Sleep patterns, genetic susceptibility, and osteoarthritis risk: insights from the UK Biobank and external validation...

Unhealthy sleep behaviors may contribute to osteoarthritis (OA), but their interrelated nature complicates evaluation and longitudinal studies examining the correlation between overall sleep behaviors and OA incidence are lacking. We explored the impact of sleep patterns on OA incidence and investigated whether genetic susceptibility plays a modifying role.

We analyzed 369 795 OA-free participants from the UK Biobank (discover cohort). A composite sleep score was derived from five behaviors: sleep duration, snoring, chronotype, daytime sleepiness, and insomnia symptoms. Incident site-specific OA were identified using ICD-codes. Genetic risk scores (GRS) were calculated. Cox regression models were used to estimated hazard ratios (HR) and 95% confidence intervals (CI). Finally, we verified the association between sleep patterns and OA in the Xiangya Osteoarthritis Study (validation cohort).

During a median follow-up of 11.9 years, 17 152 knee, 11 101 hip, and 2714 hand OA cases were recorded. Participants with the lowest sleep scores (0-1) had significantly higher OA risks, showing a 32% increased risk for knee OA, 19% for hip OA, and 42% for hand OA. Poor sleep patterns were associated with elevated OA risk across all GRS categories, though not all associations reached statistical significant. For knee OA, HRs were 1.13 (95% CI: 0.95-1.34), 1.22 (95% CI: 1.11-1.34), and 1.16 (95% CI: 1.00-1.36) in the low, intermediate, and high GRS groups, with similar trends for hip and hand OA. The validation cohort further supported a dose-response relationship, with intermediate and poor sleep patterns linked to higher risks of knee ( Ptrend  = 0.026) and hand OA ( Ptrend  = 0.041), relative to healthy sleep.

These findings demonstrate that an optimal sleep pattern is associated with a decreased OA risk, independent of genetic susceptibility. Our results emphasize the protective role of sleep in OA prevention and the importance of integrating sleep assessment into prevention strategies.