IR4FTD · Discovery of new Frontal Temporal Dementia multimodal spectral markers in biofluids.
Horizon Europe — Marie Skłodowska-Curie Actions
- Duration
- 2023-10-01 → 2026-09-30
- EU contribution
- €287,152
- Participants
- 3
- Scheme
- HORIZON-TMA-MSCA-PF-GF
Lines connect the coordinator with its partners.
Results in brief
Discovery of new Frontal Temporal Dementia multimodal spectral markers in biofluids.
Frontotemporal Dementia (FTD), the second most prevalent dementia in individuals under 60, is a rare and challenging disease to diagnose. Unlike other conditions, FTD lacks a single definitive diagnostic test, often requiring a combination of costly or invasive examinations. Its symptoms can also overlap with those of Alzheimer's Disease, further complicating diagnosis. The search for reliable biomarkers is a significant challenge in FTD research. This project proposes a holistic approach, using vibrational spectroscopy to acquire the complete chemical fingerprint in a label-free manner, rather than focusing on individual biomarkers. The central aim is to identify distinct spectroscopic fingerprints for FTD and Alzheimer’s disease (AD) in saliva and plasma samples using multimodal spectroscopy and machine learning. Samples from FTD, AD, and healthy individuals over 45 years of age will be analyzed using Raman, mid-infrared, and near-infrared spectroscopy. The successful outcome of this research could lead to the development of a novel screening tool capable of detecting chemical fingerprints indicative of FTD, AD, and potentially other diseases, significantly improving early detection and diagnosis.
Data: CORDIS, © European Union
Project objective
The central aim of the project is to apply multimodal spectroscopy combined with machine learning to identify a fingerprint for Frontal Temporal Dementia (FTD) and Alzheimer’s disease (AD) in saliva and plasma. FTD is the second most common dementia and usually affects individuals younger than 60 years old. FTD is difficult to diagnose, since there is no single exam that determines the disease, but instead many costly or painful exams that together link the disease. Some of the symptoms of the disease may be confounding with others such as AD. While the usual search for biomarkers focuses on individual patterns, the present proposal is to use a holistic approach. Vibrational spectroscopy provides a snapshot of the entire chemical finger print in a label-free way. In this project, samples from FTD, AD, and healthy subjects of >45 years old, will be analysed using Raman, mid and near infrared spectroscopy @Monash University in Australia, and complemented with Mass Spectrometry on the same samples @ICGEB in Italy. Advanced machine learning tools provide a powerful approach for data analysis unravelling hidden trends, correlations and also identify the main contributions that characterize the type of sample. The spectra recorded using the extended wavelength range encompassing the mid-infrared and near-infrared spectral regions will be processed with state-of-the-art machine learning tools to identify the molecular phenotype and establish markers in patients with TDP and AD. These findings will pave the way to the development of a new screening tool that would decrease the costs associated with the current diagnosis of FTD and in general for neurodegenerative disorders.
Original text from CORDIS.
Participants
Links
- View on CORDIS
- DOI: 10.3030/101106307
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e50bb37512&appId=PPGMS
Data: CORDIS, © European Union