Large scale differential gene expression analysis identifies genes associated with Bipolar Disorder

Abstract Background Bipolar disorder (BD) remains one of the most common psychiatric disorders with high morbidity and mortality. Several polymorphisms have been found to be implicated in the pathogenesis of BD, however, these loci have small effect sizes that fail to explain the high heritability of the disease. Here, we attempt to better understand the genetic basis of bipolar disorder by identifying differentially expressed genes (DEG) in post-mortem brain tissues of patients with BD versus normal controls. Methods Nine publicly available gene expression data sets with 702 samples derived from human post-mortem brain tissues were used for differential expression analysis. 7 data sets were used for the discovery of the gene signature and the other two were left for independent validation. The multi-cohort analysis was performed using a random-effects model utilizing R and MetaIntegrator package. Results The analysis resulted in the identification of 13 up-regulated and 9 down-regulated genes in BD. The BD gene signature was further validated in two independent data sets and resulted in an Area Under the ROC Curve (AUC) of 0.74 and 0.73, respectively. Gene set enrichment analysis was performed and resulted in the identification of several biological processes and pathways related to BD including Ca transport, inflammation and DNA damage response. Conclusion Our findings support the previous findings that link BD pathogenesis to abnormalities in glial inflammation and calcium transport and also identify several other biological processes not previously reported to be associated with the development of BD. Such findings will improve our understanding of the genetic basis underlying BD and may have future clinical implications.