Faculty, Staff and Student Publications

Publication Date

7-16-2022

Journal

Cells

Abstract

BACKGROUND: Genome-wide association studies have successfully identified variants associated with multiple conditions. However, generalizing discoveries across diverse populations remains challenging due to large variations in genetic composition. Methods that perform gene expression imputation have attempted to address the transferability of gene discoveries across populations, but with limited success.

METHODS: Here, we introduce a pipeline that combines gene expression imputation with gene module discovery, including a dense gene module search and a gene set variation analysis, to address the transferability issue. Our method feeds association probabilities of imputed gene expression with a selected phenotype into tissue-specific gene-module discovery over protein interaction networks to create higher-level gene modules.

RESULTS: We demonstrate our method's utility in three case-control studies of Alzheimer's disease (AD) for three different race/ethnic populations (Whites, African descent and Hispanics). We discovered 182 AD-associated genes from gene modules shared between these populations, highlighting new gene modules associated with AD.

CONCLUSIONS: Our innovative framework has the potential to identify robust discoveries across populations based on gene modules, as demonstrated in AD.

Keywords

Alzheimer Disease, Gene Regulatory Networks, Genome-Wide Association Study, Genotype, Humans, Phenotype

DOI

10.3390/cells11142219

PMID

35883662

PMCID

PMC9319087

PubMedCentral® Posted Date

7-16-2022

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes

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