Meta-analysis of 12 genomic studies in bipolar disorder

Michael Elashoff, Brandon W. Higgs, Robert H. Yolken, Michael B. Knable, Serge Weis, Maree J. Webster, Beata M. Barci, E. Fuller Torrey

Research output: Contribution to journalArticlepeer-review

Abstract

Multiple genome-wide expression studies of bipolar disorder have been published. However, a unified picture of the genomic basis for the disease has not yet emerged. Genes identified in one study often fail to be identified in other studies, prompting the question of whether microarray studies in the brain are inherently unreliable. To answer this question, we performed a meta-analysis of 12 microarray studies of bipolar disorder. These studies included >500 individual array samples, on a range of microarray platforms and brain regions. Although we confirmed that individual studies showed some differences in results, clear and striking regulation patterns emerged across the studies. These patterns were found at the individual gene level, at the functional level, and at the broader pathway level. The patterns were generally found to be reproducible across platform and region, and were highly statistically significant. We show that the seeming discordance between the studies was primarily a result of the following factors, which are also typical for other brain array studies: (1) Sample sizes were, in retrospect, too small; (2) criteria were at once too restrictive (generally focusing on fold changes >1.5) and too broad (generally using p<0.05 or p<0.01 as criteria for significance); and (3) statistical adjustments were not consistently applied for confounders. In addition to these general conclusions, we also summarize the primary biological findings of the meta-analysis, focusing on areas that confirm previous research and also on novel findings.

Original languageEnglish (US)
Pages (from-to)221-243
Number of pages23
JournalJournal of Molecular Neuroscience
Volume31
Issue number3
StatePublished - Mar 1 2007

Keywords

  • Bipolar disorder
  • Confounders
  • Energy production
  • Gene expression
  • Meta-analysis
  • Metallothionein

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience

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