Clinical biomarker-based biological ageing and the risk of adverse outcomes in patients with chronic kidney disease.

Abstract

Patients with chronic kidney disease (CKD) show features of premature ageing. We aimed to evaluate the association between biological ageing and adverse outcomes, including end-stage kidney disease (ESKD), cardiovascular diseases (CVD) and all-cause mortality, in patients with CKD. 23435 participants with CKD and free of related adverse outcomes at baseline from the UK Biobank were included. Leukocyte telomere length (LTL) was measured by quantitative polymerase chain reaction assay. Clinical biomarker-based biological ages were quantified using Klemera-Doubal method biological age (KDM-BA) and PhenoAge algorithms. During a median follow-up of 12years, 3417 incident CVD, 383 incident ESKD and 3195 all-cause mortality were recorded. Per SD increment of KDM-BA acceleration was associated with a 56% [95% confidence interval (CI): 41%-73%], 26% (95% CI: 21%-31%) and 39% (95% CI: 34%-44%) increase in the risk of incident ESKD, incident CVD and all-cause mortality, respectively. Similar results were found for PhenoAge acceleration. LTL (per SD increment) was inversely associated with the risk of incident CVD [hazard ratio (HR): 0.96, 95% CI: 0.92-0.99] and all-cause mortality (HR: 0.94, 95% CI: 0.91-0.98) and was not significantly associated with the risk of incident ESKD (HR: 0.96, 95% CI: 0.86-1.06). Adding KDM-BA acceleration or PhenoAge acceleration, but not LTL, to the traditional validated clinical prediction models significantly improved the predictive performance for incident ESKD, all-cause mortality and CVD. In patients with CKD, both KDM-BA acceleration and PhenoAge acceleration were associated with an increased risk of ESKD, CVD and all-cause mortality, and KDM-BA or PhenoAge may be a better predictor on adverse outcomes than LTL.