Background Rheumatoid Arthritis (RA) is a systemic autoimmune inflammatory disease represented by synovitis as well as bone and cartilage damage leading to articular destruction and other co-morbidities. The synovitis in RA is typified by the migration and proliferation of immune cells leading to uncontrolled cytokine and chemokine production and tissue damage.
Studies have shown that aberrant micro RNA (miRNA) expression in the peripheral mononuclear cells and synovia might lead to the molecular mechanisms that cause RA pathogenesis.
Objectives In this study, we investigate the genomic and miRNA signatures linked with the pathogenesis of RA using systems immunological techniques.
Methods Raw microarray gene expression data (Affymetrix CEL files) derived from studies using whole blood, synovium, synovial macrophages, and synovial fibroblasts from RA patients were downloaded from the Gene Expression Omnibus (GEO) and analysed by Genespring GX 12.6 software (Agilent, USA). The statistical significance (P<0.05) was calculated by ANOVA (2-way) with Benjamini Hochberg Correction. The significantly expressed genes were selected by a standard 2-fold cut-off compared with the normal controls and investigated by Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 and Ingenuity Pathway Analysis (IPA) knowledgebase (Qiagen, USA) for the identification of canonical and novel pathways implicated in RA. Besides, the miRNA expression data (Agilent, USA) of RA patients obtained from GEO were also analysed using Genespring GX 12.6 to decipher the disease-associated pathways regulated by miRNAs.
Results Our results show an imbalance in proinflammatory and anti-inflammatory cytokines and chemokines in RA. These proinflammatory genes play a key role in the destruction of adjacent cartilages and sub-chondral bone erosions in RA. Furthermore, we have identified novel miRNA signatures in the T-cells of RA patients that regulate the expression of genomic signatures associated with RA pathogenesis.
Conclusions The analysis of high throughput gene and miRNA expression data from RA patients is important to comprehend various disease causing genomic and miRNA signatures. Besides, It may help to effectively formulate individualized medical care to control the disease-associated pathogenic mechanism (s) and successfully reduce the incidence of relapse and achieve remission in RA patients.
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Acknowledgements This study was supported by the NSTIP strategic technologies program in the Kingdom of Saudi Arabia (KSA) by the Project Numbers 12-BIO2719-03 and 12-BIO2267-03. The authors also acknowledge with thanks the Science and Technology Unit (STU), King Abdulaziz University (KAU) for technical support.
Disclosure of Interest P. Pushparaj Grant/research support from: NSTIP Strategic Technologies Program Project Numbers 12-BIO2719-03 and 12-BIO2267-03, L. Damiati: None declared, S. Bahlas: None declared