Family-based association analysis of alcohol dependence criteria and severity.
Ontology highlight
ABSTRACT: BACKGROUND:Despite the high heritability of alcohol dependence (AD), the genes found to be associated with it account for only a small proportion of its total variability. The goal of this study was to identify and analyze phenotypes based on homogeneous classes of individuals to increase the power to detect genetic risk factors contributing to the risk of AD. METHODS:The 7 individual DSM-IV criteria for AD were analyzed using latent class analysis (LCA) to identify classes defined by the pattern of endorsement of the criteria. A genome-wide association study was performed in 118 extended European American families (n = 2,322 individuals) densely affected with AD to identify genes associated with AD, with each of the 7 DSM-IV criteria, and with the probability of belonging to 2 of 3 latent classes. RESULTS:Heritability for DSM-IV AD was 61% and ranged from 17 to 60% for the other phenotypes. A single nucleotide polymorphism (SNP) in the olfactory receptor OR51L1 was significantly associated (7.3 × 10(-8) ) with the DSM-IV criterion of persistent desire to, or inability to, cut down on drinking. LCA revealed a 3-class model: the "low-risk" class (50%) rarely endorsed any criteria and none met criteria for AD; the "moderate-risk" class (33%) endorsed primarily 4 DSM-IV criteria and 48% met criteria for AD; and the "high-risk" class (17%) manifested high endorsement probabilities for most criteria and nearly all (99%) met criteria for AD. One SNP in a sodium leak channel NALCN demonstrated genome-wide significance with the high-risk class (p = 4.1 × 10(-8) ). Analyses in an independent sample did not replicate these associations. CONCLUSIONS:We explored the genetic contribution to several phenotypes derived from the DSM-IV AD criteria. The strongest evidence of association was with SNPs in NALCN and OR51L1.
SUBMITTER: Wetherill L
PROVIDER: S-EPMC3946798 | biostudies-literature | 2014 Feb
REPOSITORIES: biostudies-literature
ACCESS DATA