Rheumatoid arthritis (RA) is an autoimmune disease that involves T and B cells and their reciprocal immune interactions with proinflammatory cytokines. T cells, an essential part of the immune system, play an important role in RA. T helper 1 (Th1) cells induce interferon-γ (IFN-γ), tumour necrosis factor-α (TNF-α), and interleukin (IL)-2, which are proinflammatory cytokines, leading to cartilage destruction and bone erosion. Th2 cells primarily secrete IL-4, IL-5, and IL-13, which exert anti-inflammatory and anti-osteoclastogenic effects in inflammatory arthritis models. IL-22 secreted by Th17 cells promotes the proliferation of synovial fibroblasts through induction of the chemokine C-C chemokine ligand 2 (CCL2). T follicular helper (Tfh) cells produce IL-21, which is key for B cell stimulation by the C-X-C chemokine receptor 5 (CXCR5) and coexpression with programmed cell death-1 (PD-1) and/or inducible T cell costimulator (ICOS). PD-1 inhibits T cell proliferation and cytokine production. In addition, there are many immunomodulatory agents that promote or inhibit the immunomodulatory role of
Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA. First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) was used to verify the effectiveness of markers.Aims
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Rheumatoid arthritis (RA) is a systematic autoimmune disorder, characterized by synovial inflammation, bone and cartilage destruction, and disease involvement in multiple organs. Although numerous drugs are employed in RA treatment, some respond little and suffer from severe side effects. This study aimed to screen the candidate therapeutic targets and promising drugs in a novel method. We developed a module-based and cumulatively scoring approach that is a deeper-layer application of weighted gene co-expression network (WGCNA) and connectivity map (CMap) based on the high-throughput datasets.Aims
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