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Discovery involved untargeted plasma metabolite profiling of 896 incident cases and 896 age-\/sex-\/race-matched controls (~300 pairs per race: Black, White, Asian) from the Southern Community Cohort Study (SCCS; baseline: 2002\u20132009) and the Shanghai Women\u2019s Health Study and Shanghai Men\u2019s Health Study (SWHS\/SMHS; baseline: 1996\u20132000 and 2002\u20132006). In-silico validation was conducted in the Atherosclerosis Risk in Communities Study (ARIC;\n                      <jats:italic>N<\/jats:italic>\n                      \u2009=\u20093,539; 663 cases; baseline: 1987\u20131989) and Multi-Ethnic Study of Atherosclerosis (MESA;\n                      <jats:italic>N<\/jats:italic>\n                      \u2009=\u20093,860; 446 cases; baseline: 2000\u20132002). Lastly, a quantitative assay was developed and applied to a new set of 864 cases and 864 age-\/sex-\/race-matched controls (~260\u2212340 pairs per race) from the SCCS and SWHS\/SMHS. Conditional logistic regression estimated odds ratios (ORs) of incident CHD per standard deviation (SD) metabolite increase in discovery and quantitative stages with a nested case-control design. Cox regression was used in ARIC and MESA with a cohort design. Similar covariates were adjusted across stages, including age, sex (if applicable), race (if applicable), education, income, smoking status, alcohol consumption, physical activity, diet quality, and body mass index (BMI). The mean (SD) time between enrollment and CHD diagnosis was 5.6 (3.8), 6.9 (4.4), 15.0 (7.4), and 8.0 (4.9) years in the SCCS, SWHS\/SMHS, ARIC, and MESA, respectively. The discovery stage identified 73 circulating microbiota-related metabolites associated with incident CHD (false discovery rate &lt;0.10). Sixty-one metabolites were available for in-silico validation, of which 24 showed a significant association (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05) in the same direction as in the discovery. The targeted assay quantified eight of the 24 metabolites, with five significantly associated with incident CHD: imidazole propionate, 3-hydroxy-2-ethylpropionate, 4-hydroxyphenylacetate,\n                      <jats:italic>trans-<\/jats:italic>\n                      4-hydroxyproline, and 3-hydroxybutyrate; OR per SD ranged from 1.18 to 1.27 after adjustment for sociodemographics, lifestyles, and BMI. The targeted assay measured eight other promising microbial metabolites, four of which were significant: trimethylamine N-oxide, phenylacetyl-L-glutamine, 4-hydroxyhippuric acid, and indolepropionate. Most associations were consistent across participant subgroups by demographics, lifestyles, metabolic disease history, family CHD history, and follow-up time, although some potential effect modifications were found by race, age, obesity status, and follow-up time. The main limitations of the study are the observational design and the inability to validate all significant metabolites due to differences in metabolomic assay coverage across the three stages.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We identified and validated circulating gut microbial metabolites associated with incident CHD across diverse populations. Our findings offer novel epidemiological evidence on the importance of gut microbial metabolism in CHD development and highlight specific metabolites to prioritize for mechanistic investigation, biomarker validation, and therapeutic development.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pmed.1004750","type":"journal-article","created":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T17:21:14Z","timestamp":1773768074000},"page":"e1004750","update-policy":"https:\/\/doi.org\/10.1371\/journal.pmed.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Circulating gut microbial metabolites and risk of coronary heart disease: A prospective multi-stage metabolomics study"],"prefix":"10.1371","volume":"23","author":[{"given":"Yulu","family":"Zheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jae 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