Peripheral inflammation predicts motor, cognitive, and disease progression in Parkinson’s disease: A 4-year longitudinal study from the PPMI cohorts
摘要
This study investigated the associations between peripheral inflammation and motor severity, cognitive function, and disease stage in Parkinson’s disease (PD), and determined whether inflammatory markers can predict long-term clinical outcomes.
MethodsData were obtained from the Parkinson’s Progression Markers Initiative (PPMI), including 482 PD patients and 182 healthy controls. Baseline peripheral inflammatory indices were calculated, including neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI). Spearman correlation analyses explored the associations between baseline inflammatory markers and clinical measures (MDS-UPDRS III, Montreal Cognitive Assessment, and Hoehn and Yahr scale). Linear mixed-effects models evaluated the predictive effects of inflammatory markers on longitudinal changes in motor function, cognition, and disease stage during a 4-year follow-up. Subgroup analyses were conducted based on motor symptom severity at the 4-year follow-up.
ResultsLevels of peripheral inflammation were significantly elevated in PD patients versus healthy controls. Higher baseline neutrophil, NLR, SII, and SIRI were significantly associated with worse motor impairment, poorer cognitive performance, and more advanced disease stage at baseline (all p < 0.05). Longitudinal analyses demonstrated that elevated baseline neutrophil, NLR, SII, and SIRI independently predicted accelerated deterioration of motor function, decreased cognitive abilities and disease progression over 4 years (all p < 0.05). Notably, the predictive effects of inflammatory markers were more pronounced in subgroup with moderate-to-severe motor symptom at follow-up.
ConclusionsPeripheral inflammation is associated with greater baseline clinical severity and long-term progression in PD. Neutrophil, NLR, SII, and SIRI emerge as potential biomarkers for prognostic risk stratification.