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Identification of distinct synovial fibroblast subsets associated with pain and progression of knee osteoarthritis using single-cell RNA sequencing

ABSTRACT: Synovial inflammation is associated with pain severity in patients with knee osteoarthritis (OA). The aim here was to determine in a population with knee OA, whether synovial tissue from areas associated with pain exhibited different synovial fibroblast subsets, compared to synovial tissue from sites not associated with pain. A further aim was to compare differences between early and end-stage disease synovial fibroblast subsets. Parapatellar synovitis was significantly associated with the pattern of patient-reported pain in knee OA patients. Synovial tissue from sites of patient-reported pain exhibited a differential transcriptomic phenotype, with distinct synovial fibroblast subsets in early OA and end-stage OA. Functional pathway analysis revealed that synovial tissue and fibroblast subsets from painful sites promoted fibrosis, inflammation and the growth and activity of neurons. The secretome of fibroblasts from early OA painful sites induced neurite outgrowth in dorsal root ganglion neurons. Sites of patient-reported pain in knee OA is associated with a different synovial tissue phenotype and distinct synovial fibroblast subsets. Further interrogation of these fibroblast pathotypes will increase our understanding of the role of synovitis in OA joint pain and provide a rationale for the therapeutic targeting of fibroblast subsets to alleviate pain in patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE176308 | GEO | 2021/10/20

REPOSITORIES: GEO

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Project description:Synovial fibroblasts in persistent inflammatory arthritis have been suggested to have parallels with cancer growth and wound healing, both of which involve a stereotypical serum response program. We tested the hypothesis that a serum response program can be used to classify diseased tissues, and investigated the serum response program in fibroblasts from multiple anatomical sites and two diseases. To test our hypothesis we utilized a bioinformatics approach to explore a publicly available microarray dataset including RA, OA and normal synovial tissue, then extended those findings in a new microarray dataset representing matched synovial, bone marrow and skin fibroblasts cultured from RA and OA patients undergoing arthroplasty. The classical fibroblast serum response program discretely classified RA, OA and normal synovial tissues. Analysis of low and high serum treated fibroblast microarray data revealed a hierarchy of control, with anatomical site the most powerful classifier followed by response to serum and then disease. In contrast to skin and bone marrow fibroblasts, exposure of synovial fibroblasts to serum led to convergence of RA and OA expression profiles. Pathway analysis revealed three inter-linked gene networks characterising OA synovial fibroblasts: Cell remodelling through insulin-like growth factors, differentiation and angiogenesis through ?3 integrin, and regulation of apoptosis through CD44. We have demonstrated that Fibroblast serum response signatures define disease at the tissue level, and that an OA specific, serum dependent repression of genes involved in cell adhesion, extracellular matrix remodelling and apoptosis is a critical discriminator between cultured OA and RA synovial fibroblasts. Fibroblasts were isolated from synovium, bone marrow and skin tissue samples taken at the time of knee or hip replacement surgery from 12 rheumatoid arthritis patients meeting the 1987 ACR criteria and 6 osteoarthritis patients diagnosed on the basis of characteristic x-ray findings and the absence of features suggestive of inflammatory arthritis. Only one hip sample was present in either disease group. Fibroblasts were maintained in fibroblast medium (consisting of 81.3% RPMI 1640, 10% FCS, 0.81x MEM non-essential amino acids, 0.81mM sodium orthopyruvate, 1.62mM glutamine, 810U/ml penicillin and 81?g/ml streptomycin) at 37°C in a humidified 5% CO2 atmosphere.

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Identification of distinct synovial fibroblast subsets associated with pain and progression of knee osteoarthritis using single-cell RNA sequencing

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