Sustainable Method for Alzheimer's Prediction

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

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.

Study Overview

• Status: Completed
• Conditions: Alzheimer Disease; Amnestic-Mild Cognitive Impairment
• Intervention / Treatment: Diagnostic test: EEG; Genetic: ApoE

Detailed Description

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

• Study Type: Observational
• Enrollment (Actual): 150

Contacts and Locations

Study Locations

• Italy
  • Rome, Italy
    • Fondazione Policlinico A.Gemelli IRCCS, Università Cattolica del Sacro Cuore

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Participants 150 aMCI will be recruited (including 90 already available EEG and clinical data recordings) in order to obtain two homogeneous sub-groups according to the clinical follow-up, classifying them as converted to AD or stable aMCI after a 12 to 24 months period from the time of baseline EEG recording.

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
aMCI subjects; EEG recording, ApoE testing	Diagnostic test: EEG; EEG; Genetic: ApoE; ApoE

What is the study measuring?

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

Collaborators and Investigators

• Sponsor: Catholic University of the Sacred Heart

Publications and helpful links

General Publications

• Vecchio F, Miraglia F, Iberite F, Lacidogna G, Guglielmi V, Marra C, Pasqualetti P, Tiziano FD, Rossini PM. Sustainable method for Alzheimer dementia prediction in mild cognitive impairment: Electroencephalographic connectivity and graph theory combined with apolipoprotein E. Ann Neurol. 2018 Aug;84(2):302-314. doi: 10.1002/ana.25289. Epub 2018 Aug 25.

Study record dates

Study Major Dates

• Study Start (ACTUAL): April 11, 2018
• Primary Completion (ACTUAL): June 28, 2019
• Study Completion (ACTUAL): January 31, 2020

Study Registration Dates

• First Submitted: July 10, 2018
• First Submitted That Met QC Criteria: August 30, 2018
• First Posted (ACTUAL): August 31, 2018

Study Record Updates

• Last Update Posted (ACTUAL): July 22, 2020
• Last Update Submitted That Met QC Criteria: July 21, 2020
• Last Verified: July 1, 2020

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Mental Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Neurocognitive Disorders; Neurodegenerative Diseases; Dementia; Tauopathies; Cognition Disorders; Alzheimer Disease; Cognitive Dysfunction
• Other Study ID Numbers: ROSSINI_MSD_ID1764

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No