title: A Comprehensive Gene Expression Meta-analysis Identifies Novel Immune Signatures in Rheumatoid Arthritis Patients.
abstract: Rheumatoid arthritis (RA), a symmetric polyarticular arthritis, has long been feared as one of the most disabling forms of arthritis. Identification of gene signatures associated with RA onset and progression would lead toward development of novel diagnostics and therapeutic interventions. This study was undertaken to identify unique gene signatures of RA patients through large-scale meta-profiling of a diverse collection of gene expression data sets. We carried out a meta-analysis of 8 publicly available RA patients' (107 RA patients and 76 healthy controls) gene expression data sets and further validated a few meta-signatures in RA patients through quantitative real-time PCR (RT-qPCR). We identified a robust meta-profile comprising 33 differentially expressed genes, which were consistently and significantly expressed across all the data sets. Our meta-analysis unearthed upregulation of a few novel gene signatures includingPLCG2, HLA-DOB, HLA-F, EIF4E2, andCYFIP2, which were validated in peripheral blood mononuclear cell samples of RA patients. Further, functional and pathway enrichment analysis reveals perturbation of several meta-genes involved in signaling pathways pertaining to inflammation, antigen presentation, hypoxia, and apoptosis during RA. Additionally, PLCG2 (phospholipase Cγ2) popped out as a novel meta-gene involved in most of the pathways relevant to RA including inflammasome activation, platelet aggregation, and activation, thereby suggesting PLCG2 as a potential therapeutic target for controlling excessive inflammation during RA. In conclusion, these findings highlight the utility of meta-analysis approach in identifying novel gene signatures that might provide mechanistic insights into disease onset, progression and possibly lead toward the development of better diagnostic and therapeutic interventions against RA.
authors.affiliation: Department of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad , Hyderabad , India.
authors.forename: Sumbul
authors.initials: S
authors.lastname: Afroz
authors.affiliation: Department of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad , Hyderabad , India.
authors.forename: Jeevan
authors.initials: J
authors.lastname: Giddaluru
authors.affiliation: Centre for Liver Research and Diagnostics, Central Laboratory for Stem Cell Research and Translational Medicine, Deccan College of Medical Sciences, Kanchanbagh , Hyderabad , India.
authors.forename: Sandeep
authors.initials: S
authors.lastname: Vishwakarma
authors.affiliation: Centre for Liver Research and Diagnostics, Central Laboratory for Stem Cell Research and Translational Medicine, Deccan College of Medical Sciences, Kanchanbagh , Hyderabad , India.
authors.forename: Saima
authors.initials: S
authors.lastname: Naz
authors.affiliation: Centre for Liver Research and Diagnostics, Central Laboratory for Stem Cell Research and Translational Medicine, Deccan College of Medical Sciences, Kanchanbagh , Hyderabad , India.
authors.forename: Aleem Ahmed
authors.initials: AA
authors.lastname: Khan
authors.affiliation: Department of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad , Hyderabad , India.
authors.forename: Nooruddin
authors.initials: N
authors.lastname: Khan
keywords: autoimmunity; meta-analysis; microarrays; rheumatoid arthritis; synovial inflammation