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

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

Abstract Background Metabolic syndrome (MetS) has been proposed as a clinically identifiable high-risk state for the prediction and prevention of cardiovascular diseases and type 2 diabetes mellitus. As a promising “omics” technology, metabolomics provides an innovative strategy to gain a deeper und...

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Bibliographic Details
Main Authors: Hao Wang, Youxin Wang, Xingang Li, Xuan Deng, Yuanyuan Kong, Wei Wang, Yong Zhou
Format: Article
Language:English
Published: BMC 2022-12-01
Series:Cardiovascular Diabetology
Subjects:
Metabolic syndrome
Machine learning
Metabolomics
Biomarkers
Diagnostic models
Amino acid metabolism
Online Access:https://doi.org/10.1186/s12933-022-01716-0

Internet

https://doi.org/10.1186/s12933-022-01716-0

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