Systematic review of genome-wide gene expression studies of bipolar disorder

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Figure 1

Workflow for data processing and analysis.

Figure 2

Volcano plots showing effect size estimates by significance of each gene for the three mega-analyses. Effect sizes captured as log₂(FC) are shown on the X-axis, and significance levels measured as –log₁₀(p-value) are shown on the Y-axis. Each dot represents an individual gene. Red dots represent significantly up-regulated genes with log₂(FC) > 0.1 (FC > 1.07) at p-value < 0.05, while green dots represent significantly down-regulated genes with log₂(FC) < -0.1 (FC < -1.07) at p-value < 0.05.

Figure 3

Venn diagram showing the concordance of 382 significant differentially expressed genes with a regression beta estimate = ±0.1, equivalent to fold change (FC) > 1.07 (up-regulated) or FC < −1.07 (down-regulated) with p-value < 0.05 from the three mega-analyses.

Figure 4

Forest Plots of two genes of interest in mood disorders (q-value < 0.05) showing the estimated fold change (FC) of gene expression comparing BP cases and controls and 95% confidence interval for each study. Summary estimates are provided for any brain regions, prefrontal cortex and hippocampus.