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An Integrative Genomic Study Implicates the Postsynaptic Density in the Pathogenesis of Bipolar Disorder.


ABSTRACT: Genome-wide association studies (GWAS) have identified several common variants associated with bipolar disorder (BD), but the biological meaning of these findings remains unclear. Integrative genomics-the integration of GWAS signals with gene expression data-may illuminate genes and gene networks that have key roles in the pathogenesis of BD. We applied weighted gene co-expression network analysis (WGCNA), which exploits patterns of co-expression among genes, to brain transcriptome data obtained by sequencing of poly-A RNA derived from postmortem dorsolateral prefrontal cortex from people with BD, along with age- and sex-matched controls. WGCNA identified 33 gene modules. Many of the modules corresponded closely to those previously reported in human cortex. Three modules were associated with BD, enriched for genes differentially expressed in BD, and also enriched for signals in prior GWAS of BD. Functional analysis of genes within these modules revealed significant enrichment of several functionally related sets of genes, especially those involved in the postsynaptic density (PSD). These results provide convergent support for the hypothesis that dysregulation of genes involved in the PSD is a key factor in the pathogenesis of BD. If replicated in larger samples, these findings could point toward new therapeutic targets for BD.

SUBMITTER: Akula N 

PROVIDER: S-EPMC4707835 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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An Integrative Genomic Study Implicates the Postsynaptic Density in the Pathogenesis of Bipolar Disorder.

Akula Nirmala N   Wendland Jens R JR   Choi Kwang H KH   McMahon Francis J FJ  

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 20150727 3


Genome-wide association studies (GWAS) have identified several common variants associated with bipolar disorder (BD), but the biological meaning of these findings remains unclear. Integrative genomics-the integration of GWAS signals with gene expression data-may illuminate genes and gene networks that have key roles in the pathogenesis of BD. We applied weighted gene co-expression network analysis (WGCNA), which exploits patterns of co-expression among genes, to brain transcriptome data obtained  ...[more]

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