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Reconstruction and Computational Modelling for Inherited Metabolic Diseases

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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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-HLTH-2022-TOOL-12-two-stage

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Coordinator

UNIVERSITY OF GALWAY
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 500 993,75
Address
UNIVERSITY ROAD
H91 Galway
Ireland

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Region
Ireland Northern and Western West
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 500 993,75

Participants (28)

Partners (5)

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