Sustainable Method for Alzheimer's Prediction

Study Overview
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Brief Summary
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This is an observational study with the aim of validating, in a consistent population sample, with appropriate follow-up, whether EEG connectivity analysis combined with the neuropsychological evaluation and ApoE genotype testing in aMCI could be of help in early identification of converted aMCI as a first-line screening method in order to intercept early those subjects with a high risk for rapid progression to AD.

Detailed Description
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Primary aim of the present project is to investigate the dynamic connectivity among brain centers by using a mathematical (Small World) approach to the analysis of EEG-related neural networks. The aim is to provide reliable discrimination of amnesic-Mild Cognitive Impairment (a MCI) subjects who, on individual basis, will rapidly convert to Alzheimer Disease (AD) after a relatively brief follow-up. Moreover, keeping in mind that the epsilon-4 allele of the ApoE gene is a genetically determined risk factor for pathogenesis of late-onset AD, a secondary endpoint is introduced to investigate whether the EEG connectivity markers together with a genetically determined risk of dementia as represented by ApoE testing can reach higher sensitivity/specificity for early discrimination of MCI converting to AD

Official Title
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Sustainable Method for Alzheimer's Prediction in Mild Cognitive Impairment: EEG Connectivity and Graph Theory Combined With ApoE Testing.

Conditions
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Alzheimer Disease, Amnestic-Mild Cognitive Impairment

Intervention / Treatment
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* Diagnostic Test: EEG
* Genetic: ApoE


Participation Criteria
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Eligibility Criteria
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Exclusion criteria for AD will be: frontotemporal dementia; behavioural variant of frontotemporal dementia; vascular dementia; extra-pyramidal syndromes; reversible dementias (including pseudodementia of depression); Lewy body dementia. The exclusion criteria for aMCI will be: mild AD, as diagnosed by standard protocols including National Institute on Aging-Alzheimer's Association workgroups (McKhann et al. 2011); evidence (including magnetic resonance imaging -MRI procedures) of concomitant dementia such as frontotemporal, vascular and reversible dementias (including pseudo-depressive dementia), marked fluctuations in cognitive performance compatible with Lewy body dementia and/or features of mixed dementias; evidence of concomitant extrapyramidal symptoms; clinical and indirect evidence of depression as revealed by the Geriatric Depression Scale GDS (Yesavage et al. 1982); scores lower than 14 (no depression); other psychiatric diseases, epilepsy, drug addiction, alcohol dependence, use of neuro/psychoactive drugs including acetylcholinesterase inhibitors; current or previous uncontrolled or complicated systemic diseases (including diabetes mellitus) or traumatic brain injuries.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| aMCI subjects<br>EEG recording, ApoE testing | Diagnostic Test: EEG<br>* EEG<br>Genetic: ApoE<br>* ApoE<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Biomarkers: EEG | EEG recording will be performed at rest, with closed eyes from routine electrode scalp positions according to the International 10-20 system. Functional connectivity analysis will be performed using eLORETA evaluating intracortical Lagged Linear Coherence. Weighted and undirected networks will be built from the above measure. Small World parameter is a dimentionless number that will be assessed as Biomarker of brain connectivity networks, since it measures the balance between local connectedness and the global integration of a network, representing brain network organization. Small world index will be computed in the seven EEG frequency bands delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz) and gamma (30-45 Hz) (Vecchio et al., 2018 doi: 10.1002/ana.25289) | 2 years | 
| Biomarker: ApoE4 | It will be evaluated the allele of the Apo-E gene as biomarker for the pathogenesis of late-onset and sporadic AD. The Apo-E test provides a dimentionless value represented by the type of the allele (ε2, ε3,ε4). | 2 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Biomarker: Accuracy of digital classifier | Secondary endpoint will be to investigate whether EEG connectivity markers (small world ) along with genetically determined risk-indicators for dementia, as represented by Apo-E testing can reach a greater sensitivity, specificity and accuracy for a digital classifier (i.e. an algorithm that solve the problem of identifying to which of a set of categories a new observation belongs) able to predict the MCI conversion to AD. The accuracy value is dimentionless number represented by a percentual value and it is the biomarker for the ability of the classifier for the early identification of AD (Vecchio F. et al., 2018 doi: 10.1002/ana.25289) | 2 years |