Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes.

ABSTRACT:

Aims/hypothesis

Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes.

Methods

We combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multivariable-adjusted Cox regression was used in a discovery/replication design to identify biomarkers for incident MACE. We used gradient-boosted machine learning and lasso regularised Cox regression in a random 75% training subsample to assess whether adding proteins to risk factors included in the Swe

SUBMITTER: Nowak C 

PROVIDER: S-EPMC6061158 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature