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Usage Information

An aggrecan fragment drives osteoarthritis pain through Toll-like receptor 2
Rachel E. Miller, Shingo Ishihara, Phuong B. Tran, Suzanne B. Golub, Karena Last, Richard J. Miller, Amanda J. Fosang, Anne-Marie Malfait
Rachel E. Miller, Shingo Ishihara, Phuong B. Tran, Suzanne B. Golub, Karena Last, Richard J. Miller, Amanda J. Fosang, Anne-Marie Malfait
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Research Article Bone biology Neuroscience

An aggrecan fragment drives osteoarthritis pain through Toll-like receptor 2

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Abstract

Pain is the predominant symptom of osteoarthritis, but the connection between joint damage and the genesis of pain is not well understood. Loss of articular cartilage is a hallmark of osteoarthritis, and it occurs through enzymatic degradation of aggrecan by cleavage mediated by a disintegrin and metalloproteinase with thrombospondin motif 4 (ADAMTS-4) or ADAMTS-5 in the interglobular domain (E373–374A). Further cleavage by MMPs (N341–342F) releases a 32-amino-acid aggrecan fragment (32-mer). We investigated the role of this 32-mer in driving joint pain. We found that the 32-mer excites dorsal root ganglion nociceptive neurons, both in culture and in intact explants. Treatment of cultured sensory neurons with the 32-mer induced expression of the proalgesic chemokine CCL2. These effects were mediated through TLR2, which we demonstrated was expressed by nociceptive neurons. In addition, intra-articular injection of the 32-mer fragment provoked knee hyperalgesia in WT but not Tlr2-null mice. Blocking the production or action of the 32-mer in transgenic mice prevented the development of knee hyperalgesia in a murine model of osteoarthritis. These findings suggest that the aggrecan 32-mer fragment directly activates TLR2 on joint nociceptors and is an important mediator of the development of osteoarthritis-associated joint pain.

Authors

Rachel E. Miller, Shingo Ishihara, Phuong B. Tran, Suzanne B. Golub, Karena Last, Richard J. Miller, Amanda J. Fosang, Anne-Marie Malfait

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Usage data is cumulative from March 2025 through March 2026.

Usage JCI PMC
Text version 1,395 199
PDF 206 34
Figure 315 4
Table 97 0
Supplemental data 70 22
Citation downloads 89 0
Totals 2,172 259
Total Views 2,431
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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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