Evidence map›Paper›PMID 31785998›Full record

ArticleDrug and alcohol dependence2020

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

Andries T Marees, Eric R Gamazon, Zachary Gerring, Florence Vorspan, Josh Fingal, Wim van den Brink, Dirk J A Smit, Karin J H Verweij, Henry R Kranzler, Richard Sherva and 4 more

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in Drug and alcohol dependence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03170362 (PRIME Care), which is not on this map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03170362 nacompletednot on this map

PRIME Care (PRecision Medicine In MEntal Health Care)

TypeinterventionalSponsorVA Office of Research and DevelopmentRan2017 to 2022Enrolled1,944ConditionsMajor DepressionArmsPharmacogenetic Test
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
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  5. Integrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022
    Article
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  11. Review
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  14. An integrative systems-based analysis of substance use: eQTL-informed gene-based tests, gene networks, and biological mechanisms.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 8 institutions in 5 countries.

Andries T MareesDepartment 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.
Eric R GamazonVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States; Clare Hall, University of Cambridge, Cambridge, CB3 9AL, United Kingdom.
Zachary GerringQIMR Berghofer, Translational Neurogenomics group, Brisbane, Australia.
Florence VorspanAssistance 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.
Josh FingalDepartment of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands.
Wim van den BrinkDepartment of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands.
Dirk J A SmitDepartment of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands.
Karin J H VerweijDepartment 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.
Henry R KranzlerCenter for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine and Crescenz VAMC, Philadelphia, PA 19104, United States.
Richard ShervaSection of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston, MA, United States.
Lindsay FarrerSection of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston, MA, United States.
International Cannabis Consortium
Joel GelernterDepartment of Psychiatry, Genetics, and Neuroscience, Yale University School of Medicine, New Haven, CT, United States.
Eske M DerksDepartment of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands; QIMR Berghofer, Translational Neurogenomics group, Brisbane, Australia.
Amsterdam Neuroscience · NLBoston University · USQIMR Berghofer Medical Research Institute · AUAmsterdam University Medical Centers · NLUniversité Paris Cité · FRUniversity of Pennsylvania · USVanderbilt University Medical Center · USYale University · US

Funding

Functional Genomics: A Phenome-wide SurveyR35HG010718 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GAMAZON, ERIC R · 2019 to 2023
$2.2M
Medical Research Council MC_UU_00011/7NHGRI NIH HHS R35 HG010718
6 · The paper itself

Abstract

backgroundLittle 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.

methodsWe 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.

resultsUsing 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.

Indexed as

BloodBrainDrug UsersGene Expression ProfilingGene Expression RegulationGenetic Predisposition to DiseaseHumansMeta-Analysis as TopicPhenotypeQuantitative Trait LociSubstance-Related DisordersTranscriptomeAddictioneQTLsFunctional annotationGTExS-PrediXcanSubstance use

Identifiers

PMID31785998
PMCPMC9159918
OpenAlexW2986514014

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.