Proteomics and lipidomics in atherosclerotic cardiovascular disease risk prediction.

ABSTRACT: Given the limited accuracy of clinically used risk scores such as the Systematic COronary Risk Evaluation 2 system and the Second Manifestations of ARTerial disease 2 risk scores, novel risk algorithms determining an individual's susceptibility of future incident or recurrent atherosclerotic cardiovascular disease (ASCVD) risk are urgently needed. Due to major improvements in assay techniques, multimarker proteomic and lipidomic panels hold the promise to be reliably assessed in a high-throughput routine. Novel machine learning-based approaches have facilitated the use of this high-dimensional data resulting from these analyses for ASCVD risk prediction. More than a dozen of large-scale retrospective studies using different sets of biomarkers and different statistical methods have consiste

SUBMITTER: Nurmohamed NS 

PROVIDER: S-EPMC10163980 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature