The Signature of Alzheimer's Disease in Subjective Cognitive Decline

NCT07402161 | Recruiting

• 2 other identifiers: CET 25-2025Robert-Katzman Award 2024
• Study Type: observational
• Target: 250
• Locations: 1 country
• Sites: 1

Brief Summary

This study focuses on improving early detection of Alzheimer's disease (AD) in patients with subjective cognitive decline (SCD), a preclinical stage of cognitive impairment, in the context of emerging disease-modifying therapies (DMTs). Current biomarkers, such as brain MRI, PET scans, and cerebrospinal fluid (CSF) markers, are highly accurate but costly, invasive, and not widely accessible. The study aims to provide cost-effective, scalable tools for early identification of individuals at risk, enabling personalized assessment and timely DMT administration. Objectives:

• Evaluate the accuracy of innovative, easily accessible biomarkers in predicting biologically confirmed AD.
• Assess the predictive utility of previously studied methods for SCD patients.
• Explore new approaches, including automated speech analysis, to identify cognitive decline.
• Evaluate genetic contributions to AD risk.
• Integrate data from these various modalities using machine learning to create a predictive model for AD in SCD patients. Study Design: This is a multicenter, longitudinal, low-intervention study conducted at IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy (UO1) and the Center for Research and Innovation in Dementia, Careggi Hospital, Florence, Italy (UO2). Eligible participants are adults with SCD, intact daily functioning, and Mini-Mental State Examination (MMSE) scores \>24. Exclusion criteria include neurological or systemic diseases, major psychiatric disorders, substance use, or prior head injury. Participants undergo:
• Detailed medical and family history collection.
• Comprehensive neuropsychological, personality, and independence in daily activities assessment
• EEG recording in resting state.
• Blood sampling for plasma biomarkers (Aβ42, Aβ40, p-tau181, p-tau217, t-tau, NfL, GFAP).
• CSF biomarker analysis (Aβ42, Aβ40, p-tau, t-tau).
• Genetic analysis of AD-related genes (PSEN1, PSEN2, APOE, TREM2, ABCA7, BDNF, HTT).
• Speech recording and analysis using standardized tasks to extract features for automated evaluation. The study expects to create a machine learning-based predictive model combining biomarker, neuropsychological, EEG, speech, and genetic data to improve early detection and guide personalized patient care. Procedures:
• Neuropsychological evaluations occur at baseline and two-year follow-up.
• Language recordings are conducted in controlled settings using standardized picture description tasks.
• EEG is recorded using 21-channel systems.
• Blood and CSF samples are collected, processed, and stored at -80°C for subsequent analysis at respective institutional laboratories.
• Plasma biomarkers are analyzed with Simoa technology; CSF biomarkers are analyzed using chemiluminescent enzyme immunoassay (CLEIA).
• Genetic analyses employ PCR, high-resolution melting analysis (HRMA), sequencing, and capillary electrophoresis as appropriate for specific genes or polymorphisms. The study expects to create a machine learning-based predictive model combining biomarker, neuropsychological, EEG, speech, and genetic data to improve early detection and guide personalized patient care.

Conditions

Subjective Cognitive Decline (SCD); Subjective Cognitive Complaints (SCCs); Subjective Cognitive Impairment; Subjective Cognitive Concerns; Subjective Memory Complaint; Subjective Memory Decline

Keywords

Alzheimer; Neuropsychology; EEG; Machine Learning; Biomarkers; Speech

Outcome Measures

Primary Outcomes (1)

• Diagnostic accuracy of biomarkers in detecting Alzheimer's disease

  The accuracy of blood-based biomarkers will be evaluated for predicting a biological diagnosis of AD and for predicting progression of cognitive decline during follow-up. The biological diagnosis of AD will be defined by cerebrospinal fluid biomarker positivity, specifically an abnormal Aβ42/Aβ40 ratio and elevated CSF p-tau181. Progression of cognitive decline will be defined as worsening in at least one cognitive domain, loss of autonomy, or progression to MCI or dementia.

  12-24 months

Secondary Outcomes (4)

• Accuracy of neuropsychological and neurophysiological measures in predicting AD pathology defined according to CSF biomarker profile.

  12-24 months

• Accuracy of automated speech analysis in predicting AD

  12-24 months

• Effect of genetic variants on the risk of AD in patients with SCD

  12-24 months

• A machine learning model to predict AD

  12-24 months

Study Arms (1)

Subjective Cognitive Decline

Individuals complaining of cognitive decline that are not confirmed by neuropsychological examination

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Participants will be consecutively recruited among patients referred for cognitive disorders to the Neurology Unit (U.O.C.) of IRCCS Policlinico San Donato (hereinafter referred to as UO1) and to the Research and Innovation Center for Dementia (CRIDEM) of the Careggi University Hospital in Florence (AOUC, hereinafter referred to as UO2).

You may qualify if:

• Clinical diagnosis of SCD according to the SCD-I criteria;
• Mini-Mental State Examination (MMSE) score greater than 24, adjusted for age and education level;
• Normal functioning on the Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) scales.

You may not qualify if:

• History of head trauma;
• Current neurological and/or systemic diseases;
• Symptoms of psychosis, major depression, or substance use disorder.

Sponsors & Collaborators

• IRCCS Policlinico S. Donato: lead
• Azienda Ospedaliero-Universitaria Careggi: collaborator

Study Sites (1)

IRCCS Policlinico San Donato

San Donato Milanese, Milan, 20097, Italy

RECRUITING

Related Publications (11)

• Bessi V, Balestrini J, Bagnoli S, Mazzeo S, Giacomucci G, Padiglioni S, Piaceri I, Carraro M, Ferrari C, Bracco L, Sorbi S, Nacmias B. Influence of ApoE Genotype and Clock T3111C Interaction with Cardiovascular Risk Factors on the Progression to Alzheimer's Disease in Subjective Cognitive Decline and Mild Cognitive Impairment Patients. J Pers Med. 2020 May 29;10(2):45. doi: 10.3390/jpm10020045.

  PMID: 32485802 BACKGROUND

• Bessi V, Giacomucci G, Mazzeo S, Bagnoli S, Padiglioni S, Balestrini J, Tomaiuolo G, Piaceri I, Carraro M, Bracco L, Sorbi S, Nacmias B. PER2 C111G polymorphism, cognitive reserve and cognition in subjective cognitive decline and mild cognitive impairment: a 10-year follow-up study. Eur J Neurol. 2021 Jan;28(1):56-65. doi: 10.1111/ene.14518. Epub 2020 Oct 18.

  PMID: 32896064 BACKGROUND

• Bessi V, Mazzeo S, Bagnoli S, Padiglioni S, Carraro M, Piaceri I, Bracco L, Sorbi S, Nacmias B. The implication of BDNF Val66Met polymorphism in progression from subjective cognitive decline to mild cognitive impairment and Alzheimer's disease: a 9-year follow-up study. Eur Arch Psychiatry Clin Neurosci. 2020 Jun;270(4):471-482. doi: 10.1007/s00406-019-01069-y. Epub 2019 Sep 27.

  PMID: 31560105 BACKGROUND

• Mazzeo S, Bessi V, Padiglioni S, Bagnoli S, Bracco L, Sorbi S, Nacmias B. KIBRA T allele influences memory performance and progression of cognitive decline: a 7-year follow-up study in subjective cognitive decline and mild cognitive impairment. Neurol Sci. 2019 Aug;40(8):1559-1566. doi: 10.1007/s10072-019-03866-8. Epub 2019 Apr 5.

  PMID: 30953258 BACKGROUND

• Mazzeo S, Ingannato A, Giacomucci G, Manganelli A, Moschini V, Balestrini J, Cavaliere A, Morinelli C, Galdo G, Emiliani F, Piazzesi D, Crucitti C, Frigerio D, Polito C, Berti V, Bagnoli S, Padiglioni S, Sorbi S, Nacmias B, Bessi V. Plasma neurofilament light chain predicts Alzheimer's disease in patients with subjective cognitive decline and mild cognitive impairment: A cross-sectional and longitudinal study. Eur J Neurol. 2024 Jan;31(1):e16089. doi: 10.1111/ene.16089. Epub 2023 Oct 5.

  PMID: 37797300 BACKGROUND

• Lassi M, Fabbiani C, Mazzeo S, Burali R, Vergani AA, Giacomucci G, Moschini V, Morinelli C, Emiliani F, Scarpino M, Bagnoli S, Ingannato A, Nacmias B, Padiglioni S, Micera S, Sorbi S, Grippo A, Bessi V, Mazzoni A. Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum? Neuroimage Clin. 2023;38:103407. doi: 10.1016/j.nicl.2023.103407. Epub 2023 Apr 19.

  PMID: 37094437 BACKGROUND

• Giacomucci G, Mazzeo S, Bagnoli S, Ingannato A, Leccese D, Berti V, Padiglioni S, Galdo G, Ferrari C, Sorbi S, Bessi V, Nacmias B. Plasma neurofilament light chain as a biomarker of Alzheimer's disease in Subjective Cognitive Decline and Mild Cognitive Impairment. J Neurol. 2022 Aug;269(8):4270-4280. doi: 10.1007/s00415-022-11055-5. Epub 2022 Mar 14.

  PMID: 35288777 BACKGROUND

• Mazzeo S, Emiliani F, Bagnoli S, Padiglioni S, Conti V, Ingannato A, Giacomucci G, Balestrini J, Ferrari C, Sorbi S, Nacmias B, Bessi V. Huntingtin gene intermediate alleles influence the progression from subjective cognitive decline to mild cognitive impairment: A 14-year follow-up study. Eur J Neurol. 2022 Jun;29(6):1600-1609. doi: 10.1111/ene.15291. Epub 2022 Feb 28.

  PMID: 35181957 BACKGROUND

• Mazzeo S, Padiglioni S, Bagnoli S, Carraro M, Piaceri I, Bracco L, Nacmias B, Sorbi S, Bessi V. Assessing the effectiveness of subjective cognitive decline plus criteria in predicting the progression to Alzheimer's disease: an 11-year follow-up study. Eur J Neurol. 2020 May;27(5):894-899. doi: 10.1111/ene.14167. Epub 2020 Mar 8.

  PMID: 32043740 BACKGROUND

• Bessi V, Mazzeo S, Padiglioni S, Piccini C, Nacmias B, Sorbi S, Bracco L. From Subjective Cognitive Decline to Alzheimer's Disease: The Predictive Role of Neuropsychological Assessment, Personality Traits, and Cognitive Reserve. A 7-Year Follow-Up Study. J Alzheimers Dis. 2018;63(4):1523-1535. doi: 10.3233/JAD-171180.

  PMID: 29782316 BACKGROUND

• Jessen F, Amariglio RE, van Boxtel M, Breteler M, Ceccaldi M, Chetelat G, Dubois B, Dufouil C, Ellis KA, van der Flier WM, Glodzik L, van Harten AC, de Leon MJ, McHugh P, Mielke MM, Molinuevo JL, Mosconi L, Osorio RS, Perrotin A, Petersen RC, Rabin LA, Rami L, Reisberg B, Rentz DM, Sachdev PS, de la Sayette V, Saykin AJ, Scheltens P, Shulman MB, Slavin MJ, Sperling RA, Stewart R, Uspenskaya O, Vellas B, Visser PJ, Wagner M; Subjective Cognitive Decline Initiative (SCD-I) Working Group. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease. Alzheimers Dement. 2014 Nov;10(6):844-52. doi: 10.1016/j.jalz.2014.01.001. Epub 2014 May 3.

  PMID: 24798886 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

CSF and blood

MeSH Terms

Conditions

Speech

Condition Hierarchy (Ancestors)

Verbal Behavior; Communication; Behavior

Study Officials

• Salvatore Mazzeo, MD, PhD

  Università Vita-Salute San Raffaele, Milano - Neurology Unit, IRCCS Policlinico San Donato, San Donato Milanese

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Mattia Ricotti

CONTACT

+390252774236; mattia.ricotti@grupposandonato.it

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor in Neurology and Consultant Neurologist

Study Record Dates

• First Submitted: September 11, 2025
• First Posted: February 11, 2026
• Study Start: October 1, 2025
• Primary Completion (Estimated): October 1, 2027
• Study Completion (Estimated): March 1, 2028
• Last Updated: February 11, 2026

Record last verified: 2026-02

Locations

IT (1)