Cross-platform transcriptomic data integration identifies an overactive neuro-immune signature in human osteoarthritis synovium

Chronic synovitis is associated with osteoarthritis (OA) pain, but the molecular underpinnings remain unclear. Our objective was to characterize the transcriptional phenotype of OA synovium with a focus on signaling relevant to pain. Eight publicly-available microarray and RNA-sequencing GEO datasets from human non-OA and OA subjects underwent quality control and re-analysis for differentially-expressed genes (DEGs). Cross-platform statistical integration was performed via a weighted Z-test to combine detection power across datasets. Gene set enrichment, cell type enrichment, and regulon analyses were performed. Human single-cell RNA sequencing data was used to map gene expression to cell types. Ligand-receptor interactions were predicted via multi-omic data from human dorsal root ganglia (DRG). Following statistical integration of individual studies (N=153 subjects), gene set enrichment analysis identified 276 differentially-activated pathway terms in OA synovium, including strong enrichment for pathways related to innate and adaptive immunity (notably MHC Class II) and fibrotic remodeling-relevant extracellular matrix organization. VEGF signaling and angiogenesis-related terms were downregulated. Enriched pain and neuronal pathways primarily related to neuro-immune interactions, including neuroinflammation, and were associated with macrophages, B and T lymphocytes, and synovial fibroblasts. A gene regulatory network comprised of STAT1, FLI1, and VDR putatively governed the expression of 27 genes driving neuro-immune signaling. An unbiased synovium-DRG interactome predicted 76 potential interactions between synovial cells and DRG nociceptors, involving 68 neuronal receptors interacting with 32 ligands overexpressed in OA synovium. End-stage OA synovium is markedly enriched for neuroinflammatory and neuro-immune signaling, putatively governed by STAT1, FLI1, and VDR.