A dynamic multi-tissue model to study human metabolism
| Autor: | Thomas Pfau, Thomas Sauter, Maria Irene Pires Pacheco, Patricia Martins Conde |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Dynamic networks
QH301-705.5 Metabolite Genome scale Human metabolism Computational biology Multidisciplinary general & others [F99] [Life sciences] Biology Models Biological Article General Biochemistry Genetics and Molecular Biology Omics data 03 medical and health sciences chemistry.chemical_compound Multidisciplinaire généralités & autres [F99] [Sciences du vivant] 0302 clinical medicine Drug Discovery Humans Metabolomics Metabolic modeling Computer Simulation Biology (General) 030304 developmental biology 0303 health sciences Biochemical networks Systems Biology Applied Mathematics Tissue Model Computational Biology Computer Science Applications chemistry Organ Specificity Modeling and Simulation Multicellular systems Computer modelling Biomarkers 030217 neurology & neurosurgery |
| Zdroj: | npj Systems Biology and Applications, Vol 7, Iss 1, Pp 1-16 (2021) NPJ Systems Biology and Applications |
| Popis: | Metabolic modeling enables the study of human metabolism in healthy and in diseased conditions, e.g., the prediction of new drug targets and biomarkers for metabolic diseases. To accurately describe blood and urine metabolite dynamics, the integration of multiple metabolically active tissues is necessary. We developed a dynamic multi-tissue model, which recapitulates key properties of human metabolism at the molecular and physiological level based on the integration of transcriptomics data. It enables the simulation of the dynamics of intra-cellular and extra-cellular metabolites at the genome scale. The predictive capacity of the model is shown through the accurate simulation of different healthy conditions (i.e., during fasting, while consuming meals or during exercise), and the prediction of biomarkers for a set of Inborn Errors of Metabolism with a precision of 83%. This novel approach is useful to prioritize new biomarkers for many metabolic diseases, as well as for the integration of various types of personal omics data, towards the personalized analysis of blood and urine metabolites. |
| Databáze: | OpenAIRE |
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