{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["He M"],"funding":["Jiangnan University Project of Jiangsu Provincial Center of Technology Innovation for Future Food","National Natural Science Foundation of China","Natural Science Foundation of Jiangsu Province","Postdoctoral Fellowship Program of CPSF"],"pagination":["e70451"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12371206"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(8)"],"pubmed_abstract":["Coronary atherosclerosis (CA) is a leading cause of cardiovascular diseases with the high morbidity and mortality; however, the current diagnostic methods, primarily based on symptoms, signs, lab examination and imaging, are often inadequate for detecting subclinical or early-stage CA, costly, and inaccessible in many cases. The objective of this study was to discover sensitive and specific biomarkers for the diagnosis of CA severity. We enrolled 443 participants, including CA patients and healthy controls, from three independent cohorts: discovery, testing, and blinded validation. Multi-omics data integration during the discovery phase identified key features of atherosclerotic progression and potential biomarkers. Biomarker panels were refined using random forest models in the testing co"],"journal":["Clinical and translational medicine"],"pubmed_title":["Multi-omics analysis revealed biomarkers for coronary atherosclerosis: Occurrence and development."],"pmcid":["PMC12371206"],"funding_grant_id":["BK20231145","GZC20230985","82370342","BM2020023"],"pubmed_authors":["Liu Y","Wang RX","He Y","Zhang Y","Wang D","He M","Gao Y","Xu YJ","Liu A","Shi J","Zhao X"],"additional_accession":[]},"is_claimable":false,"name":"Multi-omics analysis revealed biomarkers for coronary atherosclerosis: Occurrence and development.","description":"Coronary atherosclerosis (CA) is a leading cause of cardiovascular diseases with the high morbidity and mortality; however, the current diagnostic methods, primarily based on symptoms, signs, lab examination and imaging, are often inadequate for detecting subclinical or early-stage CA, costly, and inaccessible in many cases. The objective of this study was to discover sensitive and specific biomarkers for the diagnosis of CA severity. We enrolled 443 participants, including CA patients and healthy controls, from three independent cohorts: discovery, testing, and blinded validation. Multi-omics data integration during the discovery phase identified key features of atherosclerotic progression and potential biomarkers. Biomarker panels were refined using random forest models in the testing co","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Aug","modification":"2026-05-08T06:48:34.628Z","creation":"2026-04-07T23:31:04.932Z"},"accession":"S-EPMC12371206","cross_references":{"pubmed":["40842288"],"doi":["10.1002/ctm2.70451"]}}