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Meta-analysis of genetic association studies on bipolar disorder.

ABSTRACT: Numerous candidate gene association studies of bipolar disorder (BP) have been carried out, but the results have been inconsistent. Individual studies are typically underpowered to detect associations with genes of small effect sizes. We conducted a meta-analysis of published candidate gene studies to evaluate the cumulative evidence. We systematically searched for all published candidate gene association studies of BP. We then carried out a random-effects meta-analysis on all polymorphisms that were reported on by three or more case-control studies. The results from meta-analyses of these genes were compared with the findings from a recent mega-analysis of eleven genome-wide association studies (GWAS) in BP performed by the Psychiatric GWAS Consortium (PGC). A total of 487 articles were included in our review. Among these, 33 polymorphisms in 18 genes were reported on by three or more case-control studies and included in the random-effects meta-analysis. Polymorphisms in BDNF, DRD4, DAOA, and TPH1, were found to be nominally significant with a P-value?

SUBMITTER: Seifuddin F

PROVIDER: S-EPMC3582382 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Meta-analysis of genetic association studies on bipolar disorder.

Seifuddin Fayaz F Mahon Pamela Belmonte PB Judy Jennifer J Pirooznia Mehdi M Jancic Dubravka D Taylor Jacob J Goes Fernando S FS Potash James B JB Zandi Peter P PP

American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics 20120509 5

Numerous candidate gene association studies of bipolar disorder (BP) have been carried out, but the results have been inconsistent. Individual studies are typically underpowered to detect associations with genes of small effect sizes. We conducted a meta-analysis of published candidate gene studies to evaluate the cumulative evidence. We systematically searched for all published candidate gene association studies of BP. We then carried out a random-effects meta-analysis on all polymorphisms that ...[more]

PMID: 22573399

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Project description:BackgroundBipolar disorder, particularly in children, is characterized by rapid cycling and switching, making circadian clock genes plausible molecular underpinnings for bipolar disorder. We previously reported work establishing mice lacking the clock gene D-box binding protein (DBP) as a stress-reactive genetic animal model of bipolar disorder. Microarray studies revealed that expression of two closely related clock genes, RAR-related orphan receptors alpha (RORA) and beta (RORB), was altered in these mice. These retinoid-related receptors are involved in a number of pathways including neurogenesis, stress response, and modulation of circadian rhythms. Here we report association studies between bipolar disorder and single-nucleotide polymorphisms (SNPs) in RORA and RORB.MethodsWe genotyped 355 RORA and RORB SNPs in a pediatric cohort consisting of a family-based sample of 153 trios and an independent, non-overlapping case-control sample of 152 cases and 140 controls. Bipolar disorder in children and adolescents is characterized by increased stress reactivity and frequent episodes of shorter duration; thus our cohort provides a potentially enriched sample for identifying genes involved in cycling and switching.ResultsWe report that four intronic RORB SNPs showed positive associations with the pediatric bipolar phenotype that survived Bonferroni correction for multiple comparisons in the case-control sample. Three RORB haplotype blocks implicating an additional 11 SNPs were also associated with the disease in the case-control sample. However, these significant associations were not replicated in the sample of trios. There was no evidence for association between pediatric bipolar disorder and any RORA SNPs or haplotype blocks after multiple-test correction. In addition, we found no strong evidence for association between the age-at-onset of bipolar disorder with any RORA or RORB SNPs.ConclusionOur findings suggest that clock genes in general and RORB in particular may be important candidates for further investigation in the search for the molecular basis of bipolar disorder.

Project description:BackgroundLittle is known about the pathogenesis of Bipolar Disorder, and even less is known about the genetic differences between its subtypes. Bipolar Disorder is classified into different subtypes, which present different symptoms and lifetime courses. While genetic studies have been conducted in Bipolar Disorder, most examined the gene expression of only Bipolar Disorder Type 1. Studies that include Bipolar Disorder Type 1 and Bipolar Disorder Type 2 often fail to differentiate them into separate conditions. Few large transcriptomic meta-analyses in Bipolar Disorder have been conducted to identify genetic pathways. Thus, using publicly available data sets we aim here to uncover significant differential gene expression that allows distinguishing Type 1 and Type 2 Bipolar Disorders, as well as find patterns in Bipolar Disorder as a whole.MethodsWe analyze 17 different gene expression data sets from different tissue in Bipolar Disorder using GEO2R and manual analysis, of which 15 contained significant differential gene expression results. We use STRING and Cytoscape to examine Gene Ontology to find significantly affected genetic pathways. We identify hub genes using cytoHubba, a plugin in Cytoscape. We find genes common to data sets of the same material or subtype.Results12 out of 15 data sets are enriched for immune system and RNA related pathways. 9 out of 15 data sets are enriched for neurocognitive and metal ion related GO terms. Analysis of Bipolar Disorder Type 1 vs Bipolar Disorder Type 2 revealed most differentially expressed genes were related to immune function, especially cytokines. Terms related to synaptic signaling and neurotransmitter secretion were found in down-regulated GO terms while terms related to neuron apoptosis and death were up-regulated. We identify the gene SNCA as a potential biomarker for overall Bipolar Disorder diagnosis due to its prevalence in our data sets.ConclusionsThe immune system and RNA related pathways are significantly enriched across the Bipolar Disorder data sets. The role of these pathways is likely more critically important to the function of Bipolar Disorder than currently understood. Further studies should clearly label the subtype of Bipolar Disorder used in their research and more effort needs to be undertaken to collect samples from Cyclothymic Disorder and Bipolar Disorder Type 2.

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Meta-analysis of genetic association studies on bipolar disorder.

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Meta-analysis of genetic association studies on bipolar disorder.

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