Objective
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.
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Programme(s)
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
H91 Galway
Ireland
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Participants (28)
33100 Udine
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72074 Tuebingen
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49074 Osnabrueck
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9713 GZ Groningen
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2311 EZ Leiden
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A91 Dundalk
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69120 Heidelberg
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00162 Roma
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81675 Muenchen
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D08 HP97 Dublin
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30625 Hannover
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00165 Roma
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1105AZ Amsterdam
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1090 Wien
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7 Dublin
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2650 Edegem
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50139 Firenze
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55131 Mainz
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48903 Barakaldo Bizkaia
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15706 Santiago De Compostela
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462 80 Vanersborg
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3584 CX Utrecht
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3400 Hillerod
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0450 Oslo
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12808 Praha 2
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79106 Freiburg
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3000 Leuven
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3015 GD Rotterdam
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Partners (5)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
1206 Geneve
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
NE1 7RU Newcastle Upon Tyne
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
OX1 2JD Oxford
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
WC1E 6BT London
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
BT9 7AS Belfast
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