Blood-based biological ageing and red cell distribution width are associated with prevalent Parkinson's disease: findings from a large Italian population cohort.

Background: Aging clocks tag the actual underlying age of an organism and its discrepancy with chronological age and have been reported to predict incident disease risk in the general population. However, the relationship with neurodegenerative risk and in particular with Parkinson's Disease (PD) remains unclear, with few discordant findings reporting associations with both incident and prevalent PD risk. Objective: To clarify this relationship, we computed a common aging clock based on blood markers and tested the resulting discrepancy with chronological age (ΔPhenoAge) for association with both incident and prevalent PD risk. Methods: In a large Italian population cohort - the Moli-sani study (N=23,437; age ≥ 35 years; 52% women) - we carried out both Cox Proportional Hazards regressions modelling ΔPhenoAge as exposure and incident PD as outcome, and linear models testing prevalent PD as exposure and ΔPhenoAge as outcome. All models were incrementally adjusted for age, sex, education level completed and other risk/protective factors previously associated with PD risk in the same cohort (prevalent dysthyroidism, hypertension, diabetes, use of oral contraceptives, exposure to paints, daily coffee intake and cigarette smoking). Results: No significant association between incident PD risk (209 cases, median (IQR) follow-up time 11.19 (2.03) years) and PhenoAging was observed (Hazard Ratio [95% Confidence Interval] = 0.98 [0.71; 1.37]). However, a small but significant increase of ΔPhenoAge was observed in prevalent PD cases vs healthy subjects (ß (Standard Error) = 1.39 (0.70)). An analysis of each component biomarker of PhenoAge revealed a significant positive association of prevalent PD status with red cell distribution width (RDW; ß (SE) = 0.46 (0.18)). All the remaining markers did not show any significant evidence of association. Conclusion: The reported evidence highlights systemic effects of prevalent PD status on biological aging and red cell distribution width. Further cohort and functional studies may help shedding a light on the related pathways altered at the organism level in prevalent PD, like red cells variability, inflammatory and oxidative stress mechanisms.

Risk and protective factors in Parkinson's disease: a simultaneous and prospective study with classical statistical and novel machine learning models.

BACKGROUND: Several environmental/lifestyle factors have been individually investigated in previous Parkinson's disease (PD) studies with controversial results. No study has prospectively and simultaneously investigated potential risk/protective factors of PD using both classical statistical and novel machine learning analyses. The latter may reveal more complex associations and new factors that are undetected by merely linear models. To fill this gap, we simultaneously investigated potential risk/protective factors involved in PD in a large prospective population study using both approaches. METHODS: Participants in the Moli-sani study were enrolled between 2005 and 2010 and followed up until December 2018. Incident PD cases were identified by individual-level record linkage to regional hospital discharge forms, the Italian death registry, and the regional prescription register. Exposure to potential risk/protective factors was assessed at baseline. Multivariable Cox Proportional Hazards (PH) regression models and survival random forests (SRF) were built to identify the most influential factors. RESULTS: We identified 213 incident PD cases out of 23,901 subjects. Cox PH models revealed that age, sex, dysthyroidism and diabetes were associated with an increased risk of PD. Both hyper and hypothyroidism were independently associated with PD risk. SRF showed that age was the most influential factor in PD risk, followed by coffee intake, daily physical activity, and hypertension. CONCLUSION: This study sheds light on the role of dysthyroidism, diabetes and hypertension in PD onset, characterized to date by an uncertain relationship with PD, and also confirms the relevance of most factors (age, sex, coffee intake, daily physical activity) reportedly shown be associated with PD. Further methodological developments in SRF models will allow to untangle the nature of the potential non-linear relationships identified.