Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals.

Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.

Genetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample.

OBJECTIVE: Recent genome-wide association studies (GWASs) of alcohol-related phenotypes have uncovered key differences in the underlying genetic architectures of alcohol consumption and alcohol use disorder (AUD), with the two traits having opposite genetic correlations with psychiatric disorders. Understanding the genetic factors that underlie the transition from heavy drinking to AUD has important theoretical and clinical implications. METHODS: The authors used longitudinal data from the cross-ancestry Million Veteran Program sample to identify 1) novel loci associated with AUD and alcohol consumption (measured by the score on the consumption subscale of the Alcohol Use Disorders Identification Test [AUDIT-C]), 2) the impact of phenotypic variation on genetic discovery, and 3) genetic variants with direct effects on AUD that are not mediated through alcohol consumption. RESULTS: The authors identified 26 loci associated with AUD and 22 loci associated with AUDIT-C score, including ancestry-specific and novel loci. In secondary GWASs that excluded individuals who report abstinence, the authors identified seven additional loci for AUD and eight additional loci for AUDIT-C score. Although the heterogeneity of the abstinent group biases the GWAS findings, unique variance between alcohol consumption and disorder remained after the abstinent group was excluded. Finally, using mediation analysis, the authors identified a set of variants with effects on AUD that are not mediated through alcohol consumption. CONCLUSIONS: Differences in genetic architecture between alcohol consumption and AUD are consistent with their having different biological contributions. Genetic variants with direct effects on AUD are potentially relevant to understanding the transition from heavy alcohol consumption to AUD and may be targets for translational prevention and treatment efforts.

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program.

Smoking behaviors and alcohol use disorder (AUD), both moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to co-occurring smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N = 318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 17 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants on SIX3, NCAM1, and near DRD2. Functional annotation of the MTAG variants highlighted biologically important regions on ZBTB20, DRD2, PPP6C, and GCKR that contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly co-occuring phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD.

Multi-ancestry study of the genetics of problematic alcohol use in >1 million individuals.

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. To improve our understanding of the genetics of PAU, we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals. We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine-mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and/or chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by drug repurposing analysis. Cross-ancestry polygenic risk scores (PRS) showed better performance in independent sample than single-ancestry PRS. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. The analysis of diverse ancestries contributed significantly to the findings, and fills an important gap in the literature.

Variance Estimation and Confidence Intervals from Genome-wide Association Studies Through High-dimensional Misspecified Mixed Model Analysis.

We study variance estimation and associated confidence intervals for parameters characterizing genetic effects from genome-wide association studies (GWAS) in misspecified mixed model analysis. Previous studies have shown that, in spite of the model misspecification, certain quantities of genetic interests are consistently estimable, and consistent estimators of these quantities can be obtained using the restricted maximum likelihood (REML) method under a misspecified linear mixed model. However, the asymptotic variance of such a REML estimator is complicated and not ready to be implemented for practical use. In this paper, we develop practical and computationally convenient methods for estimating such asymptotic variances and constructing the associated confidence intervals. Performance of the proposed methods is evaluated empirically based on Monte-Carlo simulations and real-data application.

The impact of removing former drinkers from genome-wide association studies of AUDIT-C.

BACKGROUND AND AIMS: The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire screens for harmful drinking using a 12-month timeframe. A score of 0 is assigned to individuals who report abstaining from alcohol in the past year. However, many middle-age individuals reporting current abstinence are former drinkers (FDs). Because FDs may be more genetically prone to harmful alcohol use than lifelong abstainers (LAs) and are often combined with LAs, we evaluated the impact of differentiating them on the identification of genetic association. DESIGN AND SETTING: The United Kingdom Biobank (UKBB) includes AUDIT-C and alcohol drinker status. PARTICIPANTS: 131 510 Europeans, including 5135 FDs. MEASUREMENTS: We compared three genome-wide association (GWAS) analyses to explore the effects of removing FDs: the full AUDIT-C data, AUDIT-C data without FDs, and data from a random sample numerically matched to the data without FDs. Because prior studies show a consistent association of the ADH1B polymorphism rs1229984 with both alcohol consumption and alcohol use disorder, we compared allele frequencies for rs1229984 stratified by AUDIT-C value and FD versus LA status. Additionally, we calculated polygenic risk scores (PRS) of related diseases. FINDINGS: The rs1229984 allele frequencies among FDs were numerically comparable to those with high AUDIT-C scores and very different from those of LAs. Removing FDs from GWAS yielded a stronger association with rs1229984 (P value after removal: 1.9 × 10-70 vs 1.7 × 10-65 and 2.5 × 10-62 ), more statistically significant single nucleotide polymorphisms (SNPs) (after removal: 11 vs 9 and 8), and genomic loci (after removal: 11 vs 9 and 7). Additional independent SNPs were identified after removal of FDs: rs2817866 (PTGER3), rs7105867 (ANO3), and rs17601612 (DRD2). For PRS of alcohol use disorder and major depressive disorder, there are statistically significant differences between FDs and LAs. CONCLUSIONS: Differentiating between former drinkers and lifelong abstainers can improve Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) genome-wide association results.

Women Have a Lower Risk of Nonalcoholic Fatty Liver Disease but a Higher Risk of Progression vs Men: A Systematic Review and Meta-analysis.

BACKGROUND & AIMS: The risk of nonalcoholic fatty liver disease (NAFLD) and its progression may differ between men and women. We conducted a systematic review and meta-analysis to determine the relationship between sex and NAFLD, nonalcoholic steatohepatitis (NASH), and advanced NAFLD fibrosis. METHODS: Studies reporting sex-stratified NAFLD prevalence among population-based samples and either NASH or advanced fibrosis among patients with biopsy-proven NAFLD were identified from MEDLINE, EMBASE, and Cochrane databases through December 2017. We calculated pooled relative risk ratios comparing women vs men for each outcome. RESULTS: Our final analysis comprised 54 studies. Samples sizes were 62,239 for the NAFLD analysis, 5428 for the NASH analysis, and 6444 for the advanced fibrosis analysis. Women had a 19% lower risk of NAFLD than men in the general population (pooled risk ratio [RR], 0.81; 95% CI, 0.68-0.97; I2 = 97.5%). Women had a similar risk of NASH (RR, 1.00; 95% CI, 0.88-1.14; I2 = 85.1%), and a 37% higher risk of advanced fibrosis (RR, 1.37; 95% CI, 1.12-1.68; I2 = 74.0%) than men. Age modified the effect of sex on NAFLD severity. Risks of NASH (RR, 1.17; 95% CI, 1.01-1.36) and advanced fibrosis (RR, 1.56; 95% CI, 1.36-1.80; I2 = 0) were substantially higher in women in study populations with average ages of 50 years and older; sex differences in NASH and advanced fibrosis were attenuated in younger populations. CONCLUSIONS: In a systematic review and meta-analysis, we found women to have a lower risk of NAFLD than men. However, once NAFLD is established, women have a higher risk of advanced fibrosis than men, especially after age 50 years.

Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals.

Here we report a large genome-wide association study (GWAS) for longitudinal smoking phenotypes in 286,118 individuals from the Million Veteran Program (MVP) where we identified 18 loci for smoking trajectory of current versus never in European Americans, one locus in African Americans, and one in Hispanic Americans. Functional annotations prioritized several dozen genes where significant loci co-localized with either expression quantitative trait loci or chromatin interactions. The smoking trajectories were genetically correlated with 209 complex traits, for 33 of which smoking was either a causal or a consequential factor. We also performed European-ancestry meta-analyses for smoking status in the MVP and GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN) (Ntotal = 842,717) and identified 99 loci for smoking initiation and 13 loci for smoking cessation. Overall, this large GWAS of longitudinal smoking phenotype in multiple populations, combined with a meta-GWAS for smoking status, adds new insights into the genetic vulnerability for smoking behavior.

Association of OPRM1 Functional Coding Variant With Opioid Use Disorder: A Genome-Wide Association Study.

Importance: With the current opioid crisis, it is important to improve understanding of the biological mechanisms of opioid use disorder (OUD). Objectives: To detect genetic risk variants for OUD and determine genetic correlations and causal association with OUD and other traits. Design, Setting, and Participants: A genome-wide association study of electronic health record-defined OUD in the Million Veteran Program sample was conducted, comprising 8529 affected European American individuals and 71 200 opioid-exposed European American controls (defined by electronic health record trajectory analysis) and 4032 affected African American individuals and 26 029 opioid-exposed African American controls. Participants were enrolled from January 10, 2011, to May 21, 2018, with electronic health record data for OUD diagnosis from October 1, 1999, to February 7, 2018. Million Veteran Program results and additional OUD case-control genome-wide association study results from the Yale-Penn and Study of Addiction: Genetics and Environment samples were meta-analyzed (total numbers: European American individuals, 10 544 OUD cases and 72 163 opioid-exposed controls; African American individuals, 5212 cases and 26 876 controls). Data on Yale-Penn participants were collected from February 14, 1999, to April 1, 2017, and data on Study of Addiction: Genetics and Environment participants were collected from 1990 to 2007. The key result was replicated in 2 independent cohorts: proxy-phenotype buprenorphine treatment in the UK Biobank and newly genotyped Yale-Penn participants. Genetic correlations between OUD and other traits were tested, and mendelian randomization analysis was conducted to identify potential causal associations. Main Outcomes and Measures: Main outcomes were International Classification of Diseases, Ninth Revision-diagnosed OUD or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision-diagnosed OUD (Million Veteran Program), and DSM-IV-defined opioid dependence (Yale-Penn and Study of Addiction: Genetics and Environment). Results: A total of 114 759 individuals (101 016 men [88%]; mean [SD] age, 60.1 [12.8] years) were included. In 82 707 European American individuals, a functional coding variant (rs1799971, encoding Asn40Asp) in OPRM1 (µ-opioid receptor gene, the main biological target for opioid drugs; OMIM 600018) reached genome-wide significance (G allele: ß = -0.066 [SE = 0.012]; P = 1.51 × 10-8). The finding was replicated in 2 independent samples. Single-nucleotide polymorphism-based heritability of OUD was 11.3% (SE = 1.8%). Opioid use disorder was genetically correlated with 83 traits, including multiple substance use traits, psychiatric illnesses, cognitive performance, and others. Mendelian randomization analysis revealed the following associations with OUD: risk of tobacco smoking, depression, neuroticism, worry neuroticism subcluster, and cognitive performance. No genome-wide significant association was detected for African American individuals or in transpopulation meta-analysis. Conclusions and Relevance: This genome-wide meta-analysis identified a significant association of OUD with an OPRM1 variant, which was replicated in 2 independent samples. Post-genome-wide association study analysis revealed associated pleiotropic characteristics. Recruitment of additional individuals with OUD for future studies-especially those of non-European ancestry-is a crucial next step in identifying additional significant risk loci.

Differentiating Types of Self-Reported Alcohol Abstinence.

We contrast three types of abstinence: quit after alcohol associated problems (Q-AP), quit for other reasons (Q-OR), and lifetime abstainer (LTA). We summarized the characteristics of people living with HIV (PLWH), and matched uninfected individuals, by levels of alcohol use and types of abstinence. We then identified factors that differentiate abstinence and determined whether the association with an alcohol biomarker or a genetic polymorphism is improved by differentiating abstinence. Among abstainers, 34% of PLWH and 38% of uninfected were Q-AP; 53% and 53% were Q-OR; and 12% and 10% were LTA. Logistic regression models found smoking, alcohol, cocaine, and hepatitis C increased odds of Q-AP, whereas smoking and marijuana decreased odds of LTA. Differentiating types of abstinence improved association. Q-APs and LTAs can be readily differentiated by an alcohol biomarker and genetic polymorphism. Differentiating type of abstinence may enhance understanding of alcohol health effects.