Neuroimaging and clinical predictors of fatigue in Parkinson disease

Abstract

Background: Fatigue is disabling in Parkinson disease. It is often associated with other non-motor symptoms, but little is known about its underlying pathophysiology.

Objective: To investigate neuroimaging (using dopaminergic and cholinergic PET) and clinical factors associated with fatigue severity in PD.

Methods: 133 PD subjects (96M/37F) completed the Fatigue Severity Scale, Movement Disorders Society-Sponsored Revision of the Unified PD Rating Scale (MDS-UPDRS), Hoehn-Yahr staging, validated scales for depression, anxiety, apathy, sleep, and cognition, and underwent [(11)C]methyl-4-piperidinyl propionate (PMP) acetylcholinesterase (AChE) and [(11)C]dihydrotetrabenazine (DTBZ) monoaminergic PET imaging. We explored contributions to PD fatigue using separate regression models based either on neuroimaging parameters or clinicometric scales.

Results: In a neuroimaging regression model, neither striatal DTBZ uptake nor AChE PMP uptake were predictors of fatigue in PD. In a post-hoc neuroimaging regression model, stratifying the total cohort into mild vs. moderate-to-severe PD, striatal DTBZ uptake was a significant predictor of fatigue in mild but not moderate-to-severe PD. In a clinicometric regression model, higher Beck Depression Inventory-somatic subscore, higher levodopa dose equivalents and younger age were all significant predictors of fatigue in PD, but the MDS-UPDRS non-motor experiences of daily living score was the best predictor overall.

Conclusions: Cholinergic uptake was not a predictor of fatigue in PD, but nigrostriatal dopaminergic denervation predicted fatigue in mild disease. Total non-motor symptom burden, somatic affective symptoms, levodopa dose equivalents, and younger age were independent clinical predictors of fatigue.

Keywords: Fatigue; PET imaging; Parkinson disease.