Defining type 2 diabetes polygenic risk scores through colocalization and network-based clustering of metabolic trait genetic associations.

ABSTRACT:

Background

Type 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations.

Methods

We applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21

SUBMITTER: Ghatan S 

PROVIDER: S-EPMC10777532 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature