Article Text

PDF
THU0494 Meta-Analysis of Differentially Expressed Genes in Ankylosing Spondylitis
  1. Y.H. Lee1,
  2. S.J. Choi2,
  3. J.D. Ji2,
  4. G.G. Song2
  1. 1Rheumatology
  2. 2Korea University Medicial Center, Seoul, Korea, Republic Of

Abstract

Background Microarrays measure the expression of thousands of genes simultaneously on a genome-wide scale. Alterations in genetic profiles can be correlated to altered gene functions and biochemical activities. Although many microarray studies have produced lists of differentially expressed (DE) genes, there tend to be inconsistencies between studies due to the limitations of small sample sizes and variable results.

Objectives The purpose of this study was to identify differentially expressed (DE) genes and biological processes associated with changes in gene expression in ankylosing spondylitis (AS) using meta-analysis approach.

Methods We performed a meta-analysis using the integrative meta-analysis of expression data (INMEX) program on publicly available microarray AS Gene Expression Omnibus (GEO) datasets. We performed Gene Ontology (GO) enrichment analyses and pathway analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG).

Results Four GEO datasets, including 31 cases and 39 controls, were available for the meta-analysis. We identified 65 genes across the studies that were consistently DE in AS cases vs. controls (23 up-regulated and 42 down-regulated). The up-regulated gene with the largest effect size (ES; -1.2628, P=0.020951) was ITM2A (integral membrane protein 2A), which is expressed by CD4+ T cells and plays a role in activation of T cells. The up-regulated gene with the lowest P-value (0.005673) was TGFBR3 (transforming growth factor beta receptor III), which is a true BMD-associated gene as part of the TGF pathway. The down-regulated gene with the largest ES (1.2299, P=0.040075) was MRPS11 (mitochondrial ribosomal protein S11). The most significant GO enrichment was in the respiratory electron transport chain category (P=1.67x10–9).

Conclusions Our meta-analysis identified genes including ITM2A and TGFBR3 that were consistently DE and biological pathways associated with gene expression changes in AS.

References

  1. Xia J, Fjell CD, Mayer ML, Pena OM, Wishart DS, Hancock RE. INMEX–a web-based tool for integrative meta-analysis of expression data. Nucleic Acids Res. 2013;41(W1):W63-W70.

Disclosure of Interest : None declared

DOI 10.1136/annrheumdis-2014-eular.1187

Statistics from Altmetric.com

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.