Genetics of bipolar disorder.
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ABSTRACT:
SUBMITTER: Escamilla MA
PROVIDER: S-EPMC3181866 | biostudies-literature | 2008
REPOSITORIES: biostudies-literature
Publications
Genetics of bipolar disorder.
Escamilla Michael A MA Zavala Juan M JM
Dialogues in clinical neuroscience 20080101 2
Bipolar disorder especially the most severe type (type I), has a strong genetic component. Family studies suggest that a small number of genes of modest effect are involved in this disorder. Family-based studies have identified a number of chromosomal regions linked to bipolar disorder, and progress is currently being made in identifying positional candidate genes within those regions. A number of candidate genes have also shown evidence of association with bipolar disorder, and genome-wide asso ...[more]
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Project description:Although genetic studies of Bipolar Disorder have been pursued for decades, it has only been in the last several years that clearly replicated findings have emerged. These findings, typically of modest effects, point to a polygenic genetic architecture consisting of multiple common and rare susceptibility variants. While larger genome-wide association studies are ongoing, the advent of whole exome and genome sequencing should lead to the identification of rare, and potentially more penetrant, variants. Progress along both fronts will provide novel insights into the biology of Bipolar Disorder and help usher in a new era of personalized medicine and improved treatments.
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Project description:BackgroundBipolar disorder (BD) presents with high obesity and type 2 diabetes (T2D) and pathophysiological and phenomenological abnormalities shared with cardiometabolic disorders. Genomic studies may help define if they share genetic liability. This selective review of BD with obesity and T2D will focus on genomic studies, stress their current limitations and guide future steps in developing the field.MethodsWe searched electronic databases (PubMed, Scopus) until December 2021 to identify genome-wide association studies, polygenic risk score analyses, and functional genomics of BD accounting for body mass index (BMI), obesity, or T2D.ResultsThe first genome-wide association studies (GWAS) of BD accounting for obesity found a promising genome-wide association in an intronic gene variant of TCF7L2 that was further replicated. Polygenic risk scores of obesity and T2D have also been associated with BD, yet, no genetic correlations have been demonstrated. Finally, human-induced stem cell studies of the intronic variant in TCF7L2 show a potential biological impact of the products of this genetic variant in BD risk.LimitationsThe narrative nature of this review.ConclusionsFindings from BD GWAS accounting for obesity and their functional testing, have prompted potential biological insights. Yet, BD, obesity, and T2D display high phenotypic, genetic, and population-related heterogeneity, limiting our ability to detect genetic associations. Further studies should refine cardiometabolic phenotypes, test gene-environmental interactions and add population diversity.
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Project description:BackgroundDisentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype-phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted.ResultsTwo of these rules-one associated with eating disorder and the other with anxiety-remained significant in an independent dataset after robust correction for multiple testing. Both showed considerable effect sizes (odds ratio ~ 3.4 and 3.0, respectively) and support previously reported molecular biological findings.ConclusionOur approach detected novel specific genotype-phenotype relationships in BD that were missed by standard analyses like GWAS. While we developed and applied our method within the context of BD gene discovery, it may facilitate identifying highly specific genotype-phenotype relationships in subsets of genome-wide data sets of other complex phenotype with similar epidemiological properties and challenges to gene discovery efforts.
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2019-11-12 | PXD009219 | Pride