Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci

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Int Cannabis Consortium , Marees , A T , Gamazon , E R , Gerring , Z , Loukola , A , Korhonen , T , Qaiser , B & Kaprio , J 2020 , ' Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci ' , Drug and Alcohol Dependence , vol. 206 , 107703 . https://doi.org/10.1016/j.drugalcdep.2019.107703

Title: Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci
Author: Int Cannabis Consortium; Marees, Andries T.; Gamazon, Eric R.; Gerring, Zachary; Loukola, Anu; Korhonen, Tellervo; Qaiser, Beenish; Kaprio, Jaakko
Contributor: University of Helsinki, HUSLAB
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Department of Public Health
University of Helsinki, Institute for Molecular Medicine Finland
Date: 2020-01-01
Language: eng
Number of pages: 9
Belongs to series: Drug and Alcohol Dependence
ISSN: 0376-8716
URI: http://hdl.handle.net/10138/313377
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.
Subject: Addiction
eQTLs
Functional annotation
GTEx
Substance use
S-PrediXcan
ANTERIOR CINGULATE CORTEX
FAMILY-HISTORY
ALCOHOL DEPENDENCE
NUCLEUS-ACCUMBENS
EXPRESSION
COCAINE
TRANSCRIPTION
ASSOCIATION
17Q21.31
3124 Neurology and psychiatry
3142 Public health care science, environmental and occupational health
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