Project: An integrated approach to predict disease activity in the early phases of Multiple Sclerosis
Acronym | FindingMS (Reference Number: ERAPERMED2018-233) |
Duration | 01/03/2019 - 28/02/2022 |
Project Topic | Multiple Sclerosis (MS) is an autoimmune disorder of the central nervous system characterized by inflammation, demyelination and axonal degeneration. It is a disabling disorder affecting more than 2 million people worldwide with a high socio-economic impact. Given its marked heterogeneity, including clinical manifestations and individual treatment response, MS is a typical condition where a more personalized intervention would be highly beneficial. Our hypothesis is that a comprehensive characterization of a large set of patients, integrating multi-layer data (clinical, molecular, environmental), could contribute to accelerate personalized medicine in MS through the identification of biomarkers of inflammatory activity and the development of network-based and artificial intelligence approaches able to predict disease activity and to support treatment choice in the early phases of the disease. Taking advantage of an already available well-characterized cohort of MS patients (>4,500), we will assess genetic and environmental factors associated with disease activity. A subset of 300 patients will be extensively studied at the molecular level by performing a comprehensive “omics” profiling covering transcriptome, miRNome and methylome, together with vitamin D measurements. Omics data will be integrated using genome-scale biological networks to yield modules of altered genes and unravel the molecular mechanisms underlying disease activity. We will then design a predictive algorithm of disease activity based on Deep Learning models suitable for personalized medicine applications in clinical practice. The findings from the present project, besides clarifying the master-regulators of MS heterogeneity, should contribute to guide a more tailored use of currently available drugs. This more personalized MS management will allow to improve quality of life and to slow disability progression, in turn reducing health system costs. |
Network | ERA PerMed |
Call | 1st Joint Transnational Call for Proposals (2018) |
Project partner
Number | Name | Role | Country |
---|---|---|---|
1 | IRCCS Ospedale San Raffaele | Coordinator | Italy |
2 | Centre Hospitalier Universitaire de Toulouse | Partner | France |
3 | National Research Council - Institute of Biomedical Technologies | Partner | Italy |
4 | geneXplain GmbH | Partner | Germany |