Examining the role of common genetic variants on alcohol, tobacco, cannabis and illicit drug dependence: genetics of vulnerability to drug dependence.
- Authors
- Palmer, Rohan H C; Brick, Leslie; Nugent, Nicole R; Bidwell, L Cinnamon; McGeary, John E; Knopik, Valerie S; Keller, Matthew C
- Year
- 2015
- Journal
- Addiction (Abingdon, England)
- PMID
- 25424661
- DOI
- 10.1111/add.12815
- PMCID
- PMC4329043
BACKGROUND AND AIMS: Twin and family studies suggest that genetic influences are shared across substances of abuse. However, despite evidence of heritability, genome-wide association and candidate gene studies have indicated numerous markers of limited effects, suggesting that much of the heritability remains missing. We estimated (1) the aggregate effect of common single nucleotide polymorphisms (SNPs) on multiple indicators of comorbid drug problems that are typically employed across community and population-based samples, and (2) the genetic covariance across these measures. PARTICIPANTS: A total of 2596 unrelated subjects from the Study of Addiction: Genetics and Environment provided information on alcohol, tobacco, cocaine, cannabis and other illicit substance dependence. Phenotypic measures included: (1) a factor score based on DSM-IV drug dependence diagnoses (DD), (2) a factor score based on problem use (PU; i.e. 1+ DSM-IV symptoms) and (3) dependence vulnerability (DV; a ratio of DSM-IV symptoms to the number of substances used). FINDINGS: Univariate and bivariate genome-wide complex trait analyses of this selected sample indicated that common SNPs explained 25-36% of the variance across measures, with DD and DV having the largest effects [h(2) SNP (standard error) = 0.36 (0.13) and 0.33 (0.13), respectively; PU = 0.25 (0.13)]. Genetic effects were shared across the three phenotypic measures of comorbid drug problems [rDD-PU = 0.92 (0.08), rDD-DV = 0.97 (0.08) and rPU-DV = 0.96 (0.07)]. CONCLUSION: At least 20% of the variance in the generalized vulnerability to substance dependence is attributable to common single nucleotide polymorphisms. The additive effect of common single nucleotide polymorphisms is shared across important indicators of comorbid drug problems.
The Common Pathway Model. The observed phenotypic variance/covariance of the measured dependence phenotypes (rectangles) represent alternate manifestations of a generalized vulnerability to dependence (indicated by the latent trait (solid circle), Substance Dependence Vulnerability). Variation in the latent trait and the variance in the observed phenotypes are decomposable into genetic (G) and environmental/residual (E) influences (dashed-circles).
Proportion of variance explained (VG/VP) of individual chromosomes on each phenotype while imposing strict QC and adjusting for cryptic relatedness. Note: Additive effects attributable to variants across chromosome were estimated at 1E-6 across all phenotypes. Abbreviations: DD = Dependence Diagnosis Factor; PU = Problem Use Factor; DV = Dependence Vulnerability Score.
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| Individual Differences in Different Measures of Opioid Self-Administration in Rats Are Accounted for by a Single Latent Variable. | Swain Y et al. | — | 2021 | → |
| Reward Deficiency Syndrome (RDS): A Cytoarchitectural Common Neurobiological Trait of All Addictions. | Blum K et al. | — | 2021 | → |
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| DSM-5 Maladaptive Personality Domains among Treatment-Seeking Individuals with Alcohol Use Disorder: The Role of Disinhibition and Negative Affectivity. | Cavicchioli M et al. | — | 2020 | → |
| ADGRL3 (LPHN3) variants predict substance use disorder. | Arcos-Burgos M et al. | — | 2019 | → |
| Beyond genome-wide significance: integrative approaches to the interpretation and extension of GWAS findings for alcohol use disorder. | Salvatore JE et al. | — | 2019 | → |
| Characterization of DSM-IV Opioid Dependence Among Individuals of European Ancestry. | Brick LA et al. | — | 2019 | → |
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| Relationships between substance abuse/dependence and psychiatric disorders based on polygenic scores. | Gurriarán X et al. | — | 2019 | → |
| The etiology of DSM-5 alcohol use disorder: Evidence of shared and non-shared additive genetic effects. | Palmer RHC et al. | — | 2019 | → |
| The Relationship Between Tobacco and Cannabis Use: A Review. | Lemyre A et al. | — | 2019 | → |
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| Nicotine dependence predicts cannabis use disorder symptoms among adolescents and young adults. | Dierker L et al. | — | 2018 | → |
| Sociogenomics in the 21<sup>st</sup> Century: An Introduction to the History and Potential of Genetically-informed Social Science. | Braudt DB | — | 2018 | → |
| The Benefits of Genetic Addiction Risk Score (GARS<sup>™</sup>) Testing in Substance Use Disorder (SUD). | Blum K et al. | — | 2018 | → |
| The genetic and environmental architecture of substance use development from early adolescence into young adulthood: a longitudinal twin study of comorbidity of alcohol, tobacco and illicit drug use. | Waaktaar T et al. | — | 2018 | → |
| Do addicts have free will? An empirical approach to a vexing question. | Heyman GM | — | 2017 | → |
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| The genetic epidemiology of substance use disorder: A review. | Prom-Wormley EC et al. | — | 2017 | → |
| Additive genetic contribution to symptom dimensions in major depressive disorder. | Pearson R et al. | — | 2016 | → |
| Etiological theories of addiction: A comprehensive update on neurobiological, genetic and behavioural vulnerability. | Ouzir M et al. | — | 2016 | → |
| Evidence of Shared Genome-Wide Additive Genetic Effects on Interpersonal Trauma Exposure and Generalized Vulnerability to Drug Dependence in a Population of Substance Users. | Palmer RH et al. | — | 2016 | → |
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| Genome-Wide Estimates of Heritability for Social Demographic Outcomes. | Domingue BW et al. | — | 2016 | → |
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| Smokescreen: a targeted genotyping array for addiction research. | Baurley JW et al. | — | 2016 | → |
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| Epidemiology of substance abuse in the population of Lucknow. | Kumar S et al. | — | 2015 | → |
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| Molecular Genetic Testing in Pain and Addiction: Facts, Fiction and Clinical Utility. | Blum K et al. | — | 2015 | → |
| Molecular Genetic Testing in Reward Deficiency Syndrome (RDS): Facts and Fiction. | Blum K et al. | — | 2015 | → |
| Shared additive genetic influences on DSM-IV criteria for alcohol dependence in subjects of European ancestry. | Palmer RH et al. | — | 2015 | → |