Early pain in females is linked to late pathological features in murine experimental osteoarthritis

Osteoarthritis (OA) is a progressive joint disease and a major cause of chronic pain in adults. The prevalence of OA is higher in female patients, who tend to have worse OA outcomes, partially due to pain. The association between joint pain and OA pathology is often inconclusive. Preclinical research studies have largely overlooked sex as a potential determinant in joint pain during OA. This study aimed to investigate the role of sex in joint pain in the collagenase-induced OA (CiOA) model and its link with joint pathology.

Multiple aspects of pain were evaluated during identically executed experiments of CiOA in male and female C57BL/6J mice. Cartilage damage, osteophyte formation, synovial thickness, and cellularity were assessed by histology on day 56. The association between pain and pathology was investigated, disaggregated by sex.

Differences in pain behavior between sexes were found in the majority of the evaluated pain methods. Females displayed lower weight bearing ability in the affected leg compared to males during the early phase of the disease, however, the pathology at the end stage was comparable between sexes. In the second cohort, males displayed increased mechanical sensitivity in the affected joint compared to females but also showed more cartilage damage at the end stage of the model. Within this cohort, gait analysis showed varied results. Males used the affected paw less often and displayed dynamic weight-bearing compensation in the early phase of the model. These differences were not observed in females. Other evaluated parameters displayed comparable gait behavior between males and females. A detailed analysis of individual mice revealed that seven out of 10 pain measurements highly correlated with OA histopathology in females (Pearson r range: 0.642-0.934), whereas in males this measurement was only two (Pearson r range: 0.645-0.748).

Our data show that sex is a determinant in the link between pain-related behavior with OA features. Therefore, to accurately interpret pain data it is crucial to segregate data analysis by sex to draw the correct mechanistic conclusion.