Longitudinal Biomarker Prediction of Altered Cognition and Mood Outcomes in the Parkinson’s Progression Markers Initiative (PPMI) Study

Abstract

Parkinson´s disease (PD) is a neurodegenerative disorder that is associated with severely debilitating non-motor symptoms (e.g., cognitive and mood dysfunction) that negatively affect quality of life. Prodromal symptoms (REM sleep behaviour disorder (RSBD) and olfactory dysfunction) and inflammation are risk factors for neuropsychiatric alterations, but their predictive value is currently unknown. Data at PD diagnosis and 5-year follow-ups were obtained from the longitudinal PPMI database. Latent growth curve modelling was used to investigate whether baseline prodromal symptoms, urate and six immunomarkers could predict the initial value and the change in cognition and mood over time. A large analysis was undertaken for prodromal symptoms, serum urate and insulin-like growth factor-1 (n = 399) and smaller exploratory analyses for immunomarkers (n = 75-99). Confounders included sex, education, age and BMI at PD diagnosis. Age had a negative effect on cognition and its change, education had a positive effect on cognition, mood and its change. Urate and immunomarkers did not significantly influence cognition or mood. RSBD predicted significantly lower cognitive function and mood at PD diagnosis (p ≤ .001) and a decline in cognitive function over time (p = .01). Olfactory dysfunction negatively affected mood function at diagnosis (p ˂ .05) and predicted decline in cognitive function and mood over time (p = .000 and p = .073, respectively). These prodromal symptoms are both valuable markers for early detection of PD, cognitive and mood dysfunction and for predicting individual trajectories of change in neuropsychiatric disorders post-diagnosis, thus allowing for personalised therapeutic interventions.