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Item Alcohol metabolizing genes and alcohol phenotypes in an Israeli household sample(Wiley, 2013-11) Meyers, Jacquelyn L.; Shmulewitz, Dvora; Aharonovich, Efrat; Waxman, Rachel; Frisch, Amos; Weizman, Abraham; Spivak, Baruch; Edenberg, Howard J.; Gelernter, Joel; Hasin, Deborah; Biochemistry & Molecular Biology, School of MedicineBACKGROUND: Alcohol dehydrogenase 1B and 1C (ADH1B and ADH1C) variants have been robustly associated with alcohol phenotypes in East Asian populations, but less so in non-Asian populations where prevalence of the most protective ADH1B allele is low (generally <5%). Further, the joint effects of ADH1B and ADH1C on alcohol phenotypes have been unclear. Therefore, we tested the independent and joint effects of ADH1B and ADH1C on alcohol phenotypes in an Israeli sample, with higher prevalence of the most protective ADH1B allele than other non-Asian populations. METHODS: A structured interview assessed lifetime drinking and alcohol use disorders (AUDs) in adult Israeli household residents. Four single nucleotide polymorphisms (SNPs) were genotyped: ADH1B (rs1229984, rs1229982, and rs1159918) and ADH1C (rs698). Regression analysis examined the association between alcohol phenotypes and each SNP (absence vs. presence of the protective allele) as well as rs698/rs1229984 diplotypes (also indicating absence or presence of protective alleles) in lifetime drinkers (n = 1,129). RESULTS: Lack of the ADH1B rs1229984 protective allele was significantly associated with consumption- and AUD-related phenotypes (OR = 1.77 for AUD; OR = 1.83 for risk drinking), while lack of the ADH1C rs698 protective allele was significantly associated with AUD-related phenotypes (OR = 2.32 for AUD). Diplotype analysis indicated that jointly ADH1B and ADH1C significantly influenced AUD-related phenotypes. For example, among those without protective alleles for ADH1B or ADH1C, OR for AUD was 1.87 as compared to those without the protective allele for ADH1B only and was 3.16 as compared to those with protective alleles for both ADH1B and ADH1C. CONCLUSIONS: This study adds support for the relationship of ADH1B and ADH1C and alcohol phenotypes in non-Asians. Further, these findings help clarify the mixed results from previous studies by showing that ADH1B and ADH1C jointly effect AUDs, but not consumption. Studies of the association between alcohol phenotypes and either ADH1B or ADH1C alone may employ an oversimplified model, masking relevant information.Item Genome-Wide Association Study Meta-Analysis of the Alcohol Use Disorders Identification Test (AUDIT) in Two Population-Based Cohorts(American Psychiatric Publishing, 2019-02-01) Sanchez-Roige, Sandra; Palmer, Abraham A.; Fontanillas, Pierre; Elson, Sarah L.; The 23andMe Research Team; Substance Use Disorder Working Group of the Psychiatric Genomics Consortium; Adams, Mark J.; Howard, David M.; Edenberg, Howard J.; Davies, Gail; Crist, Richard C.; Deary, Ian J.; McIntosh, Andrew M.; Clarke, Toni-Kim; Biochemistry and Molecular Biology, School of MedicineOBJECTIVE: Alcohol use disorders are common conditions that have enormous social and economic consequences. Genome-wide association analyses were performed to identify genetic variants associated with a proxy measure of alcohol consumption and alcohol misuse and to explore the shared genetic basis between these measures and other substance use, psychiatric, and behavioral traits. METHOD: This study used quantitative measures from the Alcohol Use Disorders Identification Test (AUDIT) from two population-based cohorts of European ancestry (UK Biobank [N=121,604] and 23andMe [N=20,328]) and performed a genome-wide association study (GWAS) meta-analysis. Two additional GWAS analyses were performed, a GWAS for AUDIT scores on items 1-3, which focus on consumption (AUDIT-C), and for scores on items 4-10, which focus on the problematic consequences of drinking (AUDIT-P). RESULTS: The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; this study 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 DSM-IV alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C scores showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P score was significantly positively genetically correlated with schizophrenia (rg=0.22), major depressive disorder (rg=0.26), and attention deficit hyperactivity disorder (rg=0.23), whereas AUDIT-C score was significantly negatively genetically correlated with major depressive disorder (rg=-0.24) and ADHD (rg=-0.10). This study also used the AUDIT data in the UK Biobank to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total scores ≤4 as control subjects and those with scores ≥12 as case subjects produced a significant high genetic correlation with DSM-IV alcohol dependence (rg=0.82) while retaining most subjects. CONCLUSIONS: AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and alcohol use disorders.