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Reconstruction and Computational Modelling for Inherited Metabolic Diseases
| Funder | European Commission |
|---|---|
| Recipient Organization | University of Galway |
| Country | Ireland |
| Start Date | Jun 01, 2023 |
| End Date | May 31, 2027 |
| Duration | 1,460 days |
| Number of Grantees | 34 |
| Roles | Participant; Associated Partner; Coordinator |
| Data Source | European Commission |
| Grant ID | 101080997 |
Grant Description
Our overall objectives are to accelerate the diagnosis, and enable personalised management, of inherited metabolic diseases (IMDs).
Established academic technology for statistical genomic analysis, deep learning-based prediction of protein structure, and whole-body metabolic network modelling shall be applied to generate personalised computational models, given patient-derived genomic, transcriptomic, proteomic and metabolomic data.
To train diagnostic models, a comprehensive clinical team will recruit 1,945 diagnosed patients with a wide variety of IMDs, then validate the clinical utility of personalised computational models on a set of 685 undiagnosed patients.
An enhanced human metabolic network reconstruction, especially for lipid metabolism, reaction kinetics and inherited metabolic disease pathways, will increase the predictive capacity of cellular and whole-body metabolic network models.
As an exemplar for other IMDs, personalised computational modelling will be used to identify compensatory and aggravating mechanisms that associate with clinical severity in Gaucher disease.
The predictive capacity of personalised models will be validated by comparison with additional empirical investigations of protein structure and function as well as metabolomics, tracer-based metabolomics and proteomics of patient-derived in vitro disease models.
To maximise the potential for impact, personalised modelling software will be developed to be generally applicable to a broad variety of IMDs, and implemented in a way that is both accessible to clinicians and admissible to regulatory authorities.
Sustainability will be promoted by development of a roadmap for a European foundation to aid personalised diagnosis and management of IMDs, informed by broad stakeholder consultation.
This is a unique opportunity to realise the potential of personalised computational modelling for a broad set of rare diseases, which is a field where European collaboration is an essential for progress.
All Grantees
Medizinische Universitaet Wien; Region Hovedstaden; Vseobecna Fakultni Nemocnice V Praze; Belfast Health and Social Care Trust; Universiteit Leiden; University of Galway; Uniamo - Federazione Italiana Malattie Rare - Onlus Associazione; Academisch Ziekenhuis Groningen; Oslo Universitetssykehus Hf; University of Newcastle Upon Tyne; Medizinische Hochschule Hannover; Sib Swiss Institute of Bioinformatics; Children'S Health Ireland; Universitair Ziekenhuis Antwerpen; Universitair Medisch Centrum Utrecht; Asociacion Instituto de Investigacion Sanitaria Biobizkaia; Stichting Amsterdam Umc; Azienda Ospedaliera Universitaria Meyer Irccs; Västra Götalandsregionen; Universitatsklinikum Heidelberg; Dundalk Institute of Technology; Klinikum Der Technischen Universität München (Tum Klinikum); Universitaet Osnabrueck; Universitaetsmedizin Der Johannes Gutenberg-Universitaet Mainz; The Chancellor, Masters and Scholars of the University of Oxford; Erasmus Universitair Medisch Centrum Rotterdam; Eberhard Karls Universitaet Tuebingen; University College London; Universitaetsklinikum Freiburg; Mater Misericordiae University Hospital; Katholieke Universiteit Leuven; Fundacion Publica Galega Instituto de Investigacion Sanitaria de Santiago de Compostela; Ospedale Pediatrico Bambino Gesu; Azienda Sanitaria Universitaria Friuli Centrale
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