A predictive model for the investigation of osteoarthritic pain [Abstract]

Jones, Ryan, Gilbert, Sophie and Mason, Deborah ORCID: https://orcid.org/0000-0002-8666-6094 2026. A predictive model for the investigation of osteoarthritic pain [Abstract]. Osteoarthritis and Cartilage 34 (S) , S61. 10.1016/j.joca.2026.01.058

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Abstract

Purpose (the aim of the study): Osteoarthritis (OA) is a major cause of chronic pain and an estimated 34% of OA patients still experience chronic pain after joint arthroplasty. There are no effective treatments to reduce the burden of pain in these patients. In OA physiologically silent nociceptors become activated, increasing their responses to noxious, or even innocuous, stimuli. Many OA patients also develop neuropathic features linked to changes in channel activity and gene expression at the nerve cell body within the dorsal root ganglia (DRG) causing chronic debilitating pain. However, the molecular mechanisms governing nociception and neuropathic development of OA pain remain elusive. Animal models have phenotypically different peripheral nerve populations to humans. OA risk factor TRPV1, an ion channel that is expressed in 75% of human DRG cells, is expressed in under a third of mouse DRG cells. There is a need for more accurate models of human OA pain. We describe an in vitro human induced pluripotent stem cell (iPSC) derived nociceptor model for investigating OA pain and test whether it can predict patient pain experience.

Item Type:	Short Communication
Date Type:	Publication
Status:	Published
Schools:	Schools > Biosciences
Publisher:	Elsevier
ISSN:	1063-4584
Last Modified:	05 May 2026 14:09
URI:	https://orca.cardiff.ac.uk/id/eprint/186756

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