Enabling personalised diagnosis, treatment, and stratification through whole-body metabolic modelling of an individual’s genome, metabolome, and metagenome.
AVATAR aims to develop a mechanistic computational modeling framework to link genetic variants, metabolism, and environmental factors for personalized medicine in diagnosing and treating metabolic diseases.
Projectdetails
Introduction
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
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.
Extrinsic Factors
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.
Project Overview
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.
Algorithm Development
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.
- The metabolic pathway-based stratification of individuals with cognitive impairment.
Impact on Precision Medicine
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.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.999.991 |
Totale projectbegroting | € 1.999.991 |
Tijdlijn
Startdatum | 1-4-2024 |
Einddatum | 31-3-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- UNIVERSITY OF GALWAYpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Resolving metabolic interactions between the gut microbiota and the host with multi-omics-based modellingThis project aims to systematically characterize gut bacteria interactions and their metabolic contributions to host health using experimental and computational methods, enabling targeted microbiota interventions. | ERC Starting... | € 1.499.323 | 2024 | Details |
Metabolomics-driven Molecular Source Analysis for personalized medicine in childrenMeMoSA aims to enhance personalized medicine for children by identifying gastrointestinal metabolite sources through advanced metabolomics and machine learning, improving disease prevention and treatment efficacy. | ERC Consolid... | € 1.999.763 | 2024 | Details |
Gut microbiota drug biotransformation as a tool to unravel the mechanisms of metabolic microbiota-host interactionsThis project aims to systematically study metabolic interactions between gut microbiota and hosts using drug biotransformation to improve understanding of microbiome-related health variations and drug responses. | ERC Starting... | € 1.894.858 | 2023 | Details |
Integrated Mechanistic Modelling and Analysis of Large-scale Biomedical DataINTEGRATE aims to enhance cancer treatment by developing advanced computational models that integrate patient-derived data for improved drug targeting and clinical trial planning. | ERC Consolid... | € 1.854.546 | 2024 | Details |
Proteome-wide Functional Interrogation and Modulation of Gut Microbiome SpeciesThis project aims to identify and manipulate gut microbiome protein functions using high-throughput proteomics to develop targeted therapies for restoring microbial health. | ERC Starting... | € 1.499.980 | 2023 | Details |
Resolving metabolic interactions between the gut microbiota and the host with multi-omics-based modelling
This project aims to systematically characterize gut bacteria interactions and their metabolic contributions to host health using experimental and computational methods, enabling targeted microbiota interventions.
Metabolomics-driven Molecular Source Analysis for personalized medicine in children
MeMoSA aims to enhance personalized medicine for children by identifying gastrointestinal metabolite sources through advanced metabolomics and machine learning, improving disease prevention and treatment efficacy.
Gut microbiota drug biotransformation as a tool to unravel the mechanisms of metabolic microbiota-host interactions
This project aims to systematically study metabolic interactions between gut microbiota and hosts using drug biotransformation to improve understanding of microbiome-related health variations and drug responses.
Integrated Mechanistic Modelling and Analysis of Large-scale Biomedical Data
INTEGRATE aims to enhance cancer treatment by developing advanced computational models that integrate patient-derived data for improved drug targeting and clinical trial planning.
Proteome-wide Functional Interrogation and Modulation of Gut Microbiome Species
This project aims to identify and manipulate gut microbiome protein functions using high-throughput proteomics to develop targeted therapies for restoring microbial health.
Vergelijkbare projecten uit andere regelingen
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
A Multi-Omics Approach for Novel Drug Targets, Biomarkers and Risk Algorithms for Myocardial InfarctionTargetMI aims to rapidly discover novel drug targets and biomarkers for myocardial infarction using a high-throughput multi-omic approach on 1000 samples, enhancing clinical risk prediction and translation. | EIC Pathfinder | € 3.999.840 | 2023 | Details |
A Multi-Omics Approach for Novel Drug Targets, Biomarkers and Risk Algorithms for Myocardial Infarction
TargetMI aims to rapidly discover novel drug targets and biomarkers for myocardial infarction using a high-throughput multi-omic approach on 1000 samples, enhancing clinical risk prediction and translation.