Evidence map›Paper›PMID 26110981›Full record

ReviewAlcoholism, clinical and experimental research2015

Alcohol Dependence Genetics: Lessons Learned From Genome-Wide Association Studies (GWAS) and Post-GWAS Analyses.

Amy B Hart, Henry R Kranzler

Abstract readReview
In one paragraph

Review in Alcoholism, clinical and experimental research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

82 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Genome-wide meta-analysis of alcohol use disorder in East Asians.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022
    Pooled it
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  11. "General Addiction Liability" Revisited.Clinical psychological science : a journal of the Association for Psychological Science · 2025
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  20. Genetic and environmental etiology of drinking motives in college students.Alcoholism, clinical and experimental research · 2022
    Article

22 more citing papers are in PubMed but not listed here.

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

2 authors.

Amy B HartCenter for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Henry R KranzlerCenter for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.

Funding

T32 Translational Addiction Research Fellowship ProgramT32DA028874 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI Julie A Blendy, Anna Rose Childress · 2010 to 2026
$5.0M
2/2 Pharmacogenetic Treatment for AlcoholismR01AA021164 · NIAAA · UNIVERSITY OF PENNSYLVANIA · PI KRANZLER, HENRY RICHARD, PETTINATI, HELEN M · 2012 to 2016
$2.1M
NIAAA NIH HHS R01 AA021164NIDA NIH HHS T32 DA028874
6 · The paper itself

Abstract

backgroundAlcohol dependence (AD) is a complex psychiatric disorder and a significant public health problem. Twin and family-based studies have consistently estimated its heritability to be approximately 50%, and many studies have sought to identify specific genetic variants associated with susceptibility to AD. These studies have been primarily linkage or candidate gene based and have been mostly unsuccessful in identifying replicable risk loci. Genome-wide association studies (GWAS) have improved the detection of specific loci associated with complex traits, including AD. However, findings from GWAS explain only a small proportion of phenotypic variance, and alternative methods have been proposed to investigate the associations that do not meet strict genome-wide significance criteria.

methodsThis review summarizes all published AD GWAS and post-GWAS analyses that have sought to exploit GWAS data to identify AD-associated loci.

resultsFindings from AD GWAS have been largely inconsistent, with the exception of variants encoding the alcohol-metabolizing enzymes. Analyses of GWAS data that go beyond standard association testing have demonstrated the polygenic nature of AD and the large contribution of common variants to risk, nominating novel genes and pathways for AD susceptibility.

conclusionsFindings from AD GWAS and post-GWAS analyses have greatly increased our understanding of the genetic etiology of AD. However, it is clear that larger samples will be necessary to detect loci in addition to those that encode alcohol-metabolizing enzymes, which may only be possible through consortium-based efforts. Post-GWAS approaches to studying the genetic influences on AD are increasingly common and could greatly increase our knowledge of both the genetic architecture of AD and the specific genes and pathways that influence risk.

Indexed as

AlcoholismAnimalsGenetic LinkageGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideAlcohol DependenceGenome-Wide Association StudiesPathway AnalysisRisk Profile ScoringSNP Heritability

Identifiers

PMID26110981
PMCPMC4515198

What OpenQuestion holds

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Registered trials

None linked

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.