ArticlePLoS computational biology2017
Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Modeling Red Blood Cell Metabolism in the Omics Era.Metabolites · 2023Review
- Red Blood Cell Metabolism In Vivo and In Vitro.Metabolites · 2023Review
- Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics.Frontiers in oncology · 2021Review
- Systems biology as an emerging paradigm in transfusion medicine.BMC systems biology · 2018Review
- Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks.The Journal of biological chemistry · 2017Article
- Article
- Metabolism of Citrate and Other Carboxylic Acids in Erythrocytes As a Function of Oxygen Saturation and Refrigerated Storage.Frontiers in medicine · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Deep-coverage metabolomic profiling has revealed a well-defined development of metabolic decay in human red blood cells (RBCs) under cold storage conditions. A set of extracellular biomarkers has been recently identified that reliably defines the qualitative state of the metabolic network throughout this metabolic decay process. Here, we extend the utility of these biomarkers by using them to quantitatively predict the concentrations of other metabolites in the red blood cell. We are able to accurately predict the concentration profile of 84 of the 91 (92%) measured metabolites (p < 0.05) in RBC metabolism using only measurements of these five biomarkers. The median of prediction errors (symmetric mean absolute percent error) across all metabolites was 13%. The ability to predict numerous metabolite concentrations from a simple set of biomarkers offers the potential for the development of a powerful workflow that could be used to evaluate the metabolic state of a biological system using a minimal set of measurements.
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Registered trials
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