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Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning

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机构: [1]Jiangnan Univ, Wuxi Sch Med, Wuxi 214000, Jiangsu, Peoples R China [2]Shanghai Jiao Tong Univ, Ctr Spinal Minimally Invas Res, Lab Key Technol & Mat Minimally Invas Spine Surg, Dept Orthopaed,Tongren Hosp,Hongqiao Int Inst Med,, 1111 XianXia Rd, Shanghai 200336, Peoples R China
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关键词: Osteoarthritis Infrapatellar fat pad Synovial macrophages scRNA-seq Machine learning Diagnostic signature

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BackgroundOsteoarthritis (OA) is the leading cause of degenerative joint disease, with total joint replacement as the only definitive cure. However, no disease-modifying therapy is currently available. Inflammation and fibrosis in the infrapatellar fat pad (IPFP) contribute to OA onset and progression. However, the cellular composition and molecular mechanisms in the IPFP microenvironment remain unclear. This study investigates the functions of OA-macrophages and their clinical significance.MethodsWe analyzed single-cell RNA sequencing (scRNA-seq) data from normal and OA patients. Enrichment analysis revealed differences in biological pathways across cell types. Pseudotime and cell-cell communication analyses revealed the developmental trajectory and interactions of OA-macrophages with other cell types. Machine learning (ML) algorithms identified feature genes of OA-macrophages. An OAMGS diagnostic score was developed, and CIBERSORT was used to analyze immune infiltration and its association with immune cells. Rat OA and normal models were established, and feature gene expression was validated using immunofluorescence (IF) staining and quantitative reverse transcription PCR (RT-qPCR).ResultsOA-macrophages play a central role in inflammation and fibrosis, enhancing leukocyte recruitment, chondrocyte apoptosis, and angiogenesis. They interact with chondrocytes, endothelial cells, and fibroblasts via CXCL and NF-kappa B signaling. High-dimensional weighted gene co-expression network analysis (hdWGCNA) identified 352 module genes linked to OA-macrophages. Machine learning developed a four-gene-based OAMGS score that accurately identifies OA-macrophages, with an AUC of 1 in the discovery cohort and 0.990 in an external cohort. Gene expression was validated in the OA model using RT-qPCR and IF.ConclusionThis study identifies a macrophage subcluster elevated in OA patients. OA-macrophages play an immunoregulatory role and may serve as diagnostic markers. The OAMGS score, based on four genes, provides an accurate diagnostic tool and potential therapeutic target for OA.

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大类 | 3 区 医学
小类 | 3 区 骨科
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大类 | 3 区 医学
小类 | 3 区 骨科
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Q1 ORTHOPEDICS
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Q1 ORTHOPEDICS

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第一作者机构: [1]Jiangnan Univ, Wuxi Sch Med, Wuxi 214000, Jiangsu, Peoples R China [2]Shanghai Jiao Tong Univ, Ctr Spinal Minimally Invas Res, Lab Key Technol & Mat Minimally Invas Spine Surg, Dept Orthopaed,Tongren Hosp,Hongqiao Int Inst Med,, 1111 XianXia Rd, Shanghai 200336, Peoples R China
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