Abstract
Despite compelling evidence for a major genetic contribution to risk of bipolar mood disorder, conclusive evidence implicating specific genes or pathophysiological systems has proved elusive. In part this is likely to be related to the unknown validity of current phenotype definitions and consequent aetiological heterogeneity of samples. In the recent Wellcome Trust Case Control Consortium genome-wide association analysis of bipolar disorder (1868 cases, 2938 controls) one of the most strongly associated polymorphisms lay within the gene encoding the GABAA receptor β1 subunit, GABRB1. Aiming to increase biological homogeneity, we sought the diagnostic subset that showed the strongest signal at this polymorphism and used this to test for independent evidence of association with other members of the GABAA receptor gene family. The index signal was significantly enriched in the 279 cases meeting Research Diagnostic Criteria for schizoaffective disorder, bipolar type (P=3.8 × 10−6). Independently, these cases showed strong evidence that variation in GABAA receptor genes influences risk for this phenotype (independent system-wide P=6.6 × 10−5) with association signals also at GABRA4, GABRB3, GABRA5 and GABRR1. Our findings have the potential to inform understanding of presentation, pathogenesis and nosology of bipolar disorders. Our method of phenotype refinement may be useful in studies of other complex psychiatric and non-psychiatric disorders.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Neuroscience and Mental Health Research Institute (NMHRI) Medicine MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Systems Immunity Research Institute (SIURI) |
Subjects: | R Medicine > RZ Other systems of medicine |
Uncontrolled Keywords: | bipolar disorder; schizoaffective disorder; GABAA receptors; genetic; nosology |
Publisher: | Nature Publishing Group |
ISSN: | 1359-4184 |
Last Modified: | 06 Jun 2024 17:52 |
URI: | https://orca.cardiff.ac.uk/id/eprint/27849 |
Citation Data
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