Screening for Alzheimer's disease in the community using an AI-driven screening platform: design of the PREDICTOM study.
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Brem Anna-Katharine, Khan Zunera, Radermacher Jonas, Georgiadis Kostas, Lazarou Ioulietta, Grammatikopoulou Margarita, Pickering Ellie, Mitterreiter Johanna, Aakre Jon Arild, Ashton Nicholas J, Baquero Miguel, Beser-Robles Maria, Braboszcz Claire, Brandt Sigurd, Brown James, Cacciamani Federica, Campill Sarah, Collins Christopher, Deshpande Pushkar, Diaz Ana, Durrleman Stanley, Engelborghs Sebastiaan, Ferré-González Laura, Frisoni Giovani B, Gjestsen Martha Therese, Gove Dianne, Honigberg Lee, Huang Bin, Hudak Anett, Kaushik Sandeep, Letoha Tamas, Marquardt Gaby, Mendes Augusto J, Müllenborn Matthias, Paletta Lucas, de Barros Nuno Pedrosa, Pszeida Martin, Vik-Mo Audun Osland, Rostamipour Hossein, Perneczky Robert, Rauchmann Boris-Stephan, Russegger Silvia, Schirmer Timo, Shadmaan Amied, Solana Ana Beatriz, Soria-Frisch Aureli, Tegethoff Paulina, Ribbens Annemie, De Witte Sara, van der Giezen Mark, Nikolopoulos Spiros, Corbett Anne, Fröhlich Holger, Aarsland Dag, PREDICTOM Consortium
Аннотация
OBJECTIVES: The aim of PREDICTOM is to develop and test the accuracy of an artificial intelligence (AI) driven screening platform for the risk assessment and early detection of AD to extend the clinical pathway to home-based screening using established and novel biomarkers.
DESIGN/SETTING: PREDICTOM is a European (Norway, UK, Belgium, France, Switzerland, Germany, Spain) observational, prospective cohort study using a cloud-based platform that stores a digitalised journey for each participant and provides a collection of artificial-intelligence (AI) algorithms and tools for risk assessment and early diagnosis and prognosis.
PARTICIPANTS: Cohort 1 consists of 4000 adults aged 50 years or older at risk of developing AD. Cohort 2 consists of 615 participants selected from Cohort 1 based on estimates indicating high (N = 415) or low (N = 200) risk of AD. Data from existing cohorts will guide the analytic strategy of the study.
MEASUREMENTS: Cohort 1 will undergo home-based assessments (Level 1), Cohort 2 will undergo in-clinic assessments (Levels 2 and 3). Level 1 includes at-home screening, collecting digital and physiological data (questionnaires, cognition, hearing, eye-tracking) and biofluids (capillary blood via finger-stick and saliva) for biomarker analysis. Level 2 comprises a more complex biomarker collection, most of which can be completed in primary care, including EEG, MRI, venous blood, microbiome from stool, cognition, hearing, and eye-tracking. Level 3 includes a diagnostic evaluation to confirm or rule out AD pathology using established biomarkers (cerebrospinal fluid, or amyloid PET).
CONCLUSIONS: PREDICTOM will develop AI-driven algorithms for the early detection of AD using biomarkers that can be collected at home or in the community care setting, and evaluate their integration into a well-defined and comprehensive clinical pathway.