Neuroimaging and clinical predictors of fatigue in Parkinson disease.

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.