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Quantitative EEG as a biomarker in mild cognitive impairment with Lewy bodies

Lookup NU author(s): Julia Schumacher, Professor John-Paul Taylor, Calum Hamilton, Dr Michael Firbank, Dr Ruth Cromarty, Dr Paul Donaghy, Dr Gemma Roberts, Dr Louise Allan, Dr James Lloyd, Dr Rory Durcan, Nicola Barnett, Professor John O'Brien, Professor Alan Thomas

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

OBJECTIVES: To investigate using quantitative EEG the (1) differences between patients with mild cognitive impairment with Lewy bodies (MCI-LB) and MCI with Alzheimer's disease (MCI-AD) and (2) its utility as a potential biomarker for early differential diagnosis. METHODS: We analyzed eyes-closed, resting-state, high-density EEG data from highly phenotyped participants (39 MCI-LB, 36 MCI-AD, and 31 healthy controls). EEG measures included spectral power in different frequency bands (delta, theta, pre-alpha, alpha, and beta), theta/alpha ratio, dominant frequency, and dominant frequency variability. Receiver operating characteristic (ROC) analyses were performed to assess diagnostic accuracy. RESULTS: There was a shift in power from beta and alpha frequency bands towards slower frequencies in the pre-alpha and theta range in MCI-LB compared to healthy controls. Additionally, the dominant frequency was slower in MCI-LB compared to controls. We found significantly increased pre-alpha power, decreased beta power, and slower dominant frequency in MCI-LB compared to MCI-AD. EEG abnormalities were more apparent in MCI-LB cases with more diagnostic features. There were no significant differences between MCI-AD and controls. In the ROC analysis to distinguish MCI-LB from MCI-AD, beta power and dominant frequency showed the highest area under the curve values of 0.71 and 0.70, respectively. While specificity was high for some measures (up to 0.97 for alpha power and 0.94 for theta/alpha ratio), sensitivity was generally much lower. CONCLUSIONS: Early EEG slowing is a specific feature of MCI-LB compared to MCI-AD. However, there is an overlap between the two MCI groups which makes it difficult to distinguish between them based on EEG alone.


Publication metadata

Author(s): Schumacher J, Taylor J-P, Hamilton CA, Firbank M, Cromarty RA, Donaghy PC, Roberts G, Allan L, Lloyd J, Durcan R, Barnett N, O'Brien JT, Thomas AJ

Publication type: Article

Publication status: Published

Journal: Alzheimer's research & therapy

Year: 2020

Volume: 12

Issue: 1

Online publication date: 08/07/2020

Acceptance date: 02/07/2020

Date deposited: 20/07/2020

ISSN (electronic): 1758-9193

Publisher: BMC

URL: https://doi.org/10.1186/s13195-020-00650-1

DOI: 10.1186/s13195-020-00650-1

PubMed id: 32641111


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