AzTrials
AzTrials

Mild Cognitive Impairment (MCI)NCT07516119

Predicting Pre-dementia

An observational study of Mild Cognitive Impairment (MCI) and Alzheimer Dementia (AD), run by Prevention Research Consortium Corp. at 1 site in United States.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts
Official record
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Trial summary

The goal of this observational study is to learn how well a multimodal "Progression and Risk" (PR) model can predict and stage early mild cognitive impairment (MCI) due to Alzheimer's disease in cognitively normal or very mildly impaired ApoE4-positive adults aged 55 and older. Read more about this study

Who is it for?
Ages 55 years and olderHealthy volunteers can take part
How many people
100 participants
Where
1 siteUnited States
Study dates
15 Nov 2026to 15 Apr 2029
Phase
Observational
Are there results?
Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 55 years and older
  • All sexes
  • Healthy volunteers accepted
  • Adult, Older adult

Study population: The Study population will be selected from patients that are part of the principal investigators private practice, from online ApoE4 support groups, and from referrals from other physicians.

Who may be able to join

  • Age
  • Age 55 years or older at enrollment.
  • APOE Genotype
  • Documented carrier of at least one APOE ε4 allele, based on prior testing (e.g., clinical APOE testing, prior genetic panel, research cohort genotyping, or direct-to-consumer testing).
  • Existing Genomic Data for PRS
  • Whole-genome sequencing (WGS) data already completed, with willingness to provide existing WGS data files (e.g., VCF, FASTQ, or equivalent) to the study team for Alzheimer's disease polygenic risk score (PRS) calculation; or
Show all 22Show fewer
  • If WGS is not available, prior high-density or targeted genotyping array data covering Alzheimer's disease risk loci, with willingness to provide these data for PRS calculation (feasibility of array-based PRS will be evaluated case-by-case).
  • Note: The study does not perform APOE genotyping or WGS as part of the research; these must be completed before enrollment.
  • Cognitive Status at Baseline
  • Cognitively normal or very mildly impaired at baseline, defined by:
  • Digital cognitive assessment and/or Punto Test consistent with a Global Clinical Dementia Rating (CDR) of 0 or 0.5.
  • No clinical diagnosis of dementia.
  • For cognitively normal (CN) and subjective cognitive decline (SCD) participants, staging by the Progression and Risk (P\&R) model (combining PRS, biomarker, and cognitive data) will be applied for risk stratification.
  • Absence of Baseline AD-MCI by Biomarkers
  • Does not currently qualify for Alzheimer's disease-related MCI (AD-MCI), operationalized as no evidence of MCI with plasma or CSF pTau217 level above a validated cutoff for AD-MCI pathology.
  • Capacity and Participation Ability
  • Able to provide informed consent (with capacity assessments and, where applicable, involvement of a legally authorized representative per institutional policy and IRB approval).
  • Able and willing to comply with study procedures, including clinic visits, cognitive testing, and biospecimen collection.
  • Willingness to Use Digital Monitoring Tools
  • Willing to wear and/or carry digital devices for continuous or frequent monitoring (e.g., smartphone app, wearable sensors such as Oura Ring, sleep device), and to participate in app-based cognitive and speech assessments.
  • Data-Sharing Authorizations
  • Willingness to sign data release authorizations allowing the study to obtain existing genomic data (WGS or array) and relevant electronic medical record (EMR) data needed for risk modeling and outcome adjudication.

Who cannot join

  • Baseline Dementia Diagnosis
  • Clinical diagnosis of dementia of any cause at baseline.
  • Major Neurological Disorders Affecting Cognition
  • History of major neurological conditions that in the investigator's judgment may confound cognitive assessment or outcomes, such as:
  • Parkinson's disease.
  • Stroke with residual neurological deficits.
Show all 21Show fewer
  • Epilepsy with frequent seizures.
  • Major Psychiatric Illness
  • Major psychiatric disorders that significantly interfere with participation or data interpretability, such as uncontrolled major depressive disorder or schizophrenia, as judged by the investigator.
  • Serious or Unstable Medical Conditions
  • Uncontrolled systemic medical illness expected to limit life expectancy to less than approximately 3 years, including but not limited to unstable cardiac, hepatic, or renal disease.
  • Recent Investigational or Disease-Modifying AD Treatments
  • Use of investigational drugs or disease-modifying Alzheimer's therapies within 6 months prior to baseline, if such treatments are likely to confound biomarker trajectories or cognitive outcomes.
  • Inability or Unwillingness to Use Required Digital Tools
  • Lack of Required Genomic Documentation or Refusal to Share Data
  • No prior APOE genotype documenting at least one ε4 allele; or
  • No available WGS or suitable genotyping array data; or
  • Refusal to share existing APOE/genomic data and necessary EMR data with the study team.
  • Baseline MCI with Positive pTau217
  • Vulnerable Populations Not Targeted
  • Children, prisoners, and pregnant individuals are not specifically targeted and will be excluded from enrollment.

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

United States1 site, 1 recruiting
  • Foster Carr MD

    San Diego, California, 92101

    Foster Carr, MD, 877-271-6078, drcarr@prevention-research.org

    Foster Carr, MD, 8772716078, drcarr@prevention-research.org

    Recruiting

Other trials in United States

About this study

Official title: Assessing Tools That Predict and Stage Mild Cognitive Impairment

The goal of this observational study is to learn how well a multimodal "Progression and Risk" (PR) model can predict and stage early mild cognitive impairment (MCI) due to Alzheimer's disease in cognitively normal or very mildly impaired ApoE4-positive adults aged 55 and older. The main questions it aims to answer are:

Can a prespecified proteogenomic PR model accurately predict conversion from cognitively normal (CN) or very mildly impaired status to pTau217-positive MCI Stage I within 24 months in ApoE4-positive adults?

Read more

Does adding digital monitoring features (e.g., sleep, activity, speech), EMR-lifestyle risk scores, and plasma biomarkers to a polygenic risk score (PRS) meaningfully improve risk stratification and time-to-conversion prediction compared with simpler models (e.g., PRS alone or standard clinical risk factors)?

If there is a comparison group: Researchers will compare performance of the full multimodal PR model (integrating PRS, plasma proteomics and other omics, digital monitoring, and EMR-lifestyle data) with simpler or reduced models (for example, PRS-only, biomarker-only, or models without continuous digital monitoring) to see if the full model provides higher discrimination (AUC/ROC), better calibration, and improved time-to-conversion prediction for CN to pTau217-positive MCI transitions.

Participants will:

Provide prior genomic data (ApoE genotype and whole-genome sequencing or high-density genotyping array data) for calculation of an ancestry- and sex-normalized Alzheimer's disease PRS and assignment to PRS-based risk strata.

Attend an in-person baseline visit and follow-up visits at months 6, 12, 18, and 24 (±2 months) for clinical evaluation, neurocognitive testing (including CDR and digital cognitive batteries), and venous or capillary blood collection for plasma pTau217 and other AD biomarkers, proteomic and methylome panels, and routine safety labs when indicated.

Use digital devices (e.g., Oura Ring and smartphone-based tools) for continuous or frequent remote monitoring of sleep, activity, heart rate metrics, mobility/location, and speech-linked digital cognitive tasks, with adherence checks at study visits.

Undergo optional or sub-cohort procedures as clinically indicated or as resources allow, such as EEG, retinal hyperspectral imaging, MRI, or amyloid PET, and optionally allow clinically indicated lumbar puncture CSF samples and external clinical data to be shared with the study for exploratory biomarker analyses.

Read the detailed description

This is an observational, first-in-human (FIH) cohort study that follows ApoE4-positive adults over two years to see how well a multimodal "Progression and Risk" (P\&R) model can predict who will develop very early, biomarker-confirmed mild cognitive impairment (MCI) due to Alzheimer's disease. The study combines genetic risk, blood biomarkers, digital testing, and wearable data to stage risk in people who are currently cognitively normal or only very mildly affected.

Background and motivation Alzheimer's disease usually develops slowly over many years, beginning with a long "preclinical" phase in which people are cognitively normal but silently accumulate disease-related changes in the brain. During this period, subtle cognitive shifts may occur before symptoms reach the level of MCI or dementia. Blood and spinal fluid markers of phosphorylated tau 217 (pTau217) have emerged as highly accurate indicators of underlying Alzheimer's pathology and predictors of progression from MCI to dementia, with performance (AUC values) in the 0.8-0.9 range in prior work. The Clinical Dementia Rating scale, particularly the Sum of Boxes (CDR-SB), is a well-validated way to stage people from normal cognition through very mild impairment and MCI, where even small changes reflect meaningful clinical transitions.

However, tools like the CDR typically require an informant and are not routinely used in primary care for people who appear cognitively normal. At the same time, large genetic studies have shown that late-onset Alzheimer's is highly polygenic: many common genetic variants, along with the APOE ε4 allele, together shape an individual's inherited risk. Polygenic risk scores (PRS) summarize this inherited risk by combining information across thousands of genetic variants, weighted by their association with Alzheimer's in genome-wide association studies. These scores, particularly when considered alongside APOE status, can help identify people with much higher odds of developing Alzheimer's and earlier onset, and they distinguish cases from controls with AUCs often in the 0.70-0.80 range.

Recent work has expanded PRS into integrative scores that incorporate genetic signals across neurodegenerative, vascular, and metabolic pathways, sometimes using deep-learning methods to capture non-linear effects. In parallel, large plasma proteomic studies and multi-omic analyses (including DNA methylation) have identified protein and molecular signatures that correlate with Alzheimer's pathology and progression. Together, these advances suggest that combining PRS with blood-based proteomic and other "omics" data, plus clinical and digital assessments, could provide a rich picture of near-term risk and disease stage in people who are still functionally normal.

The present study builds on "in silico" (computer-based) modeling work using existing cohorts that already have whole-genome sequencing, plasma proteomics including pTau217, imaging, and longitudinal cognitive and clinical data. Those analyses are being used to develop and calibrate candidate P\&R models that estimate the short-term hazard of conversion from cognitively normal or very mildly impaired status to pTau217-positive MCI. The current protocol is a prospective test of one pre-specified P\&R model in a new clinical cohort.

Overall goals and main questions This study's overarching aim is to validate a fixed proteogenomic P\&R model in a real-world group of ApoE4-positive older adults and to assess whether such a model can feasibly be implemented using a combination of existing genomic data, blood tests, and scalable digital monitoring.

For a broad audience, the main questions the study asks are:

Among ApoE4-positive adults aged 55 and older who are cognitively normal or only very mildly impaired at the start of the study, how well does a pre-specified P\&R model distinguish those who will convert to early, pTau217-positive MCI Stage I within 24 months from those who will not convert during that time?

How practical and acceptable is it to carry out this kind of multimodal assessment-combining existing genetic data, repeated blood tests, digital cognitive and speech measures, and continuous wearable monitoring-over a two-year period in this population?

How does the performance of the full P\&R model compare with simpler approaches, such as models based only on APOE plus PRS or standard clinical and cognitive measures, when predicting early MCI due to Alzheimer's?

Do digital and wearable measures (such as Oura Ring-derived sleep and activity metrics, brief speech features, and app-based cognitive tasks) meaningfully improve prediction beyond what can be achieved with genetic, blood-based, and traditional clinical measures alone?

What are the practical costs and logistics of different sampling strategies (for example, venous vs fingerstick blood, more in-person visits vs more remote monitoring), and how do these relate to the number of true conversion events correctly identified?

Secondary and exploratory goals include estimating short-term (2-5-year) and modeled longer-term (up to 10-year) conversion probabilities from cognitively normal status to MCI in this enriched, higher-risk population, and examining how an Oura Ring-based exposome risk score relates to proteogenomic risk scores and cognitive-functional measures.

Study design in plain language This is a longitudinal observational cohort study: researchers observe and measure participants over time without giving any experimental drugs or devices. The cohort will include up to roughly 90 ApoE4-positive adults at first, with plans to expand toward 100 participants as the study matures; participants are at least 55 years old and either cognitively normal or only very mildly impaired at baseline.

The study follow-up lasts 24 months from the baseline visit. Each participant attends in-person clinic visits at baseline (month 0) and at months 6, 12, 18, and 24, with an allowable window of about two months around each follow-up. Between visits, participants are monitored continuously or frequently through digital tools, including an Oura Ring and a smartphone app, to track sleep, physical activity, heart rate metrics, mobility and location, and short digital cognitive or speech tasks. A subset of about ten participants will have especially intensive wearable monitoring.

No experimental treatment is given. Instead, the focus is on gathering detailed data-genetic, blood-based, cognitive, and digital-from a well-characterized, higher-risk group in order to apply and test the P\&R model. If participants meet criteria for MCI with positive Alzheimer's biomarkers (for example, if pTau217 becomes elevated), they are referred to a neurologist, and they may be discharged from the study once they are considered "MCI positive."

Who can take part? The target population consists of adults who already know they carry at least one copy of the ApoE4 variant and have existing genomic data from earlier testing. These people may come from prior clinical care, previous research studies, or commercial direct-to-consumer genetic services, but they must be willing to share their data with the study.

Key inclusion criteria:

Age 55 or older at enrollment.

At least one ApoE4 allele documented by prior testing (for example, clinical ApoE testing, a genetic panel, or research genotyping).

Whole-genome sequencing (WGS) or, if WGS is not available, a high-density genotyping array covering Alzheimer's risk loci, with willingness to provide the raw data files (e.g., VCF, FASTQ) for PRS calculation.

Cognitively normal or very mildly impaired at baseline, as judged by digital cognitive testing and standardized scales (global CDR 0 or 0.5, no diagnosis of dementia).

For cognitively normal (CN) and subjective cognitive decline (SCD) participants, the P\&R model staging criteria-which combine PRS, biomarker, and cognitive data-will be applied to assign risk levels.

Ability to provide informed consent and to comply with study procedures.

Willingness to use digital devices (such as a smartphone, wearable sensors, and a sleep device like the Oura Ring) for continuous or frequent monitoring.

Important notes for potential participants:

The study does not perform ApoE genotyping or whole-genome sequencing as part of the research; these must already have been done before enrollment.

People without documented ApoE4 carrier status, or without available genomic data suitable for PRS calculation, are not eligible.

Exclusion criteria include:

A diagnosis of dementia (of any cause) at baseline.

Major neurological conditions that could interfere with cognitive assessment, such as Parkinson's disease, stroke with ongoing deficits, or frequent seizures.

Major psychiatric illness (for example, uncontrolled major depression or schizophrenia) that would interfere with participation or interpretation of data.

Serious uncontrolled medical illness (such as unstable heart, liver, or kidney disease) likely to limit life expectancy to less than about three years.

Use of investigational drugs or disease-modifying Alzheimer's therapies within the previous six months, if these could alter biomarker trajectories.

Contraindications to optional procedures like EEG, MRI, or PET scans (for example, certain implanted devices or severe claustrophobia).

Inability or unwillingness to use required digital monitoring tools, such as lack of smartphone access or severe sensory impairments that prevent use.

Refusal to share existing ApoE/genomic data or electronic medical record (EMR) information as needed for the study.

Participants who at screening already meet criteria for MCI with elevated pTau217 (that is, biomarker-positive MCI due to Alzheimer's) will not continue in the study and will instead be referred to a neurologist.

The initial plan is to start with a small "vanguard" group of about ten participants who already use Oura Rings, then gradually expand to a total of around 100 participants over time, with roughly equal representation across low, average, and high PRS categories among cognitively normal ApoE4 carriers.

What is the P\&R model and PRS? The polygenic risk score (PRS) used in this study is derived from genome-wide data using effect sizes from large, well-validated Alzheimer's GWAS and meta-analyses. To avoid double-counting, the APOE region is excluded from the PRS, and APOE genotype (such as number of ApoE4 alleles) is modeled separately as its own predictor.

In simplified terms, PRS is calculated by:

Selecting a set of common genetic variants (single nucleotide polymorphisms, or SNPs) that have been associated with Alzheimer's risk in prior GWAS.

For each variant, multiplying the number of risk alleles a person carries (0, 1, or 2) by the corresponding effect size (log-odds ratio) from the discovery study.

Summing these weighted contributions across all selected SNPs to obtain a single score per person.

Standard quality control and ancestry checks are performed on the genetic data, and methods like linkage disequilibrium pruning and p-value thresholds help balance predictive performance against the complexity of the score. Once computed, the PRS is standardized (converted to a z-score) within an ancestry-matched reference group and divided into quantiles (for example, lowest ~25%, next 25%, next 25%, highest ~25%). These categories are used both for recruitment (to ensure a range of genetic risk) and for subgroup analyses of conversion risk.

The broader P\&R model adds additional layers on top of PRS and APOE, potentially including:

Plasma proteomic features, including pTau217 and other Alzheimer's-related markers like pTau181, Aβ42/40 ratio, GFAP, and neurofilament light (NfL).

DNA methylation features linked to proteomic changes and cognitive or brain-related phenotypes.

Clinical and neuropsychological measures of cognition and function.

EMR-derived lifestyle and medical risk factors (forming a dementia risk score).

Digital and wearable metrics from Oura and smartphone apps (sleep patterns, activity, heart rate, speech features, etc.).

Using existing cohort data, researchers will test different time-to-event models (such as Cox proportional hazards models) that predict conversion to MCI or pTau217-positive MCI and compare them based on statistical performance (e.g., discrimination and calibration), cost, and practicality. One "best" P\&R model will be selected and then "locked" before analyzing data from this FIH cohort. For each participant in the study, the fixed model will generate a baseline risk estimate and assign them to risk levels; those predictions are then followed prospectively to see how well they match actual outcomes.

What do participants actually do? For a participant, the study experience includes a combination of clinic visits, blood draws, digital assessments, and continuous or frequent use of wearable devices.

Main activities:

Screening and consent (may overlap with baseline)

Review of eligibility, including confirmation of prior ApoE4 genotype and availability of WGS or suitable genotyping data.

Signing of informed consent and data-sharing authorizations, including permission to obtain genomic data from prior labs, research biobanks, or direct-to-consumer companies.

Optional permission to access past and future Oura Ring data.

Medical, neurologic, and psychiatric history, medication review, physical and neurological examination, and vital signs (some of which can be derived from wearables).

Review of any prior cognitive tests, imaging, and biomarker results if available.

Baseline visit (Month 0)

At the baseline clinic visit, participants undergo:

Standard cognitive and functional assessments, including the CDR (global and Sum of Boxes) and a neuropsychological battery covering memory, executive function, and language.

A digital cognitive battery (e.g., from Punto Health), designed to be sensitive to subtle changes between normal cognition and early MCI.

Blood collection (via venipuncture or fingerstick) for:

Plasma pTau217 and other Alzheimer's biomarkers (pTau181, Aβ42/40, GFAP, NfL).

Proteomic and methylome profiling using validated laboratory assays.

Clinical lab tests like complete blood count and metabolic panel, as needed.

Optional clinically indicated lumbar puncture (not required for the study) if the person's own clinician recommends it to clarify diagnosis; leftover cerebrospinal fluid can be shared for exploratory analyses with a separate biobanking consent.

Optional EEG (resting and task-based paradigms) and retinal hyperspectral imaging, if available in the clinical setting.

Optional imaging (MRI or amyloid PET) if ordered by a treating clinician as part of standard care; the study can use these imaging results if participants agree.

Initiation of digital monitoring: participants are trained to use the Oura Ring and smartphone apps that track smell tests, location/mobility, activity, speech patterns, and sleep.

Based on all baseline information, including PRS, biomarkers, and cognitive data, the P\&R model is applied to assign each participant to a risk stage (such as cognitively normal, subjective cognitive decline, or MCI Stage I) and to a risk level within those stages. Participants who already meet criteria for pTau217-positive MCI at baseline are referred to a neurologist and typically do not remain in the main CN-focused cohort.

Follow-up visits (Months 6, 12, 18, and 24)

At each scheduled follow-up visit, participants:

Provide an interval history, including any new symptoms, events, or medication changes.

Repeat CDR and selected neuropsychological tests to detect changes consistent with MCI criteria or progression.

Repeat digital cognitive assessments.

Have blood drawn again (fingerstick or venous) for pTau217 and other biomarkers; additional proteomics or methylome panels are done as budget allows.

Review adherence to digital monitoring and troubleshoot any device issues.

In some cases, repeat EEG and retinal imaging at selected timepoints (for example, baseline and 24 months) or in a subset of participants.

Undergo MRI or PET only if clinically indicated or available as standard-of-care, not as mandatory research procedures.

At each visit, the P\&R risk scores and staging categories are updated to reflect new biomarker and cognitive data.

Continuous digital monitoring and "triggered" visits

Between clinic visits, participants wear the Oura Ring and use smartphone apps that collect information on sleep, activity, heart rate, location/mobility, and performance on brief app-based cognitive or speech tasks. If these systems, or the participant themselves, flag potential cognitive or functional decline (for example, changes in sleep pattern, reduced activity, altered speech metrics, or decline on digital tasks), the study team can schedule a "triggered" visit or remote assessment.

Triggered assessments may include focused cognitive testing, repeat pTau217 and other blood biomarkers, and could lead to referral to a neurologist if criteria for MCI with positive biomarkers are met. Participants who convert to biomarker-positive MCI are referred for clinical care and may stop further intensive research follow-up according to the protocol.

In total, each participant typically has at least five in-clinic visits and five planned biospecimen collections over two years, plus any additional visits prompted by triggered assessments.

Outcomes and how they are analyzed

The primary outcome is conversion from cognitively normal status to pTau217-positive MCI Stage I within 24 months. This is defined by:

Meeting consensus criteria for MCI due to Alzheimer's disease, including objective cognitive decline on standardized tests and a CDR global score around 0.5 with CDR-SB in the "questionable impairment" or very mild range; and

Having plasma pTau217 above a validated threshold for Alzheimer's pathology, using a clinically validated assay.

CSF pTau217, if available from clinically indicated lumbar puncture outside the study, may be examined as an exploratory component but is not required. A subset analysis focuses on participants with especially high baseline risk according to the P\&R model, to examine time to conversion within that group.

Key secondary outcomes include:

Time to conversion from cognitively normal to MCI Stage I, regardless of pTau217 status, and time to biomarker conversion from pTau217-negative to pTau217-positive.

Estimated ten-year conversion rates from cognitively normal to MCI Stage I, extrapolating from the observed two-year data and informed by external cohort data.

Hazard ratios for late-onset Alzheimer's disease associated with P\&R risk scores, PRS categories, and biomarker trajectories.

Cost per participant and per detected conversion event for different sampling and monitoring strategies (e.g., fingerstick vs venous blood, more vs fewer in-person visits, different intensities of digital monitoring).

Incremental predictive value of digital monitoring features (smell, location, activity, speech, EEG, sleep) beyond more traditional risk factors and biomarkers, assessed using measures like AUC/ROC and net reclassification improvement.

Statistical analyses are primarily exploratory and hypothesis-generating, given the modest sample size and FIH nature of the study. The team will estimate P\&R model performance (such as AUC/ROC) with confidence intervals, compare alternative models using tests like DeLong's test, and use survival models and logistic regression to study time-to-event and binary outcomes. Missing data will be handled with appropriate methods (for example, multiple imputation or mixed-effects models), and sensitivity analyses will check how robust the results are to different assumptions about missingness.

Data handling, privacy, and safety All study data are captured in a secure, regulatory-compliant electronic data capture system such as REDCap or an equivalent platform. Each participant is assigned a unique study ID, and information that directly identifies individuals is stored separately from research data, linked through a secure key file. Digital device data are transmitted over encrypted channels and stored on secure servers with role-based access controls; only authorized study staff can access identifiable data, and most analyses use coded datasets.

To protect confidentiality, all staff receive training in human subjects protections and HIPAA requirements. Reports and publications share only aggregated or de-identified information; data sharing with collaborators or sponsors uses de-identified or limited datasets under formal data use agreements that forbid re-identification and require appropriate safeguards. A HIPAA authorization is incorporated into the consent process, or a waiver is obtained when appropriate. Any future uses of stored biospecimens or data beyond the current protocol will either require explicit participant consent or appropriate IRB and HIPAA determinations.

Potential risks to participants include:

Physical risks from blood draws (brief discomfort, bruising, rarely infection or fainting) and from lumbar puncture if clinically performed (headache, back pain, very rare bleeding or infection).

Minimal risks from EEG and retinal imaging (mild discomfort or fatigue).

Radiation exposure from amyloid PET scans when clinically indicated, as well as possible anxiety about imaging results.

Privacy risks from digital monitoring of location, activity, and speech-related features, including the possibility-however low with safeguards-of data breaches.

Psychological risks, such as anxiety or distress related to learning about genetic risk, biomarker status, or early cognitive changes.

Risk mitigation strategies include using trained personnel and standard procedures for sample collection, limiting imaging to what is clinically necessary, implementing robust cybersecurity measures, and offering counseling and referrals around genetic and biomarker information. Participants can opt out of specific optional components (for example, CSF sharing or certain digital features) while continuing in other parts of the study where feasible. Because the study is observational with minimal to moderate risk, a formal external Data Safety Monitoring Board is not initially planned, but could be added if requested by the IRB or sponsors; the principal investigator oversees ongoing safety monitoring and reports serious adverse events to the IRB according to institutional policy.

Informed consent and sharing of results Before any study-specific procedures, qualified staff obtain informed consent in a private setting. The consent discussion covers the purpose of the study, what participation involves, potential risks and benefits, alternatives (including not taking part), how confidentiality will be protected, how data may be shared, and the voluntary nature of participation (including the right to withdraw without affecting clinical care). The consent process also explains how genetic and biomarker results may be handled and under what conditions individual results might be returned.

For digital monitoring, the consent materials clearly describe what kinds of data are collected (for example, GPS-based location, accelerometry, and speech features but not the actual spoken content), how those data are used, and how participants can pause or discontinue certain digital components if they wish. The study does not enroll children, prisoners, or pregnant individuals; these groups are explicitly excluded. For older adults with subtle cognitive changes, the study will formally assess decision-making capacity when there is concern and may involve legally authorized representatives when allowed by institutional policy and approved by the IRB.

At the end of the study, findings will be disseminated through scientific publications and conference presentations, using de-identified or aggregated data. Participants will be offered a lay-language summary of the overall results if they would like one, so they can understand what the study learned about early detection and risk staging in Alzheimer's disease.

Keywords
Observational cohort preclinical Alzheimer's disease, ApoE4-positive cognitively normal adults 55+, Plasma pTau217 and blood biomarkers for MCI, Polygenic risk score and proteogenomic risk model, Digital cognitive assessment and Oura Ring monitoring
Medical subject headings
Cognitive Dysfunction, Alzheimer Disease, Genetic Risk Score

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

Study groups in NCT07516119
Study groupRoleWhat they receive
Oura Ring and Apple KitDigital Biomarkers
Non Digital BiomarkerNon Digital Biomarker Group
Food for the BrainDigital Cognitive Screening
Punto TestSpeech Biomarker Screening
No Cognitive ScreeningNo cognitive Screening performed

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Conversion from Cognitively Normal (CN) pTau217 Negative to pTau217-Positive

    Proportion of participants who convert from cognitively normal pTau217 negative status at baseline to pTau217 positive . With plasma pTau217 exceeding a validated cutoff for AD pathology on a clinically validated assay.

    Measured: 0-24 months

Secondary outcomes (1)
  1. Time to Conversion from CN pTau217 negative to pTau217-Positive Status (Biomarker Conversion)

    Time from baseline to first occurrence of plasma pTau217 exceeding a validated cutoff for Alzheimer's pathology on a clinically validated assay, among participants who are pTau217-negative at baseline.

    Measured: 0-24 months

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted7 Apr 2026
  2. Study start15 Nov 2026 (estimated)
  3. Primary completion15 Apr 2029 (estimated)
  4. Study completion15 Apr 2029 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
100 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT07516119
Sponsor's protocol ID
1.1c
Status last verified
Sep 2026
First submitted
31 Mar 2026
Last updated
22 Sep 2026
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
Undecided

Publications

  • Duggan MR, Paterson C, Lu Y, Biegel H, Dark HE, Cordon J, Bilgel M, Kaneko N, Shibayama M, Kato S, Furuichi M, Waga I, Hiraga K, Katsuno M, Nishita Y, Otsuka R, Davatzikos C, Erus G, Loupy K, Simpson M, Lewis A, Moghekar A, Palta P, Gottesman RF, Resnick SM, Coresh J, Williams SA, Walker KA. The Dementia SomaSignal Test (dSST): A plasma proteomic predictor of 20-year dementia risk. Alzheimers Dement. 2025 Feb;21(2):e14549. doi: 10.1002/alz.14549. Epub 2025 Feb 12.

    PubMed 39936291
  • Shen Y, Timsina J, Heo G, Beric A, Ali M, Wang C, Yang C, Wang Y, Western D, Liu M, Gorijala P, Budde J, Do A, Liu H, Gordon B, Llibre-Guerra JJ, Joseph-Mathurin N, Perrin RJ, Maschi D, Wyss-Coray T, Pastor P, Renton AE, Surace EI, Johnson ECB, Levey AI, Alvarez I, Levin J, Ringman JM, Allegri RF, Seyfried N, Day GS, Wu Q, Fernandez MV, Tarawneh R, McDade E, Morris JC, Bateman RJ, Goate A; Dominantly Inherited Alzheimer Network; Ibanez L, Sung YJ, Cruchaga C. CSF proteomics identifies early changes in autosomal dominant Alzheimer's disease. Cell. 2024 Oct 31;187(22):6309-6326.e15. doi: 10.1016/j.cell.2024.08.049. Epub 2024 Sep 26.

    PubMed 39332414
  • Heo G, Xu Y, Wang E, Ali M, Oh HS, Moran-Losada P, Anastasi F, Gonzalez Escalante A, Puerta R, Song S, Timsina J, Liu M, Western D, Gong K, Chen Y, Kohlfeld P, Flynn A, Thomas AG, Lowery J, Morris JC, Holtzman DM, Perlmutter JS, Schindler SE, Vilor-Tejedor N, Suarez-Calvet M, Garcia-Gonzalez P, Marquie M, Fernandez MV, Boada M, Cano A, Ruiz A, Zhang B, Bennett DA, Benzinger T, Wyss-Coray T, Ibanez L, Sung YJ, Cruchaga C. Large-scale plasma proteomic profiling unveils diagnostic biomarkers and pathways for Alzheimer's disease. Nat Aging. 2025 Jun;5(6):1114-1131. doi: 10.1038/s43587-025-00872-8. Epub 2025 May 20.

    PubMed 40394224
  • Jiang Y, Uhm H, Ip FC, Ouyang L, Lo RMN, Cheng EYL, Cao X, Tan CMC, Law BCH, Ortiz-Romero P, Puig-Pijoan A, Fernandez-Lebrero A, Contador J, Mok KY, Hardy J, Kwok TCY, Mok VCT, Suarez-Calvet M, Zetterberg H, Fu AKY, Ip NY. A blood-based multi-pathway biomarker assay for early detection and staging of Alzheimer's disease across ethnic groups. Alzheimers Dement. 2024 Mar;20(3):2000-2015. doi: 10.1002/alz.13676. Epub 2024 Jan 6.

    PubMed 38183344
  • Son A, Kim H, Diedrich JK, Bamberger C, Wilkins HM, Burns JM, Morris JK, Rissman RA, Swerdlow RH, Yates JR 3rd. Structural signature of plasma proteins classifies the status of Alzheimer's disease. Nat Aging. 2026 Mar;6(3):597-611. doi: 10.1038/s43587-026-01078-2. Epub 2026 Feb 27.

    PubMed 41760935
  • Western D, Timsina J, Wang L, Wang C, Yang C, Phillips B, Wang Y, Liu M, Ali M, Beric A, Gorijala P, Kohlfeld P, Budde J, Levey AI, Morris JC, Perrin RJ, Ruiz A, Marquie M, Boada M, de Rojas I, Rutledge J, Oh H, Wilson EN, Le Guen Y, Reus LM, Tijms B, Visser PJ, van der Lee SJ, Pijnenburg YAL, Teunissen CE, Del Campo Milan M, Alvarez I, Aguilar M; Dominantly Inherited Alzheimer Network (DIAN); Alzheimer's Disease Neuroimaging Initiative (ADNI); Greicius MD, Pastor P, Pulford DJ, Ibanez L, Wyss-Coray T, Sung YJ, Cruchaga C. Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for Alzheimer's disease. Nat Genet. 2024 Dec;56(12):2672-2684. doi: 10.1038/s41588-024-01972-8. Epub 2024 Nov 11.

    PubMed 39528825
  • Ali M, Timsina J, Western D, Liu M, Beric A, Budde J, Do A, Heo G, Wang L, Gentsch J, Schindler SE, Morris JC, Holtzman DM, Ruiz A, Alvarez I, Aguilar M, Pastor P, Rutledge J, Oh H, Wilson EN, Guen YL, Khalid RR; Knight Alzheimer Disease Research Center (Knight ADRC); Alzheimer Disease Neuroimaging Initiative (ADNI); Fundacio ACE Alzheimer Center Barcelona (FACE); Barcelona-1; Stanford Alzheimer Disease Research Center (Stanford ADRC); Robins C, Pulford DJ, Tarawneh R, Ibanez L, Wyss-Coray T, Sung YJ, Cruchaga C. Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuum. Neuron. 2025 May 7;113(9):1363-1379.e9. doi: 10.1016/j.neuron.2025.02.014. Epub 2025 Mar 14.

    PubMed 40088886
  • Shrestha HK, Sun H, Yarbro JM, Lee D, Liu D, Wang E, McReynolds M, Zhang N, Xie B, Yang S, Yu K, Poudel S, Li Y, Yuan ZF, Kong D, Wang M, Wang Z, Niu M, Wang H, Zaman M, Wang J, Vanderwall DR, Sun Y, Wu Z, Chen PC, Bai B, High AA, Faura J, Liu C, Bennett DA, Johnson ECB, Seyfried NT, Levey AI, Haroutunian V, Serrano GE, Beach TG, DeTure M, Kanekiyo T, Petersen RC, Bu G, McLean PJ, Dickson DW, Rademakers R, Yu G, Wang X, Zhang B, Peng J. Pan-neurodegeneration proteomics reveals disease subtypes and molecular signatures. Cell. 2026 May 14;189(10):3124-3143.e15. doi: 10.1016/j.cell.2026.02.026. Epub 2026 Mar 23.

    PubMed 41875888
  • Nielsen JE, Honore B, Vestergard K, Maltesen RG, Christiansen G, Boge AU, Kristensen SR, Pedersen S. Shotgun-based proteomics of extracellular vesicles in Alzheimer's disease reveals biomarkers involved in immunological and coagulation pathways. Sci Rep. 2021 Sep 16;11(1):18518. doi: 10.1038/s41598-021-97969-y.

    PubMed 34531462
  • Ibanez L, Pottier C, Beric A, Western D, Ali M, Cruchaga C. Understanding Neurodegenerative Diseases From the -Omics Perspective: Lessons Learnt. Ann Neurol. 2026 Mar;99(3):566-587. doi: 10.1002/ana.78170. Epub 2026 Feb 4.

    PubMed 41636082
  • Xu Y, Western D, Heo G, Nho K, Huang YN, Liu S, Oh HS, Chen Y, Timsina J, Liu M, Tang Y, Gong K, Budde J, Krish V, Imam F, Fuentes RP, Cano A, Marquie M, Boada M; Knight Alzheimer Disease Research Center (Knight-ADRC), Dominantly Inherited Alzheimer Network (DIAN), Alzheimer Disease Neuroimaging Initiative (ADNI), ACE Alzheimer Center Barcelona (ACE), Barcelona-1, Stanford Alzheimer Disease Research Center (Stanford-ADRC), The Global Neurodegeneration Proteomics Consortium (GNPC); Pastor P, Ruiz A, Fernandez MV, Bennett D, Wyss-Coray T, Saykin AJ, Ali M, Cruchaga C. Protein-based Diagnosis and Analysis of Co-pathologies Across Neurodegenerative Diseases: Large-Scale AI-Boosted CSF and Plasma Classification. medRxiv [Preprint]. 2025 Jul 10:2025.07.09.25331192. doi: 10.1101/2025.07.09.25331192.

    PubMed 40672487
  • D'Aoust T, Clocchiatti-Tuozzo S, Rivier CA, Mishra A, Hachiya T, Grenier-Boley B, Soumare A, Duperron MG, Le Grand Q, Bouteloup V, Proust-Lima C, Samieri C, Neuffer J, Sargurupremraj M, Chene G, Helmer C, Thibault M, Amouyel P, Lambert JC, Kamatani Y, Jacqmin-Gadda H, Tregouet DA, Inouye M, Dufouil C, Falcone GJ, Debette S. Polygenic score integrating neurodegenerative and vascular risk informs dementia risk stratification. Alzheimers Dement. 2025 Mar;21(3):e70014. doi: 10.1002/alz.70014.

    PubMed 40042447
  • Leonenko G, Baker E, Stevenson-Hoare J, Sierksma A, Fiers M, Williams J, de Strooper B, Escott-Price V. Identifying individuals with high risk of Alzheimer's disease using polygenic risk scores. Nat Commun. 2021 Jul 23;12(1):4506. doi: 10.1038/s41467-021-24082-z.

    PubMed 34301930
  • de Rojas I, Moreno-Grau S, Tesi N, Grenier-Boley B, Andrade V, Jansen IE, Pedersen NL, Stringa N, Zettergren A, Hernandez I, Montrreal L, Antunez C, Antonell A, Tankard RM, Bis JC, Sims R, Bellenguez C, Quintela I, Gonzalez-Perez A, Calero M, Franco-Macias E, Macias J, Blesa R, Cervera-Carles L, Menendez-Gonzalez M, Frank-Garcia A, Royo JL, Moreno F, Huerto Vilas R, Baquero M, Diez-Fairen M, Lage C, Garcia-Madrona S, Garcia-Gonzalez P, Alarcon-Martin E, Valero S, Sotolongo-Grau O, Ullgren A, Naj AC, Lemstra AW, Benaque A, Perez-Cordon A, Benussi A, Rabano A, Padovani A, Squassina A, de Mendonca A, Arias Pastor A, Kok AAL, Meggy A, Pastor AB, Espinosa A, Corma-Gomez A, Martin Montes A, Sanabria A, DeStefano AL, Schneider A, Haapasalo A, Kinhult Stahlbom A, Tybjaerg-Hansen A, Hartmann AM, Spottke A, Corbaton-Anchuelo A, Rongve A, Borroni B, Arosio B, Nacmias B, Nordestgaard BG, Kunkle BW, Charbonnier C, Abdelnour C, Masullo C, Martinez Rodriguez C, Munoz-Fernandez C, Dufouil C, Graff C, Ferreira CB, Chillotti C, Reynolds CA, Fenoglio C, Van Broeckhoven C, Clark C, Pisanu C, Satizabal CL, Holmes C, Buiza-Rueda D, Aarsland D, Rujescu D, Alcolea D, Galimberti D, Wallon D, Seripa D, Grunblatt E, Dardiotis E, Duzel E, Scarpini E, Conti E, Rubino E, Gelpi E, Rodriguez-Rodriguez E, Duron E, Boerwinkle E, Ferri E, Tagliavini F, Kucukali F, Pasquier F, Sanchez-Garcia F, Mangialasche F, Jessen F, Nicolas G, Selbaek G, Ortega G, Chene G, Hadjigeorgiou G, Rossi G, Spalletta G, Giaccone G, Grande G, Binetti G, Papenberg G, Hampel H, Bailly H, Zetterberg H, Soininen H, Karlsson IK, Alvarez I, Appollonio I, Giegling I, Skoog I, Saltvedt I, Rainero I, Rosas Allende I, Hort J, Diehl-Schmid J, Van Dongen J, Vidal JS, Lehtisalo J, Wiltfang J, Thomassen JQ, Kornhuber J, Haines JL, Vogelgsang J, Pineda JA, Fortea J, Popp J, Deckert J, Buerger K, Morgan K, Fliessbach K, Sleegers K, Molina-Porcel L, Kilander L, Weinhold L, Farrer LA, Wang LS, Kleineidam L, Farotti L, Parnetti L, Tremolizzo L, Hausner L, Benussi L, Froelich L, Ikram MA, Deniz-Naranjo MC, Tsolaki M, Rosende-Roca M, Lowenmark M, Hulsman M, Spallazzi M, Pericak-Vance MA, Esiri M, Bernal Sanchez-Arjona M, Dalmasso MC, Martinez-Larrad MT, Arcaro M, Nothen MM, Fernandez-Fuertes M, Dichgans M, Ingelsson M, Herrmann MJ, Scherer M, Vyhnalek M, Kosmidis MH, Yannakoulia M, Schmid M, Ewers M, Heneka MT, Wagner M, Scamosci M, Kivipelto M, Hiltunen M, Zulaica M, Alegret M, Fornage M, Roberto N, van Schoor NM, Seidu NM, Banaj N, Armstrong NJ, Scarmeas N, Scherbaum N, Goldhardt O, Hanon O, Peters O, Skrobot OA, Quenez O, Lerch O, Bossu P, Caffarra P, Dionigi Rossi P, Sakka P, Mecocci P, Hoffmann P, Holmans PA, Fischer P, Riederer P, Yang Q, Marshall R, Kalaria RN, Mayeux R, Vandenberghe R, Cecchetti R, Ghidoni R, Frikke-Schmidt R, Sorbi S, Hagg S, Engelborghs S, Helisalmi S, Botne Sando S, Kern S, Archetti S, Boschi S, Fostinelli S, Gil S, Mendoza S, Mead S, Ciccone S, Djurovic S, Heilmann-Heimbach S, Riedel-Heller S, Kuulasmaa T, Del Ser T, Lebouvier T, Polak T, Ngandu T, Grimmer T, Bessi V, Escott-Price V, Giedraitis V, Deramecourt V, Maier W, Jian X, Pijnenburg YAL; EADB contributors; GR@ACE study group; DEGESCO consortium; IGAP (ADGC, CHARGE, EADI, GERAD); PGC-ALZ consortia; Kehoe PG, Garcia-Ribas G, Sanchez-Juan P, Pastor P, Perez-Tur J, Pinol-Ripoll G, Lopez de Munain A, Garcia-Alberca JM, Bullido MJ, Alvarez V, Lleo A, Real LM, Mir P, Medina M, Scheltens P, Holstege H, Marquie M, Saez ME, Carracedo A, Amouyel P, Schellenberg GD, Williams J, Seshadri S, van Duijn CM, Mather KA, Sanchez-Valle R, Serrano-Rios M, Orellana A, Tarraga L, Blennow K, Huisman M, Andreassen OA, Posthuma D, Clarimon J, Boada M, van der Flier WM, Ramirez A, Lambert JC, van der Lee SJ, Ruiz A. Common variants in Alzheimer's disease and risk stratification by polygenic risk scores. Nat Commun. 2021 Jun 7;12(1):3417. doi: 10.1038/s41467-021-22491-8.

    PubMed 34099642
  • Jung SH, Kim HR, Chun MY, Jang H, Cho M, Kim B, Kim S, Jeong JH, Yoon SJ, Park KW, Kim EJ, Yoon B, Jang JW, Kim Y, Hong JY, Choi SH, Noh Y, Kim KW, Kim SE, Lee JS, Jung NY, Lee J, Lee AY, Kim BC, Cho SH, Cho H, Kim JH, Jung YH, Lee DY, Lee JH, Lee ES, Kim SJ, Moon SY, Son SJ, Hong CH, Bae JS, Lee S, Na DL, Seo SW, Cruchaga C, Kim HJ, Won HH. Transferability of Alzheimer Disease Polygenic Risk Score Across Populations and Its Association With Alzheimer Disease-Related Phenotypes. JAMA Netw Open. 2022 Dec 1;5(12):e2247162. doi: 10.1001/jamanetworkopen.2022.47162.

    PubMed 36520433

Questions about this trial

What is this clinical trial studying?

An observational study of Mild Cognitive Impairment (MCI) and Alzheimer Dementia (AD), run by Prevention Research Consortium Corp. at 1 site in United States.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 22 inclusion and 21 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: looking for participants now, as of the sponsor's last update on 22 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Contact Foster Carr, MD (8772716078, drcarr@prevention-research.org), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Conversion from Cognitively Normal (CN) pTau217 Negative to pTau217-Positive (time frame: 0-24 months). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT07516119, which also lists 16 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Sep 2026.

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