Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis

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• 作者：Wei Xia ; Jian Wu ; Fei-Yan Deng ; Long-Fei Wu ; Yong-Hong Zhang ; Yu-Fan Guo…
• 关键词：Rheumatoid arthritis ; Multi ; dataset analysis ; Integrative analysis ; Shared genetic marker
• 刊名：Immunogenetics
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：69
• 期：2
• 页码：77-86
• 全文大小：
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Immunology; Human Genetics; Gene Function; Cell Biology; Allergology;
• 出版者：Springer Berlin Heidelberg
• ISSN：1432-1211
• 卷排序：69

文摘

Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.