Improved cardiovascular risk prediction using targeted plasma proteomics in primary prevention.

ABSTRACT:

Aims

In the era of personalized medicine, it is of utmost importance to be able to identify subjects at the highest cardiovascular (CV) risk. To date, single biomarkers have failed to markedly improve the estimation of CV risk. Using novel technology, simultaneous assessment of large numbers of biomarkers may hold promise to improve prediction. In the present study, we compared a protein-based risk model with a model using traditional risk factors in predicting CV events in the primary prevention setting of the European Prospective Investigation (EPIC)-Norfolk study, followed by validation in the Progressione della Lesione Intimale Carotidea (PLIC) cohort.

Methods and results

Using the proximity extension assay, 368 proteins were measured in a nested case-control sample of 8

SUBMITTER: Hoogeveen RM 

PROVIDER: S-EPMC7672529 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature