Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
31785998
TITLE
Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci.
ABSTRACT
BACKGROUND NlmCategory: 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 NlmCategory: METHODS
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. 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 NlmCategory: RESULTS
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. 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. 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 NlmCategory: CONCLUSIONS
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. 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. 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. Annotating genes based on transcriptomic regulation improves the identification and functional characterization of candidate loci and genes for substance use traits.
Copyright 2019 The Authors. Published by Elsevier B.V. All rights reserved.
DATE PUBLISHED
2020 Jan 01
HISTORY
PUBSTATUS PUBSTATUSDATE
received 2019/01/12
revised 2019/10/21
accepted 2019/10/22
pubmed 2019/12/02 06:00
medline 2019/12/02 06:00
entrez 2019/12/02 06:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Marees AT Marees Andries T AT Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands; QIMR Berghofer, Translational Neurogenomics group, Brisbane, Australia; Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. Electronic address: andriestm@hotmail.com.
Gamazon ER Gamazon Eric R ER Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States; Clare Hall, University of Cambridge, Cambridge, CB3 9AL, United Kingdom.
Gerring Z Gerring Zachary Z QIMR Berghofer, Translational Neurogenomics group, Brisbane, Australia.
Vorspan F Vorspan Florence F Assistance Publique - Hôpitaux de Paris, Hôpital Fernand Widal, Département de Psychiatrie et de Médecine Addictologique, 200 rue du Faubourg Saint Denis, 75010 Paris, France; Inserm umr-s 1144, Université Paris Descartes, Université Paris Diderot, 4 avenue de l'Observatoire, 75006 Paris, France.
Fingal J Fingal Josh J Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands.
van den Brink W van den Brink Wim W Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands.
Smit DJA Smit Dirk J A DJA Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands.
Verweij KJH Verweij Karin J H KJH Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands; Behavioural Science Institute, Radboud University, Montessorilaan 3, 6525 HR Nijmegen, the Netherlands.
Kranzler HR Kranzler Henry R HR Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine and Crescenz VAMC, Philadelphia, PA 19104, United States.
Sherva R Sherva Richard R Section of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston, MA, United States.
Farrer L Farrer Lindsay L Section of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston, MA, United States.
International Cannabis Consortium
Gelernter J Gelernter Joel J Department of Psychiatry, Genetics, and Neuroscience, Yale University School of Medicine, New Haven, CT, United States.
Derks EM Derks Eske M EM Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands; QIMR Berghofer, Translational Neurogenomics group, Brisbane, Australia.
INVESTIGATORS
JOURNAL
VOLUME: 206
ISSUE:
TITLE: Drug and alcohol dependence
ISOABBREVIATION: Drug Alcohol Depend
YEAR: 2020
MONTH: Jan
DAY: 01
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Internet
ISSN: 1879-0046
ISSNTYPE: Electronic
MEDLINE JOURNAL
MEDLINETA: Drug Alcohol Depend
COUNTRY: Ireland
ISSNLINKING: 0376-8716
NLMUNIQUEID: 7513587
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
COMMENTS AND CORRECTIONS
GRANTS
GRANTID AGENCY COUNTRY
R35 HG010718 NHGRI NIH HHS United States
GENERAL NOTE
KEYWORDS
KEYWORD
Addiction
Functional annotation
GTEx
S-PrediXcan
Substance use
eQTLs
MESH HEADINGS
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's