The application of integrated bioinformatic tools to identify SRI, SMC2, PSIP1, TLE4, and MSX1 genes as potential markers in the diagnosis and therapy of osteoarthritis

Background : Osteoarthritis (OA) is the most common degenerative joint disease, leading to severe pain and functional disability for nearly 530 million people worldwide. OA is characterized by progressive loss of cartilage and synovial hyperplasia from the articulating surfaces of any diarthrodial joints, however, the majority of cases account for the hip and knee. Currently, regenerative therapy based on stem cells has emerged as one of the most promising and rapidly evolving strategies in OA. Although progression and potential regeneration can be monitored by magnetic resonance imaging (MRI), we lack proper molecular markers of joint regeneration for diagnostic and in vitro studies. Methods: Gene expression profiles of articular cartilage (chondrocytes) and synovium from OA-affected patients’ were downloaded from The Gene Expression Omnibus database (GSE179716, GSE206848, GSE239343, GSE48556) and analyzed using various bioinformatic tools and platforms: GEO2R, FunRich, C-Big, The Human Protein Atlas, STRING, Orange data mining, Jasp, Gene Ontology and Reactome. Results: OA-affected synovium and chondrocytes present differences between aurora B and C signaling. However, major biological pathways are similarly enriched with SRI, SMC2, PSIP1, TLE4, and MSX1 genes identified as prominent molecular biomarkers of OA progression and mesenchymal stem cell-based OA regeneration. Additionally, in peripheral blood mononuclear cells (PBMCs) from OA patients PSIP1 and TLE4 present (respectively) down and up-regulated mRNA levels. Conclusions: mRNA expression levels of chosen genes can indicate OA progression mainly in the in vitro studies, whereas the mRNA level ratio of PSIP1:TLE4 from PBMCs derived from OA patients can help monitor OA progression in clinical practice.