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

OBJECTIVE: 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. DESIGN: 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). RESULTS: Following statistical integration of individual studies (N=153 total subjects, N=139 after quality control), 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. CONCLUSIONS: End-stage OA synovium is markedly enriched for neuroinflammatory and neuro-immune signaling, putatively governed by STAT1, FLI1, and VDR.