Is QEEG an effective biomarker in predicting cognitive decline?

Abstract

AbstractBackgroundAlterations in EEG traces are observed in synaptic failure with a reduction in the background α rhythm and an increase in slow frequencies (θ‐δ). The aim of the study is to evaluate whether quantitative EEG (QEEG) can be a reliable biomarker of neuro‐cognitive disorders (NCD), able to identify patients with mild and major‐NCD, and to reflect the clinical course over time.Method63 donors from the Abbiategrasso Brain Bank were included in the study. According to our protocol, the subjects were evaluated longitudinally (2015‐21) through a multidimensional assessment, and divided into 3 groups age and sex matched (NOLD for normal old, mild‐NCD and major‐NCD). A selection of 12 donors was further divided into 3 groups based on the change of the clinical state over time (NOLD>NOLD; NOLD>mild‐NCD and mild‐NCD>major‐NCD). The QEEG analysis was performed considering the relative power distribution (RPD) of band frequency (β, α, θ, δ) and the peak frequency (PF), as synthetic index. The Kruskall Wallis test, with post hoc analysis, and change analysis through one‐way ANOVA were used for the comparison between groups. Kendall’s TAU was used for correlations.ResultThe RPD of the different frequency bands as well as the PF were significantly different in the NOLD, mild‐NCD and major‐NCD groups (p<0.001); α‐RPD and PF decreased, while θ and δ‐RPD increased. NOLDs and mild‐NCDs were always different from major‐NCDs (p<0.001), while NOLDs were statistically different from mild‐NCDs only for θ‐RPD (p = 0.019), b+a‐RPD (p = 0.028) and q+d‐RPD (p = 0.025). A strong correlation between PF and MMSE (p<0.001) was present. Change analysis demonstrated that PF was lower in the NOLD>mild‐NCD group compared to the NOLD>NOLD group (p = 0.049). Interestingly, PF did not present any correlation with depression using CES‐D score (Center Epidemiological Studies‐Depression).ConclusionThe RPD is able to distinguish NOLDs from mild‐ and major‐NCDs. If determined from the initial stages of the disorder, PF may be a promising biomarker for mild‐NCD diagnosis discriminating initial cognitive impairment from depression, and it may be useful to follow the evolution of dementia. PF appears to be a synthetic and simple quantitative index, easily obtained from a standard digital EEG, and widely applicable.