An integrative systems-based analysis of substance use: eQTL-informed gene-based tests, gene networks, and biological mechanisms.

ABSTRACT: Genome-wide association studies have identified multiple genetic risk factors underlying susceptibility to substance use, however, the functional genes and biological mechanisms remain poorly understood. The discovery and characterization of risk genes can be facilitated by the integration of genome-wide association data and gene expression data across biologically relevant tissues and/or cell types to identify genes whose expression is altered by DNA sequence variation (expression quantitative trait loci; eQTLs). The integration of gene expression data can be extended to the study of genetic co-expression, under the biologically valid assumption that genes form co-expression networks to influence the manifestation of a disease or trait. Here, we integrate genome-wide association data with

SUBMITTER: Gerring ZF 

PROVIDER: S-EPMC8137546 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature