Biomarkers in Alzheimer's and Parkinson's Diseases for IA (PREDICT-NEUR)
Effects of Endogenous and Exogenous Risk Factors in Patients With Alzheimer's and Parkinson's Diseases Using Clinical Indexes and Endophenotypes (Biomarkers) as Inputs to Artificial Intelligence
Studieoversigt
Status
Detaljeret beskrivelse
Study Description
Brief Summary
The study will investigate whether endogenous and exogenous risk factors, the presence of pathological amyloid aggregates and alpha-synuclein in cerebrospinal fluid (CSF), brain connectivity, and selected clinical and biological indices, including vigilance, general motility, sleep-wake cycle characteristics, genomic instability, and DNA damage, are associated with or predictive of mild cognitive impairment (MCI) and dementia in patients with Alzheimer's disease (AD) and Parkinson's disease (PD).
Detailed Description
Parkinson's disease (PD) and Alzheimer's disease (AD) are characterized by progressive neurodegeneration associated predominantly with alpha-synuclein and beta-amyloid pathology, respectively. In patients with PD, mild cognitive impairment (PD-MCI), characterized primarily by executive dysfunction, and Parkinson's disease dementia (PDD) are common and have been associated with functional abnormalities in frontal, temporal, and parietal neural networks as identified through resting-state electroencephalography (rsEEG) and magnetic resonance imaging (MRI). In patients with AD-related MCI (AD-MCI) and Alzheimer's disease dementia (ADD), these techniques have revealed predominant episodic memory deficits associated with alterations in default mode and visuospatial neural networks.
Both disorders are also associated with frequently underrecognized abnormalities in vigilance and sleep regulation. Endogenous risk factors, including genetic profile, frailty, sex, and age, as well as exogenous factors such as lifestyle, may significantly influence cognitive impairment in PD and AD. Biomarkers derived from MRI and rsEEG may reflect these effects and contribute to variability in disease progression, prevention strategies, and therapeutic interventions.
Artificial intelligence (AI) systems integrating genetic, clinical, neuropsychological, neuroimaging, and EEG data obtained in hospital settings and through home-based telemonitoring may improve the classification and prediction of clinical status in individuals with PD and AD presenting with MCI or dementia. Clinical and instrumental data will be collected both in hospital and at home during a one-week monitoring period and will be used as input for AI-based predictive models.
Hospital-based assessments will include blood sampling, neurological and neuropsychological evaluations, MRI and EEG recordings in patients with PD, AD, and healthy control participants. Additional assessments in patients with PD and AD will include cerebrospinal fluid biomarkers, dopamine transporter single-photon emission computed tomography (DAT-SPECT), and home-based telemonitoring of vigilance, cognition, heart rate, and sleep.
The expected duration of the study is approximately two years.
Specific Aim 1
The study will evaluate whether genetic, neuropathological, neuroimaging, rsEEG, and neurophysiological markers derived from standard hospital-based procedures can be used as inputs for advanced linear regression analyses and artificial intelligence models to predict vigilance, cognitive, motor, autonomic, and clinical status (MCI and dementia) in patients with AD and PD, compared with healthy control participants, with an expected classification accuracy exceeding 80%.
Specific Aim 2
The study will evaluate whether digital markers of motor function, sleep-wake cycle regulation, cognition, and overall stress derived from one week of home-based telemonitoring can provide accurate classification of patients with PD and AD according to clinical status (MCI or dementia), with an expected accuracy exceeding 70%. Furthermore, the integration of digital telemonitoring markers with hospital-derived biomarkers will be assessed to determine whether classification performance can be improved, with an expected accuracy exceeding 85%.
Specific Aim 3
The study will evaluate the mediating and moderating effects of endogenous and exogenous risk factors on the relationships between disease-specific neuropathological biomarkers (CSF biomarkers and DAT-SPECT measures), EEG and neuroimaging markers, and the severity of cognitive impairment as reflected by MCI and dementia in patients with AD and PD. Incorporation of these risk factor effects into predictive models is expected to improve patient classification according to cognitive status, with an anticipated accuracy exceeding 90%.
Undersøgelsestype
Tilmelding (Anslået)
Kontakter og lokationer
Studiesteder
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Italy
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Rome, Italy, Italien, 00163
- IRCCS San Raffaele Roma
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Deltagelseskriterier
Berettigelseskriterier
Aldre berettiget til at studere
- Voksen
- Ældre voksen
Tager imod sunde frivillige
Prøveudtagningsmetode
Studiebefolkning
Beskrivelse
Inclusion Criteria:
- The subject must be over 60 years of age;
- The Subject must have a full understanding of the Italian language;
- The subject is available to participate in the phase telemonitoring.
Exclusion criteria:
- Inability to sign the informed consent;
- Severe dementia;
- Other concomitant diseases;
- Inability to participate in study procedures;
- Presence of arrhythmia, heart failure or previous heart attack, peripheral vascular disease or impaired circulation, valvular disease (diseases affecting the aortic valve), other diseases known conditions, end-stage renal disease (ESRD), diabetes, neurological disorders (e.g example, tremors), bleeding disorder or taking prescribed anticoagulants, tattoo(s) on the wrist where you will wear the Samsung Galaxy Watch, you will have an implanted pacemaker, a defibrillator implanted heart or other implanted electronic devices.
Studieplan
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
Kohorter og interventioner
Gruppe / kohorte |
Intervention / Behandling |
|---|---|
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healthy subjects
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Administration of Cognitive and Behavioral Tests
Andre navne:
Brain connectivity assessed through MRI biomarkers
Andre navne:
Brain connectivity assessed through EEG biomarkers
Venous blood sample of 20ml
Sample collection of exfoliated buccal mucosa
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Alzheimer MCI
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Administration of Cognitive and Behavioral Tests
Andre navne:
Brain connectivity assessed through MRI biomarkers
Andre navne:
Brain connectivity assessed through EEG biomarkers
Venous blood sample of 20ml
Sample collection of exfoliated buccal mucosa
Patients are trained in the correct use of home telemonitoring devices.
The staff will guide the patient in the use of the devices, training him in the autonomous management of the instruments.
The devices delivered to each patient will be the Samsung Galaxy4 smartwatch, and a Samsung tablet with the serious games SMARTME&YOU video game application installed.
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Alzheimer Dementia
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Administration of Cognitive and Behavioral Tests
Andre navne:
Brain connectivity assessed through MRI biomarkers
Andre navne:
Brain connectivity assessed through EEG biomarkers
Venous blood sample of 20ml
Sample collection of exfoliated buccal mucosa
Patients are trained in the correct use of home telemonitoring devices.
The staff will guide the patient in the use of the devices, training him in the autonomous management of the instruments.
The devices delivered to each patient will be the Samsung Galaxy4 smartwatch, and a Samsung tablet with the serious games SMARTME&YOU video game application installed.
|
|
Parkinson Disease MCI
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Administration of Cognitive and Behavioral Tests
Andre navne:
Brain connectivity assessed through MRI biomarkers
Andre navne:
Brain connectivity assessed through EEG biomarkers
Venous blood sample of 20ml
Sample collection of exfoliated buccal mucosa
Patients are trained in the correct use of home telemonitoring devices.
The staff will guide the patient in the use of the devices, training him in the autonomous management of the instruments.
The devices delivered to each patient will be the Samsung Galaxy4 smartwatch, and a Samsung tablet with the serious games SMARTME&YOU video game application installed.
|
|
Parkinson Disease Dementia
|
Administration of Cognitive and Behavioral Tests
Andre navne:
Brain connectivity assessed through MRI biomarkers
Andre navne:
Brain connectivity assessed through EEG biomarkers
Venous blood sample of 20ml
Sample collection of exfoliated buccal mucosa
Patients are trained in the correct use of home telemonitoring devices.
The staff will guide the patient in the use of the devices, training him in the autonomous management of the instruments.
The devices delivered to each patient will be the Samsung Galaxy4 smartwatch, and a Samsung tablet with the serious games SMARTME&YOU video game application installed.
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Hvad måler undersøgelsen?
Primære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
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Predictivity in changes of RMN parameters
Tidsramme: At patient's enrollment (Baseline)
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Changes in MRI-derived measures assess brain structural integrity, including white matter damage and the preservation of cortical networks. In detail, the following parameters will be measured: White matter lesions MRI cortical network volumes Default Mode Network (DMN) Dorsal Attention Network (DAN) |
At patient's enrollment (Baseline)
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Predictivity of EEG
Tidsramme: At patient's enrollment (baseline)
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Predictivity of changes in spectral power, measured using rsEEG sources, in detail: Power spectral density Delta band Theta band Alpha 1 band Alpha 2 band Beta 1 band Beta 2 band Gamma band |
At patient's enrollment (baseline)
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Predictivity of CFS and Blood derived Biomarkers
Tidsramme: At patient's enrollment (Baseline)
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Measurement of Biomarkers in CFS and Blood samples. In particular, from CSF we will evaluate the following biomarkers: t-tau p-tau Aβ (Amyloid-beta) in blood samples we will evaluate: N-oxoaspartic acid N-acetylspermidine Methylselenopyruvate N-methylethanolamine phosphate Succinylacetone Capryloylglycine Acetylhistamine Androsterone Glutaric acid Cadaverine Quinolinic acid Maleylacetic acid N-methyladenosine D-erythrose L-cysteine Dethiobiotin Tetradecenoylcarnitine Beta-hydroxybutyric acid L-pyroglutamic acid Creatine Uric acid Propionylcarnitine Ophthalmic acid Homovanillic acid L-histidine L-serine phosphate Nicotinuric acid Diaminoadenosine L-methionine L-asparagine |
At patient's enrollment (Baseline)
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Predictivity of clinical parameters
Tidsramme: At patient's enrollment (Baseline)
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The following clinical assessment tools will be used: Clinical assessment scales MDS-UPDRS Part III Beck Depression Inventory-II (BDI-II) Mini-Mental State Examination (MMSE) Montreal Cognitive Assessment (MoCA) Rey Auditory Verbal Learning Test - Immediate Recall (RAVLT Immediate) Rey Auditory Verbal Learning Test - Delayed Recall (RAVLT Delayed) Clock Drawing Test Semantic Fluency Test Phonemic Fluency Test Clinical and lifestyle variables Heart rate Physical activity Smoking status Hypertension Comorbidities (any additional disease) Body Mass Index (BMI) |
At patient's enrollment (Baseline)
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Predictivity of digital telemonitoring
Tidsramme: From enrollment to the end of telemonitoring at day 7
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By using electronic devices such as tablets and smartwatch we will assess parameters of cognitive function and quality of sleep. In details, by using specifically designed video games we will measured reaction time and accuracy of reaction. Quality of sleep will be recorded by wearing a smartwatch that will measure sleep duration, efficiency and quality. Interactive serious videogame response assessment Accuracy Reaction time Watch-derived measures Sleep duration Sleep efficiency Sleep quality Steps per day Intentional steps Incidental steps Average cadence during the best 30 minutes of the day |
From enrollment to the end of telemonitoring at day 7
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Samarbejdspartnere og efterforskere
Datoer for undersøgelser
Studer store datoer
Studiestart (Faktiske)
Primær færdiggørelse (Faktiske)
Studieafslutning (Anslået)
Datoer for studieregistrering
Først indsendt
Først indsendt, der opfyldte QC-kriterier
Først opslået (Faktiske)
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Faktiske)
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidst verificeret
Mere information
Begreber relateret til denne undersøgelse
Nøgleord
Yderligere relevante MeSH-vilkår
- Synukleinopatier
- Neurologiske manifestationer
- Hjernesygdomme
- Sygdomme i centralnervesystemet
- Sygdomme i nervesystemet
- Psykiske lidelser
- Neurokognitive lidelser
- Kognitionsforstyrrelser
- Tauopatier
- Neurodegenerative sygdomme
- Bevægelsesforstyrrelser
- Parkinsonlidelser
- Basal Ganglia Sygdomme
- Patologiske tilstande, tegn og symptomer
- Tegn og symptomer
- Kognitiv dysfunktion
- Alzheimers sygdom
- Parkinsons sygdom
- Demens
- Søvnvågningsforstyrrelser
Andre undersøgelses-id-numre
- RP 22/26
Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter
Studerer et amerikansk FDA-reguleret lægemiddelprodukt
Studerer et amerikansk FDA-reguleret enhedsprodukt
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