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Pham X, Sun C, Chen X, van den Oord EJ, Neale MC, Kendler KS, Hettema JM.
Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia; Department of Human Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia; Department of Pharmacy, Center for Biomarker Research and Personalized Medicine, Virginia Commonwealth University, Richmond, Virginia
Background: Human anxiety disorders are complex diseases with relatively unknown etiology. Dysfunction of the Gamma-aminobutyric acid (GABA) system has been implicated in many neuropsychiatric conditions, including anxiety and depressive disorders. In this investigation, we explored four GABA receptor genes for their possible associations with genetic risk for anxiety disorders and depression.
Methods: Our study sample consisted of 589 cases and 539 controls selected from a large population-based twin registry based upon a latent genetic risk factor shared by several anxiety disorders, major depression, and neuroticism. We subjected these to a two-stage protocol, in which all candidate genetic markers were screened for association in stage 1 (N=376), the positive results of which were tested for replication in stage 2 (N=752). We analyzed data from 26 single nucleotide polymorphisms (SNPs) from four GABA receptor genes: GABRA2, GABRA3, GABRA6, and GABRG2.
Results: Of the 26 SNPs genotyped in stage 1, we identified two markers in GABRA3 that met the threshold (P.1) to be tested in stage 2. Phenotypic associations of these two markers failed to replicate in stage 2.
Conclusions: These findings suggest that common variation in the GABRA2, GABRA3, GABRA6, and GABRG2 genes does not play a major role in liability to anxiety spectrum disorders.
(Text has been reformatted for online visual clarity, links added; ed.)
tags: anxiety disorders genetics
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Epidemiological studies describing population characteristics which collect data at one point in time and then consider relationships between observed characteristics.. Because they don't look at time trends they cannot establish causes.
