | - Sabina Rinaldi
- International Agency for Research on Cancer, Lyon, France
| | - Nadia Slimani
- International Agency for Research on Cancer, Lyon, France
| | | | - Milena Rundle
- Division of Endocrinology and Metabolism, Nutrition and Dietetic Research Group, and
| | - Gary Frost
- Division of Endocrinology and Metabolism, Nutrition and Dietetic Research Group, and
| | - Helena Gibbons
- Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Dublin, Republic of Ireland
| | - Eibhlin Carr
- Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Dublin, Republic of Ireland
| | - Lorraine Brennan
- Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Dublin, Republic of Ireland
| | - Amanda J Cross
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Valeria Pala
- Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Salvatore Panico
- Department of Clinical Medicine and Surgery, Federico II University, Naples, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Turin, Italy
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute (ISPO), Florence, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Unit, "Civic-M.P.Arezzo" Hospital, Provincial Health Unit, Ragusa, Italy
| | - Tilman Kühn
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Heiner Boeing
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Anna Floegel
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Francesca Mancini
- French National Institute of Health and Medical Research (INSERM), Centre for Research in Epidemiology and Population Health (CESP), Health across Generations Team, U1018, Villejuif, France
- Institut Gustave Roussy, Villejuif, France
| | - Marie-Christine Boutron-Ruault
- French National Institute of Health and Medical Research (INSERM), Centre for Research in Epidemiology and Population Health (CESP), Health across Generations Team, U1018, Villejuif, France
- Institut Gustave Roussy, Villejuif, France
- University Paris Sud, UMRS 1018, Villejuif, France
| | - Laura Baglietto
- Cancer Epidemiology Centre, Cancer Council of Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Antonia Trichopoulou
- Hellenic Health Foundation, Athens, Greece; and
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology, and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Androniki Naska
- Hellenic Health Foundation, Athens, Greece; and
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology, and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Philippos Orfanos
- Hellenic Health Foundation, Athens, Greece; and
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology, and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
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Garcia-Perez I, Posma JM, Gibson R, Chambers ES, Hansen TH, Vestergaard H, Hansen T, Beckmann M, Pedersen O, Elliott P, Stamler J, Nicholson JK, Draper J, Mathers JC, Holmes E, Frost G. Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial. Lancet Diabetes Endocrinol 2017; 5:184-195. [PMID: 28089709 PMCID: PMC5357736 DOI: 10.1016/s2213-8587(16)30419-3] [Citation(s) in RCA: 156] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2016] [Revised: 11/08/2016] [Accepted: 11/09/2016] [Indexed: 12/15/2022]
Abstract
BACKGROUND Accurate monitoring of changes in dietary patterns in response to food policy implementation is challenging. Metabolic profiling allows simultaneous measurement of hundreds of metabolites in urine, the concentrations of which can be affected by food intake. We hypothesised that metabolic profiles of urine samples developed under controlled feeding conditions reflect dietary intake and can be used to model and classify dietary patterns of free-living populations. METHODS In this randomised, controlled, crossover trial, we recruited healthy volunteers (aged 21-65 years, BMI 20-35 kg/m2) from a database of a clinical research unit in the UK. We developed four dietary interventions with a stepwise variance in concordance with the WHO healthy eating guidelines that aim to prevent non-communicable diseases (increase fruits, vegetables, whole grains, and dietary fibre; decrease fats, sugars, and salt). Participants attended four inpatient stays (72 h each, separated by at least 5 days), during which they were given one dietary intervention. The order of diets was randomly assigned across study visits. Randomisation was done by an independent investigator, with the use of opaque, sealed, sequentially numbered envelopes that each contained one of the four dietary interventions in a random order. Participants and investigators were not masked from the dietary intervention, but investigators analysing the data were masked from the randomisation order. During each inpatient period, urine was collected daily over three timed periods: morning (0900-1300 h), afternoon (1300-1800 h), and evening and overnight (1800-0900 h); 24 h urine samples were obtained by pooling these samples. Urine samples were assessed by proton nuclear magnetic resonance (1H-NMR) spectroscopy, and diet-discriminatory metabolites were identified. We developed urinary metabolite models for each diet and identified the associated metabolic profiles, and then validated the models using data and samples from the INTERMAP UK cohort (n=225) and a healthy-eating Danish cohort (n=66). This study is registered with ISRCTN, number ISRCTN43087333. FINDINGS Between Aug 13, 2013, and May 18, 2014, we contacted 300 people with a letter of invitation. 78 responded, of whom 26 were eligible and invited to attend a health screening. Of 20 eligible participants who were randomised, 19 completed all four 72 h study stays between Oct 2, 2013, and July 29, 2014, and consumed all the food provided. Analysis of 1H-NMR spectroscopy data indicated that urinary metabolic profiles of the four diets were distinct. Significant stepwise differences in metabolite concentrations were seen between diets with the lowest and highest metabolic risks. Application of the derived metabolite models to the validation datasets confirmed the association between urinary metabolic and dietary profiles in the INTERMAP UK cohort (p<0·0001) and the Danish cohort (p<0·0001). INTERPRETATION Urinary metabolite models developed in a highly controlled environment can classify groups of free-living people into consumers of diets associated with lower or higher non-communicable disease risk on the basis of multivariate metabolite patterns. This approach enables objective monitoring of dietary patterns in population settings and enhances the validity of dietary reporting. FUNDING UK National Institute for Health Research and UK Medical Research Council.
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Affiliation(s)
- Isabel Garcia-Perez
- Nutrition and Dietetic Research Group, Division of Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, UK; Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Joram M Posma
- Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Rachel Gibson
- Nutrition and Dietetic Research Group, Division of Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, UK
| | - Edward S Chambers
- Nutrition and Dietetic Research Group, Division of Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, UK
| | - Tue H Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Vestergaard
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Manfred Beckmann
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, Medical Research Council (MRC)-Public Health England Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; MRC-National Institute for Health Research (NIHR) National Phenome Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Jeremiah Stamler
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, USA
| | - Jeremy K Nicholson
- Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK; MRC-National Institute for Health Research (NIHR) National Phenome Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - John Draper
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
| | - John C Mathers
- Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Newcastle, UK
| | - Elaine Holmes
- Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK; MRC-National Institute for Health Research (NIHR) National Phenome Centre, Department of Surgery and Cancer, Imperial College London, London, UK.
| | - Gary Frost
- Nutrition and Dietetic Research Group, Division of Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, UK.
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Reverri EJ, Slupsky CM, Mishchuk DO, Steinberg FM. Metabolomics reveals differences between three daidzein metabolizing phenotypes in adults with cardiometabolic risk factors. Mol Nutr Food Res 2017; 61. [PMID: 27364093 DOI: 10.1002/mnfr.201600132] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2016] [Revised: 06/09/2016] [Accepted: 06/10/2016] [Indexed: 01/04/2023]
Abstract
SCOPE The soy isoflavone, daidzein, is metabolized by gut microbiota to O-desmethylangolensin (ODMA) and/or equol. Producing equol is postulated as a contributing factor for the beneficial effects of soy. METHODS AND RESULTS This randomized, controlled, cross-over design used an untargeted metabolomic approach to assess the metabolic profile of different daidzein metabolizers. Adults (n = 17) with cardiometabolic risk factors received soy nuts or control food for 4 weeks, separated by a 2-week washout. No significant differences were detected pre- and postintervention and between interventions. Examination of the ability to metabolize daidzein revealed three groups: ODMA only producers (n = 4), equol + ODMA producers (n = 8), and nonproducers (n = 5). Analysis of the serum metabolome revealed nonproducers could be distinguished from ODMA-only and equol + ODMA producers. Differences between these phenotypes were related to obesity and metabolic risk (methionine, asparagine, and trimethylamine) with equol + ODMA producers having lower concentrations, yet paradoxically higher pro-inflammatory cytokines. In urine, nonproducers clustered with ODMA producers and were distinct from equol + ODMA producers. Urinary metabolite profiles revealed significantly higher excretion of fumarate and 2-oxoglutarate, as well as pyroglutamate, alanine, and the gut microbial metabolite dimethylamine in equol + ODMA producers. CONCLUSION These results emphasize that the serum and urine metabolomes are distinct based on the ability to metabolize isoflavones.
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Affiliation(s)
| | - Carolyn M Slupsky
- Department of Nutrition, University of California, Davis, CA, USA
- Department of Food Science and Technology, University of California, Davis, CA, USA
| | - Darya O Mishchuk
- Department of Food Science and Technology, University of California, Davis, CA, USA
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Navarro SL, Neuhouser ML, Cheng TYD, Tinker LF, Shikany JM, Snetselaar L, Martinez JA, Kato I, Beresford SAA, Chapkin RS, Lampe JW. The Interaction between Dietary Fiber and Fat and Risk of Colorectal Cancer in the Women's Health Initiative. Nutrients 2016; 8:E779. [PMID: 27916893 PMCID: PMC5188434 DOI: 10.3390/nu8120779] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 11/22/2016] [Accepted: 11/25/2016] [Indexed: 12/14/2022] Open
Abstract
Combined intakes of specific dietary fiber and fat subtypes protect against colon cancer in animal models. We evaluated associations between self-reported individual and combinations of fiber (insoluble, soluble, and pectins, specifically) and fat (omega-6, omega-3, and docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), specifically) and colorectal cancer (CRC) risk in the Women's Health Initiative prospective cohort (n = 134,017). During a mean 11.7 years (1993-2010), 1952 incident CRC cases were identified. Cox regression models computed multivariate adjusted hazard ratios to estimate the association between dietary factors and CRC risk. Assessing fiber and fat individually, there was a modest trend for lower CRC risk with increasing intakes of total and insoluble fiber (p-trend 0.09 and 0.08). An interaction (p = 0.01) was observed between soluble fiber and DHA + EPA, with protective effects of DHA + EPA with lower intakes of soluble fiber and an attenuation at higher intakes, however this association was no longer significant after correction for multiple testing. These results suggest a modest protective effect of higher fiber intake on CRC risk, but not in combination with dietary fat subtypes. Given the robust results in preclinical models and mixed results in observational studies, controlled dietary interventions with standardized intakes are needed to better understand the interaction of specific fat and fiber subtypes on colon biology and ultimately CRC susceptibility in humans.
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Affiliation(s)
- Sandi L Navarro
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
| | - Marian L Neuhouser
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA 98105, USA.
| | - Ting-Yuan David Cheng
- Division of Cancer Prevention and Population Sciences, Roswell Park Cancer Institute, Buffalo, NY 14263, USA.
| | - Lesley F Tinker
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
| | - James M Shikany
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
| | - Linda Snetselaar
- Department of Epidemiology, University of Iowa, Iowa City, IA 52242, USA.
| | - Jessica A Martinez
- Department of Nutritional Sciences, University of Arizona Cancer Center, Tucson, AZ 85724, USA.
| | - Ikuko Kato
- Department of Oncology and Pathology, Wayne State University, Detroit, MI 48201, USA.
| | - Shirley A A Beresford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA 98105, USA.
| | - Robert S Chapkin
- Program in Integrative Nutrition and Complex Diseases, Texas A&M University, College Station, TX 77843, USA.
| | - Johanna W Lampe
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA 98105, USA.
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Urinary hippurate and proline betaine relative to fruit intake, blood pressure, and body mass index. Proc Nutr Soc 2016. [DOI: 10.1017/s0029665116001932] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Gil RB, Lehmann R, Schmitt-Kopplin P, Heinzmann SS. 1H NMR-based metabolite profiling workflow to reduce inter-sample chemical shift variations in urine samples for improved biomarker discovery. Anal Bioanal Chem 2016; 408:4683-91. [DOI: 10.1007/s00216-016-9552-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2016] [Revised: 03/30/2016] [Accepted: 04/06/2016] [Indexed: 12/31/2022]
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Cox IJ, Aliev AE, Crossey MME, Dawood M, Al-Mahtab M, Akbar SM, Rahman S, Riva A, Williams R, Taylor-Robinson SD. Urinary nuclear magnetic resonance spectroscopy of a Bangladeshi cohort with hepatitis-B hepatocellular carcinoma: A biomarker corroboration study. World J Gastroenterol 2016; 22:4191-4200. [PMID: 27122669 PMCID: PMC4837436 DOI: 10.3748/wjg.v22.i16.4191] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 02/19/2016] [Accepted: 03/02/2016] [Indexed: 02/06/2023] Open
Abstract
AIM: To establish if a distinct urinary metabolic profile could be identified in Bangladeshi hepatitis-B hepatocellular carcinoma (HCC) patients compared to cirrhosis patients and controls.
METHODS: Urine samples from 42 Bangladeshi patients with HCC (39 patients with hepatitis-B HCC), 47 with cirrhosis on a background of hepatitis B, 46 with chronic hepatitis B, and seven ethnically-matched healthy controls were analyzed using nuclear magnetic resonance (NMR) spectroscopy. A full dietary and medication history was recorded for each subject. The urinary NMR data were analyzed using principal component analysis (PCA) and orthogonal partial least squared discriminant analysis (OPLS-DA) techniques. Differences in relative signal levels of the most discriminatory metabolites identified by PCA and OPLS-DA were compared between subject groups using an independent samples Kruskal-Wallis one-way analysis of variance (ANOVA) test with all pairwise multiple comparisons. Within the patient subgroups, the Mann-Whitney U test was used to compare metabolite levels depending on hepatitis B e-antigen (HBeAg) status and treatment with anti-viral therapy. A Benjamini-Hochberg adjustment was applied to acquire the level of significance for multiple testing, with a declared level of statistical significance of P < 0.05.
RESULTS: There were significant differences in age (P < 0.001), weight (P < 0.001), and body mass index (P < 0.001) across the four clinical subgroups. Serum alanine aminotransferase (ALT) was significantly higher in the HCC group compared to controls (P < 0.001); serum α-fetoprotein was generally markedly elevated in HCC compared to controls; and serum creatinine levels were significantly reduced in the HCC group compared to the cirrhosis group (P = 0.004). A three-factor PCA scores plot showed clustering of the urinary NMR spectra from the four subgroups. Metabolites that contributed to the discrimination between the subgroups included acetate, creatine, creatinine, dimethyamine (DMA), formate, glycine, hippurate, and trimethylamine-N-oxide (TMAO). A comparison of relative metabolite levels confirmed that carnitine was significantly increased in HCC; and creatinine, hippurate, and TMAO were significantly reduced in HCC compared to the other subgroups. HBeAg negative patients showed a significant increase in creatinine (P = 0.001) compared to HBeAg positive patients in the chronic hepatitis B subgroup, whilst HBeAg negative patients showed a significant decrease in DMA (P = 0.004) in the cirrhosis subgroup compared to HBeAg positive patients. There were no differences in metabolite levels in HCC patients who did or did not receive antiviral treatment.
CONCLUSION: Urinary NMR changes in Bangladeshi HCC were identified, corroborating previous findings from Egypt and West Africa. These findings could form the basis for the development of a cost-effective HCC dipstick screening test.
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Smirnov KS, Maier TV, Walker A, Heinzmann SS, Forcisi S, Martinez I, Walter J, Schmitt-Kopplin P. Challenges of metabolomics in human gut microbiota research. Int J Med Microbiol 2016; 306:266-279. [PMID: 27012595 DOI: 10.1016/j.ijmm.2016.03.006] [Citation(s) in RCA: 91] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Revised: 03/08/2016] [Accepted: 03/09/2016] [Indexed: 01/17/2023] Open
Abstract
The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine.
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Affiliation(s)
- Kirill S Smirnov
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Tanja V Maier
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Alesia Walker
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Silke S Heinzmann
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Sara Forcisi
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany
| | - Inés Martinez
- Department of Agriculture, Food and Nutritional Science, University of Alberta, T6G 2E1 Edmonton, AB, Canada
| | - Jens Walter
- Department of Agriculture, Food and Nutritional Science, University of Alberta, T6G 2E1 Edmonton, AB, Canada
| | - Philippe Schmitt-Kopplin
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg, 85764, Germany; Chair of Analytical Food Chemistry, Technische Universität München, Alte Akademie 10, 85354 Freising, Germany; ZIEL, Institute for Food & Health, Weihenstephaner Berg 1, 85354 Freising, Germany.
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Shiokawa Y, Misawa T, Date Y, Kikuchi J. Application of Market Basket Analysis for the Visualization of Transaction Data Based on Human Lifestyle and Spectroscopic Measurements. Anal Chem 2016; 88:2714-9. [PMID: 26824632 DOI: 10.1021/acs.analchem.5b04182] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
With the innovation of high-throughput metabolic profiling methods such as nuclear magnetic resonance (NMR), data mining techniques that can reveal valuable information from substantial data sets are constantly desired in this field. In particular, for the analytical assessment of various human lifestyles, advanced computational methods are ultimately needed. In this study, we applied market basket analysis, which is generally applied in social sciences such as marketing, and used transaction data derived from dietary intake information and urinary chemical data generated using NMR and inductively coupled plasma optical emission spectrometry measurements. The analysis revealed several relationships, such as fish diets with high trimethylamine N-oxide excretion and N-methylnicotinamide excreted at higher levels in the morning and produced from a protein that was consumed one day prior. Therefore, market basket analysis can be applied to metabolic profiling to effectively understand the relationships between metabolites and lifestyle.
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Affiliation(s)
- Yuka Shiokawa
- Graduate School of Medical Life Science, Yokohama City University , 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Takuma Misawa
- Graduate School of Medical Life Science, Yokohama City University , 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Yasuhiro Date
- Graduate School of Medical Life Science, Yokohama City University , 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Jun Kikuchi
- Graduate School of Medical Life Science, Yokohama City University , 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,Graduate School of Bioagricultural Sciences, Nagoya University , 1 Furo-cho, Chikusa-ku, Nagoya, Aichi 464-0810, Japan
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Wu GD, Compher C, Chen EZ, Smith SA, Shah RD, Bittinger K, Chehoud C, Albenberg LG, Nessel L, Gilroy E, Star J, Weljie AM, Flint HJ, Metz DC, Bennett MJ, Li H, Bushman FD, Lewis JD. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production. Gut 2016; 65:63-72. [PMID: 25431456 PMCID: PMC4583329 DOI: 10.1136/gutjnl-2014-308209] [Citation(s) in RCA: 360] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Accepted: 10/29/2014] [Indexed: 12/17/2022]
Abstract
OBJECTIVE The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a 'Westernised' lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. DESIGN AND RESULTS Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. CONCLUSIONS Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites.
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Affiliation(s)
- Gary D Wu
- Division of Gastroenterology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Charlene Compher
- School of Nursing, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Eric Z Chen
- Departments of Biostatistics & Epidemiology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sarah A Smith
- Division of Gastroenterology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Rachana D Shah
- Divisions of Endocrinolgy, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Kyle Bittinger
- Department of Microbiology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christel Chehoud
- Department of Microbiology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lindsey G Albenberg
- Department of Gastroenterology, Hepatology, and Nutrition, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Lisa Nessel
- Departments of Biostatistics & Epidemiology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Erin Gilroy
- Departments of Biostatistics & Epidemiology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Julie Star
- Division of Gastroenterology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Aalim M Weljie
- Department of Pharmacology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Harry J Flint
- Microbiology Group, Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK
| | - David C Metz
- Division of Gastroenterology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael J Bennett
- Department of Pathology and Laboratory Medicine, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Hongzhe Li
- Departments of Biostatistics & Epidemiology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Frederic D Bushman
- Department of Microbiology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - James D Lewis
- Division of Gastroenterology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA,Departments of Biostatistics & Epidemiology, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Relative validation of 24-h urinary hippuric acid excretion as a biomarker for dietary flavonoid intake from fruit and vegetables in healthy adolescents. Eur J Nutr 2015; 56:757-766. [PMID: 26658765 DOI: 10.1007/s00394-015-1121-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2015] [Accepted: 11/29/2015] [Indexed: 10/22/2022]
Abstract
PURPOSE A biomarker for dietary flavonoid intake from fruit and vegetables (FlavFV) is needed to elucidate the relevance of flavonoids from these sources for the prevention of chronic diseases. Urinary hippuric acid (HA)-a major metabolite of flavonoids-is promising in this respect as it was shown to satisfyingly indicate fruit and vegetable consumption in different age groups. Therefore, we validated urinary HA as a biomarker for intake of FlavFV. METHODS Analyses included data from 287 healthy adolescents of the DONALD Study (aged 9-16 years) for whom a minimum of two pairs of HA measurements from 24-h urine samples (test method) and FlavFV intake estimated from 3-day weighed dietary records (reference method) existed. Agreement between both methods was assessed by Spearman correlation and cross-classification analyses. Possible confounders of the association were identified by linear regression models. Analyses were performed using a split-sample approach allowing for consecutive exploration (n = 192) and confirmation (n = 95) of results. RESULTS Agreement between urinary HA excretion and FlavFV intake was moderate according to correlation analysis in the exploratory sample (r unadjusted = 0.47, P < 0.0001). Yet, 79 % of the subjects were classified into same/adjacent quartiles, and only 5 % were misclassified into opposite quartiles. These findings were corroborated by analyses in the confirmatory sample (r unadjusted = 0.64; 88 % in same/adjacent vs. 4 % in opposite quartiles). Body surface area (BSA) was the only relevant covariate in the exploratory sample, and its adjustment improved cross-classification estimates in both subsamples. CONCLUSIONS BSA-adjusted 24-h urinary HA excretion represents a suitable biomarker of habitual FlavFV intake in healthy adolescents.
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Ahmad MS, Ashrafian H, Alsaleh M, Holmes E. Role of metabolic phenotyping in understanding obesity and related conditions in Gulf Co-operation Council countries. Clin Obes 2015; 5:302-11. [PMID: 26567983 DOI: 10.1111/cob.12121] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2015] [Revised: 09/21/2015] [Accepted: 10/01/2015] [Indexed: 01/11/2023]
Abstract
Obesity is a major health concern in the Middle East and the incidence is rising in all sections of the population. Efforts to control obesity through diet and lifestyle interventions, and by surgical means, have had limited effect, and the gene-environment interactions underpinning the development of obesity and related pathologies such as metabolic syndrome, cardiovascular disease and certain cancers are poorly defined. Lifestyle, genetics, inflammation and the interaction between the intestinal bacteria and host metabolism have all been implicated in creating an obesogenic environment. We summarize the role of metabolic and microbial phenotyping in understanding the aetiopathogenesis of obesity and in characterizing the metabolic responses to surgical and non-surgical interventions, and explore the potential for clinical translation of this approach.
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Affiliation(s)
- M S Ahmad
- Drug Metabolism Unit, King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
| | - H Ashrafian
- Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK
| | - M Alsaleh
- Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK
| | - E Holmes
- Drug Metabolism Unit, King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
- Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, UK
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Glucocorticoid (dexamethasone)-induced metabolome changes in healthy males suggest prediction of response and side effects. Sci Rep 2015; 5:15954. [PMID: 26526738 PMCID: PMC4630650 DOI: 10.1038/srep15954] [Citation(s) in RCA: 76] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Accepted: 10/05/2015] [Indexed: 02/06/2023] Open
Abstract
Glucocorticoids are indispensable anti-inflammatory and decongestant drugs with high prevalence of use at (~)0.9% of the adult population. Better holistic insights into glucocorticoid-induced changes are crucial for effective use as concurrent medication and management of adverse effects. The profiles of 214 metabolites from plasma of 20 male healthy volunteers were recorded prior to and after ingestion of a single dose of 4 mg dexamethasone (+20 mg pantoprazole). Samples were drawn at three predefined time points per day: seven untreated (day 1 midday - day 3 midday) and four treated (day 3 evening - day 4 evening) per volunteer. Statistical analysis revealed tremendous impact of dexamethasone on the metabolome with 150 of 214 metabolites being significantly deregulated on at least one time point after treatment (ANOVA, Benjamini-Hochberg corrected, q < 0.05). Inter-person variability was high and remained uninfluenced by treatment. The clearly visible circadian rhythm prior to treatment was almost completely suppressed and deregulated by dexamethasone. The results draw a holistic picture of the severe metabolic deregulation induced by single-dose, short-term glucocorticoid application. The observed metabolic changes suggest a potential for early detection of severe side effects, raising hope for personalized early countermeasures increasing quality of life and reducing health care costs.
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50
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Heinzmann SS, Holmes E, Kochhar S, Nicholson JK, Schmitt-Kopplin P. 2-Furoylglycine as a Candidate Biomarker of Coffee Consumption. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2015; 63:8615-8621. [PMID: 26357997 DOI: 10.1021/acs.jafc.5b03040] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Specific and sensitive food biomarkers are necessary to support dietary intake assessment and link nutritional habits to potential impact on human health. A multistep nutritional intervention study was conducted to suggest novel biomarkers for coffee consumption. (1)H NMR metabolic profiling combined with multivariate data analysis resolved 2-furoylglycine (2-FG) as a novel putative biomarker for coffee consumption. We relatively quantified 2-FG in the urine of coffee drinkers and investigated its origin, metabolism, and excretion kinetics. When searching for its potential precursors, we found different furan derivatives in coffee products, which are known to get metabolized to 2-FG. Maximal urinary excretion of 2-FG occurred 2 h after consumption (p = 0.0002) and returned to baseline after 24 h (p = 0.74). The biomarker was not excreted after consumption of coffee substitutes such as tea and chicory coffee and might therefore be a promising acute biomarker for the detection of coffee consumption in human urine.
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Affiliation(s)
- Silke S Heinzmann
- Helmholtz Zentrum München, Research Unit Analytical BioGeoChemistry , 85764 Neuherberg, Germany
| | - Elaine Holmes
- Biomolecular Medicine, Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London , South Kensington, London SW7 2AZ, U.K
| | - Sunil Kochhar
- Nestlé Research Center, Nestec, Vers-chez-les-Blancs, 1000 Lausanne 26, Switzerland
| | - Jeremy K Nicholson
- Biomolecular Medicine, Section of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London , South Kensington, London SW7 2AZ, U.K
| | - Philippe Schmitt-Kopplin
- Helmholtz Zentrum München, Research Unit Analytical BioGeoChemistry , 85764 Neuherberg, Germany
- Technische Universität München , Chair of Analytical Food Chemistry, 85354 Freising, Germany
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