Yazar "Porjesz, Bernice" seçeneğine göre listele

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    Further Analyses of Genetic Association Between GRM8 and Alcohol Dependence Symptoms Among Young Adults
    (Alcohol Res Documentation Inc Cent Alcohol Stud Rutgers Univ, 2015) Long, Elizabeth C.; Aliev, Fazil; Wang, Jen-Chyong; Edenberg, Howard J.; Nurnberger, John, Jr.; Hesselbrock, Victor; Porjesz, Bernice
    Objective: The gene GRM8, a metabotropic glutamate receptor, has emerged as a gene of interest for its possible role in the development of alcohol dependence, with evidence of association with an electrophysiological endophenotype and level of response to alcohol as well as suggestive evidence of association with alcohol dependence. Method: The present study further investigated the association between GRM8 and alcohol dependence symptom counts among young adults using a new sample of individuals collected as part of the prospective sample (ages 18-26 years; N = 842) from the Collaborative Study on the Genetics of Alcoholism (COGA). Results: Two single-nucleotide polymorphisms were significantly associated with alcohol dependence in European Americans using the Nyholt corrected p value of .007: rs886003 (beta = -.212, p =.0002) and rs17862325 (beta = -.234, p < .0001), but not in African Americans, likely because of the lower power to detect association in this group. Conclusions: These results further implicate the role of glutamate receptor genes such as GRM8 in the development of alcohol dependence.
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    Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders
    (Springer, 2017) Cho, Seung Bin; Aliev, Fazil; Clark, Shaunna L.; Adkins, Amy E.; Edenberg, Howard J.; Bucholz, Kathleen K.; Porjesz, Bernice
    Twin studies indicate that latent genetic factors overlap across comorbid psychiatric disorders. In this study, we used a novel approach to elucidate shared genetic factors across psychiatric outcomes by clustering single nucleotide polymorphisms based on their genome-wide association patterns. We applied latent profile analysis (LPA) to p-values resulting from genome-wide association studies across three phenotypes: symptom counts of alcohol dependence (AD), antisocial personality disorder (ASP), and major depression (MD), using the European-American case-control genome-wide association study subsample of the collaborative study on the genetics of alcoholism (N = 1399). In the 3-class model, classes were characterized by overall low associations (85.6% of SNPs), relatively stronger association only with MD (6.8%), and stronger associations with AD and ASP but not with MD (7.6%), respectively. These results parallel the genetic factor structure identified in twin studies. The findings suggest that applying LPA to association results across multiple disorders may be a promising approach to identify the specific genetic etiologies underlying shared genetic variance.