- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06826157
The Role of Advanced Electroencephalographic Data As Marker of Pathology and Prognosis in Primary Dementias
Assessing the Role of Advanced Electroencephalographic Data As Marker of Pathology and Prognosis in Primary Dementias
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:
- 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.
- 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.
- 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.
Study Overview
Status
Conditions
Intervention / Treatment
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 Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Locations
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Milano, Italy, 20132
- IRCCSS San Raffaele
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion criteria for all study subjects:
- right-handed participants;
- monolingual native Italian speakers;
- age between 50-85 years old;
- normal or corrected-to-normal visual acuity;
- oral and written informed consent to study participation.
- if assuming psychotropic drugs (i.e., benzodiazepines, antipsychotics, antidepressants), they should be at stable dosage for more than 4 weeks.
Inclusion criteria for MCI patients:
- diagnosis of amnestic MCI;
- mini Mental State Examination (MMSE) score ≥ 24;
- if assuming anticholinesterase inhibitors (i.e., galantamine, rivastigmine, donepezil) or memantine, they should be at stable dosage for more than 4 weeks;
- available CSF AD biomarkers.
Inclusion criteria for patients with mild dementia:
- diagnosis of AD dementia, FTD or LBD.
- MMSE score ≥ 15;
- if assuming anticholinesterase inhibitors (i.e., galantamine, rivastigmine, donepezil) or memantine, they should be at stable dosage for more than 4 weeks.
Exclusion criteria for patients:
- secondary forms of cognitive impairment on the basis of historical data, neurologic examination, and cerebral neuroimaging findings;
- very rapid cognitive decline that occurs over weeks or months, typically indicative of prion disease, neoplasm or metabolic disorders;
- history of other systemic (including systemic neoplasms in the last 3 years and abnormal hepatorenal functions), neurologic (including epilepsy), psychiatric diseases, head injury, cardiovascular events, and cerebrovascular alterations;
- alcohol and/or psychotropic drugs abuse;
- enrolment in clinical trials testing disease-modifying drugs for AD during study;
contraindications to MRI study:
- Cardiac pacemakers or other types of cardiac catheters;
- metal splinters or fragments;
- metal prostheses not compatible with the magnetic field generated during MRI;
- claustrophobia.
- Women who are pregnant or intending to become pregnant during the study; breastfeeding women.
Exclusion criteria for healthy controls
- History of other systemic (including systemic neoplasms in the last 3 years and abnormal hepatorenal functions), neurologic (including epilepsy), psychiatric diseases, head injury, cardiovascular events, and cerebrovascular alterations;
- alcohol and/or psychotropic drugs abuse;
- contraindications to MRI study (see above);
- women who are pregnant or intending to become pregnant during the study; breastfeeding women.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
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Experimental: Clinical, EEG, brain MRI and genetic evaluations
Participants will be screened to evaluate their eligibility.
They will undergo clinical and cognitive assessments in addition to 32-channel EEG and 3 Tesla MRI at baseline (T0) and every year for 3 years.
Furthermore, at baseline, a known genetic risk factors for AD will be explored (e., APOE gene profile).
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EEGs will be acquired to explore progressive alteration of EEG patterns throughout the neuropathology progression.
MRI evaluations will be performed to investigate structural alterations and resting state functional MRI (RS-fMRI) connectivity in participants.
Longitudinal measures of cortical/subcortical atrophy and RS-fMRI connectivity will be assessed and their relationship with EEG parameters will be explored.
At baseline, a sample of blood will be collected to perform genetic analysis (APOE alleles) for all participants
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Cortical source densities in resting-state EEG for mild cognitive impairment: Markers of differential diagnosis and dementia conversion prediction
Time Frame: 36 months
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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
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36 months
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Relationship between Alzheimer's disease and other dementias with APOE genetic variants
Time Frame: 36 months
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Relationship with APOE genetic variants (e.g., presence of APOE ε4 allele), quantified through cortical source densities reconstructed using sLORETA.
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36 months
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Accuracy of EEG markers in distinguishing Alzheimer's disease from other dementias measured by sensivity
Time Frame: 36 months
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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.
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36 months
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Accuracy of EEG markers in distinguishing Alzheimer's disease from other dementias measured by specifity
Time Frame: 36 months
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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
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36 months
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Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Massimo MF Filippi, MD, IRCCS Ospedale San Raffaele
Publications and helpful links
General Publications
- Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011 May;7(3):270-9. doi: 10.1016/j.jalz.2011.03.008. Epub 2011 Apr 21.
- McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011 May;7(3):263-9. doi: 10.1016/j.jalz.2011.03.005. Epub 2011 Apr 21.
- Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, Holtzman DM, Jagust W, Jessen F, Karlawish J, Liu E, Molinuevo JL, Montine T, Phelps C, Rankin KP, Rowe CC, Scheltens P, Siemers E, Snyder HM, Sperling R; Contributors. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018 Apr;14(4):535-562. doi: 10.1016/j.jalz.2018.02.018.
- McKeith IG, Boeve BF, Dickson DW, Halliday G, Taylor JP, Weintraub D, Aarsland D, Galvin J, Attems J, Ballard CG, Bayston A, Beach TG, Blanc F, Bohnen N, Bonanni L, Bras J, Brundin P, Burn D, Chen-Plotkin A, Duda JE, El-Agnaf O, Feldman H, Ferman TJ, Ffytche D, Fujishiro H, Galasko D, Goldman JG, Gomperts SN, Graff-Radford NR, Honig LS, Iranzo A, Kantarci K, Kaufer D, Kukull W, Lee VMY, Leverenz JB, Lewis S, Lippa C, Lunde A, Masellis M, Masliah E, McLean P, Mollenhauer B, Montine TJ, Moreno E, Mori E, Murray M, O'Brien JT, Orimo S, Postuma RB, Ramaswamy S, Ross OA, Salmon DP, Singleton A, Taylor A, Thomas A, Tiraboschi P, Toledo JB, Trojanowski JQ, Tsuang D, Walker Z, Yamada M, Kosaka K. Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology. 2017 Jul 4;89(1):88-100. doi: 10.1212/WNL.0000000000004058. Epub 2017 Jun 7.
- Pascual-Marqui RD. Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization. 2007.
- Teipel SJ, Kurth J, Krause B, Grothe MJ; Alzheimer's Disease Neuroimaging Initiative. The relative importance of imaging markers for the prediction of Alzheimer's disease dementia in mild cognitive impairment - Beyond classical regression. Neuroimage Clin. 2015 May 21;8:583-93. doi: 10.1016/j.nicl.2015.05.006. eCollection 2015.
- International AsD. World Alzheimer Report 2019: Attitudes to dementia. London: Alzheimer's Disease International, 2019
- Cecchetti G, Agosta F, Basaia S, Cividini C, Cursi M, Santangelo R, Caso F, Minicucci F, Magnani G, Filippi M. Resting-state electroencephalographic biomarkers of Alzheimer's disease. Neuroimage Clin. 2021;31:102711. doi: 10.1016/j.nicl.2021.102711. Epub 2021 May 29.
- Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, van Swieten JC, Seelaar H, Dopper EG, Onyike CU, Hillis AE, Josephs KA, Boeve BF, Kertesz A, Seeley WW, Rankin KP, Johnson JK, Gorno-Tempini ML, Rosen H, Prioleau-Latham CE, Lee A, Kipps CM, Lillo P, Piguet O, Rohrer JD, Rossor MN, Warren JD, Fox NC, Galasko D, Salmon DP, Black SE, Mesulam M, Weintraub S, Dickerson BC, Diehl-Schmid J, Pasquier F, Deramecourt V, Lebert F, Pijnenburg Y, Chow TW, Manes F, Grafman J, Cappa SF, Freedman M, Grossman M, Miller BL. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011 Sep;134(Pt 9):2456-77. doi: 10.1093/brain/awr179. Epub 2011 Aug 2.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
- Synucleinopathies
- Neurologic Manifestations
- Brain Diseases
- Central Nervous System Diseases
- Nervous System Diseases
- Mental Disorders
- Metabolic Diseases
- Neurobehavioral Manifestations
- Neurocognitive Disorders
- Cognition Disorders
- Tauopathies
- Neurodegenerative Diseases
- Movement Disorders
- Parkinsonian Disorders
- Basal Ganglia Diseases
- TDP-43 Proteinopathies
- Proteostasis Deficiencies
- Communication Disorders
- Language Disorders
- Aphasia
- Speech Disorders
- Frontotemporal Lobar Degeneration
- Cognitive Dysfunction
- Alzheimer Disease
- Dementia
- Frontotemporal Dementia
- Aphasia, Primary Progressive
- Pick Disease of the Brain
- Lewy Body Disease
Other Study ID Numbers
- DEMEEG
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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