Predicting Pre-dementia

NCT07516119 | Recruiting

• 1 other identifier: 1.1c
• Study Type: observational
• Target: 100
• Locations: 1 country
• Sites: 1

Brief 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. 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? 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.

Conditions

Mild Cognitive Impairment (MCI); Alzheimer Dementia (AD); Alzheimer Disease (AD); APOE-4 Positive

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

Outcome Measures

Primary Outcomes (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.

  0-24 months

Secondary Outcomes (1)

• Time to Conversion from CN pTau217 negative to pTau217-Positive Status (Biomarker Conversion)

  0-24 months

Study Arms (5)

Oura Ring and Apple Kit

Digital Biomarkers

Non Digital Biomarker

Non Digital Biomarker Group

Food for the Brain

Digital Cognitive Screening

Punto Test

Speech Biomarker Screening

No Cognitive Screening

No cognitive Screening performed

Eligibility Criteria

• Age: 55 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

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.

You may qualify if:

• 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
• 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.

You may not qualify if:

• 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.
• 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

Sponsors & Collaborators

• Prevention Research Consortium Corp.: lead

Study Sites (1)

Foster Carr MD

San Diego, California, 92101, United States

RECRUITING

Related Publications (16)

• 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.

  PMID: 39936291 BACKGROUND

• 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.

  PMID: 39332414 BACKGROUND

• 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.

  PMID: 40394224 BACKGROUND

• 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.

  PMID: 38183344 BACKGROUND

• 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.

  PMID: 41760935 BACKGROUND

• 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.

  PMID: 39528825 BACKGROUND

• 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.

  PMID: 40088886 BACKGROUND

• 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.

  PMID: 41875888 BACKGROUND

• 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.

  PMID: 34531462 BACKGROUND

• 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.

  PMID: 41636082 BACKGROUND

• 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.

  PMID: 40672487 BACKGROUND

• 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.

  PMID: 40042447 BACKGROUND

• 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.

  PMID: 34301930 BACKGROUND

• 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.

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  PMID: 34713027 BACKGROUND

Related Links

• Prevention Research Consortium Corp. Website

Biospecimen

Retention: SAMPLES WITHOUT DNA

Plasma

MeSH Terms

Conditions

Cognitive Dysfunction; Alzheimer Disease; Genetic Risk Score

Condition Hierarchy (Ancestors)

Cognition Disorders; Neurocognitive Disorders; Mental Disorders; Dementia; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Tauopathies; Neurodegenerative Diseases; Genetic Predisposition to Disease; Disease Susceptibility; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Foster Carr, MD

  Prevention Research Consortium Corp.

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Foster Carr, MD

CONTACT

8772716078; drcarr@prevention-research.org

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 31, 2026
• First Posted: April 7, 2026
• Study Start (Estimated): November 15, 2026
• Primary Completion (Estimated): April 15, 2029
• Study Completion (Estimated): April 15, 2029
• Last Updated: September 22, 2026

Record last verified: 2026-09

Locations

US (1)