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Usage Information

Macrophage proliferation distinguishes 2 subgroups of knee osteoarthritis patients
Matthew J. Wood, Adam Leckenby, Gary Reynolds, Rachel Spiering, Arthur G. Pratt, Kenneth S. Rankin, John D. Isaacs, Muzlifah A. Haniffa, Simon Milling, Catharien M.U. Hilkens
Matthew J. Wood, Adam Leckenby, Gary Reynolds, Rachel Spiering, Arthur G. Pratt, Kenneth S. Rankin, John D. Isaacs, Muzlifah A. Haniffa, Simon Milling, Catharien M.U. Hilkens
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Research Article Immunology Inflammation

Macrophage proliferation distinguishes 2 subgroups of knee osteoarthritis patients

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Abstract

Osteoarthritis (OA) is a leading cause of disability, globally. Despite an emerging role for synovial inflammation in OA pathogenesis, attempts to target inflammation therapeutically have had limited success. A better understanding of the cellular and molecular processes occurring in the OA synovium is needed to develop novel therapeutics. We investigated macrophage phenotype and gene expression in synovial tissue of OA and inflammatory-arthritis (IA) patients. Compared with IA, OA synovial tissue contained higher but variable proportions of macrophages (P < 0.001). These macrophages exhibited an activated phenotype, expressing folate receptor-2 and CD86, and displayed high phagocytic capacity. RNA sequencing of synovial macrophages revealed 2 OA subgroups. Inflammatory-like OA (iOA) macrophages are closely aligned to IA macrophages and are characterized by a cell proliferation signature. In contrast, classical OA (cOA) macrophages display cartilage remodeling features. Supporting these findings, when compared with cOA, iOA synovial tissue contained higher proportions of macrophages (P < 0.01), expressing higher levels of the proliferation marker Ki67 (P < 0.01). These data provide new insight into the heterogeneity of OA synovial tissue and suggest distinct roles of macrophages in pathogenesis. Our findings could lead to the stratification of OA patients for suitable disease-modifying treatments and the identification of novel therapeutic targets.

Authors

Matthew J. Wood, Adam Leckenby, Gary Reynolds, Rachel Spiering, Arthur G. Pratt, Kenneth S. Rankin, John D. Isaacs, Muzlifah A. Haniffa, Simon Milling, Catharien M.U. Hilkens

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Usage data is cumulative from August 2025 through August 2026.

Usage JCI PMC
Text version 2,168 173
PDF 242 60
Figure 610 0
Table 114 0
Supplemental data 772 36
Citation downloads 288 0
Totals 4,194 269
Total Views 4,463
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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