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

International Cannabis Consortium

Research output: Contribution to JournalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)107703
JournalDrug and Alcohol Dependence
DOIs
Publication statusAccepted/In press - 2020

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Genetic Loci
Genome-Wide Association Study
Genes
Quantitative Trait Loci
Gene expression
Databases
Blood
Cocaine-Related Disorders
Tissue
Gene Regulatory Networks
Gene Expression Regulation
Tobacco Products
Alcohol Drinking
Cocaine
Smoking
Genotype
Brain
Depression
Gene Expression
Alcohols

Bibliographical note

Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

Cite this

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title = "Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci",
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.",
author = "Marees, {Andries T} and Gamazon, {Eric R} and Zachary Gerring and Florence Vorspan and Josh Fingal and {van den Brink}, Wim and Smit, {Dirk J A} and Verweij, {Karin J H} and Kranzler, {Henry R} and Richard Sherva and Lindsay Farrer and Joel Gelernter and Derks, {Eske M} and {International Cannabis Consortium}",
note = "Copyright {\circledC} 2019 The Authors. Published by Elsevier B.V. All rights reserved.",
year = "2020",
doi = "10.1016/j.drugalcdep.2019.107703",
language = "English",
pages = "107703",
journal = "Drug and Alcohol Dependence",
issn = "0376-8716",
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Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci. / International Cannabis Consortium.

In: Drug and Alcohol Dependence, 2020, p. 107703.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci

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

AU - International Cannabis Consortium

N1 - Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

PY - 2020

Y1 - 2020

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.

U2 - 10.1016/j.drugalcdep.2019.107703

DO - 10.1016/j.drugalcdep.2019.107703

M3 - Article

SP - 107703

JO - Drug and Alcohol Dependence

JF - Drug and Alcohol Dependence

SN - 0376-8716

ER -