Elsevier

Clinical Neurophysiology

Volume 129, Issue 8, August 2018, Pages 1748-1755
Clinical Neurophysiology

Quantitative EEG reflects non-dopaminergic disease severity in Parkinson’s disease

https://doi.org/10.1016/j.clinph.2018.04.752Get rights and content

Highlights

  • EEG parameters correlate to measures of disease severity in patients with Parkinson’s Disease.

  • Both EEG slowing and reduced connectivity correlate to non-dopaminergic disease severity.

  • The proposed markers may be useful in the screening process for Deep Brain Stimulation.

Abstract

Objective

In Parkinson’s Disease (PD), measures of non-dopaminergic systems involvement may reflect disease severity and therefore contribute to patient-selection for Deep Brain Stimulation (DBS). There is currently no determinant for non-dopaminergic disease severity. In this exploratory study, we investigated whether quantitative EEG reflects non-dopaminergic disease severity in PD.

Methods

Sixty-three consecutive PD patients screened for DBS were included (mean age 62.4 ± 7.2 years, 32% females). Relative spectral powers and the Phase-Lag-Index (PLI) reflecting functional connectivity were analysed on routine EEGs. Non-dopaminergic disease severity was quantified using the SENS-PD score and its subdomains; motor-severity was quantified using the MDS-UPDRS III.

Results

The SENS-PD composite score correlated with a spectral ratio ((δ + θ)/(α1 + α2 + β) powers) (global spectral ratio Pearson’s r = 0.4, 95% Confidence Interval (95%CI) 0.1–0.6), and PLI in the α2 band (10–13 Hz) (r = −0.3, 95%CI −0.5 to −0.1). These correlations seem driven by the subdomains cognition and psychotic symptoms. MDS-UPDRS III was not significantly correlated with EEG parameters.

Conclusions

EEG slowing and reduced functional connectivity in the α2 band were associated with non-dopaminergic disease severity in PD.

Significance

The described EEG parameters may have complementary utility as determinants of non-dopaminergic involvement in PD.

Introduction

Parkinson’s Disease (PD) is a multisystem neurodegenerative disorder, caused by progressive degeneration of both dopaminergic and non-dopaminergic neurons (Jellinger, 2012). Dopaminergic neurons account primarily for the characteristic motor symptoms of PD, whilst non-dopaminergic neurons account for non-motor symptoms such as impaired cognition, psychiatric manifestations or sleep disturbances. PD is typically treated with oral dopaminergic medication, which alleviates motor symptoms. However, medication-related motor complications occur in the majority of patients within 10 years of disease (Ahlskog et al., 2001). Patients refractory to oral treatment may be eligible for Deep Brain Stimulation (DBS), which ameliorates motor complications and improves quality of life (Deuschl et al., 2013). DBS is particularly effective in patients perceiving substantial motor improvement upon dopaminergic treatment (Moldovan et al., 2015). However, non-dopaminergic symptoms such as cognitive impairment,(Contarino et al., 2007) depression (Weaver et al., 2009), speech intelligibility (Tripoliti et al., 2011) and axial symptoms (Russmann et al., 2004) may deteriorate post-DBS. This indicates the need for accurate assessment of non-dopaminergic disease severity during the preoperative selection process.

Clinical, neuropsychological and psychiatric evaluations are used to rule out severe cognitive decline or psychiatric comorbidity. However, several factors including intelligence, education, and personality limit the interpretability of clinimetric assessments (Duncan, 1993). Moreover, questionnaires and performance tasks are susceptible to misinterpretation, social desirability bias, or fatigue (Duckworth et al., 2015). Therefore, there is a need for complementary measures reflecting disease severity in PD to aid the identification of DBS candidates.

Quantitative Electroencephalography (qEEG) is an inexpensive and widely available tool which measures brain activity directly. Previous studies applied qEEG to examine clinical domains in PD, such as cognition (Caviness et al., 2015, Cozac et al., 2016), response to treatment (George et al., 2013) or motor impairment (Babiloni et al., 2011, George et al., 2013). Global oscillatory slowing of the EEG spectrogram is a highly suitable biomarker for cognitive impairment in PD (Caviness et al., 2015). Recent advances in neurophysiology have provided more complex markers such as connectivity parameters and graph theory estimations, which quantify brain network disorganization. The Phase-Lag Index (PLI), which reflects functional connectivity, was suggested as a potential biomarker of PD dementia (Utianski et al., 2016). To our knowledge the relation of qEEG parameters to measures of non-dopaminergic severity in PD has not been investigated so far. We aimed to investigate whether qEEG correlates with clinical measures of disease severity, in order to ultimately provide neurophysiological determinants of disease severity.

Section snippets

Study participants

All consecutive PD patients who were referred for preoperative screening to the DBS center of Leiden University Medical Center (LUMC) and Haga Teaching Hospital between September 2015 and July 2017 were included in the study. All patients fulfilled the Movement Disorders Society PD criteria for clinically established PD (Postuma et al., 2015). Written informed consent was obtained from all patients. A formal ethical evaluation of this study was waived by the local medical ethics committee.

Outcome measures

Motor

Patient characteristics

Eighty patients underwent DBS screening during the study period. Seventeen patients were excluded due to gross artifacts during EEG recordings (low disease severity: n = 8, intermediate severity: n = 3, high disease severity: n = 6); analysis was thus performed on 63 patients (32% female). There were no significant differences in demographic and clinical variables between included and excluded patients. Mean (SD) age was 62.4 (7.2) years, and disease duration 11.9 (6.3) years (Table 1). There

Discussion

Several qEEG parameters were found to have potential as neurophysiological determinants of advanced non-dopaminergic disease severity in PD. As high non-dopaminergic disease severity is a relative contra-indication for DBS, qEEG analysis may ultimately complement clinimetric evaluations to optimize the screening process of DBS candidates.

Slower EEG oscillatory activity was associated with more advanced non-dopaminergic disease severity measured by the SENS-PD score and, in particular, with the

Conflict of interest

This work was supported by a grant from the ‘Stichting ParkinsonFonds’ and the ‘Stichting Alkemade-Keuls’. The funding sources had no role in the study design, data collection, analysis, interpretation, writing or decision to submit the manuscript for publication. None of the authors has potential conflicts of interest that relate to this manuscript.

Acknowledgements

The authors would like to thank G.E.L. Hendriks, R.H.A.M. Reijntjes, F.I. Kerkhof and the EEG technicians of the LUMC, for their help with the data collection.

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