Backtranslation of EEG biomarkers of Alzheimer's disease from patients to mouse model

The present Ph.D. thesis has been mainly developed on the data of the project with the short name PharmaCog (2010-2015), granted by the European Framework Programme 7 with about 28 millions of Euro (i.e. Innovative Medicine Initiative, IMI, grant agreement n°115009; www.pharmacog.org). This project involved 15 academic institutions, 12 global pharmaceutical companies, and 5 small and medium sized enterprises (SMEs). The PharmaCog project aimed at improving the pathway of drug discovery in Alzheimer’s disease (AD), based on a major interest of pharma companies, namely the validation of electrophysiological, neuroimaging, and blood biomarkers possibly sensitive to the effect of disease-modifying drugs reducing Ab42 in the brain in AD patients at the prodromal stage of amnesic mild cognitive impairment (aMCI). The core concept of the PharmaCog project was that the pathway of drug discovery in AD may be enhanced by (1) the validation of biomarkers derived from blood, EEG, magnetic resonance imaging (MRI), and positron emission tomography (PET) in patients with aMCI due to AD diagnosed by in-vivo measurement of Ab42 and phospho-tau in the brain and (2) the evaluation of the translational value of those human biomarkers in wild type (WT) mice and animal models of AD including transgenic mice with the mutation of PS1 and/or APP (i.e. PDAPP and TASTPM strains). Those genetic factors induce an abnormal accumulation of Ab42 in the brain and related cognitive deficits. The expected results may be (1) the identification of a matrix of biomarkers sensitive to the prodromal AD (aMCI cognitive status) and its progression in patients and (2) the selection of similar biomarkers related to AD neuropathology and cognitive deficits in PDAPP and TASTPM strains. These biomarkers were expected to be very useful in clinical trials testing the efficacy and neurobiological impact of new disease-modifying drugs against prodromal AD. For the development of this Ph.D. thesis, the access to the experiments and the data of the PharmaCog project was allowed by Prof. Claudio Babiloni, leader of an Italian Unit (University of Foggia in 2010-2012 and Sapienza University of Rome in 2013-2015) of the PharmaCog Consortium and coordinator of study activities relative to biomarkers derived from electroencephalographic (EEG) signals recorded from human subjects and animals in that project. Specifically, Prof. Claudio Babiloni was in charge for the centralized qualification and analysis of EEG data recorded from aMCI patients (Work Package 5, WP5) and transgenic mouse models of AD such as PDAPP and TASTPM strains (WP6). The data of the present Ph.D. thesis mostly derived from the WP5 and WP6. This document illustrating the Ph.D. thesis is structured in three main Sections: ▪ An Introductive part illustrating concisely the AD neuropathology, the mouse models of AD used in this thesis, and basic concepts of EEG techniques useful to understand the present study results; ▪ An Experimental part describing the result of the four research studies led in the framework of this Ph.D. project. Two of these studies were published in international journals registered in ISI/PubMed with impact factor, while the other two are being currently under minor revisions in those journals; ▪ A Conclusion section

Functional cortical source connectivity of resting state electroencephalographic alpha rhythms shows similar abnormalities in patients with mild cognitive impairment due to Alzheimer's and Parkinson's diseases

Objective: This study tested the hypothesis that markers of functional cortical source connectivity of resting state eyes-closed electroencephalographic (rsEEG) rhythms may be abnormal in subjects with mild cognitive impairment due to Alzheimer's (ADMCI) and Parkinson's (PDMCI) diseases compared to healthy elderly subjects (Nold). Methods: rsEEG data had been collected in ADMCI, PDMCI, and Nold subjects (N = 75 for any group). eLORETA freeware estimated functional lagged linear connectivity (LLC) from rsEEG cortical sources. Area under receiver operating characteristic (AUROC) curve indexed the accuracy in the classification of Nold and MCI individuals. Results: Posterior interhemispheric and widespread intrahemispheric alpha LLC solutions were abnormally lower in both MCI groups compared to the Nold group. At the individual level, AUROC curves of LLC solutions in posterior alpha sources exhibited moderate accuracies (0.70-0.72) in the discrimination of Nold vs. ADMCI-PDMCI individuals. No differences in the LLC solutions were found between the two MCI groups. Conclusions: These findings unveil similar abnormalities in functional cortical connectivity estimated in widespread alpha sources in ADMCI and PDMCI. This was true at both group and individual levels. Significance: The similar abnormality of alpha source connectivity in ADMCI and PDMCI subjects might reflect common cholinergic impairment. (C) 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved

On-going frontal alpha rhythms are dominant in passive state and desynchronize in active state in adult gray mouse lemurs

The gray mouse lemur (Microcebus murinus) is considered a useful primate model for translational research. In the framework of IMI PharmaCog project (Grant Agreement n°115009, www.pharmacog.org), we tested the hypothesis that spectral electroencephalographic (EEG) markers of motor and locomotor activity in gray mouse lemurs reflect typical movement-related desynchronization of alpha rhythms (about 8-12 Hz) in humans. To this aim, EEG (bipolar electrodes in frontal cortex) and electromyographic (EMG; bipolar electrodes sutured in neck muscles) data were recorded in 13 male adult (about 3 years) lemurs. Artifact-free EEG segments during active state (gross movements, exploratory movements or locomotor activity) and awake passive state (no sleep) were selected on the basis of instrumental measures of animal behavior, and were used as an input for EEG power density analysis. Results showed a clear peak of EEG power density at alpha range (7-9 Hz) during passive state. During active state, there was a reduction in alpha power density (8-12 Hz) and an increase of power density at slow frequencies (1-4 Hz). Relative EMG activity was related to EEG power density at 2-4 Hz (positive correlation) and at 8-12 Hz (negative correlation). These results suggest for the first time that the primate gray mouse lemurs and humans may share basic neurophysiologic mechanisms of synchronization of frontal alpha rhythms in awake passive state and their desynchronization during motor and locomotor activity. These EEG markers may be an ideal experimental model for translational basic (motor science) and applied (pharmacological and non-pharmacological interventions) research in Neurophysiology

Measures of Resting State EEG Rhythms for Clinical Trials in Alzheimer’s Disease:Recommendations of an Expert Panel

The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12Hz) and widespread delta (<4Hz) and theta (4-8Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes

Chronic BACE-1 Inhibitor Administration in TASTPM Mice (APP KM670/671NL and PSEN1 M146V Mutation): An EEG Study

Objective: In this exploratory study, we tested whether electroencephalographic (EEG) rhythms may reflect the effects of a chronic administration (4 weeks) of an anti-amyloid β-site amyloid precursor protein (APP) cleaving enzyme 1 inhibitor (BACE-1; ER-901356; Eisai Co., Ltd., Tokyo, Japan) in TASTPM (double mutation in APP KM670/671NL and PSEN1 M146V) producing Alzheimer's disease (AD) amyloid neuropathology as compared to wild type (WT) mice. Methods: Ongoing EEG rhythms were recorded from a bipolar frontoparietal and two monopolar frontomedial (prelimbic) and hippocampal channels in 11 WT Vehicle, 10 WT BACE-1, 10 TASTPM Vehicle, and 11 TASTPM BACE-1 mice (males; aged 8/9 months old at the beginning of treatment). Normalized EEG power (density) was compared between the first day (Day 0) and after 4 weeks (Week 4) of the BACE-1 inhibitor (10 mg/Kg) or vehicle administration in the 4 mouse groups. Frequency and magnitude of individual EEG delta and theta frequency peaks (IDF and ITF) were considered during animal conditions of behaviorally passive and active wakefulness. Cognitive status was not tested. Results: Compared with the WT group, the TASTPM group generally showed a significantly lower reactivity in frontoparietal ITF power during the active over the passive condition (p < 0.05). Notably, there was no other statistically significant effect (e.g., additional electrodes, recording time, and BACE-1 inhibitor). Conclusions: The above EEG biomarkers reflected differences between the WT and TASTPM groups, but no BACE-1 inhibitor effect. The results suggest an enhanced experimental design with the use of younger mice, longer drug administrations, an effective control drug, and neuropathological amyloid markers

Measures of resting state EEG rhythms for clinical trials in alzheimer's disease patients : recommendations of an expert panel

Background and Aim: Eyes-closed resting state electroencephalographic (rsEEG) rhythms reflect neurophysiological oscillatory mechanisms of synchronization/desynchronization of activity within neural populations of ascending reticular activating brain systems and thalamus-cortical circuits involved in quite vigilance regulation. Currently, they are not considered as biomarkers of Alzheimer’s disease (AD) in the amyloid, tau and neurodegeneration (ATN) Framework of Alzheimer’s Association and National Institute of Aging (AA-NIA). The Electrophysiology Professional Interest Area (EPIA) of AA and Global Brain Consortium endorsed this article written by a multidisciplinary Expert Panel to provide recommendations on candidate rsEEG measures for AD clinical trials. Method: The Panel revised the field literature and reached consensus about the rsEEG measures consistently associated with clinical phenotypes and neuroimaging markers of AD in previous international multicentric clinical trials. Most consistent findings: AD patients with mild cognitive impairment and dementia displayed reduced peak frequency, power, and paired-electrode “interrelatedness” in posterior alpha (8-12 Hz) rhythms and topographically widespread increases in delta (< 4 Hz) and theta (4-8 Hz) rhythms. Recommendations: (i) Careful multi-center standardization of instructions to patients, rsEEG recordings, and selection of artifact-free rsEEG periods; (ii) extraction of rsEEG power density and paired-electrode “interrelatedness” (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) rsEEG measures computed at delta, theta, and alpha frequency bands by validated open-access software platforms for replicability; (iii) valid use of those measures in stratification of AD patients and monitoring of disease progression and intervention; and iv) international initiatives to cross-validate rsEEG measures (including nonlinear) for disease monitoring and intervention

Interpreting EEG alpha activity

Exploring EEG alpha oscillations has generated considerable interest, in particular with regards to the role they play in cognitive, psychomotor, psycho-emotional and physiological aspects of human life. However, there is no clearly agreed upon definition of what constitutes ‘alpha activity’ or which of the many indices should be used to characterize it. To address these issues this review attempts to delineate EEG alpha-activity, its physical, molecular and morphological nature, and examine the following indices: (1) the individual alpha peak frequency; (2) activation magnitude, as measured by alpha amplitude suppression across the individual alpha bandwidth in response to eyes opening, and (3) alpha “auto-rhythmicity” indices: which include intra-spindle amplitude variability, spindle length and steepness. Throughout, the article offers a number of suggestions regarding the mechanism(s) of alpha activity related to inter and intra-individual variability. In addition, it provides some insights into the various psychophysiological indices of alpha activity and highlights their role in optimal functioning and behavior

Sleep, Wakefulness, Dreams and Memory

Sleep-wakefulness cycle mechanisms shown in central neural activity change