Evidence map›Paper›PMID 23362995›Full record

ArticleAddiction biology2014

Using genetic information from candidate gene and genome-wide association studies in risk prediction for alcohol dependence.

Jia Yan, Fazil Aliev, Bradley T Webb, Kenneth S Kendler, Vernell S Williamson, Howard J Edenberg, Arpana Agrawal, Mark Z Kos, Laura Almasy, John I Nurnberger and 8 more

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in Addiction biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
6.6field-weighted citation impact, top 3% 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.

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

33 citing papers in PubMed, 52 citations in OpenAlex.

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  20. Polygenic risk for externalizing disorders: Gene-by-development and gene-by-environment effects in adolescents and young adults.Clinical psychological science : a journal of the Association for Psychological Science · 2015
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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

18 authors at 9 institutions in 1 country.

Jia YanVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
Fazil Aliev
Bradley T Webb
Kenneth S Kendler
Vernell S Williamson
Howard J Edenberg
Arpana Agrawal
Mark Z Kos
Laura Almasy
John I Nurnberger
Marc A Schuckit
John R Kramer
John P Rice
Samuel Kuperman
Alison M Goate
Jay A Tischfield
Bernice Porjesz
Danielle M Dick
Virginia Commonwealth University · USWashington University in St. Louis · USTexas Biomedical Research Institute · USUniversity of Iowa · USEnvironmental and Occupational Health Sciences Institute · USIndiana University – Purdue University Indianapolis · USIndiana University School of MedicineState University of New York · USUniversity of California, San Diego · US

Funding

Subject CollectionU10AA008401 · NIAAA · SUNY DOWNSTATE MEDICAL CENTER · PI JESSICA E SALVATORE · 1989 to 2026
$162.7M
JH/CIDR Genotyping for Genome-Wide Association StudiesU01HG004438 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI VALLE, DAVID · 2007 to 2011
$24.2M
The Collaborative Genetic Study of Nicotine DependenceP01CA089392 · NCI · WASHINGTON UNIVERSITY · PI RICE, JOHN P · 2001 to 2012
$17.3M
FAMILY STUDY OF COCAINE DEPENDENCER01DA013423 · NIDA · WASHINGTON UNIVERSITY · PI BIERUT, LAURA JEAN · 2000 to 2004
$2.2M
Twin, molecular, and developmental approaches to understanding alcohol misuseK02AA018755 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI DICK, DANIELLE M · 2010 to 2019
$1.3M
Case Control Candidate Gene Study of AddictionR01DA019963 · NIDA · WASHINGTON UNIVERSITY · PI BIERUT, LAURA J. · 2007 to 2009
$1.2M
Study of Addiction: Genetics and EnvironmentU01HG004422 · NHGRI · WASHINGTON UNIVERSITY · PI BIERUT, LAURA J. · 2007 to 2010
$1.2M
NCI NIH HHS P01 CA089392NHGRI NIH HHS HHSN268200782096CNHGRI NIH HHS U01 HG004422NHGRI NIH HHS U01 HG004438NHGRI NIH HHS U01HG004438NIAAA NIH HHS K02 AA018755NIAAA NIH HHS K02AA018755NIAAA NIH HHS U10 AA008401NIAAA NIH HHS U10AA008401NIDA NIH HHS R01 DA013423NIDA NIH HHS R01 DA019963
6 · The paper itself

Abstract

Family-based and genome-wide association studies (GWAS) of alcohol dependence (AD) have reported numerous associated variants. The clinical validity of these variants for predicting AD compared with family history information has not been reported. Using the Collaborative Study on the Genetics of Alcoholism (COGA) and the Study of Addiction: Genes and Environment (SAGE) GWAS samples, we examined the aggregate impact of multiple single nucleotide polymorphisms (SNPs) on risk prediction. We created genetic sum scores by adding risk alleles associated in discovery samples, and then tested the scores for their ability to discriminate between cases and controls in validation samples. Genetic sum scores were assessed separately for SNPs associated with AD in candidate gene studies and SNPs from GWAS analyses that met varying P-value thresholds. Candidate gene sum scores did not exhibit significant predictive accuracy. Family history was a better classifier of case-control status, with a significant area under the receiver operating characteristic curve (AUC) of 0.686 in COGA and 0.614 in SAGE. SNPs that met less stringent P-value thresholds of 0.01-0.50 in GWAS analyses yielded significant AUC estimates, ranging from mean estimates of 0.549 for SNPs with P < 0.01 to 0.565 for SNPs with P < 0.50. This study suggests that SNPs currently have limited clinical utility, but there is potential for enhanced predictive ability with better understanding of the large number of variants that might contribute to risk.

Indexed as

AdolescentAdultAgedAged, 80 and overAlcoholismAllelesCase-Control StudiesFemaleGenetic Association StudiesGenetic CounselingGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMiddle AgedPolymorphism, Single NucleotideClinical validitygenetic risk predictionpolygenic risk scorepsychiatric genetic counselingreceiver operating characteristic curve analysis

Identifiers

PMID23362995
PMCPMC3664249
OpenAlexW2162578054

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.