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Test for association of common variants in GRM7 with alcohol consumption
Whitney E Melroy-Greif1, Csaba Vadasz2, Helen M Kamens3
1Department of Integrative Physiology, University of Colorado, Boulder, CO 80309, USA; Institute for Behavioral Genetics, University of Colorado, Boulder, CO 80309, USA.
Abstract:
Recent work using a mouse model has identified the glutamate metabotropic receptor 7 (Grm7) gene as a strong candidate gene for alcohol consumption. Although there has been some work examining the effect of human glutamate metabotropic receptor 7 (GRM7) polymorphisms on human substance use disorders, the majority of the work has focused on other psychiatric disorders such as ADHD, major depressive disorder, schizophrenia, bipolar disorder, panic disorder, and autism spectrum disorders. The current study aimed to evaluate evidence for association between GRM7 and alcohol behaviors in humans using a single nucleotide polymorphism (SNP) approach, as well as a gene-based approach. Using 1803 non-Hispanic European Americans (EAs) (source: the Colorado Center on Antisocial Drug Dependence [CADD]) and 1049 EA subjects from an independent replication sample (source: the Genetics of Antisocial Drug Dependence [GADD]), two SNPs in GRM7 were examined for possible association with alcohol consumption using two family-based association tests implemented in FBAT and QTDT. Rs3749380 was suggestively associated with alcohol consumption in the CADD sample (p = 0.010) with the minor T allele conferring risk. There was no evidence for association in the GADD sample. A gene-based test using four Genome-Wide Association Studies (GWAS) revealed no association between variation in GRM7 and alcohol consumption. This study had several limitations: the SNPs chosen likely do not tag expression quantitative trait loci; a human alcohol consumption phenotype was used, complicating the interpretation with respect to rodent studies that found evidence for a cis-regulatory link between alcohol preference and Grm7; and only common SNPs imputed in all four datasets were included in the gene-based test. These limitations highlight the fact that rare variants, some potentially important common signals in the gene, and regions farther upstream were not examined.
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