See the published version of this preprint at Alzheimer's Research and Therapy.
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Julia Schumacher
Translational and Clinical Research Institute, Newcastle University
Corresponding Author
ORCiD: https://orcid.org/0000-0001-7323-4789
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Objectives: To investigate using quantitative EEG (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 characteristics (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, 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 overlap between the two MCI groups which makes it difficult to distinguish between them based on EEG alone.
Keywords
Dementia with Lewy bodies, Alzheimer’s disease, quantitative electroencephalography, biomarker
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CURRENT STATUS: Published
View the published article at Alzheimer's Research and Therapy.
Version 2
Posted 22 Jun, 2020
No community comments so far
Editorial decision: Accept
On 26 Jun, 2020
Reviewer #4 agreed
On 25 Jun, 2020
Review #4 received
Received 25 Jun, 2020
Reviewer #3 agreed
On 23 Jun, 2020
Review #3 received
Received 23 Jun, 2020
Reviewer #1 agreed
On 22 Jun, 2020
Reviewer #2 agreed
On 22 Jun, 2020
Review #1 received
Received 22 Jun, 2020
Review #2 received
Received 22 Jun, 2020
Reviewers invited
Invitations sent on 21 Jun, 2020
Editor assigned
On 18 Jun, 2020
Submission checks complete
On 17 Jun, 2020
Editor invited
On 17 Jun, 2020
No comments provided
Review #4 received
Received 05 Jun, 2020
Editorial decision: Minor Revision
On 05 Jun, 2020
Review #3 received
Received 04 Jun, 2020
Review #2 received
Received 29 May, 2020
Reviewer #4 agreed
On 28 May, 2020
Reviewer #3 agreed
On 27 May, 2020
Reviewer #1 agreed
On 26 May, 2020
Reviewer #2 agreed
On 26 May, 2020
Review #1 received
Received 26 May, 2020
Reviewers invited
Invitations sent on 25 May, 2020
Editor assigned
On 20 May, 2020
Editor invited
On 19 May, 2020
Submission checks complete
On 14 May, 2020
First submitted
On 13 May, 2020
Metrics
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PDF Downloads: ...
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Subject Areas
Cognitive Neuroscience
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See the published version of this preprint at Alzheimer's Research and Therapy.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Julia Schumacher
Translational and Clinical Research Institute, Newcastle University
Corresponding Author
ORCiD: https://orcid.org/0000-0001-7323-4789
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Alzheimer's Research and Therapy.
Version 2
Posted 22 Jun, 2020
No community comments so far
Editorial decision: Accept
On 26 Jun, 2020
Reviewer #4 agreed
On 25 Jun, 2020
Review #4 received
Received 25 Jun, 2020
Reviewer #3 agreed
On 23 Jun, 2020
Review #3 received
Received 23 Jun, 2020
Reviewer #1 agreed
On 22 Jun, 2020
Reviewer #2 agreed
On 22 Jun, 2020
Review #1 received
Received 22 Jun, 2020
Review #2 received
Received 22 Jun, 2020
Reviewers invited
Invitations sent on 21 Jun, 2020
Editor assigned
On 18 Jun, 2020
Submission checks complete
On 17 Jun, 2020
Editor invited
On 17 Jun, 2020
No comments provided
Review #4 received
Received 05 Jun, 2020
Editorial decision: Minor Revision
On 05 Jun, 2020
Review #3 received
Received 04 Jun, 2020
Review #2 received
Received 29 May, 2020
Reviewer #4 agreed
On 28 May, 2020
Reviewer #3 agreed
On 27 May, 2020
Reviewer #1 agreed
On 26 May, 2020
Reviewer #2 agreed
On 26 May, 2020
Review #1 received
Received 26 May, 2020
Reviewers invited
Invitations sent on 25 May, 2020
Editor assigned
On 20 May, 2020
Editor invited
On 19 May, 2020
Submission checks complete
On 14 May, 2020
First submitted
On 13 May, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cognitive Neuroscience
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Alzheimer's Research and Therapy.
Objectives: To investigate using quantitative EEG (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 characteristics (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, 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 overlap between the two MCI groups which makes it difficult to distinguish between them based on EEG alone.
Figure 1
Figure 2
Figure 3
Figure 4
This is a list of supplementary files associated with this preprint. Click to download.
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