Dataset Information

Pathway analysis using information from allele-specific gene methylation in genome-wide association studies for bipolar disorder.

ABSTRACT: Bipolar disorder (BPD) is a complex psychiatric trait with high heritability. Despite efforts through conducting genome-wide association (GWA) studies, the success of identifying susceptibility loci for BPD has been limited, which is partially attributed to the complex nature of its pathogenesis. Pathway-based analytic strategy is a powerful tool to explore joint effects of gene sets within specific biological pathways. Additionally, to incorporate other aspects of genomic data into pathway analysis may further enhance our understanding for the underlying mechanisms for BPD. Patterns of DNA methylation play important roles in regulating gene expression and function. A commonly observed phenomenon, allele-specific methylation (ASM) describes the associations between genetic variants and DNA methylation patterns. The present study aimed to identify biological pathways that are involve in the pathogenesis of BPD while incorporating brain specific ASM information in pathway analysis using two large-scale GWA datasets in Caucasian populations. A weighting scheme was adopted to take ASM information into consideration for each pathway. After multiple testing corrections, we identified 88 and 15 enriched pathways for their biological relevance for BPD in the Genetic Association Information Network (GAIN) and the Wellcome Trust Case Control Consortium dataset, respectively. Many of these pathways were significant only when applying the weighting scheme. Three ion channel related pathways were consistently identified in both datasets. Results in the GAIN dataset also suggest for the roles of extracellular matrix in brain for BPD. Findings from Gene Ontology (GO) analysis exhibited functional enrichment among genes of non-GO pathways in activity of gated channel, transporter, and neurotransmitter receptor. We demonstrated that integrating different data sources with pathway analysis provides an avenue to identify promising and novel biological pathways for exploring the underlying molecular mechanisms for bipolar disorder. Further basic research can be conducted to target the biological mechanisms for the identified genes and pathways.

SUBMITTER: Chuang LC

PROVIDER: S-EPMC3541404 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Pathway analysis using information from allele-specific gene methylation in genome-wide association studies for bipolar disorder.

Chuang Li-Chung LC Kao Chung-Feng CF Shih Wei-Liang WL Kuo Po-Hsiu PH

PloS one 20130109 1

Bipolar disorder (BPD) is a complex psychiatric trait with high heritability. Despite efforts through conducting genome-wide association (GWA) studies, the success of identifying susceptibility loci for BPD has been limited, which is partially attributed to the complex nature of its pathogenesis. Pathway-based analytic strategy is a powerful tool to explore joint effects of gene sets within specific biological pathways. Additionally, to incorporate other aspects of genomic data into pathway anal ...[more]

PMID: 23326387

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Project description:Numerous genome-wide gene expression studies of bipolar disorder (BP) have been carried out. These studies are heterogeneous, underpowered and use overlapping samples. We conducted a systematic review of these studies to synthesize the current findings.We identified all genome-wide gene expression studies on BP in humans. We then carried out a quantitative mega-analysis of studies done with post-mortem brain tissue. We obtained raw data from each study and used standardized procedures to process and analyze the data. We then combined the data and conducted three separate mega-analyses on samples from 1) any region of the brain (9 studies); 2) the prefrontal cortex (PFC) (6 studies); and 3) the hippocampus (2 studies). To minimize heterogeneity across studies, we focused primarily on the most numerous, recent and comprehensive studies.A total of 30 genome-wide gene expression studies of BP done with blood or brain tissue were identified. We included 10 studies with data on 211 microarrays on 57 unique BP cases and 229 microarrays on 60 unique controls in the quantitative mega-analysis. A total of 382 genes were identified as significantly differentially expressed by the three analyses. Eleven genes survived correction for multiple testing with a q-value < 0.05 in the PFC. Among these were FKBP5 and WFS1, which have been previously implicated in mood disorders. Pathway analyses suggested a role for metallothionein proteins, MAP Kinase phosphotases, and neuropeptides.We provided an up-to-date summary of results from gene expression studies of the brain in BP. Our analyses focused on the highest quality data available and provided results by brain region so that similarities and differences can be examined relative to disease status. The results are available for closer inspection on-line at Metamoodics [http://metamoodics.igm.jhmi.edu/], where investigators can look up any genes of interest and view the current results in their genomic context and in relation to leading findings from other genomic experiments in bipolar disorder.

Dataset Information

Pathway analysis using information from allele-specific gene methylation in genome-wide association studies for bipolar disorder.

Publications

Pathway analysis using information from allele-specific gene methylation in genome-wide association studies for bipolar disorder.

Similar Datasets

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