TY - JOUR
T1 - Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci
AU - International Cannabis Consortium
AU - Marees, Andries T
AU - Gamazon, Eric R
AU - Gerring, Zachary
AU - Vorspan, Florence
AU - Fingal, Josh
AU - van den Brink, Wim
AU - Smit, Dirk J A
AU - Verweij, Karin J H
AU - Kranzler, Henry R
AU - Sherva, Richard
AU - Farrer, Lindsay
AU - Gelernter, Joel
AU - Derks, Eske M
N1 - Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - 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.
AB - 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.
KW - Addiction
KW - Functional annotation
KW - GTEx
KW - S-PrediXcan
KW - Substance use
KW - eQTLs
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U2 - https://doi.org/10.1016/j.drugalcdep.2019.107703
DO - https://doi.org/10.1016/j.drugalcdep.2019.107703
M3 - Article
C2 - 31785998
SN - 0376-8716
VL - 206
SP - 107703
JO - Drug and alcohol dependence
JF - Drug and alcohol dependence
M1 - 107703
ER -
