» Articles » PMID: 39497149

Exploring Easily Accessible Neurophysiological Biomarkers for Predicting Alzheimer's Disease Progression: a Systematic Review

Overview
Date 2024 Nov 4
PMID 39497149
Authors
Affiliations
Soon will be listed here.
Abstract

Alzheimer disease (AD) remains a significant global health concern. The progression from preclinical stages to overt dementia has become a crucial point of interest for researchers. This paper reviews the potential of neurophysiological biomarkers in predicting AD progression, based on a systematic literature search following PRISMA guidelines, including 55 studies. EEG-based techniques have been predominantly employed, whereas TMS studies are less common. Among the investigated neurophysiological measures, spectral power measurements and event-related potentials-based measures, including P300 and N200 latencies, have emerged as the most consistent and reliable biomarkers for predicting the likelihood of conversion to AD. In addition, TMS-based indices of cortical excitability and synaptic plasticity have also shown potential in assessing the risk of conversion to AD. However, concerns persist regarding the methodological discrepancies among studies, the accuracy of these neurophysiological measures in comparison to established AD biomarkers, and their immediate clinical applicability. Further research is needed to validate the predictive capabilities of EEG and TMS measures. Advancements in this area could lead to cost-effective, reliable biomarkers, enhancing diagnostic processes and deepening our understanding of AD pathophysiology.

Citing Articles

Cortical excitability and the aging brain: toward a biomarker of cognitive resilience.

Palermo S, Di Fazio C, Scaliti E, Stanziano M, Nigri A, Tamietto M Front Psychol. 2025; 16:1542880.

PMID: 40040658 PMC: 11878273. DOI: 10.3389/fpsyg.2025.1542880.


Electrochemical Technology for the Detection of Tau Proteins as a Biomarker of Alzheimer's Disease in Blood.

Wang J, Lu X, He Y Biosensors (Basel). 2025; 15(2).

PMID: 39996987 PMC: 11853436. DOI: 10.3390/bios15020085.

References
1.
Babiloni C, Frisoni G, Vecchio F, Lizio R, Pievani M, Cristina G . Stability of clinical condition in mild cognitive impairment is related to cortical sources of alpha rhythms: an electroencephalographic study. Hum Brain Mapp. 2010; 32(11):1916-31. PMC: 6869969. DOI: 10.1002/hbm.21157. View

2.
Jackson C, Snyder P . Electroencephalography and event-related potentials as biomarkers of mild cognitive impairment and mild Alzheimer's disease. Alzheimers Dement. 2008; 4(1 Suppl 1):S137-43. DOI: 10.1016/j.jalz.2007.10.008. View

3.
Joseph S, Knezevic D, Zomorrodi R, Blumberger D, Daskalakis Z, Mulsant B . Dorsolateral prefrontal cortex excitability abnormalities in Alzheimer's Dementia: Findings from transcranial magnetic stimulation and electroencephalography study. Int J Psychophysiol. 2021; 169:55-62. DOI: 10.1016/j.ijpsycho.2021.08.008. View

4.
Poil S, de Haan W, van der Flier W, Mansvelder H, Scheltens P, Linkenkaer-Hansen K . Integrative EEG biomarkers predict progression to Alzheimer's disease at the MCI stage. Front Aging Neurosci. 2013; 5:58. PMC: 3789214. DOI: 10.3389/fnagi.2013.00058. View

5.
Dubois B, Epelbaum S, Nyasse F, Bakardjian H, Gagliardi G, Uspenskaya O . Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study. Lancet Neurol. 2018; 17(4):335-346. DOI: 10.1016/S1474-4422(18)30029-2. View