1
|
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.
Collapse
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
| |
Collapse
|