Genome-wide polygenic scores for age at onset of alcohol dependence and association with alcohol-related measures.
- Authors
- Kapoor, M; Chou, Y-L; Edenberg, H J; Foroud, T; Martin, N G; Madden, P A F; Wang, J C; Bertelsen, S; Wetherill, L; Brooks, A; Chan, G; Hesselbrock, V; Kuperman, S; Medland, S E; Montgomery, G; Tischfield, J; Whitfield, J B; Bierut, L J; Heath, A C; Bucholz, K K; Goate, A M; Agrawal, A
- Year
- 2016
- Journal
- Translational psychiatry
- PMID
- 27003187
- DOI
- 10.1038/tp.2016.27
- PMCID
- PMC4872451
Age at onset of alcohol dependence (AO-AD) is a defining feature of multiple drinking typologies. AO-AD is heritable and likely shares genetic liability with other aspects of alcohol consumption. We examine whether polygenic variation in AO-AD, based on a genome-wide association study (GWAS), was associated with AO-AD and other aspects of alcohol consumption in two independent samples. Genetic risk scores (GRS) were created based on AO-AD GWAS results from a discovery sample of 1788 regular drinkers from extended pedigrees from the Collaborative Study of the Genetics of Alcoholism (COGA). GRS were used to predict AO-AD, AD and Alcohol dependence symptom count (AD-SX), age at onset of intoxication (AO-I), as well as maxdrinks in regular drinking participants from two independent samples-the Study of Addictions: Genes and Environment (SAGE; n=2336) and an Australian sample (OZ-ALC; n=5816). GRS for AO-AD from COGA explained a modest but significant proportion of the variance in all alcohol-related phenotypes in SAGE. Despite including effect sizes associated with large numbers of single nucleotide polymorphisms (SNPs; >110 000), GRS explained, at most, 0.7% of the variance in these alcohol measures in this independent sample. In OZ-ALC, significant but even more modest associations were noted with variance estimates ranging from 0.03 to 0.16%. In conclusion, there is modest evidence that genetic variation in AO-AD is associated with liability to other aspects of alcohol involvement.
GRS generated from an analysis of AO-AD in a discovery sample, at varying P-value thresholds, predicting (a) AO-AD, (b) AO-I, (c ) AD, (d) AD-SX, (e) Maxdrinks and (f) height in SAGE dataset. The x-axis represents the GRS thresholds and y-axis represents the adjusted R2 for the trait. Each bar represents the values of adjusted R2 for SAGE. Colors of the bar represent the level of significance achieved. AD, alcohol dependence; AD-SX, total number of DSM4 AD symptoms endorsed; AO-AD, age at onset of AD; AO-I, age at onset of intoxication; GRS, genome-wide polygenic scores; SAGE, Study of Addictions: Genes and Environment.
GRS generated from an analysis of AO-AD in a discovery sample, at varying P-value thresholds, predicting (a) AO-AD, (b) AO-I, (c ) AD, (d) AD-SX, (e) Maxdrinks and (f) height in OZ-ALC dataset. The x-axis represents the GRS thresholds and y-axis represents the adjusted R2 for the trait. Each bar represents the values of adjusted R2 for OZ-ALC. Colors of the bar represent the significance level achieved. AD, alcohol dependence; AD-SX, total number of DSM4 AD symptoms endorsed; AO-AD, age at onset of AD; AO-I, age at onset of intoxication; GRS, genome-wide polygenic scores.
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| Citation | PMID | DOI | Status |
|---|---|---|---|
| Agrawal A, Sartor CE, Lynskey MT, Grant JD, Pergadia ML, Grucza R et al. Evidence for an interaction between age at first drink and genetic influences on DSM-IV alcohol dependence symptoms. Alcoholism 2009; 33: 2047β2056.1976493510.1111/j.1530-0277.2009.01044.xPMC2883563 | β | β | β |
| Babor TF, Dolinsky ZS, Meyer RE, Hesselbrock M, Hofmann M, Tennen H. Types of alcoholics: concurrent and predictive validity of some common classification schemes. Addiction 1992; 87: 1415β1431.10.1111/j.1360-0443.1992.tb01921.x1330126 | β | β | β |
| Babor TF. Types of alcoholics, I. Arch Gen Psychiatry 1992; 49: 599.163725010.1001/archpsyc.1992.01820080007002 | β | β | β |
| Begleiter H, Reich T, Nurnberger J, Li TK, Conneally PM, Edenberg H et al. Description of the genetic analysis workshop 11 collaborative study on the genetics of alcoholism. Genet Epidemiol 1999; 17: S25βS30.1059740710.1002/gepi.1370170705 | β | β | β |
| Bierut LJ, Agrawal A, Bucholz KK, Doheny KF, Laurie C, Pugh E et al. A genome-wide association study of alcohol dependence. Proc Natl Acad Sci USA 2010; 107: 5082β5087.2020292310.1073/pnas.0911109107PMC2841942 | β | β | β |
| Bierut LJ, Madden PA, Breslau N, Johnson EO, Hatsukami D, Pomerleau OF et al. Novel genes identified in a high-density genome wide association study for nicotine dependence. Hum Mol Genet 2007; 16: 24β35.1715818810.1093/hmg/ddl441PMC2278047 | β | β | β |
| Bierut LJ, Strickland JR, Thompson JR, Afful SE, Cottler LB. Drug use and dependence in cocaine dependent subjects, community-based individuals, and their siblings. Drug Alcohol Depend 2008; 95: 14β22.1824358210.1016/j.drugalcdep.2007.11.023PMC2384165 | β | β | β |
| Bucholz KK, Cadoret R, Cloninger CR, Dinwiddie SH, Hesselbrock VM, Nurnberger JI et al. A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA. J Stud Alcohol 1994; 55: 149β158.818973510.15288/jsa.1994.55.149 | β | β | β |
| Cloninger C. Neurogenetic adaptive mechanisms in alcoholism. Science 1987; 236: 410β416.288260410.1126/science.2882604 | β | β | β |
| Cloninger CR, Sigvardsson S, Gilligan SB, von Knorring A-L, Reich T, Bohman M. Genetic heterogeneity and the classification of alcoholism. Adv Alcohol Subst Abuse 1988; 7: 3β16.306619410.1300/J251v07n03_02 | β | β | β |
| Cross-Disorder Group of the Psychiatric Genomics C. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 2013; 381: 1371β1379.2345388510.1016/S0140-6736(12)62129-1PMC3714010 | β | β | β |
| Dudbridge F. Power and predictive accuracy of polygenic risk scores. PLoS Genet 2013; 9: e1003348.2355527410.1371/journal.pgen.1003348PMC3605113 | β | β | β |
| Finn PR, Sharkansky EJ, Viken R, West TL et al. Heterogeneity in the families of sons of alcoholics: the impact of familial vulnerability type on offspring characteristics. J Abnorm Psychol 1997; 106: 26β36.910371510.1037//0021-843x.106.1.26 | β | β | β |
| Grant JD, Agrawal A, Bucholz KK, Madden PAF, Pergadia ML, Nelson EC et al. Alcohol consumption indices of genetic risk for alcohol dependence. Biol Psychiatry 2009; 66: 795β800.1957657410.1016/j.biopsych.2009.05.018PMC3077105 | β | β | β |
| Heath AC, Bucholz KK, Madden PAF, Dinwiddie SH, Slutske WS, Bierut LJ et al. Genetic and environmental contributions to alcohol dependence risk in a national twin sample: consistency of findings in women and men. Psychol Med 1997; 27: 1381β1396.940391010.1017/s0033291797005643 | β | β | β |
| Heath AC, Whitfield JB, Martin NG, Pergadia ML, Goate AM, Lind PA et al. A quantitative-trait genome-wide association study of alcoholism risk in the community: findings and implications. Biol Psychiatry 2011; 70: 513β518.2152978310.1016/j.biopsych.2011.02.028PMC3210694 | β | β | β |
| Hesselbrock M, Easton C, Bucholz KK, Schuckit M, Hesselbrock V. A validity study of the SSAGA-a comparison with the SCAN. Addiction 1999; 94: 1361β1370.1061572110.1046/j.1360-0443.1999.94913618.x | β | β | β |
| Kapoor M, Wang JC, Wetherill L, Le N, Bertelsen S, Hinrichs AL et al. Genome-wide survival analysis of age at onset of alcohol dependence in extended high-risk COGA families. Drug Alcohol Depend 2014; 142: 56β62.2496232510.1016/j.drugalcdep.2014.05.023PMC4127128 | β | β | β |
| Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet Epidemiol 2010; 34: 816β834.2105833410.1002/gepi.20533PMC3175618 | β | β | β |
| Medland SE, Nyholt DR, Painter JN, McEvoy BP, McRae AF, Zhu G et al. Common variants in the trichohyalin gene are associated with straight hair in Europeans. Am J Hum Genet 2009; 85: 750β755.1989611110.1016/j.ajhg.2009.10.009PMC2775823 | β | β | β |
| Morey LC, Skinner HA Empirically derived classifications of alcohol-related problems. In: Recent Developments in Alcoholism. Springer USA, 1986, pp 145β168.10.1007/978-1-4899-1695-2_63704217 | β | β | β |
| Power RA, Verweij KJH, Zuhair M, Montgomery GW, Henders AK, Heath AC et al. Genetic predisposition to schizophrenia associated with increased use of cannabis. Mol Psychiatry 2014; 19: 1201β1204.2495786410.1038/mp.2014.51PMC4382963 | β | β | β |
| Prescott CA, Kendler KS. Age at first drink and risk for alcoholism: a noncausal association. Alcoholism 1999; 23: 101β107.10029209 | β | β | β |
| Prescott CA, Kendler KS. Genetic and environmental contributions to alcohol abuse and dependence in a population-based sample of male twins. Am J Psychiatry 1999; 156: 34β40.989229510.1176/ajp.156.1.34 | β | β | β |
| Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 2006; 38: 904β909.1686216110.1038/ng1847 | β | β | β |
| Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81: 559β575.1770190110.1086/519795PMC1950838 | β | β | β |
| Salvatore J, Aliev F, Edwards A, Evans D, Macleod J, Hickman M et al. Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment. Genes 2014; 5: 330β346.2472730710.3390/genes5020330PMC4094936 | β | β | β |
| Sartor CE, Agrawal A, Lynskey MT, Bucholz KK, Heath AC. Genetic and environmental influences on the rate of progression to alcohol dependence in young women. Alcoholism 2008; 32: 632β638.1833138010.1111/j.1530-0277.2008.00621.xPMC3593341 | β | β | β |
| Sartor CE, Lynskey MT, Bucholz KK, Madden PAF, Martin NG, Heath AC. Timing of first alcohol use and alcohol dependence: evidence of common genetic influences. Addiction 2009; 104: 1512β1518.1968652010.1111/j.1360-0443.2009.02648.xPMC2741422 | β | β | β |
| Stallings MC, Hewitt JK, Beresford T, Heath AC, Eaves LJ. A twin study of drinking and smoking onset and latencies from first use to regular use. Behav Genet 1999; 29: 409β421.1085724610.1023/a:1021622820644 | β | β | β |
| Vink JM, Hottenga JJ, de Geus EJC, Willemsen G, Neale MC, Furberg H et al. Polygenic risk scores for smoking: predictors for alcohol and cannabis use? Addiction 2014; 109: 1141β1151.2445058810.1111/add.12491PMC4048635 | β | β | β |
| Zucker RA, Ellis DA, Fitzgerald HE. Developmental evidence for at least two alcoholisms. Ann NY Acad Sci 1994; 708, (1 Types of Alco) 134β146.815467410.1111/j.1749-6632.1994.tb24706.x | β | β | β |
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External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Considerations for the application of polygenic scores to clinical care of individuals with substance use disorders. | Kember RL et al. | β | 2024 | β |
| Neural activations during cognitive and affective theory of mind processing in healthy adults with a family history of alcohol use disorder. | Schmid F et al. | β | 2024 | β |
| High Polygenic Risk Scores Are Associated With Early Age of Onset of Alcohol Use Disorder in Adolescents and Young Adults at Risk. | Nurnberger JI et al. | β | 2022 | β |
| ASSESSING SELECTION BIAS IN REGRESSION COEFFICIENTS ESTIMATED FROM NONPROBABILITY SAMPLES WITH APPLICATIONS TO GENETICS AND DEMOGRAPHIC SURVEYS. | West BT et al. | β | 2021 | β |
| Recent advances in genetic studies of alcohol use disorders. | Gupta I et al. | β | 2020 | β |
| Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism. | Kapoor M et al. | β | 2019 | β |
| Associations between polygenic risk for tobacco and alcohol use and liability to tobacco and alcohol use, and psychiatric disorders in an independent sample of 13,999 Australian adults. | Chang LH et al. | β | 2019 | β |
| Pavlovian-To-Instrumental Transfer and Alcohol Consumption in Young Male Social Drinkers: Behavioral, Neural and Polygenic Correlates. | Garbusow M et al. | β | 2019 | β |
| Polygenic approaches to detect gene-environment interactions when external information is unavailable. | Lin WY et al. | β | 2019 | β |
| Effects of autozygosity and schizophrenia polygenic risk on cognitive and brain developmental trajectories. | CΓ³rdova-Palomera A et al. | β | 2018 | β |
| Polygenic risk for alcohol consumption and its association with alcohol-related phenotypes: Do stress and life satisfaction moderate these relationships? | Mies GW et al. | β | 2018 | β |
| Heterogeneity in polygenic scores for common human traits | Ware EB et al. | β | 2017 | β |
| Polygenic Scores for Major Depressive Disorder and Risk of Alcohol Dependence. | Andersen AM et al. | β | 2017 | β |
| The genetic epidemiology of substance use disorder: A review. | Prom-Wormley EC et al. | β | 2017 | β |
| Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort. | Taylor M et al. | β | 2016 | β |