Abstract / Summary
Osteoarthritis (OA) is a whole-joint disorder lacking disease-modifying drugs. The synovium, particularly fibroblast-like synoviocytes (FLS), plays a key role in progression. This study aimed to identify novel synovial therapeutic targets using a bioinformatic repurposing approach. Transcriptomic datasets of human osteoarthritis (OA) and non-OA knee synovium were analyzed to identify common differentially expressed genes (DEGs). The Connectivity Map (CMap) was queried with the directional DEG signature to predict compounds capable of reversing the OA-associated expression pattern. The leading candidate pathway was evaluated in primary human OA fibroblast-like synoviocytes (FLS) using azacitidine and DNMT3A knockdown and in a surgically induced rat knee OA model using intra-articular shRNA. Sixty-one DEGs overlapped across the three synovial datasets, and 60 directionally concordant genes were used for the CMap query. Azacitidine was among the compounds with strong negative connectivity, and its annotated DNMT target DNMT3A was increased in human OA synovium and OA-FLS. Azacitidine treatment and DNMT3A knockdown reduced global DNA methylation and inflammatory and catabolic gene expression in OA-FLS. Conditioned-medium experiments supported an indirect contribution of OA-FLS to chondrocyte inflammatory activation. Intra-articular azacitidine or shDNMT3A attenuated synovitis and cartilage damage in the rat knee OA model. These findings identify synovial DNMT3A as a candidate epigenetic regulator associated with OA inflammation and support further evaluation of selective, locally delivered DNMT3A inhibition. Locus-specific methylation studies, safety testing, and validation in additional OA models are required before disease-modifying or clinical efficacy can be inferred.