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Evidence of the associations of air pollution and musculoskeletal diseases is inconsistent. This study aimed to examine the associations between air pollutants and the risk of incident musculoskeletal diseases, such as degenerative joint diseases (n = 38,850) and inflammatory arthropathies (n = 20,108). An air pollution score was constructed to assess the combined effect of PM 2.5 , PM 2.5-10 , NO 2 , and NO X . Cox proportional hazard model was applied to assess the relationships between air pollutants and the incidence of each musculoskeletal disease. The air pollution scores exhibited the modest association with an increased risk of osteoporosis (HR = 1.006, 95% CI: 1.002-1.011). Among the individual air pollutants, PM 2.5 and PM 2.5-10 exhibited the most significant effect on elevated risk of musculoskeletal diseases, such as PM 2.5 on osteoporosis (HR = 1.064, 95% CI: 1.020-1.110), PM 2.5-10 on inflammatory arthropathies (HR = 1.059, 95% CI: 1.037-1.081). Females were found to have a higher risk of incident musculoskeletal diseases when exposed to air pollutants. Individuals with extreme BMI or lower socioeconomic status had a higher risk of developing musculoskeletal diseases. Our findings reveal that long-term exposure to ambient air pollutants may contribute to an increased risk of musculoskeletal diseases., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Bone mineral density (BMD) is an essential predictor of osteoporosis and fracture. We conducted a genome-wide trajectory analysis of BMD and analyzed the BMD change., Purpose: This study aimed to identify the genetic architecture and potential biomarkers of BMD., Methods: Our analysis included 141,261 white participants from the UK Biobank with heel BMD phenotype data. We used a genome-wide trajectory analysis tool, TrajGWAS, to conduct a genome-wide association study (GWAS) of BMD. Then, we validated our findings in previously reported BMD genetic associations and performed replication analysis in the Asian participants. Finally, gene-set enrichment analysis (GSEA) of the identified candidate genes was conducted using the FUMA platform., Results: A total of 52 genes associated with BMD trajectory mean were identified, of which the top three significant genes were WNT16 (P = 1.31 × 10 -126 ), FAM3C (P = 4.18 × 10 -108 ), and CPED1 (P = 8.48 × 10 -106 ). In addition, 114 genes associated with BMD within-subject variability were also identified, such as AC092079.1 (P = 2.72 × 10 -13 ) and RGS7 (P = 4.72 × 10 -10 ). The associations for these candidate genes were confirmed in the previous GWASs and replicated successfully in the Asian participants. GSEA results of BMD change identified multiple GO terms related to skeletal development, such as SKELETAL SYSTEM DEVELOPMENT (P adjusted  = 2.45 × 10 -3 ) and REGULATION OF OSSIFICATION (P adjusted  = 2.45 × 10 -3 ). KEGG enrichment analysis showed that these genes were mainly enriched in WNT SIGNALING PATHWAY., Conclusions: Our findings indicated that the CPED1-WNT16-FAM3C locus plays a significant role in BMD mean trajectories and identified several novel candidate genes contributing to BMD within-subject variability, facilitating the understanding of the genetic architecture of BMD., (© 2023. International Osteoporosis Foundation and Bone Health and Osteoporosis Foundation.)