Literature DB >> 26683744

Neuroimaging and clinical predictors of fatigue in Parkinson disease.

Kelvin L Chou1, Vikas Kotagal2, Nicolaas I Bohnen3.   

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.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Fatigue; PET imaging; Parkinson disease

Mesh:

Year:  2015        PMID: 26683744      PMCID: PMC4724499          DOI: 10.1016/j.parkreldis.2015.11.029

Source DB:  PubMed          Journal:  Parkinsonism Relat Disord        ISSN: 1353-8020            Impact factor:   4.891


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