Examining the role of common genetic variants on alcohol, tobacco, cannabis and illicit drug dependence: genetics of vulnerability to drug dependence

Abstract

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 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 [h2SNP (CI)=0.36 (0.11-0.62) and 0.33(0.07-0.58), respectively; PU = 0.25 (-0.01-0.51)]. Genetic effects were shared across the three phenotypic measures of comorbid drug problems (rSNP; rDD-PU = 0.92 (0.76-1.00), rDD-DV = 0.97 (0.87-1.00), and rPU-DV = 0.96 (0.82-1.00)). 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.

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings

“…The available genome-wide association studies (GWAS) on adulthood antisocial behaviours have thus far been too small and heterogeneous to yield any robust findings and comprehensive meta-analyses have failed to identify a single significant polymorphism associated with aggression (34, 35). Similarly, only a handful of SNPs have been found to be individually associated with different substance misuse phenotypes but a recent study adopting the genome-wide complex trait analysis (GCTA) approach found that the combined influence of all SNPs explained between 25% to 36% of the variance in different substance misuse phenotypes (36). Data on five common psychiatric disorders from the PGC was recently re-examined using multivariate GCTA models and the authors concluded that the genetic risk predictions had improved substantially with the addition of multiple genetically similar phenotypes (37).…”

Epidemiology of substance abuse in the population of Lucknow

“…Subjects addicted to the use of such substances develop a strong desire for repeated use, despite their harmful consequences. [4][5][6] The habit of chewing tobacco and areca-nut has been associated with an increase in the incidence of oral potentially malignant disorders such as oral sub-mucous fibrosis, leukoplakia and cancer. 7,8 Various substances can be grouped into three broad categories as tobacco containing substances, tobaccoless substances and substances that include alcohol, ganja, bhang and afeem.…”

The genetic epidemiology of substance use disorder: A review

“…For example, although several significant genetic associations have been reported, few associations for nicotine dependence have replicated (Lerman & Berrettini, 2003; Quaak, van Schayck, Knaapen, & van Schooten, 2009). This may be due to a variety of reasons including: (1) low effect sizes of variants where each significant variant detected by a genetic association study will have a small influence on an SUD (Marjoram, Zubair, & Nuzhdin, 2014); (2) insufficient power to detect significant associations resulting from low sample sizes particularly in single-site studies (Visscher, Brown, McCarthy, & Yang, 2012); (3) phenotypic heterogeneity due to variance in the measurement of SUDs across samples that may reflect different stages of SUD; (4) genetic heterogeneity characterized by an outcome arising from multiple sets of genes or genetic mechanisms that likely decrease the power to detect a significant genetic association specific to a substance; (5) racial/ethnic inconsistency between discovery and replication samples (i.e., participants of European ancestry in the discovery sample and African ancestry in the replication sample) that result in a failure to reproduce significant genetic association across samples as a result of differences in ancestry-related local haplotype structures at loci associated with SUD (Enoch, 2013; Melroy-Greif, et al, 2017; Polimanti, Yang, Zhao, & Gelernter, 2015; Verweij, et al, 2012) and (6) phenotypic comorbidity where the SUD diagnosis, itself, may have multiple subtypes (i.e., single-drug versus poly-drug dependence, rate of time from initiation to the development of dependence, or comorbidity between substance dependence and psychiatric conditions) with shared genetic and environmental architecture (Bi, et al, 2014; Palmer et al, 2014). Consequently, there remains discrepancies in the convergence of results from different genetic epidemiology study designs (Vrieze, McGue, Miller, Hicks, & Iacono, 2013).…”