Diagnosis and Monitoring of Disease Progression Using Deep Neuro Signatures

N/AActive Not RecruitingNCT05153941

Altoida3,500 enrolled

Overview

Alzheimer's disease (AD) clinically characterized by the cognitive impairment and lowering of various functional abilities lead to staggering costs and suffering, which are particularly related to the social impacts of caring for increasingly disabled individuals. Some of these changes can be almost undetectable in the early stages of the disease, worsening over time often and at a varying rate of progression in different people. The traditional clinical scales or questionnaires such as ADCS (Alzheimer's Disease Cooperative Study) - ADL (Activities of Daily Living) for detecting such functional disabilities are typically blunt and rely on direct observation or caregiver recall. Digital technologies, particularly those based on the use of smart phones, wearable 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 potential to obtain better measurements of behavioral 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 incipient functional impairment at the very early stages of AD. Therefore, the main hypothesis of this study is that RMTs should allow the detection of impairments in functional components of ADLs that occur below the detection threshold of clinical scale or questionnaires.

Relevant outcome measurements for the study have been selected through the following longitudinal process: Identification of functional domains that meet one or more of the following criteria: Predicts conversion of MCI due to AD to mild AD dementia. Impaired in mild AD dementia. Predicts functional decline in AD dementia. Reported as important by an AD dementia patient advisory board. Identification of candidate RMTs to cover real-life measurement of the functional domains identified in step 1. Identification of candidate digital biomarkers, which are life-log data such as steps, sleep, heart rate and exercise collected by RMTs, to cover clinical measurement of the functional domains identified in step 1. Functional domains, RMTs, and clinical assessments that resulted from the selection process above are listed in Table 1, and 2. The selection process described in step 1 resulted in the identification of the following functional domains, sorted by relevance \[HR (highly relevant), R (relevant), N (neutral), and LR (least relevant)\]. The central assumption of the study is that functional disabilities proportionally increase with the progressive worsening of the AD. A recent classification proposed by the FDA 2018 draft guidance for the development of novel treatments in AD identifies the early disease progression in 3 stages: (a) Patients with characteristic pathophysiologic changes of Preclinical AD but no evidence of clinical impact (Stage 1) (b) Patients with characteristic pathophysiologic changes of AD and subtle or more apparent detectable abnormalities on sensitive neuropsychological measures, but no functional impairment (Stage 2), and (c) Patients with characteristic pathophysiologic changes of AD and subtle or more apparent detectable abnormalities on sensitive neuropsychological measures, but mild and detectable functional impairment (Stage 3). The aim of the DNS study is to assess the feasibility, utility and performance of selected RMTs in profiling ADL in real-world settings. This goal will be achieved by evaluating digital signals collected either continuously, or daily, or weekly at home, either using wearable devices or home-located ambient devices, determining as much as possible the specific context-dependent conditions in which the signals are measured. As a general hypothesis, RMTs will deliver more sensitive and less variable measurements when compared to standard clinical assessments, questionnaires and tests measuring specific functional capabilities in the clinics. The most important results of the study will be (1) the evidence that some RMT parameters will provide insights for lower variance than the standard scales or questionnaires, (2) the capacity of Altoida, Inc. NMI and/or RMTs to significantly differentiate the preclinical AD stages 1 \& 2 when compared to healthy volunteers with negative AD biomarkers as a control, and (3) a similar capabilities of Altoida, Inc. NMI and/or RMTs to detect monotonic change in the mild cognitive impairment (MCI) due to AD group and, even more, in mild, moderate and severe AD dementia groups, proportional to the specific functional impairment known to worsen during the disease progression.

Eligibility

Sex: ALLMin age: 50 YearsHealthy volunteers:

Medical Language ↔ Plain English

• Inclusion criteria Subjects enrolled in this study are diagnosed based on the established criteria as described below by physicians/medical doctors with expertise in Alzheimer's disease and other neurodegenerative disorders. To be eligible to participate in this study, a subject must meet the following criteria: 1a. For subjects in the Alzheimer's continuum and those with non-AD pathologic changes, (n=3,110): * Male or female over 50 years of age. * Approximately age and gender matched among groups as classified below. * A study partner (caregiver/family member) is available to collaborate to visit the site together with the subject and give necessary information on the subject. * Physician's clinical judgement of individuals by classifying into three syndromal stages of cognitive continuum: cognitively unimpaired, mild cognitive impairment, and dementia as described in 2018 NIA-AA research framework \[39\], \[40\] while taking into account of clinical assessment performance such as MMSE and CDR scores. This syndromic staging is applicable to all members of a research cohort independent from biomarker profiles. * Numeric clinical staging in 2018 NIA-AA research framework may also be applied to cognitive staging in the Alzheimer's continuum \[40\] . * cognitively unimpaired * mild cognitive impairment * mild dementia * moderate dementia * severe dementia * AT(N) biomarker profile as evidenced by CSF test results is combined with the clinical staging for the classification of each subject. * Aβ biomarker positive subjects without cognitive impairment, those with MCI, and those with dementia are considered as preclinical AD, MCI due to AD, and dementia due to AD, respectively. In case otherwise stated, these nomenclatures are used throughout this study. * Informed consent signed by the subject and/or study partner. * Study partners should be able to read and communicate in the language of the Hospital site and available to actively engage in tests and questionnaires. * Subject or the study partner owns a smart phone. * Their house should allow appropriate Wi-Fi and/or phone line connectivity. * For those participating in the sub-study from each intended respective subject grouping described in Sub-study section, signature on an additional Informed Consent 1b. Healthy volunteer subjects (n=400): * Male or female over 50 years of age. * Individuals with all AT(N) biomarkers at normal levels (i.e., A-,T-, (N)-) as confirmed by negative status of respective AD biomarker test utilized in this study. * Approximately age and gender matched to subjects in the Alzheimer's continuum and those with non-AD pathologic changes on a group level. * A study partner is available to collaborate. * Cognitively unimpaired as defined by syndrome staging of cognitive continuum in 2018 NIA-AA research framework \[40\], \[41\] supported by each of the following test scores: MMSE ≥27, and 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 center. * Informed consent signed by the subject and study partner. * Subject or study partner owns a smart phone. * Their house should allow appropriate Wi-Fi and/or phone line connectivity. * For those participating in the sub-study from each intended respective subject grouping described in Sub-study section, signature on an additional Informed Consent Exclusion criteria A potential subject who meets any of the following criteria will be excluded from participation in this study. Those criteria would be applied at the subject screening: 2a. For subjects in the Alzheimer's continuum and those with non-AD pathologic changes: * Presence of an additional neurological, psychiatric, or chronic disease that may affect ADL, cognitive function or social interactions. * 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.). MRI assessment should be utilized for verifying those disorders. * TSH above normal range * T3 or T4 outside normal range with clinically significant. * Positive test for SARS-CoV-2 on a nasopharyngeal swab * Failure to show negative PCR results for Covid19 or proof of vaccination 2b. Healthy volunteer subjects: * Presence of an additional neurological, psychiatric, or chronic 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. * Positive test for SARS-CoV-2 on a nasopharyngeal swab * Failure to show negative PCR results for Covid19 or proof of vaccination

Outcomes

Primary Outcomes

ADL using selected RMTs

Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia in outcome measures of ADL using selected RMTs.

Time frame: 5 years

Neuropsychological assessment like the Clinical Dementia Rating (CDR) scale

Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia using RMTs, neuropsychological assessment like CDR.

Time frame: 5 years

Neuropsychological assessment like Altoida, Inc. Neuro Motor Index (NMI) medical device

Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia using RMTs, neuropsychological assessment like the Altoida, Inc. Neuro Motor Index (NMI) medical device.

Time frame: 5 years

Demographics, medical history, physical status, life-habits, and medication from the analysis of neuropsychological assessments.

Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia focusing on their demographics, medical history, physical status, life-habits, and medication from the analysis of neuropsychological assessments.

Time frame: 5 years

Demographics, medical history, physical status, life-habits, and medication from the analysis of biomarker measurements.

Time frame: 5 years

Demographics, medical history, physical status, life-habits, and medication from the analysis of RMTs

Time frame: 5 years

Demographics, medical history, physical status, life-habits, and medication from the analysis of Altoida NMI medical device.

Time frame: 5 years

Diagnosis and Monitoring of Disease Progression Using Deep Neuro Signatures

Overview

Conditions

Eligibility

Locations (1)

Outcomes

Primary Outcomes