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Completed

NCT Number: NCT03654911

Sustainable Method for Alzheimer's Prediction

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.

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Key information

Conditions

Alzheimer Disease Amnestic-Mild Cognitive Impairment Brain Diseases Central Nervous System Diseases Dementia Mental Disorders Nervous System Diseases Neurocognitive Disorders Neurodegenerative Diseases Tauopathies

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

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

Rome, Italy

About this study

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

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

EEG

Diagnostic Test

EEG

ApoE

Genetic

ApoE

Primary outcomes

  1. Biomarkers: EEG

    Time frame: 2 years

    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. Biomarker: ApoE4

    Time frame: 2 years

    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).

Secondary outcomes

  1. Biomarker: Accuracy of digital classifier

    Time frame: 2 years

    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)

Sponsors and collaborators

Lead sponsor

Catholic University of the Sacred Heart

Other

Registry information

Official study title

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

Important dates

Study start
2018
Primary completion
2019
Study completion
2020
First posted
Aug 31, 2018
Registry last updated
Jul 22, 2020

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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