RT Journal Article
SR Electronic
T1 Genome-wide association study meta-analysis of the Alcohol Use Disorder Identification Test (AUDIT) in two population-based cohorts (N=141,932)
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 275917
DO 10.1101/275917
A1 Sandra Sanchez-Roige
A1 Abraham A. Palmer
A1 Pierre Fontanillas
A1 Sarah L. Elson
A1 The 23andMe Research Team
A1 Substance Use Disorder Working Group of the Psychiatric Genomics Consortium
A1 Mark J. Adams
A1 David M. Howard
A1 Howard J. Edenberg
A1 Gail Davies
A1 Richard C. Crist
A1 Ian J. Deary
A1 Andrew M. McIntosh
A1 Toni-Kim Clarke
YR 2018
UL http://biorxiv.org/content/early/2018/08/02/275917.abstract
AB Alcohol use disorders (AUD) are common conditions that have enormous social and economic consequences. We obtained quantitative measures using the Alcohol Use Disorder Identification Test (AUDIT) from two population-based cohorts of European ancestry: UK Biobank (UKB; N=121,604) and 23andMe (N=20,328) and performed a genome-wide association study (GWAS) meta-analysis. We also performed GWAS for AUDIT items 1-3, which focus on consumption (AUDIT-C), and for items 4-10, which focus on the problematic consequences of drinking (AUDIT-P). The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; we also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76-0.92) and Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P was positively genetically correlated with schizophrenia (rg=0.22, p=3.0×10−10), major depressive disorder (rg=0.26, p=5.6×10−3), and attention-deficit/hyperactivity disorder (ADHD; rg=0.23, p=1.1×10−5), whereas AUDIT-C was negatively genetically correlated with major depressive disorder (rg=−0.24, p=3.7×10−3) and ADHD (rg=−0.10, p=1.8×10−2). We also used the AUDIT data in the UKB to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total score of ≤4 as controls and ≥12 as cases produced a high genetic correlation with DSM-IV alcohol dependence (rg=0.82, p=3.2×10−6) while retaining most subjects. We conclude that AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and AUD.