The Role of Advanced Electroencephalographic Data As Marker of Pathology and Prognosis in Primary Dementias

Not Applicable

• Conditions: Alzheimer Disease; Lewy Body Dementia (LBD); Mild Alzheimer Disease; Frontotemporal Dementia (FTD); Mild Cognitive Impairment (MCI); Healthy Subjects

• Registration Number: NCT06826157
• Lead Sponsor: IRCCS San Raffaele

Brief Summary

The study aims to use advanced brainwave recordings of electroencephalogram (EEG) to understand early signs of Alzheimer's disease (AD) in people with mild memory problems, known as amnestic Mild Cognitive Impairment (MCI). The goals of the study are to:

1. Find early markers of Alzheimer by analyzing EEG recordings, the researchers hope to identify patterns that indicate the presence of Alzheimer's disease. They will compare these patterns with other brain scans, like Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scans, and look at different biological markers in the participants' spinal fluid and genetic data.

2. Predict the risk of Alzheimer's disease. The study will try to find EEG patterns that can predict whether someone with MCI will develop full-blown Alzheimer's disease. The aim is to create a system that combines EEG data with other brain scans and genetic information to better understand the risk of disease progression.

3. Track changes over time: The research will also monitor changes in brain activity and structure over time to understand how Alzheimer's disease progresses.

In addition to studying people with MCI, the researchers will also look at EEG patterns in people with mild Alzheimer's disease (MILD AD), frontotemporal dementia (FTD), and Lewy-body dementia (LBD) to see how these patterns differ across various brain conditions. This could help improve the accuracy of diagnosing these diseases and understanding their link to genetic factors.

Detailed Description

The main aim of the project is to examine resting-state high definition EEG cortical sources of participants diagnosed with amnestic MCI with the goal of:

- exploring EEG-markers of Alzheimer's disease pathology and their relationships with both conventional and non-conventional brain MRI data. Researchers will explore these relationships after grouping participants according to their cerebrospinal fluid (CSF) biomarkers profile.

Researchers will explain further relationships through brain Positron Tomography Emission with fluorodeoxyglucose (PET-FDG) data performed during clinical diagnostic work-up and with Apolipoprotein E (APOE) gene profile.

* prospectively identifying EEG-markers predictive of clinical conversion to full-blown AD dementia and defining an algorithm for risk stratification by combining them with brain MRI, brain FDG-PET and genetic data;

* assessing the longitudinal changes of electrophysiological and MRI signals throughout the AD neuropathology progression;

The secondary aim of the project is to assess the accuracy of the Alzheimer-related EEG signal patterns identified in the MCI group. This will be done by comparing the EEG data with the APOE genetic information in a group of patients diagnosed with mild dementia due to Alzheimer's disease, frontotemporal dementia and Lewy-Body dementia

Study Timeline

• Study Start: 2021-11-05
• Study First Submitted: 2024-12-04
• Status Verified: 2025-02
• Study First Submitted QC: 2025-02-10
• Study First Posted: 2025-02-13
• Last Update Submitted: 2025-02-13
• Last Update Posted: 2025-02-17
• Primary Completion: 2026-04-15
• Study Completion: 2027-01-01

Recruitment & Eligibility

• Status: ENROLLING_BY_INVITATION
• Sex: All
• Target Recruitment: 175

Inclusion Criteria

Not provided

Exclusion Criteria

Not provided

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Primary Outcome Measures

Name	Time	Method
Cortical source densities in resting-state EEG for mild cognitive impairment: Markers of differential diagnosis and dementia conversion prediction	36 months	Source densities in resting-state high-definition EEG in patients with mild cognitive impairment, measured as cortical markers for differential diagnosis of dementias and prediction of conversion to full-blown dementia

Secondary Outcome Measures

Name	Time	Method
Accuracy of EEG markers in distinguishing Alzheimer's disease from other dementias measured by sensivity	36 months	Diagnostic accuracy of EEG markers in distinguishing Alzheimer's disease (AD) from other dementias (e.g., frontotemporal dementia, Lewy-body dementia), measured as the ability to correctly identify cases that are not Alzheimer's (e.g., frontotemporal dementia, Lewy-body dementia) compared to Alzheimer's cases.
Accuracy of EEG markers in distinguishing Alzheimer's disease from other dementias measured by specifity	36 months	Diagnostic accuracy of EEG markers in distinguishing Alzheimer's disease (AD) from other dementias measured as the ability to correctly identify cases that are not Alzheimer's (e.g., frontotemporal dementia, Lewy-body dementia) compared to Alzheimer's cases
Relationship between Alzheimer's disease and other dementias with APOE genetic variants	36 months	Relationship with APOE genetic variants (e.g., presence of APOE ε4 allele), quantified through cortical source densities reconstructed using sLORETA.

Trial Locations

Locations (1)

IRCCSS San Raffaele; 🇮🇹 Milano, Italy