Phenotypic and genetically predicted leukocyte telomere length and prostate cancer risk: Results from a large-scale longitudinal cohort study.

404 Background: Previous studies on the correlation between leukocyte telomere length (LTL) and prostate cancer (PCa) have shown contradictory results. Our study aims to further explore the potential relationship between LTL and PCa. Methods: In this study, a total of 229,022 male individuals were enrolled from the UK Biobank to investigate this association . Both unadjusted and covariates-adjusted Cox proportional hazards regression models were employed. The primary outcome was defined as the diagnosis of incident prostate cancer using in-patient data and the death registry of the UKB cohort. To validate the reliability of the primary findings, secondary analyses, including Mendelian randomization (MR) were conducted. Results: The primary analysis demonstrated that longer LTL was substantially associated with higher risk of prostate cancer, with associations remaining robust after adjusting for potential covariates (HR: 1.444, 95% CI: 1.247-1.673, P < 0.001). Similar results were observed when LTL was analyzed as both a continuous and categorical variable, and the association were shown to be inversely U-shaped. At the genetic level, the association was further validated using MR across different prostate cancer databases, with results consistent with our primary analysis. Conclusions: Our findings offer compelling evidence that leukocyte telomere length is an important risk factor for prostate cancer. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between leukocyte telomere length (analyzed both as a continuous variable and by quartile categories) and prostate cancer risk in the UK Biobank study. Model I Model II Model III Cases N Median HR 95%CI HR 95%CI HR 95%CI 10693 198830 0.810 1.505 1.301-1.741 1.454 1.256-1.683 1.444 1.247- 1.673 <0.001 <0.001 <0.001 2761 49708 0.683 ref ref ref 2782 49707 0.773 1.088 1.032 -1.147 1.087 1.031 - 1.145 1.084 1.029-1.143 2607 49707 0.849 1.090 1.033-1.151 1.086 1.029-1.146 1.084 1.028-1.144 2543 49708 0.960 1.187 1.124-1.253 1.174 1.112- 1.240 1.170 1.108-1.236 <0.001 <0.001 <0.001 Model I adjust for age; Model II adjust for demographic variables (age; ethnic background) and socioeconomic variables (socioeconomic status; education); Model III adjust for demographic variables (age class; ethnic background) socioeconomic variables (socioeconomic status; education) and lifestyle variables (alcohol intake frequency; smoking history; body mass index; duration of walks; sleep duration; blood pressure).