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Nogal A, Alkis T, Lee Y, Kifer D, Hu J, Murphy RA, Huang Z, Wang-Sattler R, Kastenmüler G, Linkohr B, Barrios C, Crespo M, Gieger C, Peters A, Price J, Rexrode KM, Yu B, Menni C. Predictive metabolites for incident myocardial infarction: a two-step meta-analysis of individual patient data from six cohorts comprising 7897 individuals from the COnsortium of METabolomics Studies. Cardiovasc Res 2023; 119:2743-2754. [PMID: 37706562 PMCID: PMC10757581 DOI: 10.1093/cvr/cvad147] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/28/2023] [Accepted: 07/18/2023] [Indexed: 09/15/2023] Open
Abstract
AIMS Myocardial infarction (MI) is a major cause of death and disability worldwide. Most metabolomics studies investigating metabolites predicting MI are limited by the participant number and/or the demographic diversity. We sought to identify biomarkers of incident MI in the COnsortium of METabolomics Studies. METHODS AND RESULTS We included 7897 individuals aged on average 66 years from six intercontinental cohorts with blood metabolomic profiling (n = 1428 metabolites, of which 168 were present in at least three cohorts with over 80% prevalence) and MI information (1373 cases). We performed a two-stage individual patient data meta-analysis. We first assessed the associations between circulating metabolites and incident MI for each cohort adjusting for traditional risk factors and then performed a fixed effect inverse variance meta-analysis to pull the results together. Finally, we conducted a pathway enrichment analysis to identify potential pathways linked to MI. On meta-analysis, 56 metabolites including 21 lipids and 17 amino acids were associated with incident MI after adjusting for multiple testing (false discovery rate < 0.05), and 10 were novel. The largest increased risk was observed for the carbohydrate mannitol/sorbitol {hazard ratio [HR] [95% confidence interval (CI)] = 1.40 [1.26-1.56], P < 0.001}, whereas the largest decrease in risk was found for glutamine [HR (95% CI) = 0.74 (0.67-0.82), P < 0.001]. Moreover, the identified metabolites were significantly enriched (corrected P < 0.05) in pathways previously linked with cardiovascular diseases, including aminoacyl-tRNA biosynthesis. CONCLUSIONS In the most comprehensive metabolomic study of incident MI to date, 10 novel metabolites were associated with MI. Metabolite profiles might help to identify high-risk individuals before disease onset. Further research is needed to fully understand the mechanisms of action and elaborate pathway findings.
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Affiliation(s)
- Ana Nogal
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, Westminster Bridge Road, SE1 7EH London, UK
| | - Taryn Alkis
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Yura Lee
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Jie Hu
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Rachel A Murphy
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | - Zhe Huang
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Gabi Kastenmüler
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Birgit Linkohr
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Clara Barrios
- Department of Nephrology, Hospital del Mar, Institut Hospital del Mar d´Investigacions Mediques, Barcelona, Spain
| | - Marta Crespo
- Department of Nephrology, Hospital del Mar, Institut Hospital del Mar d´Investigacions Mediques, Barcelona, Spain
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jackie Price
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Kathryn M Rexrode
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Cristina Menni
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, Westminster Bridge Road, SE1 7EH London, UK
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Nogal A, Tettamanzi F, Dong Q, Louca P, Visconti A, Christiansen C, Breuninger T, Linseisen J, Grallert H, Wawro N, Asnicar F, Wong K, Baleanu AF, Michelotti GA, Segata N, Falchi M, Peters A, Franks PW, Bagnardi V, Spector TD, Bell JT, Gieger C, Valdes AM, Menni C. A Fecal Metabolite Signature of Impaired Fasting Glucose: Results From Two Independent Population-Based Cohorts. Diabetes 2023; 72:1870-1880. [PMID: 37699401 PMCID: PMC10658071 DOI: 10.2337/db23-0170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 08/30/2023] [Indexed: 09/14/2023]
Abstract
Prediabetes is a metabolic condition associated with gut microbiome composition, although mechanisms remain elusive. We searched for fecal metabolites, a readout of gut microbiome function, associated with impaired fasting glucose (IFG) in 142 individuals with IFG and 1,105 healthy individuals from the UK Adult Twin Registry (TwinsUK). We used the Cooperative Health Research in the Region of Augsburg (KORA) cohort (318 IFG individuals, 689 healthy individuals) to replicate our findings. We linearly combined eight IFG-positively associated metabolites (1-methylxantine, nicotinate, glucuronate, uridine, cholesterol, serine, caffeine, and protoporphyrin IX) into an IFG-metabolite score, which was significantly associated with higher odds ratios (ORs) for IFG (TwinsUK: OR 3.9 [95% CI 3.02-5.02], P < 0.0001, KORA: OR 1.3 [95% CI 1.16-1.52], P < 0.0001) and incident type 2 diabetes (T2D; TwinsUK: hazard ratio 4 [95% CI 1.97-8], P = 0.0002). Although these are host-produced metabolites, we found that the gut microbiome is strongly associated with their fecal levels (area under the curve >70%). Abundances of Faecalibacillus intestinalis, Dorea formicigenerans, Ruminococcus torques, and Dorea sp. AF24-7LB were positively associated with IFG, and such associations were partially mediated by 1-methylxanthine and nicotinate (variance accounted for mean 14.4% [SD 5.1], P < 0.05). Our results suggest that the gut microbiome is linked to prediabetes not only via the production of microbial metabolites but also by affecting intestinal absorption/excretion of host-produced metabolites and xenobiotics, which are correlated with the risk of IFG. Fecal metabolites enable modeling of another mechanism of gut microbiome effect on prediabetes and T2D onset. ARTICLE HIGHLIGHTS Prediabetes is a metabolic condition associated with gut microbiome composition, although mechanisms remain elusive. We investigated whether there is a fecal metabolite signature of impaired fasting glucose (IFG) and the possible underlying mechanisms of action. We identified a fecal metabolite signature of IFG associated with prevalent IFG in two independent cohorts and incident type 2 diabetes in a subanalysis. Although the signature consists of metabolites of nonmicrobial origin, it is strongly correlated with gut microbiome composition. Fecal metabolites enable modeling of another mechanism of gut microbiome effect on prediabetes by affecting intestinal absorption or excretion of host compounds and xenobiotics.
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Affiliation(s)
- Ana Nogal
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Francesca Tettamanzi
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
- Humanitas Clinical and Research Centre, IRCCS, Rozzano (Milan), Italy
| | - Qiuling Dong
- Institute of Epidemiology, Helmholtz Zentrum München, Research Unit of Molecular Epidemiology, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Panayiotis Louca
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Alessia Visconti
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Colette Christiansen
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
- School of Mathematics and Statistics, The Open University, Milton Keynes, U.K
| | - Taylor Breuninger
- Epidemiology, University Hospital Augsburg, University of Augsburg, Augsburg, Germany
| | - Jakob Linseisen
- Epidemiology, University Hospital Augsburg, University of Augsburg, Augsburg, Germany
- ZIEL-Institute for Food & Health, Technische Universität München, Freising, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology, Medical Faculty, Ludwig-Maximilian University Munich, Munich, Germany
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München, Research Unit of Molecular Epidemiology, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Nina Wawro
- Epidemiology, University Hospital Augsburg, University of Augsburg, Augsburg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Francesco Asnicar
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | | | - Andrei-Florin Baleanu
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | | | - Nicola Segata
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Mario Falchi
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Annette Peters
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Munich Heart Alliance, German Center for Cardiovascular Research (DZHK e.V., Partner-Site Munich), Munich, Germany
| | - Paul W. Franks
- Lund University Diabetes Center, Lund University, Malmö, Sweden
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Vincenzo Bagnardi
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, Milan, Italy
| | - Tim D. Spector
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Jordana T. Bell
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, Research Unit of Molecular Epidemiology, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Ana M. Valdes
- Academic Rheumatology Clinical Sciences Building, Nottingham City Hospital, University of Nottingham, U.K
| | - Cristina Menni
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
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