{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T21:54:36Z","timestamp":1769205276715,"version":"3.49.0"},"reference-count":40,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T00:00:00Z","timestamp":1683072000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cardiovasc. Med."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>The intermediate metabolites associated with the development of atherosclerotic cardiovascular disease (ASCVD) remain largely unknown. Thus, we conducted a large panel of metabolomics profiling to identify the new candidate metabolites that were associated with 10-year ASCVD risk.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Thirty acylcarnitines and twenty amino acids were measured in the fasting plasma of 1,102 randomly selected individuals using a targeted FIA-MS\/MS approach. The 10-year ASCVD risk score was calculated based on 2013 ACC\/AHA guidelines. Accordingly, the subjects were stratified into four groups: low-risk (<jats:italic>n<\/jats:italic>\u2009=\u2009620), borderline-risk (<jats:italic>n<\/jats:italic>\u2009=\u2009110), intermediate-risk (<jats:italic>n<\/jats:italic>\u2009=\u2009225), and high-risk (<jats:italic>n<\/jats:italic>\u2009=\u2009147). 10 factors comprising collinear metabolites were extracted from principal component analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>C<jats:sub>4<\/jats:sub>DC, C<jats:sub>8:1<\/jats:sub>, C<jats:sub>16<\/jats:sub>OH, citrulline, histidine, alanine, threonine, glycine, glutamine, tryptophan, phenylalanine, glutamic acid, arginine, and aspartic acid were significantly associated with the 10-year ASCVD risk score (<jats:italic>p<\/jats:italic>-values\u2009\u2264\u20090.044). The high-risk group had higher odds of factor 1 (12 long-chain acylcarnitines, OR\u2009=\u20091.103), factor 2 (5 medium-chain acylcarnitines, OR\u2009=\u20091.063), factor 3 (methionine, leucine, valine, tryptophan, tyrosine, phenylalanine, OR\u2009=\u20091.074), factor 5 (6 short-chain acylcarnitines, OR\u2009=\u20091.205), factor 6 (5 short-chain acylcarnitines, OR\u2009=\u20091.229), factor 7 (alanine, proline, OR\u2009=\u20091.343), factor 8 (C<jats:sub>18:2<\/jats:sub>OH, glutamic acid, aspartic acid, OR\u2009=\u20091.188), and factor 10 (ornithine, citrulline, OR\u2009=\u20091.570) compared to the low-risk ones; the odds of factor 9 (glycine, serine, threonine, OR\u2009=\u20090.741), however, were lower in the high-risk group. \u201cD-glutamine and D-glutamate metabolism\u201d, \u201cphenylalanine, tyrosine, and tryptophan biosynthesis\u201d, and \u201cvaline, leucine, and isoleucine biosynthesis\u201d were metabolic pathways having the highest association with borderline\/intermediate\/high ASCVD events, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Abundant metabolites were found to be associated with ASCVD events in this study. Utilization of this metabolic panel could be a promising strategy for early detection and prevention of ASCVD events.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fcvm.2023.1161761","type":"journal-article","created":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T05:11:31Z","timestamp":1683090691000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Metabolomics profile and 10-year atherosclerotic cardiovascular disease (ASCVD) risk 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