Alcohol Consumption and Alcohol Use Disorder: Exposing an Increasingly Shared Genetic Architecture.

Back to table of contents Previous article Next article EditorialsFull AccessAlcohol Consumption and Alcohol Use Disorder: Exposing an Increasingly Shared Genetic ArchitectureJulie D. White, Ph.D., Laura J. Bierut, M.D.Julie D. WhiteSearch for more papers by this author, Ph.D., Laura J. BierutSearch for more papers by this author, M.D.Published Online:1 Aug 2023https://doi.org/10.1176/appi.ajp.20230456AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail In this issue, Kember et al. (1) report an impressive undertaking to identify genetic contributors to both alcohol consumption and alcohol use disorder (AUD) in the largest study to date, both in terms of sample size and in terms of inclusion of non-European population groups. The authors also capitalize on the unique construction of the Million Veteran Program (MVP), with longitudinal data from alcohol consumption screenings and alcohol use disorder diagnoses in health records, to better refine phenotypes and analyses, something few other studies can accomplish. In these analyses, performed within and across ancestries, they report a notable 24 independent variants (19 loci) associated with alcohol consumption, quantified by Alcohol Use Disorder Identification Test–Consumption (AUDIT-C) scores (2), and 26 independent variants (21 loci) associated with alcohol use disorder. The authors also perform gene-based associations, conduct mediation analyses, calculate genetic correlations, construct polygenic risk scores, and perform a phenome-wide association study in two external data sets: the Vanderbilt Biobank (BioVU) and the UK Biobank. Through these analyses, they conclude that differences in the associated loci, differences in genetic and phenotypic correlations, and nonmediating genetic variation support a conclusion that alcohol consumption and AUD have distinct underlying genetic architectures. We submit that, considered with other recent publications on the genetics of both alcohol use and disorder, the results presented by Kember et al. highlight the necessity of minimizing trait heterogeneity by reducing the misclassification of individuals who now abstain from alcohol but who have a lifetime history of alcohol use disorder. When trait heterogeneity is minimized, the overall genetic underpinnings of alcohol consumption and use disorder are, in composition and pattern, quite similar.Given the heavy focus on genetic correlations as an indication of shared versus distinct genetic architectures for alcohol consumption and AUD, we think it prudent to give a brief overview of genetic correlations reported for these traits. Genetic correlations reported from twin studies suggested moderate to high correlations (rg range, 0.45–0.99) among several alcohol consumption traits and high correlations between alcohol consumption traits and problematic alcohol use (3, 4). Using cross-trait linkage disequilibrium score regression, reported genetic correlations between alcohol consumption traits and problematic alcohol use or alcohol use disorder have ranged widely (Table 1). In one of the earliest studies of individuals of European ancestry, the reported genetic correlation between AUDIT score and alcohol use disorder was negligible (rg=0.08) (5). Notice that several of the comparisons in Table 1 used the same cohorts or used the same trait (e.g., AUDIT-C score) in different cohorts, illustrating that seemingly innocuous differences in trait derivation and sample makeup can lead to large differences in estimated genetic correlations. Importantly, the study by Kember et al. compares alcohol consumption and alcohol use disorder measured in the same individuals, which eliminates biases in the estimated genetic correlations from sample selection and comorbid illness. When the authors focus analyses on those who report current drinking and exclude those who abstain from alcohol, 15% of whom have a lifetime history of alcohol use disorder, the genetic correlation between alcohol consumption and alcohol use disorder increases (rg=0.86–1), and the genetic correlations for individuals of African ancestry are very high (rg=0.98–1). These findings highlight that the genetic architecture of alcohol consumption and alcohol use disorder is primarily shared.TABLE 1. Reported genetic correlations between alcohol consumption traits and problematic alcohol useaConsumptionProblem UseICD-based AUD (stringent, among AUDIT-C >0) (1)ICD-based AUD (stringent) in MVP (1, 6)ICD-based AUD (less stringent) in MVP (1)AUDIT-C (among AUDIT-C >0) in MVP (1)EUR: 0.86EUR: 0.87EUR: 0.90AFR: 1AFR: 1AFR: 0.98AUDIT-C in MVP (1)EUR: 0.71EUR: 0.76EUR: 0.78AFR: 0.97AFR: 0.96AFR: 0.93AUDIT-C in MVP (6)EUR: 0.52AFR: 0.93DSM-IV AUD in PGC (7)AUD in MVP, PGC (8)Problematic alcohol use in MVP, UKB, and PGC (8, 9)DSM-IV AUD symptom count (10)AUDIT-P in UKB (11)Maximum drinks in 1 day in a typical month in MVP (12)0.76EUR: 0.790.73AFR: 0.67AUDIT-C in UKB (11)0.330.410.70AUDIT in UKB (11)0.390.480.81Drinking quantity among those who drink at least once or twice a week in UKB (13)0.75Drinking frequency in UKB (13)n.s.Derived average intake per week in UKB (14)0.370.76AUDIT in 23andMe (5)0.080.64Average number of drinks per week in GSCAN (15)0.77Average number of drinks per week in GSCAN (16)0.76Derived grams per day in AlcGen and CHARGE+ (17)0.700.76aExcept as otherwise noted, the reported correlations are from genetic studies using individuals of European ancestry. AlcGen=Alcohol Genome-Wide Association Consortium; AUD=alcohol use disorder; AUDIT=Alcohol Use Disorder Identification Test, consisting of all 10 questions; AUDIT-C=AUDIT-Consumption, consisting of the first three questions of the AUDIT; AUDIT-P=AUDIT-Problems, consisting of the last seven questions of the AUDIT; CHARGE+=Cohorts for Heart and Aging Research in Genomic Epidemiology Plus; GSCAN=GWAS and Sequencing Consortium of Alcohol and Nicotine Use; ICD-based AUD (less stringent)=at least one ICD-9 or ICD-10 code for AUD (1); ICD-based AUD (stringent)=at least one inpatient or two outpatient codes for AUD (1, 6); n.s.=not significant; PGC=Psychiatric Genomics Consortium; UKB=UK Biobank.TABLE 1. Reported genetic correlations between alcohol consumption traits and problematic alcohol useaEnlarge tableSeveral previous studies have reported seemingly divergent patterns of genetic correlation between consumption and use disorder when compared with non-alcohol-related traits. The AUDIT-C was reported to have puzzling positive genetic associations with variables related to socioeconomic status (e.g., educational attainment) and some health outcomes (e.g., HDL cholesterol levels), and negative associations with other health outcomes (e.g., obesity, triglyceride levels) and some forms of psychopathology (e.g., major depression diagnosis, attention deficit hyperactivity disorder) (5, 6, 11, 14). Opposite patterns of correlation were observed for AUDIT-P (problem items) score or alcohol use disorder (6, 11). Explanations for these divergent patterns have included true biological differences, confounding by selection bias, genetic heterogeneity, and measurement error. Kember and colleagues again help clarify most of these discrepancies among genetic correlations between alcohol consumption and use disorder and other traits. When the authors examined only those who report consuming alcohol and excluded those who abstain, fewer differences in the genetic correlation patterns for consumption and alcohol use disorder were still evident. Most were different in magnitude, not direction of effect, as reported in Table S16 in the online supplement for the Kember et al. article, and visualized in Figure 2C.We are at the crux of a revolution in which increasingly data-driven approaches are used to increase phenotypic precision and mitigate biases in genetic analyses of an inherently heterogeneous behavior and disease (18–20). With recent evidence that Black and Hispanic veterans from the MVP data set were more likely to have an AUD diagnosis than White veterans, despite similar AUDIT-C scores (21), this revolution is needed not only to improve our statistical power in genetic association studies, but also to mitigate racial and ethnic bias in diagnosis. We applaud Kember and colleagues for engaging with this revolution by examining different ancestral groups and exploring variations in the trait definitions under study, namely, by modifying the AUD case threshold and excluding those who abstain from alcohol (those with an AUDIT-C score >0), who were previously shown to affect genetic associations (1, 20). In excluding those who abstain, the authors only “lost” one to two genome-wide significant loci, despite losing almost a quarter of their original sample, suggesting greater power from higher phenotypic precision and reduced misclassification. Kember et al. also observed an increase in the SNP heritability of both AUDIT-C score and AUD diagnosis, further demonstrating the positive impact of reducing bias and improving phenotypic precision in understanding the genetic architecture both of consumption and of AUD (18, 20).As with all behavior and neuropsychiatric studies, we are at the mercy of phenotype definitions that boil into a single scale (AUDIT scores) or code (diagnoses) a lifetime of intersecting factors: genetic, social, environmental, and institutional. This heterogeneity of individual experience means that we simply cannot make the mistake of assuming that individuals who share a diagnosis are homogeneous in trait presentation or genetics. This may seem a pessimistic view, but on the contrary, the underlying variation is ripe for interesting studies in which geneticists, epidemiologists, and medical professionals can work together. By using refined phenotype definitions and careful studies, we can find meaningful associations to translate into clinical knowledge and therapeutics. For example, are there methods to mitigate bias in diagnoses of AUD, especially in individuals with moderate to high AUDIT-C scores? Or are there social and genetic factors distinctive to individuals with similarly moderate consumption but disparate AUD diagnoses? As we work to answer these questions, we posit that, in the effort to understand the genetic etiology of alcohol consumption and alcohol use disorder, there is more in common than there is different. We look forward to other creative work from this group and others to move the field further along the path to understanding alcohol consumption and treating problematic alcohol use and alcohol use disorder.GenOmics and Translational Research Center, RTI International, Research Triangle Park, N.C. (White); Department of Psychiatry, Washington University School of Medicine, St. Louis (Bierut).Send correspondence to Dr. Bierut ([email protected]).Dr. Bierut and Dr. White were supported by NIAAA grant R01AA027049, and Dr. Bierut was also supported by NIAAA grant U10AA008401.Dr. Bierut is listed as an inventor on a patent covering the use of certain SNPs in the diagnosis, prognosis, and treatment of addiction. Dr. White reports no financial relationships with commercial interests.References1. Kember RL, Vickers-Smith R, Zhou H, et al.: Genetic underpinnings of the transition from alcohol consumption to alcohol use disorder: shared and unique genetic architectures in a cross-ancestry sample. Am J Psychiatry 2023; 180:584–593Abstract, Google Scholar2. Bush K, Kivlahan DR, McDonell MB, et al.: The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Arch Intern Med 1998; 158:1789–1795Crossref, Medline, Google Scholar3. Dick DM, Meyers JL, Rose RJ, et al.: Measures of current alcohol consumption and problems: two independent twin studies suggest a complex genetic architecture. Alcohol Clin Exp Res 2011; 35:2152–2161Crossref, Medline, Google Scholar4. Kendler KS, Myers J, Dick D, et al.: The relationship between genetic influences on alcohol dependence and on patterns of alcohol consumption. Alcohol Clin Exp Res 2010; 34:1058–1065Crossref, Medline, Google Scholar5. Sanchez-Roige S, Fontanillas P, Elson SL, et al.: Genome-wide association study of Alcohol Use Disorder Identification Test (AUDIT) scores in 20,328 research participants of European ancestry. Addict Biol 2019; 24:121–131Crossref, Medline, Google Scholar6. Kranzler HR, Zhou H, Kember RL, et al.: Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat Commun 2019; 10:1499Crossref, Medline, Google Scholar7. Walters RK, Polimanti R, Johnson EC, et al.: Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. Nat Neurosci 2018; 21:1656–1669Crossref, Medline, Google Scholar8. Zhou H, Sealock JM, Sanchez-Roige S, et al.: Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. Nat Neurosci 2020; 23:809–818Crossref, Medline, Google Scholar9. Zhou H, Kember RL, Deak JD, et al.: Multi-ancestry study of the genetics of problematic alcohol use in >1 million individuals [preprint]. MedRxiv, January 30, 2023. https://www.medrxiv.org/content/10.1101/2023.01.24.23284960v2 Google Scholar10. Gelernter J, Kranzler H, Sherva R, et al.: Genome-wide association study of alcohol dependence: significant findings in African- and European-Americans including novel risk loci. Mol Psychiatry 2014; 19:41–49Crossref, Medline, Google Scholar11. Sanchez-Roige S, Palmer AA, Fontanillas P, et al.: Genome-wide association study meta-analysis of the Alcohol Use Disorders Identification Test (AUDIT) in two population-based cohorts. Am J Psychiatry 2019; 176:107–118Link, Google Scholar12. Deak JD, Levey DF, Wendt FR, et al.: Genome-wide investigation of maximum habitual alcohol intake in US veterans in relation to alcohol consumption traits and alcohol use disorder. JAMA Netw Open 2022; 5:e2238880Crossref, Medline, Google Scholar13. Polimanti R, Peterson RE, Ong JS, et al.: Evidence of causal effect of major depression on alcohol dependence: findings from the Psychiatric Genomics Consortium. Psychol Med 2019; 49:1218–1226Crossref, Medline, Google Scholar14. Clarke T-K, Adams MJ, Davies G, et al.: Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112 117). Mol Psychiatry 2017; 22:1376–1384Crossref, Medline, Google Scholar15. Liu M, Jiang Y, Wedow R, et al.: Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nat Genet 2019; 51:237–244Crossref, Medline, Google Scholar16. Saunders GRB, Wang X, Chen F, et al.: Genetic diversity fuels gene discovery for tobacco and alcohol use. Nature 2022; 612:720–724Crossref, Medline, Google Scholar17. Schumann G, Liu C, O’Reilly P, et al.: KLB is associated with alcohol drinking, and its gene product β-Klotho is necessary for FGF21 regulation of alcohol preference. Proc Natl Acad Sci U S A 2016; 113:14372–14377Crossref, Medline, Google Scholar18. Mallard TT, Savage JE, Johnson EC, et al.: Item-level genome-wide association study of the Alcohol Use Disorders Identification Test in three population-based cohorts. Am J Psychiatry 2022; 179:58–70Link, Google Scholar19. Xue A, Jiang L, Zhu Z, et al.: Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes. Nat Commun 2021; 12:20211Crossref, Medline, Google Scholar20. Dao C, Zhou H, Small A, et al.: The impact of removing former drinkers from genome-wide association studies of AUDIT-C. Addiction 2021; 116:3044–3054Crossref, Medline, Google Scholar21. Vickers-Smith R, Justice AC, Becker WC, et al.: Racial and ethnic bias in the diagnosis of alcohol use disorder in veterans. Am J Psychiatry 2023; 180:426–436Link, Google Scholar FiguresReferencesCited byDetailsCited byEarly-life Adversity and Genetics Associated With the Risk to Develop Psychiatric IllnessesNed H. Kalin, M.D.1 August 2023 | American Journal of Psychiatry, Vol. 180, No. 8 Volume 180Issue 8 August 01, 2023Pages 530-532 Metrics KeywordsSubstance-Related and Addictive DisordersAlcoholGenetics/GenomicsPDF download History Accepted 7 June 2023 Published online 1 August 2023 Published in print 1 August 2023