Sex Specific EEG Signatures Associated with Cerebrospinal Fluid Biomarkers in Mild Cognitive Impairment
Overview
Psychiatry
Authors
Affiliations
Objective: The use of the electroencephalography (EEG) technique in Alzheimer's disease (AD) diagnosis is scarce due to a lack of validation of its neurophysiological information with current biomarkers. Therefore, our goal was to assess correlations between brain spectral power signatures and cerebrospinal fluid markers (CSF) such as amyloid-β 42 load (Aβ-42), total tau (t-tau), and phosphorylated tau (p-tau) in a mild cognitive impairment (MCI) population. Furthermore, given the AD sex-dependent vulnerability related to CSF biomarkers, we went a little forward looking for different electrophysiological correlations for males and females independently.
Methods: A data-driven approach was employed to determine bidimensional spectral power signatures (space-frequency) that correlated (Spearman) significantly with any of the three CSF markers in 27 patients with MCI in any of the two sex-dependent subsamples (i.e., 12 females and 15 males).
Results: Our main significant outcomes evidenced 1) a negative correlation of Aβ-42 load with central-posterior theta power and a negative correlation of t-tau with widespread alpha power within the male subsample, and 2) a significant negative correlation between t-tau and widespread beta power in the female subgroup.
Conclusions: There is a distinctive profile of correlations between resting-state electrophysiological signatures and CSF markers in male and female individuals.
Significance: The combination of these two measures would be pointing out the need of a more personalized approach to promote early AD diagnosis.
Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach.
Gaeta A, Quijada-Lopez M, Barbe F, Vaca R, Pujol M, Minguez O Front Aging Neurosci. 2024; 16:1369545.
PMID: 38988328 PMC: 11233742. DOI: 10.3389/fnagi.2024.1369545.
Yener G, Kiyi I, Duzenli-Ozturk S, Yerlikaya D Brain Sci. 2024; 14(6).
PMID: 38928567 PMC: 11202018. DOI: 10.3390/brainsci14060567.
Li Z, Wu M, Yin C, Wang Z, Wang J, Chen L Front Aging Neurosci. 2024; 16:1364808.
PMID: 38646447 PMC: 11026635. DOI: 10.3389/fnagi.2024.1364808.
Fernandez A, Cuesta P, Marcos A, Montenegro-Pena M, Yus M, Rodriguez-Rojo I Geroscience. 2023; 46(2):2619-2640.
PMID: 38105400 PMC: 10828170. DOI: 10.1007/s11357-023-01020-z.
Morrone C, Raghuraman R, Hussaini S, Yu W Mol Neurodegener. 2023; 18(1):27.
PMID: 37085942 PMC: 10119020. DOI: 10.1186/s13024-023-00617-4.