Usage Information
Abstract
Inflammation driven by the innate immune response plays a crucial role in osteoarthritis (OA) pathogenesis, yet the underlying mechanisms remain incompletely understood. Moreover, current antiinflammatory therapies primarily offer symptomatic relief without altering disease progression. Nucleotide-binding oligomerization domain 2 (NOD2) is an intracellular pattern recognition receptor that detects a broad range of microbial and damage-associated stimuli and has been implicated in several inflammatory conditions. In this study, we investigated the role of NOD2 in OA-associated inflammation and cartilage degradation. Elevated NOD2 expression was observed in both human and mouse osteoarthritic cartilage. Conditional KO of Nod2 in chondrocytes suppressed inflammation-induced catabolic responses in vitro and protected against cartilage degradation in mouse OA models. Mechanistically, we identified tumor necrosis factor receptor–associated factor 6 (TRAF6) as a key downstream mediator through which NOD2 promotes chondrocyte catabolism. Furthermore, we showed that pharmacological inhibition of NOD2 using 2 independent small-molecule inhibitors significantly attenuated OA progression in vivo. Collectively, these findings establish NOD2 as a critical regulator of OA-associated inflammation and cartilage degradation, and they highlight its potential as a therapeutic target for disease-modifying OA treatment.
Authors
Yuting Wang, Song Li, Yonghui Dong, Jiaming Zhang, Jian Liu, Zhenggang Wang, Shuang Liang, Nathan R. Martinez, Hongxu Pu, Peng Cheng, Anmin Chen, Qing Yang, Charles K.F. Chan, Wen Jiang, Jun Xiao, Fengjing Guo, Liming Zhao
Usage data is cumulative from August 2026 through September 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 608 | 21 |
| 238 | 4 | |
| Figure | 580 | 0 |
| Supplemental data | 209 | 1 |
| Citation downloads | 129 | 0 |
| Totals | 1,764 | 26 |
| Total Views | 1,790 | |
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.
