Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci. (1st January 2020)

• Record Type: Journal Article
• Authors: Marees, Andries T.; Gamazon, Eric R.; Gerring, Zachary; Vorspan, Florence; Fingal, Josh; van den Brink, Wim; Smit, Dirk J.A.; Verweij, Karin J.H.; Kranzler, Henry R.; Sherva, Richard; Farrer, Lindsay; Gelernter, Joel; Derks, Eske M.
• Is Part Of: Drug and alcohol dependence. Volume 206(2020)
• Publication Date: 2020-01-01
• Subjects: Addiction -- eQTLs -- Functional annotation -- GTEx -- Substance use -- S-PrediXcan; Drug abuse -- Periodicals; Alcoholism -- Periodicals; 616.86
• DOI: 10.1016/j.drugalcdep.2019.107703
• Languages: English
• ISSNs: 0376-8716

Abstract

Highlights: Gene-expression based approaches can identify many novel candidate loci and genes. Transcriptomic annotation improves the functional characterization of genetic loci. Variants often exert their effect through a gene other than their proximal gene. Abstract: Background: Little is known about the functional mechanisms through which genetic loci associated with substance use traits ascertain their effect. This study aims to identify and functionally annotate loci associated with substance use traits based on their role in genetic regulation of gene expression. Methods: We evaluated expression Quantitative Trait Loci (eQTLs) from 13 brain regions and whole blood of the Genotype-Tissue Expression (GTEx) database, and from whole blood of the Depression Genes and Networks (DGN) database. The role of single eQTLs was examined for six substance use traits: alcohol consumption (N = 537, 349), cigarettes per day (CPD; N = 263, 954), former vs. current smoker (N = 312, 821), age of smoking initiation (N = 262, 990), ever smoker (N = 632, 802), and cocaine dependence (N = 4, 769). Subsequently, we conducted a gene level analysis of gene expression on these substance use traits using S-PrediXcan. Results: Using an FDR-adjusted p-value <0.05 we found 2, 976 novel candidate genetic loci for substance use traits, and identified genes and tissues through which these loci potentially exert their effects. Using S-PrediXcan, we identified significantly associated genes for all substance traits. Discussion: Annotating genes based on transcriptomic regulation improves the identification and functional characterization of candidate loci and genes for substance use traits.