Shared additive genetic influences on DSM‐IV criteria for alcohol dependence in subjects of European ancestry

Abstract

Background and Aims Genetic studies of alcohol dependence (AD) have identified several candidate loci and genes, but most observed effects are small and difficult to reproduce. A plausible explanation for inconsistent findings may be a violation of the assumption that genetic factors contributing to each of the seven DSM-IV criteria point to a single underlying dimension of risk. Given that recent twin studies suggest that the genetic architecture of AD is complex and likely involves multiple discrete genetic factors, the current study employed common single nucleotide polymorphisms in two multivariate genetic models to examine the assumption that the genetic risk underlying DSM-IV AD is unitary. Design, setting, participants, measurements AD symptoms and genome-wide SNP data from 2596 individuals of European descent from the Study of Addiction: Genetics and Environment were analyzed using Genomic-relatedness-matrix restricted maximum likelihood. DSM-IV AD symptom covariance was described using two multivariate genetic factor models. Findings Common SNPs explained 30% (s.e.=0.136, p=0.012) of the variance in AD diagnosis. Additive genetic effects varied across AD symptoms. The Common Pathway Model approach suggested that symptoms could be described by a single latent variable that had a SNP-heritability of 31% (0.130, p=0.008). Likewise, the Exploratory Genetic Factor Model approach suggested that the genetic variance/covariance across symptoms could be represented by a single genetic factor that accounted for at least 60% of the genetic variance in any one symptom. Conclusion Additive genetic effects on DSM-IV alcohol dependence criteria overlap. The assumption of common genetic effects across alcohol dependence symptoms appears to be a valid assumption.

Trans-ancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

“…The estimated h 2 g = .09 for AD in EU is 511 only modestly lower than those recently reported for alcohol consumption (h 2 g = .13) 37 512 and AUDIT scores (h 2 g = .12) 38 , and comparable to estimates derived for cigarettes-per-513 day 33 . Our h 2 g estimate is lower than a prior report 8 , likely reflecting a combination of 514 differences in estimation method and greater heterogeneity in ascertainment strategy across samples in the current study. The latter is especially relevant given that we 516 incorporated population-based cohorts with a wide range of ages at ascertainment and 517 cultural environments, as well as cohorts enriched for other substance use disorders.…”

Shared additive genetic variation for alcohol dependence among subjects of African and European ancestry

“…These estimates are similar to the 30 percent SNP‐based heritability estimated by Palmer et al . () by using an AD factor in a sample in EAs from only the SAGE subsample, within the margin of error. Recent studies that utilized AD diagnosis, rather than the factor score, have estimated a heritability of 21 percent in a Caucasian sample (Vrieze et al .…”

“…; Palmer et al . ). Data for participants in each study were subset to include only those participants who were unrelated and were genetically determined to be EA or AA; consequently, data for 6514 genetically determined EAs and 2196 genetically determined AAs who had phenotypic data were used for factor analysis.…”

Genome-wide single nucleotide polymorphism heritability of nicotine dependence as a multidimensional phenotype

“…The effects of common SNPs appear to account for a relatively large portion of genetic effects detected using traditional twin modeling approaches suggesting that candidate and whole genome genetic association (including GREML) approaches focused on common SNPs will have utility for contributing to the understanding of ND genetic risk pathways. As illustrated by the present article and recent addiction studies (Palmer et al , 2015a, Palmer et al , 2015b, Vrieze et al , 2013), GREML holds unique promise for advancing the field to the extent that researchers find novel ways to parse the observed genetic variance to relevant genetic loci (either by function or prior knowledge). Likewise, the ability to examine the aggregate genetic effect allows for the explicit testing of the assumptions of GWAS.…”

“…SNPs had to meet the following criteria for inclusion in the study: minor allele frequency >1%, genotyping call rate ≥99%, and a Hardy–Weinberg Equilibrium (HWE) p-value greater than 0.0001 among subjects of European descent (Palmer et al , 2015b). Genomic principal component analysis was used to identify and retain subjects of European ancestry by including samples from the haplotype mapping project (HAPMAP; i.e., CEPH, Yoruban, Han Chinese, and Japanese) as ancestral reference groups in the genetic principal component analysis in SNP and Variation Suite (Palmer et al , 2015a, SNP & Variation Suite [Version 8.3.4]).…”