Project description
Early diagnosis of frontotemporal dementia
Frontotemporal dementia (FTD) is a condition that affects both patients and their caregivers, leading to high emotional and financial burden. About 15-30 % of FTD cases are inherited, caused by known genetic mutations, while the majority – 70-85 % – are sporadic. Diagnosing sporadic FTD is difficult, often taking years and leading to misdiagnoses due to its varied symptoms. This delay in diagnosis hinders early treatment and care. The EU-funded PREDICTFTD project aims to change this by developing a diagnostic tool for early detection of both familial and sporadic FTD. By using patient data from multiple cohorts and advanced AI technology, the project will validate biomarkers that can diagnose FTD quickly, helping patients receive treatment sooner.
Objective
Frontotemporal dementia (FTD) has a debilitating effect on patients and their caregivers and leads to substantial economic costs. 15-30% of patients have familial FTD caused by known pathogenetic mutations. For the other 70-85% of patients, termed sporadic FTD, diagnosis is slow (~3.6 years) with frequent misdiagnosis due to clinical, genetic and molecular heterogeneity. Thus, there is great need for biomarkers for early diagnosis of sporadic FTD and its pathological subtypes.
In PREDICTFTD, we will validate a set of biomarkers and create a diagnostic tool for early diagnosis of familial and sporadic FTD, which will facilitate tailored support and symptomatic treatments and care. We will apply several new approaches to achieve this: 1) we combine 11 geographically diverse cohorts of sporadic and familial FTD with retrospective and prospective longitudinal liquid biopsy samples and extensive clinical and behavioural data; 2) we are the first to use multimodal clinical and liquid biomarker data to train an AI-algorithm as a diagnostic tool for quick and early clinical FTD diagnosis; and 3) we implement a novel robust two-stage strategy for biomarker and AI algorithm validation, where phase I validates biomarkers and algorithms on a cohort of genetic and autopsied cases and phase II assesses biomarker value for diagnosis of sporadic FTD and at-risk pre-symptomatic mutation carriers. We will apply this two-stage validation strategy to address three critical clinical challenges: i) To distinguish sporadic FTD from (non-) neurodegenerative disorders that show significant clinical/symptomatic overlap, ii) To robustly detect FTD pathological subtypes in sporadic FTD and iii) pre-symptomatic identification of FTD onset. Thus, PREDICTFTD will transform FTD diagnosis, offering potential for early disease confirmation, guiding treatment decisions, facilitating patient recruitment for clinical trials, guidance of patients and caregivers, and enabling preventive measures.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- medical and health sciencesbasic medicineneurologydementia
- natural sciencesbiological sciencesgeneticsmutation
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Programme(s)
Call for proposal
(opens in new window) HORIZON-HLTH-2024-DISEASE-03-two-stage
See other projects for this callFunding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
3015 GD Rotterdam
Netherlands