Arthritis Research & Therapy (Aug 2017)
Biosemantics guided gene expression profiling of Sjögren’s syndrome: a comparative analysis with systemic lupus erythematosus and rheumatoid arthritis
Abstract
Abstract Background Sjögren's syndrome (SS) shares many clinical and pathological similarities with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). These autoimmune diseases mostly affect women. In this study, concept profile analysis (CPA) and gene expression meta-analysis were used to identify genes potentially involved in SS pathogenesis. Methods Human genes associated with SS, SLE, and RA were identified using the CPA tool, Anni 2.1. The differential mRNA expression of genes common to SS and SLE (SS-SLE) was determined in female peripheral blood mononuclear cells (PBMCs) using NCBI-GEO2R. Differentially expressed (DE) SS-SLE PBMC genes in common with the SS-SLE CPA-identified genes were analyzed for differential expression in salivary glands or synovial biopsies, and for genes common to SS and RA and SLE and RA, analyzing differential expression in salivary glands in SS, synovial fibroblasts in RA, and synovial fluid in SLE. Among common genes, DE genes found in salivary gland mRNA expression in patients with SS were used for gene enrichment and SS molecular network construction. Secondary analysis was performed to identify DE genes unique to the disease site tissues, by excluding PBMC and CPA common DE genes to complement the SS network. Results We identified 22 DE genes in salivary gland datasets in SS that have not previously been clearly associated with SS pathogenesis. Among these, higher levels of checkpoint kinase 1 (CHEK1), V-Ets avian erythroblastosis virus E26 oncogene homolog 1 (ETS1), and lymphoid enhancer binding factor 1 (LEF1) were significantly correlated with higher matrix metalloproteinase 9 (MMP9) levels. Higher MMP9 levels have been implicated in degradation of salivary gland structural integrity, leading to hypo-salivation in patients with SS. Salivary gland mRNA expression of MMP9 and the expression of cytokine CXCL10 were higher in patients with SS. CXCL10 has been shown to increase MMP9 expression and therefore may also play an important role in SS pathogenesis. Conclusion Using CPA and gene expression analysis, we identified factors targeting MMP9 expression and/or function, namely CHEK1, CXCL10, ETS1, LEF1, and tissue inhibitor of metalloproteinase 1; altered mRNA expression of these could increase expression/activity of MMP9 in a concerted manner, thereby potentially impacting SS pathogenesis.
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