Reconstruction and Computational Modelling for Inherited Metabolic Diseases
Accelerating the diagnosis and personalising the management
of inherited metabolic diseases.
Key features of Recon4IMD
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Overall objectives: Accelerate diagnosis and personalise management of inherited metabolic diseases.
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Primary output: Clinically validated decision support tools enabling accelerated diagnosis and personalised management of inherited metabolic diseases, based on genomic, proteomic, and metabolomic data-driven computational models.
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Sustainability: Development of academic technology to meet medical regulatory standards and a roadmap for exploitation within a European foundation to aid personalised diagnosis and management of inherited metabolic diseases.
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Implemented by: A group of world-class scientists and clinicians from a diversity of disciplines who have collaborated multiple times and have a track record of leading key national and EU-funded initiatives to deliver high-impact results.
Pathogenic variants in the GBA1 gene, which encodes the lysosomal enzyme 𝛽 -glucocerebrosidase, cause Gaucher disease (GD) and represent one of the strongest genetic risk factors for Parkinson’s disease (PD). However, not all carriers develop PD, suggesting the involvement of additional modifiers. Transcriptomic alterations shared between GD and PD may reveal such modifiers and provide insights into the mechanisms linking GBA1 to PD.
Latest Publications
GBA1 Gene-Associated Transcriptomic Signatures Reveal Risk Genes in Parkinson’s Disease
Pathogenic variants in the GBA1 gene, which encodes the lysosomal enzyme 𝛽-glucocerebrosidase, cause Gaucher disease (GD) and represent one of the strongest genetic risk factors for Parkinson’s disease (PD). However, not all carriers develop PD, suggesting the involvement of additional modifiers. Transcriptomic alterations shared between GD and PD may reveal such modifiers and provide insights into the mechanisms linking GBA1 to PD.
