Early diagnosis of Alzheimer's disease: the role of biomarkers including advanced EEG signal analysis. Report from the IFCN-sponsored panel of experts

Alzheimer's disease (AD) is the most common neurodegenerative disease among the elderly with a progressive decline in cognitive function significantly affecting quality of life. Both the prevalence and emotional and financial burdens of AD on patients, their families, and society are predicted to grow significantly in the near future, due to a prolongation of the lifespan. Several lines of evidence suggest that modifications of risk-enhancing life styles and initiation of pharmacological and non-pharmacological treatments in the early stage of disease, although not able to modify its course, helps to maintain personal autonomy in daily activities and significantly reduces the total costs of disease management. Moreover, many clinical trials with potentially disease-modifying drugs are devoted to prodromal stages of AD. Thus, the identification of markers of conversion from prodromal form to clinically AD may be crucial for developing strategies of early interventions. The current available markers, including volumetric magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebral spinal fluid (CSF) analysis are expensive, poorly available in community health facilities, and relatively invasive. Taking into account its low cost, widespread availability and non-invasiveness, electroencephalography (EEG) would represent a candidate for tracking the prodromal phases of cognitive decline in routine clinical settings eventually in combination with other markers. In this scenario, the present paper provides an overview of epidemiology, genetic risk factors, neuropsychological, fluid and neuroimaging biomarkers in AD and describes the potential role of EEG in AD investigation, trying in particular to point out whether advanced analysis of EEG rhythms exploring brain function has sufficient specificity/sensitivity/accuracy for the early diagnosis of AD

Memorization test and resting state EEG components in mild and subjective cognitive impairment

BACKGROUND: Mild (MCI) and Subjective Cognitive Impairment (SCI) are conditions at risk of developing Alzheimer's disease (AD). Differential between normal aging at early stages can be really challenging; available biomarkers need to be combined and can be quite invasive and expensive. OBJECTIVE: The aim of this pilot study is to examine possible EEG alterations in MCI and SCI compared to controls, analyzing if a cognitive task could highlight early AD hallmarks. METHOD: We recruited 11 MCI, 8 SCI and 7 healthy subjects as controls (CS), all matched for age and education. Neuropsychological assessment and EEG recording, at resting state and during a mental memory task, were performed. Classical spectral measures and nonlinear parameters were used to characterize EEGs. RESULTS: During cognitive task, \u3b1-band power reduction was found predominantly in frontal regions in SCI and CS, diffused to all regions in MCI; moreover, decreased EEG complexity was found in SCI compared to controls. The \u3b1 -band power attenuation restricted to frontal regions in SCI during a free recall task (involving frontal areas), suggests that MCI patients compensate for encoding deficit by activating different brain networks to perform the same task. Furthermore, EEG complexity reduction - that has been found already in SCI - could be a possible early hallmark of AD. CONCLUSION: This study draws attention on the importance of nonlinear approach in EEG analysis and the potential role of cognitive task in highlighting EEG alterations at very early stages of cognitive impairment; EEG could therefore have a practical impact on dementia diagnosis

Small-World Network Analysis of Cortical Connectivity in Chronic Fatigue Syndrome using EEG

The primary aim of this thesis was to explore the relationship between electroencephalography (qEEG) and brain system dysregulation in people with Chronic Fatigue Syndrome (CFS). EEG recordings were taken from an archival dataset of 30 subjects, 15 people with CFS and 15 healthy controls (HCs), evaluated during an eye-closed resting state condition. Exact low resolution electromagnetic tomography (eLORETA) was applied to the qEEG data to estimate cortical sources and perform functional connectivity analysis assessing the strength of time-varying signals between all pairwise cortical regions of interest. To obtain a comprehensive view of local and global processing, eLORETA lagged coherence was computed on 84 regions of interest representing 42 Brodmann areas for the left and right hemispheres of the cortex, for the delta (1-3 Hz) and alpha-1 (8-10 Hz) and alpha-2 (10-12 Hz) frequency bands. Graph theory analysis of eLORETA coherence matrices for each participant was conducted to derive the “small-worldness” index, a measure of the optimal balance between the functional integration (global) and segregation (local) properties known to be present in brain networks. The data were also associated with the cognitive impairment composite score on the DePaul Symptom Questionnaire (DSQ), a patient-reported symptom outcome measure of frequency and severity of cognitive symptoms. Results showed that small-worldness for the delta band was significantly lower for patients with CFS compared to HCs. Small-worldness for delta, alpha-1, and alpha-2 were associated with higher cognitive composite scores on the DSQ. Finally, small-worldness in all 3 frequency bands correctly distinguished those with CFS from HCS with a classification rate of nearly 87 percent. These preliminary findings suggest disease processes in CFS may be functionally disruptive to small-world characteristics, especially in the delta frequency band, resulting in cognitive impairments. In turn, these findings may help to confirm a biological basis for cognitive symptoms, providing clinically relevant diagnostic indicators, and characterizing the neurophysiological status of people with CFS

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

Visual processing speed in the aging brain

Either reading a text in the office or looking for an apple in the supermarket, we are continuously flooded with visual stimuli. But how does the human brain support the efficient processing of those stimuli? And, if pathological changes occur in the brain, how do these changes lead to reductions in such efficient processing? In the present dissertation, aging is used as a model to address these two questions. First, individual differences in visual processing speed are examined in association with the coherence of the brain’s spontaneous activity and how this coherence is affected by normal aging. Second, individual differences in visual processing speed are studied in association with behavior in tasks that measure complex visual object perception in patients at risk of Alzheimer’s dementia and healthy aging adults. Based on these two approaches, evidence will be presented for an association of a slowed visual processing with (a) decreased coherent activity of a frontoinsular network in healthy aging and (b) simultaneous object perception deficits in patients at risk of Alzheimer’s dementia. This evidence provides critical insights into the particular link between visual processing speed and the coherence of the brain’s spontaneous activity and reveals perceptual deficits in patients whose clinically most apparent impairments lie in memory

Association of plasma amyloid-β oligomerization with theta/beta ratio in older adults

BackgroundOligomeric Aβ (OAβ) is a promising candidate marker for Alzheimer’s disease (AD) diagnosis. Electroencephalography (EEG) is a potential tool for early detection of AD. Still, whether EEG power ratios, particularly the theta/alpha ratio (TAR) and theta/beta ratio (TBR), reflect Aβ burden—a primary mechanism underlying cognitive impairment and AD. This study investigated the association of TAR and TBR with amyloid burden in older adults based on MDS-OAβ levels.Methods529 individuals (aged ≥60 years) were recruited. All participants underwent EEG (MINDD SCAN, Ybrain Inc., South Korea) and AlzOn™ test (PeopleBio Inc., Gyeonggi-do, Republic of Korea) for quantifying MDS-OAβ values in the plasma. EEG variables were log-transformed to normalize the data distribution. Using the MDS-OAβ cutoff value (0.78 ng/mL), all participants were classified into two groups: high MDS-OAβ and low MDS-OAβ.ResultsParticipants with high MDS-OAβ levels had significantly higher TARs and TBRs than those with low MDS-OAβ levels. The log-transformed TBRs in the central lobe (β = 0.161, p = 0.0026), frontal lobe (β = 0.145, p = 0.0044), parietal lobe (β = 0.166, p = 0.0028), occipital lobe (β = 0.158, p = 0.0058), and temporal lobe (beta = 0.162, p = 0.0042) were significantly and positively associated with increases in MDS-OAβ levels. After adjusting for the Bonferroni correction, the TBRs in all lobe regions, except the occipital lobe, were significantly associated with increased MDS-OAβ levels.ConclusionWe found a significant association of MDS-OAβ with TBR in older adults. This finding indicates that an increase in amyloid burden may be associated with an increase in the low-frequency band and a decrease in the relatively high-frequency band

Understanding the temporal dynamics of visual hallucinations in Parkinson's Disease with dementia

PhD ThesisBackground Integrative models of visual hallucinations (VH) posit that the symptom requires disruptions to both bottom-up and top-down visual processing. Although many lines of evidence point to a mixture of aberrant processing and disconnection between key nodes in the visual system, in particular the dorsal and ventral attention networks, there have been no attempts to understand the dynamic behaviour of these systems in Parkinson’s disease with dementia (PDD) with VH. Aims The primary aim of this thesis was to explore the correlates of synaptic communication in the visual system and how spatio-temporal dynamics of the early visual system are altered in relation to the severity of VH. The secondary aim was to help understand the balance between the contributions of bottom-up and top-down processing for the experience of VH in PDD. Methods An assortment of investigative approaches, including resting state electroencephalography (EEG), visual evoked potentials (VEPs), and concurrent EEG and transcranial magnetic stimulation (TMS) were applied in a group of PDD patients with a range of VH severities (n = 26) and contrasted with a group of age matched healthy controls (n = 17). Results Latency of the N1 component was similar between groups, suggesting intact transfer between the retina and the cortex. However, PDD patients had an inherent reduction in the amplitude of the VEP components and displayed a pattern of declining P1 latencies in association with more frequent and severe VH. Evoked potentials arising from TMS of the striate cortex were similar in amplitude and latency for each of the components between PDD and controls. However, inter-component activity at several stages was altered in the PDD group, whilst the frequency and severity of VH was positively associated with the amplitudes of several components in the occipital and parietal regions. Finally, attentional modulation as measured by the alpha-band reactivity was also compromised in PDD patients. iv Conclusions These data provide neurophysiological evidence that both early bottom-up and top-down dysfunctions of the visual system occur in PDD patients who hallucinate, thus supporting integrative models of VH.National Institute for Health Research (NIHR) Biomedical Research Unit (BRU)

Synchronization during an internally directed cognitive state in healthy aging and mild cognitive impairment: a MEG study

Mild Cognitive Impairment (MCI) is a stage between healthy aging and dementia. Functional connectivity is widely used to study the brain activity during resting state or cognitive tasks. We aimed to determine the functional connectivity changes required to deal with an Internally Directed Cognitive State (IDICS) in healthy aging and MCI. This task differs from the most commonly employed in Magnetoencephalograpy (MEG)/ Electroencephalography (EEG), since inhibition from external stimuli is needed, and it allows the study of this control mechanism in healthy and pathological aging. To this end, MEG signals were acquired from 32 healthy individuals and 38 MCI patients, both in resting state and while performing a subtraction task of two levels of difficulty. Phase Locking Value (PLV) was calculated for five frequency bands: delta, theta, alpha, beta and gamma. Synchronization patterns changed in both groups while performing the task. MCI patients presented higher connectivity changes than those in the control group, and this was related to a lower cognitive performance. In particular, in MCIs a hypersynchronization in delta, theta, beta and gamma bands was found, which reveals an abnormal functioning in this group. Contrary to controls, MCIs presented a lack of synchronization in the alpha band which may denote an inhibition deficit. Additionally, the magnitude of connectivity changes rose with the task difficulty in controls but not in MCIs, in line with the CRUNCH model (Compensation-Related Utilization of Neural Circuits Hypothesis)