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Meta-Analysis
. 2015:2015:826316.
doi: 10.1155/2015/826316. Epub 2015 Jan 22.

Identification of potential transcriptomic markers in developing ankylosing spondylitis: a meta-analysis of gene expression profiles

Fang Fang  1 , Jian Pan  1 , Lixiao Xu  1 , Gang Li  1 , Jian Wang  1
Affiliations
Meta-Analysis

Identification of potential transcriptomic markers in developing ankylosing spondylitis: a meta-analysis of gene expression profiles

Fang Fang et al. Biomed Res Int. 2015.

Abstract

The goal of this study was to identify potential transcriptomic markers in developing ankylosing spondylitis by a meta-analysis of multiple public microarray datasets. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed (DE) genes in ankylosing spondylitis and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DE genes identified in the meta-analysis. Three microarray datasets (26 cases and 29 controls in total) were collected for meta-analysis. 905 consistently DE genes were identified in ankylosing spondylitis, among which 482 genes were upregulated and 423 genes were downregulated. The upregulated gene with the smallest combined rank product (RP) was GNG11 (combined RP=299.64). The downregulated gene with the smallest combined RP was S100P (combined RP=335.94). In the gene ontology (GO) analysis, the most significantly enriched GO term was "immune system process" (P=3.46×10(-26)). The most significant pathway identified in the pathway analysis was antigen processing and presentation (P=8.40×10(-5)). The consistently DE genes in ankylosing spondylitis and biological pathways associated with those DE genes identified provide valuable information for studying the pathophysiology of ankylosing spondylitis.

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Figures

Figure 1
Figure 1
Heat map for visualization of gene pattern changes across different datasets (row-wise comparison). Individual datasets were rescaled in this map to prevent the influence of study-specific effects.
Figure 2
Figure 2
Venn diagram for overlap visualization between meta-analysis results and individual dataset analysis results. Meta-DE: DE genes identified in meta-analysis; individual-DE: DE genes identified in individual dataset analysis.
Figure 3
Figure 3
Summary of the GO analysis results for the DE genes in ankylosing spondylitis.
See this image and copyright information in PMC

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