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Meta-Analysis
. 2020 Jul;23(7):809-818.
doi: 10.1038/s41593-020-0643-5. Epub 2020 May 25.

Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits

Hang Zhou  1   2 , Julia M Sealock  3   4 , Sandra Sanchez-Roige  5 , Toni-Kim Clarke  6 , Daniel F Levey  1   2 , Zhongshan Cheng  1   2 , Boyang Li  7 , Renato Polimanti  1   2 , Rachel L Kember  8   9 , Rachel Vickers Smith  10 , Johan H Thygesen  11 , Marsha Y Morgan  12 , Stephen R Atkinson  13 , Mark R Thursz  13 , Mette Nyegaard  14   15   16   17 , Manuel Mattheisen  14   18   19 , Anders D Børglum  14   15   16   17 , Emma C Johnson  20   21 , Amy C Justice  2   21   22 , Abraham A Palmer  5   23 , Andrew McQuillin  11 , Lea K Davis  3   4   24 , Howard J Edenberg  25   26 , Arpana Agrawal  20 , Henry R Kranzler  9   27 , Joel Gelernter  28   29   30
Affiliations
Meta-Analysis

Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits

Hang Zhou et al. Nat Neurosci. 2020 Jul.

Abstract

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.

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Figures

Figure 1.
Figure 1.. Overview of the analysis.
The four datasets that were meta-analyzed as the discovery sample for problematic alcohol use (PAU) included MVP phase1, MVP phase2, PGC, and UK Biobank (UKB). MVP phase1 and phase2 were meta-analyzed, and the result was used to test the genetic correlation with PGC alcohol dependence. An intermediary meta-analysis (AUD meta) combining MVP phase1, phase2, and PGC was then conducted to measure the genetic correlation with UKB AUDIT-P. Due to the sample overlap between UKB and GSCAN, we used the AUD (intermediary) meta-analysis for Mendelian Randomization (MR) analysis rather than the PAU (i.e., from the final) meta-analysis. MTAG, which used the summary data from PAU and DrnkWk (drinks per week) in GSCAN (without 23andMe samples, as those data were not available) as input to increase the power for each trait without introducing bias from sample overlap, returned summary results for PAU and DrnkWk separately.
Figure 2.
Figure 2.. Association results for AUD and PAU meta-analyses.
a. Manhattan and QQ plots for AUD (MVP+PGC), ncase=57,564, ncontrol=256,395, neffective=179,185; b. Manhattan and QQ plots for PAU, n=435,563, neffective=300,789. Effective sample size weighted meta-analyses were performed using METAL. Red lines indicate GWS after correction for multiple testing (p < 5×10–8).
Figure 3.
Figure 3.. Estimated SNP-based h2.
h2 results for single datasets or meta-analysis between datasets, from published studies or analyzed here. MVP is the phase1-phase2 MVP metaanalysis, PAU is the discovery meta-analysis. Effective sample sizes (nE) were used in LDSC. Center values are the estimated h2 and error bars indicate 95% confidence intervals.
Figure 4.
Figure 4.. Genetic correlations with published traits.
LDSC was applied to test genetic correlation between PAU and 715 traits. Of 228 published traits, 26 were genetically correlated with PAU after Bonferroni correction (p < 6.99×10−5). MDD, major depressive disorder; ADHD, attention deficit hyperactivity disorder. Center values are the estimated genetic correlation and error bars indicate 95% confidence intervals.
Figure 5.
Figure 5.. Phenome-Wide associations with PAU PRS in BioVU.
Polygenic score for PAU was calculated in 67,588 participants in BioVU (Vanderbilt University Medical Center’s biobank) using PRS-CS. 1,372 phenotypes were tested and Bonferroni correction (p < 3.64×10−5) was applied.
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