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Genome-wide association studies of alcohol dependence, DSM-IV criterion count and individual criteria

Authors :
Arpana Agrawal
Philip L. De Jager
Ryan Bogdan
John Kramer
Howard J. Edenberg
Caitlin E. Carey
Jay A. Tischfield
John I. Nurnberger
Kathleen K. Bucholz
Alison Goate
Danielle M. Dick
Jacquelyn L. Meyers
Samuel Kuperman
Tatiana Foroud
Victor Hesselbrock
Towfique Raj
Bernice Porjesz
Katharine Chang
Denise M. Scott
Leah Wetherill
David A. Bennett
Chella Kamarajan
Marc A. Schuckit
Robert E. Taylor
Dongbing Lai
Andrey P. Anokhin
Sarah Bertelsen
Ahmad R. Hariri
Manav Kapoor
Source :
Genes, brain, and behavior, vol 18, iss 6, Genes Brain Behav
Publication Year :
2019
Publisher :
eScholarship, University of California, 2019.

Abstract

Genome-wide association studies (GWAS) of alcohol dependence (AD) have reliably identified variation within alcohol metabolizing genes (eg, ADH1B) but have inconsistently located other signals, which may be partially attributable to symptom heterogeneity underlying the disorder. We conducted GWAS of DSM-IV AD (primary analysis), DSM-IV AD criterion count (secondary analysis), and individual dependence criteria (tertiary analysis) among 7418 (1121 families) European American (EA) individuals from the Collaborative Study on the Genetics of Alcoholism (COGA). Trans-ancestral meta-analyses combined these results with data from 3175 (585 families) African-American (AA) individuals from COGA. In the EA GWAS, three loci were genome-wide significant: rs1229984 in ADH1B for AD criterion count (P = 4.16E-11) and Desire to cut drinking (P = 1.21E-11); rs188227250 (chromosome 8, Drinking more than intended, P = 6.72E-09); rs1912461 (chromosome 15, Time spent drinking, P = 1.77E-08). In the trans-ancestral meta-analysis, rs1229984 was associated with multiple phenotypes and two additional loci were genome-wide significant: rs61826952 (chromosome 1, DSM-IV AD, P = 8.42E-11); rs7597960 (chromosome 2, Time spent drinking, P = 1.22E-08). Associations with rs1229984 and rs18822750 were replicated in independent datasets. Polygenic risk scores derived from the EA GWAS of AD predicted AD in two EA datasets (P

Details

Database :
OpenAIRE
Journal :
Genes, brain, and behavior, vol 18, iss 6, Genes Brain Behav
Accession number :
edsair.doi.dedup.....95aca911a1267dd3ce8a275c219e16d7