Work

A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer’s Disease

Year: 2022

Type: article

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.

Source: Cells

DOI: 10.3390/cells11142219

Authors: Yulin Dai, Peilin Jia, Zhongming Zhao, Assaf Gottlieb

Institution: The University of Texas Health Science Center at Houston

Language: English

Topic: Bioinformatics and Genomic Networks

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,303