Development of risk prediction models for depression combining genetic and early life risk factors.

ABSTRACT:

Background

Both genetic and early life risk factors play important roles in the pathogenesis and progression of adult depression. However, the interplay between these risk factors and their added value to risk prediction models have not been fully elucidated.

Methods

Leveraging a meta-analysis of major depressive disorder genome-wide association studies (N = 45,591 cases and 97,674 controls), we developed and optimized a polygenic risk score for depression using LDpred in a model selection dataset from the UK Biobank (N = 130,092 European ancestry individuals). In a UK Biobank test dataset (N = 278,730 European ancestry individuals), we tested whether the polygenic risk score and early life risk factors were associated with each other and compared their

SUBMITTER: Lu T 

PROVIDER: S-EPMC10390723 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature