Renal Impairment and Parkinson's Disease in Cardiovascular Patients: Associations, Pre-diagnostic Trajectories, and Predictive Enhancement

Background: Renal impairment is associated with increased risk of Parkinson's disease (PD) in general populations; however, the renal-PD link within cardiovascular disease (CVD) patients remains unclear through the high comorbidity of renal dysfunction and elevated PD risk among this special population. Objectives: To assess renal function's association, longitudinal trajectories and predictive value for PD specifically within a cardiovascular disease cohort. Methods: Among 29,266 UK Biobank CVD patients, we assessed baseline renal function via creatinine-based (eGFRcr) and cystatin C-based (eGFRcys) estimated glomerular filtration. Multivariable Cox regression analyzed associations with incident PD and all-cause mortality, with wide sensitivity analyses addressing reverse causation/confounding. Nested case-control analysis characterized pre-PD eGFR trajectories over 14 years. We finally evaluated whether renal function improved the PREDICT-PD's predictive ability. Results: Over a median 13.1-year follow-up, 489 incident PD cases and 5,919 deaths occurred. Lower eGFR levels exhibited dose-dependent associations with increased PD risk (eGFRcr: HR=0.87 [0.80~0.95]; eGFRcys: HR=0.90 [0.82~0.99]) and all-cause mortality (eGFRcr: HR=0.77 [0.75~0.79]; eGFRcys: HR=0.64 [0.63~0.66]). Pre-PD eGFR trajectories diverged significantly from controls starting over 14 years before diagnosis. eGFR-defined chronic kidney disease (<60 ml/min/1.73m2) conferred 38~60% higher PD risk and 159~234% elevated mortality risk, and could significantly enhance PREDICT-PD's discrimination, with a 1.18~1.34% increase in prediction accuracy. Conclusions: Impaired renal function is an independent PD and all-cause mortality risk factor of CVD patients, preceded by a slow, progressive eGFR decline starting >14 years before diagnosis. Incorporating renal function substantially improves PD risk prediction in this population.