{"doi":"10.1093/cvr/cvad147","title":"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","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.","journal":"Cardiovascular Research","year":2023,"id":328088,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":24,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.926,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":343207,"name":"Taryn Alkis","orcid":null,"position":1,"is_corresponding":false},{"id":1049405,"name":"Yura Lee","orcid":"0000-0003-2048-3727","position":2,"is_corresponding":false},{"id":553498,"name":"Domagoj Kifer","orcid":"0000-0002-7956-3484","position":3,"is_corresponding":false},{"id":230959,"name":"Jie Hu","orcid":"0000-0001-8282-4895","position":4,"is_corresponding":false},{"id":305422,"name":"Rachel A. Murphy","orcid":"0000-0003-4383-5641","position":5,"is_corresponding":false},{"id":1049406,"name":"Zhe Huang","orcid":"0000-0002-4441-0015","position":6,"is_corresponding":false},{"id":11475,"name":"Rui Wang‐Sattler","orcid":"0000-0002-8794-8229","position":7,"is_corresponding":false},{"id":1050052,"name":"Gabi Kastenmüler","orcid":null,"position":8,"is_corresponding":false},{"id":6221,"name":"Birgit Linkohr","orcid":"0000-0002-3387-5685","position":9,"is_corresponding":false},{"id":554821,"name":"Clara Barrios","orcid":null,"position":10,"is_corresponding":false},{"id":1049407,"name":"Marta Crespo","orcid":"0000-0001-6992-6379","position":11,"is_corresponding":false},{"id":2351,"name":"Christian Gieger","orcid":"0000-0001-6986-9554","position":12,"is_corresponding":false},{"id":2343,"name":"Annette Peters","orcid":"0000-0001-6645-0985","position":13,"is_corresponding":false},{"id":21925,"name":"Jackie F. Price","orcid":"0000-0003-3251-3970","position":14,"is_corresponding":false},{"id":17007,"name":"Kathryn Rexrode","orcid":"0000-0003-3387-8429","position":15,"is_corresponding":false},{"id":51217,"name":"Bing Yu","orcid":"0000-0003-4818-1077","position":16,"is_corresponding":false},{"id":21805,"name":"Cristina Menni","orcid":"0000-0001-9790-0571","position":17,"is_corresponding":false},{"id":652253,"name":"Ana Nogal","orcid":"0000-0002-0973-4313","position":0,"is_corresponding":true}],"reference_count":59,"raw_metadata":null,"created_at":"2026-07-19T01:08:52.196069Z","pmid":"37706562","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}