Evidence map›Paper›PMID 42769165›Full record

ArticleFrontiers in neurology2026

Resting-state EEG biomarkers of general and domain-specific cognitive impairment and plasma P-tau217 in patients with Alzheimer's disease and mild cognitive impairment.

Liu Yang, Hang Yu, Ze-Yu Hong, Zhiyu Liu, Xiao-Jia Li, Fang Ye

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Article in Frontiers in neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Liu YangDepartment of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Hang YuClinical Research Department, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
Ze-Yu HongDepartment of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Zhiyu LiuDepartment of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Xiao-Jia LiDepartment of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Fang YeDepartment of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Early detection of Alzheimer's disease (AD)-related cognitive impairment remains challenging due to the lack of convenient, non-invasive screening tools. Objective: To explore the multidimensional utility of quantitative electroencephalography (EEG) as a complementary tool for early detection of AD-related cognitive impairment. Methods: Clinical data, electroencephalogram (EEG) records, cognitive scale scores and blood samples were collected. According to the established clinical diagnostic criteria, the participants were divided into three groups: cognitive normal group, mild cognitive impairment group (MCI) and Alzheimer's disease (AD) dementia group. Traditional statistical methods and machine learning algorithms were used to analyze the correlation between 200 EEG indexes and the severity of cognitive impairment, domain-specific cognitive impairment and plasma P-tau217 concentration. Results: A total of 360 participants (154 dementia patients with Alzheimer's disease, 116 mild cognitive impairment patients and 90 healthy controls) were included. The area under the curve (AUC) of EEG in 360 participants is 0.70-0.87, which can effectively distinguish cognitive dysfunction related to Alzheimer's disease. Among them, 102 participants improved the cognitive domain assessment scale, and the results showed that several EEG indexes were correlated with cognitive domain function score. The blood samples of 105 normal and MCI participants were tested for blood P-tau217 concentration. The relative power of right temporal lobe and right parietal lobe was negatively correlated with blood P-tau217 concentration, and the relative power of right parietal lobe was an independent influencing factor for the increase of blood P-tau217 level (AUC = 0.68). Conclusion: Quantitative EEG indicators show potential as a complementary screening approach for AD-related cognitive impairment. Further validation in prospective, multicenter cohorts is needed before implementation in clinical practice.

Indexed as

Alzheimer DiseaseCognitive DysfunctionElectroencephalographytau ProteinsAgedBiomarkersEarly DiagnosisFemaleHumansMaleMiddle AgedBiomarkersMAPT protein, humantau ProteinsAlzheimer’s diseasecognitive domaincognitive impairmentplasma biomarkerquantitative EEG

Identifiers

PMID42769165
PMCPMC13590305

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.