Construction and Validation of Plasma Protein‐Based Musculoskeletal Biological Age and Genetic and Environmental Risk Profiles

ABSTRACT The musculoskeletal system is key to aging. Nonetheless, existing protein‐based musculoskeletal aging clocks have limited predictive performance and fail to characterize genetic or environmental determinants. We first constructed a musculoskeletal protein pool by integrating transcriptomic enrichment, protein functional annotation, and literature expertise. Two musculoskeletal aging clocks—MSKAge and MSKAgeMort—were then developed using proteomic data of 21,070 UK Biobank participants. Acceleration metric (MSKAgeAccel/MSKAgeMortAccel) quantified deviations of biological age from chronological age, with positive values indicating accelerated musculoskeletal aging. Associations of MSKAgeAccel/MSKAgeMortAccel with mortality, musculoskeletal disorders, and age‐related diseases were assessed using Cox proportional hazards models. Environmental and genetic determinants were evaluated by linear regression and genome‐wide association analyses, respectively. Drug repurposing was used to identify potential targets of musculoskeletal diseases. A total of 39 musculoskeletal‐related proteins constituted the pool. Leveraging these proteins, MSKAge ( r female = 0.62; r male = 0.56) and MSKAgeMort ( r female = 0.93; r male = 0.88) were constructed. Both MSKAgeAccel and (in particular) MSKAgeMortAccel predicted mortality, musculoskeletal diseases, and age‐related diseases effectively. MSKAgeMortAccel showed significant associations with musculoskeletal disorders, including osteoarthritis, rheumatoid arthritis, gout, and low back pain. MSKAgeMortAccel was influenced by environmental pollutants, psychological factors, and unhealthy lifestyles. Genetic analyses revealed 13 variants and 71 genes enriched in epigenetic regulation and extracellular environment‐receptor interaction. Zinc was identified as a candidate musculoskeletal drug. We established a reliable musculoskeletal aging clock and elucidated genetic and environmental determinants. This framework enables stratification of individuals at risk of accelerated musculoskeletal aging, paving the way for anti‐aging interventions.