Machine learning of plasma metabolome identifies biomarker panels for metabolic syndrome: findings from the China Suboptimal Health Cohort

• DOI: 10.1186/s12933-022-01716-0
• Publication Date: 2022-12-23T17:19:03Z
• Authors: Hao Wang; Youxin Wang; Xingang Li; Xuan Deng; Yuanyuan Kong; Wei Wang; Yong Zhou
• Keywords: Metabolome; Angiology; Biomarker Discovery

Metabolic syndrome (MetS) has been proposed as a clinically identifiable high-risk state for the prediction and prevention of cardiovascular diseases type 2 diabetes mellitus. As promising "omics" technology, metabolomics provides an innovative strategy to gain deeper understanding pathophysiology MetS. The study aimed systematically investigate metabolic alterations in MetS identify biomarker panels identification using machine learning methods.