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Enabling personalised diagnosis, treatment, and stratification through whole-body metabolic modelling of an individual’s genome, metabolome, and metagenome.

Project description

Innovative whole-body metabolism models for personalised medicine

Whole-genome sequences are increasingly available, facilitating the transition to personalised medicine. However, understanding which genetic variants influence a person’s characteristics is essential. Genome-wide association studies have linked genetic variants to numerous traits, but these methods do not consider the biochemical network connecting these variants to the metabolic phenotype. External factors such as diet and the microbiome also play a role in modulating the metabolic phenotype. The ERC-funded AVATAR project aims to develop a new computational modelling framework to enhance whole-body metabolism models. It will create in silico models that explain genetic variants, genes, proteins, biochemical reactions, and underlying physiological processes affecting microbial and nutrient metabolism. AVATAR will provide a personalised modelling analysis framework for computer-guided diagnosis and treatment strategies.

Objective

The increasing availability of whole-genome sequences will ultimately transform medicine into personalised medicine. To realise this potential, we need to understand which of the millions of genetic variants in a person’s genome can alter a phenotype. Genome-wide association studies (GWAS) have associated many genetic variants with thousands of phenotypic traits. Metabolomics has further informed GWAS. However, these methods do generally not consider the biochemical network connecting genetic variants with the metabolic phenotype. Additionally, extrinsic factors, such as diet and the microbiome, also modulate the metabolic phenotype. A computational systems approach is required to untangle this complex interplay. In AVATAR, I shall develop and apply a novel mechanistic computational modelling framework that will significantly expand cutting-edge computational models of whole-body metabolism. The novel in silico models will mechanistically describe the network of genetic variants, genes, proteins, and biochemical reactions, as well as underlying physiological processes that are influenced by microbial and nutrient metabolism. I shall devise a novel algorithm to predict phenotypically relevant genetic variants based on a person’s genome and metabolome. The validated algorithm and the modelling framework shall then be used for two distinct biomedical proof-of-concept studies: the diagnosis and diet-based treatment of inherited metabolic diseases and the metabolic pathway-based stratification of individuals with cognitive impairment. AVATAR will enable novel insights into the genotype-phenotype-environment relationship by enabling systematic mechanism-based analyses of genetic variants, diet, and the microbiome. This ground-breaking, innovative, multidisciplinary project will influence precision medicine by providing a personalisable modelling analysis framework that may ultimately provide a foundation for computer-guided diagnosis and treatment strategies.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

(opens in new window) ERC-2023-COG

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Host institution

UNIVERSITY OF GALWAY
Net EU contribution
€ 1 999 991,00
Address
UNIVERSITY ROAD
H91 Galway
Ireland
Region
Ireland Northern and Western West
Activity type
Higher or Secondary Education Establishments
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Total cost
€ 1 999 991,00

Beneficiaries (1)