PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer’s Disease With machine learning: the PREVIEW study protocol

Abstract

Background and aims: Subjective Cognitive Decline (SCD) is a condition in which individuals complain of cognitive decline with normal performances on neuropsychological evaluation. Many studies demonstrated a higher prevalence of Alzheimer's pathology in patients diagnosed with SCD compared to the general population. Consequently, SCD was suggested as an early symptomatic phase of Alzheimer's disease (AD). We will describe the study protocol of a prospective cohort study (PREVIEW) that aim to identify features and tools to accurately detect SCD patients who will progress to AD. Methods: We will include patients self-referred to our memory clinic and diagnosed with SCD. Participants will undergo: clinical, neurologic and neuropsychological examination, estimation of cognitive reserve and depression, evaluation of personality traits, APOE and BDNF genotyping, electroencephalography and event-related potential recording, lumbar puncture for measurement of Aβ42, t-tau, and p-tau concentration and Aβ42/Aβ40 ratio. Recruited patients will have follow-up neuropsychological examinations every two years. Collected data will be used to train a machine learning algorithm to define the risk of progression from SCD to MCI and AD. Discussion: There is an urgent need to select cost-effective and easily accessible tools to identify patients at the earliest stages of the disease. Previous studies identified demographic, cognitive, genetic, neurophysiological and brain structure features to stratify SCD patients according to the risk of progression to objective cognitive decline. Nevertheless, only a few studies considered all these features together and applied machine learning approaches to SCD patients. Conclusions: the PREVIEW study aims to identify new cost-effective disease biomarkers (e.g., EEG-derived biomarkers) and define an automated algorithm to detect patients at risk for AD in a very early stage of the disease.

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer’s Disease continuum?

“…The “PRedicting the EVolution of SubjectIvE Cognitive Decline to Alzheimer’s Disease With machine learning (PREVIEW)” project ( Mazzeo et al, 2023 ) is an ongoing prospective cohort study started in October 2020 and including consecutive patients with SCD and MCI who self-referred to the Regional Reference Center for Alzheimer's Disease and Cognitive Disorders of Careggi Hospital, Florence. All patients underwent a comprehensive family and clinical history, neurological examination, extensive neuropsychological investigation, estimation of premorbid intelligence, and assessment of depression.…”