Digitally-enhanced, Decentralized, Multi-omics Observational Cohort

Overview

The study is carried out as part of the GR2021 Priority project "Healthy Brains for life (Age 20-99): Digitally-enhanced personalized medicine study ANANEOS" and code numbered GR-00546 and it will look at the decentralized and remote assessment of the symptoms of preclinical stages in Alzheimer's disease and movement disorders, e.g. Parkinson's. For this study we are looking for participants aged over 45 without cognitive complaints or with subjective perception of cognitive decline or with mild cognitive complaints. Specific aims for the proposed study: a) to develop novel sensitive measures that can provide an early identification of those SCD and MCI individuals harboring AD pathology that are at high risk of cognitive worsening over time; b) to track pre-motor stages in Parkinson's disease and trials that enable active digital functional biomarkers; c) to track disease progression during pre-dementia and pre-motor stages in clinical practice and trials with measures that enable to capture subtle changes.

Full Title of Study: “Precision Medicine Initiative Against Alzheimer’s Disease (PMIAAD): Digitally-enhanced, Decentralized, Multi-omics, Observational Cohort”

Study Type

  • Study Type: Observational [Patient Registry]
  • Study Design
    • Time Perspective: Prospective
  • Study Primary Completion Date: October 30, 2026

Detailed Description

Digital technologies, particularly those based on the use of smartphones, wearables and/or home-based monitoring devices, here defined as 'Remote Measurement Technologies' (RMTs), provide an opportunity to change radically the way in which functional assessment is undertaken in AD, RMTs have the potential to obtain better measurements of behavioural and biological parameters associated with individual Activities of Daily Living (ADL) when compared to the current subjective scales or questionnaires. Divergence from normative ADL profiles could objectively indicate the presence of specific incipient functional impairments even at the very early stages of AD. Therefore, the main hypothesis of this project is that RMTs should allow the detection of impairments in functional components of ADLs that occur below the threshold of clinical scale detection or disability questionnaires. ANANEOS is an independent Brain Registry (patient registry), created as an organized system to collect uniform data (clinical and other) to evaluate specified outcomes for the Neurological Progression Index (NPI) and serves as a real-world view of clinical practice, patient outcomes, safety, and can serve a number of evidence development and decision making purposes.

Interventions

  • Diagnostic Test: AltoidaML
    • Computerized Complex Instrumental Activities of Daily Living Marker (NMI) (AltoidaML). ClinicalTrials.gov Identifier: NCT02843529

Arms, Groups and Cohorts

  • Subjective cognitive decline (SCD)
    • subjective perception of cognitive decline in the absence of cognitive impairment in formal neuropsychological assessment.
  • Mild cognitive impairment (MCI)
    • Single or multidomain cognitive deficits with preservation of activities of daily living.
  • Prodromal Parkinson’s Disease
    • Parkinson’s disease (PD) has a prodromal phase during which nonmotor clinical features as well as physiological abnormalities may be present.

Clinical Trial Outcome Measures

Primary Measures

  • Establish standardized protocols for acquisition, transfer & analysis of clinical, digital, imaging, biologic and genetic data that can be used in the AD & PD research community.
    • Time Frame: baseline to 60 months
    • This protocol will build on the existing Greek Brain Registry infrastructure
  • Comprehensive and uniformly acquired dataset
    • Time Frame: baseline to 60 months
    • Develop a comprehensive and uniformly acquired clinical, digital and imaging dataset and repository of biological and genetic samples that would be available to the PD research community to test hypotheses of the underlying molecular pathobiology of PD, enable modeling of PD progression to identify clinical and/or data driven PD progression sub-sets, and inform studies testing PD therapeutics (for examples, clinical trials targeting synuclein, LRRK2, GBA as well as other targets)
  • Change in Diagnostic Area Under the Receiver Operating Characteristic Curve (ROC-AUC)
    • Time Frame: 60 months of follow up
    • The machine learning models capturing voice data, hands micromovements & micro-errors, posture changes, eye tracking, visuospatial navigation micro-errors and spatio-temporal gait parameters developed for the Altoida system will be tested in this prospective cohort. Sensitivity, specificity and accuracy of the model will be tested in differential diagnosis between the study groups as well as the accuracy of predicting cognitive trajectories as measured by neuropsychological test battery in both groups.

Secondary Measures

  • Establish the probability of phenoconversion to PD
    • Time Frame: study intervals ranging from baseline to 60 months
    • Evaluate the probability of phenoconversion to PD for individuals with prodromal PD enrolled in the prodromal cohorts (including individuals with RBD, olfactory loss, a LRRK2, GBA, SNCA or rare genetic mutations (such as Parkin or Pink1) and/ or other risk factors for PD with and without DAT deficit).

Participating in This Clinical Trial

Inclusion Criteria for Cohort participants:

  • Male or female over 45 years of age. – Subject is seen at a memory clinic or is part of an observational study. – An informant (caregiver/family member) is available to collaborate. – Diagnosis of individuals in the AD biological continuum with evidence of amyloid-beta accumulation based on the presence of Aβ load AD biomarkers (either in CSF or PET scan), MMSE, CDR score and cognitive tests as defined by the Guidance document of EMA (2016) or FDA (2018): – preclinical AD: MMSE≥27 and CDR=0, either none or borderline cognitive deficits (compatible with FDA stages 1 and 2, with positive AD biomarkers). Patients reporting subjective cognitive decline who meet the criteria above are eligible for assignment to the preclinical AD group. – prodromal AD/MCI due to AD: MMSE >23, CDR=0.5, impairment on cognitive testing with RBANS (compatible with stage 3 FDA, with positive AD biomarkers). – Prodromal PD: Male or female age 60 years or older (except age 30 years or older for SNCA, or rate genetic mutations (such as Parkin or Pink1) participants). – Individuals taking any of the following drugs: alpha methyldopa, methylphenidate, amphetamine derivatives or modafinil, must be willing and medically able to hold the medication for at least 5 half-lives before DaTscan imaging. – Informed consent signed by the subject and informant. – Informant should be able to read and communicate in the language of the recruitment centre and available to actively engage in tests and questionnaires. – Subject and the informant own a smartphone. Inclusion Criteria for Healthy volunteers: – Male or female over 45 years of age. – Individuals with no evidence of amyloid-beta accumulation based on the presence of Aβ load AD biomarkers (either in CSF or PET scan). – Approximately age and gender matched to AD subjects on a group level. – An informant is available to collaborate. – MMSE >27, CDR=0. – In otherwise good health conditions, or with diagnosis mild chronic disorders (of metabolic, respiratory, immunological, cardiologic, and metabolic origin) or any other affections that are controlled by the therapy and do not importantly limit ADLs or social interactions. – Able to read and to communicate in the language of the recruitment centre. – nformed consent signed by the subject and caregiver. – Subject and informant own a smartphone. Exclusion Criteria for Cohort participants: – Presence of an additional neurological or psychiatric disease that may affect ADL, cognitive function or social interactions. – Clinical diagnosis of PD, other parkinsonism, or dementia. – Received any of the following drugs: dopamine receptor blockers (neuroleptics), metoclopramide and reserpine within 6 months of Screening visit. – Current treatment with anticoagulants (e.g. coumadin, heparin) that might preclude safe completion of the lumbar puncture. – Abnormal VB12 value. – Any other kind of disorders that relevantly affect mobility and/or ADL, cognitive function or social interactions (e.g., immune-mediated inflammatory disorders, recovery from recent trauma, stroke, etc.). – TSH above normal range – T3 or T4 outside normal range with clinically significant. Exclusion Criteria for Healthy volunteers: – Presence of an additional neurological or psychiatric disease that may affect ADL, cognitive function or social interactions. – Diagnosis of any disorders or post traumatic conditions that are not fully controlled by the therapy and produce relevant limitations of ADL, cognitive function or social interactions.

Gender Eligibility: All

Minimum Age: 45 Years

Maximum Age: N/A

Are Healthy Volunteers Accepted: Accepts Healthy Volunteers

Investigator Details

  • Lead Sponsor
    • Greece 2021 Committee
  • Collaborator
    • Ionian University
  • Provider of Information About this Clinical Study
    • Principal Investigator: Ioannis Tarnanas, Brainregistry Task Force – Greece 2021 Committee
  • Overall Official(s)
    • Panagiotis Vlamos, PhD, Principal Investigator, Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University

References

Buegler M, Harms R, Balasa M, Meier IB, Exarchos T, Rai L, Boyle R, Tort A, Kozori M, Lazarou E, Rampini M, Cavaliere C, Vlamos P, Tsolaki M, Babiloni C, Soricelli A, Frisoni G, Sanchez-Valle R, Whelan R, Merlo-Pich E, Tarnanas I. Digital biomarker-based individualized prognosis for people at risk of dementia. Alzheimers Dement (Amst). 2020 Aug 19;12(1):e12073. doi: 10.1002/dad2.12073. eCollection 2020.

Meier IB, Buegler M, Harms R, Seixas A, Coltekin A, Tarnanas I. Using a Digital Neuro Signature to measure longitudinal individual-level change in Alzheimer's disease: the Altoida large cohort study. NPJ Digit Med. 2021 Jun 24;4(1):101. doi: 10.1038/s41746-021-00470-z.

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