Adjusting for principal components can induce collider bias in genome-wide association studies.

ABSTRACT: Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women'

SUBMITTER: Grinde KE 

PROVIDER: S-EPMC11684764 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature