Clinical trial NCT03654911: Sustainable Method for Alzheimer's Prediction
Official title: Sustainable Method for Alzheimer's Prediction in Mild Cognitive Impairment: EEG Connectivity and Graph Theory Combined With ApoE Testing.
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Alzheimer Disease
Amnestic-Mild Cognitive Impairment
Lead sponsor: Catholic University of the Sacred Heart
Sponsor class: OTHER
First posted: 2018-08-31
Enrollment: 150
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
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.

Brief summary: 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: 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

Eligibility criteria: 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.

Primary outcomes:
measure: Biomarkers: EEG
timeFrame: 2 years
measure: Biomarker: ApoE4
timeFrame: 2 years
Secondary outcomes:
measure: Biomarker: Accuracy of digital classifier
timeFrame: 2 years
Other outcomes:
Locations:
city: Rome
country: Italy
facility: Fondazione Policlinico A.Gemelli IRCCS, Università Cattolica del Sacro Cuore
Study officials:
References:
citation: 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.