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A prospective study of associations between accelerated biological aging and twenty musculoskeletal disorders

  • Wenming Wei,
  • Xin Qi,
  • Bolun Cheng,
  • Na Zhang,
  • Yijing Zhao,
  • Xiaoyue Qin,
  • Dan He,
  • Xiaoge Chu,
  • Sirong Shi,
  • Qingqing Cai,
  • Xuena Yang,
  • Shiqiang Cheng,
  • Peilin Meng,
  • Jingni Hui,
  • Chuyu Pan,
  • Li Liu,
  • Yan Wen,
  • Huan Liu,
  • Yumeng Jia,
  • Feng Zhang

摘要

Background

Musculoskeletal disorders pose major public health challenges, and accelerated biological aging may increase their risk. This study investigates the association between biological aging and musculoskeletal disorders, with a focus on sex-related differences.

Methods

We analyzed data from 172,332 UK Biobank participants (mean age of 56.03 ± 8.10 years). Biological age was calculated using the KDM-BA and PhenoAge algorithms based on blood biomarkers. Musculoskeletal disorders were diagnosed using the ICD-10 criteria, with sample sizes ranging from 1,182 to 23,668. Logistic regression assessed cross-sectional associations between age acceleration (AA) metrics and musculoskeletal disorders. Accelerated Failure Time (AFT) model was used for survival analysis to evaluate the relationships between AAs and musculoskeletal disorders onset. Models were adjusted for demographic, lifestyle, and socio-economic covariates. The threshold of P-values were set by the Holm-Bonferroni correction.

Results

Cross-sectional analyses reveal significant associations between AAs and fourteen musculoskeletal disorders. Survival analyses indicate that AAs significantly accelerate the onset of nine musculoskeletal disorders, including inflammatory polyarthropathies (RTKDM-BA = 0.993; RTPhenoAge = 0.983), systemic connective tissue disorders (RTKDM-BA = 0.987; RTPhenoAge = 0.980), spondylopathies (RTPhenoAge= 0.994), disorders of bone density and structure (RTPhenoAge= 0.991), gout (RTPhenoAge= 0.968), arthritis (RTPhenoAge= 0.991), pain in joint (RTPhenoAge= 0.989), low back pain (RTPhenoAge= 0.986), and osteoporosis (RTPhenoAge= 0.994). Sensitivity analyses are consistent with the primary findings. Sex-specific variations are observed, with AAs accelerating spondylopathies, arthritis, and low back pain in females, while osteoporosis is accelerated in males.

Conclusion

Accelerated biological aging is significantly associated with the incidence of several musculoskeletal disorders. These insights highlight the importance of biological age assessments in gauging musculoskeletal disorder risk, aiding early detection, prevention, and management.