Systems Biology As an Emerging Paradigm in Transfusion Medicine

Overview

Journal BMC Syst Biol

Publisher Biomed Central

Specialty Biology

Date 2018 Mar 9

PMID 29514691

Citations 9

Authors

James T Yurkovich

Aarash Bordbar

Olafur E Sigurjonsson

Bernhard O Palsson

Affiliations

Soon will be listed here.

Abstract

Blood transfusions are an important part of modern medicine, delivering approximately 85 million blood units to patients annually. Recently, the field of transfusion medicine has started to benefit from the "omic" data revolution and corresponding systems biology analytics. The red blood cell is the simplest human cell, making it an accessible starting point for the application of systems biology approaches.In this review, we discuss how the use of systems biology has led to significant contributions in transfusion medicine, including the identification of three distinct metabolic states that define the baseline decay process of red blood cells during storage. We then describe how a series of perturbations to the standard storage conditions characterized the underlying metabolic phenotypes. Finally, we show how the analysis of high-dimensional data led to the identification of predictive biomarkers.The transfusion medicine community is in the early stages of a paradigm shift, moving away from the measurement of a handful of chosen variables to embracing systems biology and a cell-scale point of view.

Citing Articles

Modeling Red Blood Cell Metabolism in the Omics Era.

Key A, Haiman Z, Palsson B, DAlessandro A Metabolites. 2023; 13(11).

PMID: 37999241 PMC: 10673375. DOI: 10.3390/metabo13111145.

Red Blood Cell Omics and Machine Learning in Transfusion Medicine: Singularity Is Near.

DAlessandro A Transfus Med Hemother. 2023; 50(3):174-183.

PMID: 37434999 PMC: 10331163. DOI: 10.1159/000529744.

Benford's law and metabolomics: A tale of numbers and blood.

DAlessandro A Transfus Apher Sci. 2020; 59(6):103019.

PMID: 33246837 PMC: 7736494. DOI: 10.1016/j.transci.2020.103019.

Transfusion medicine: Overtime paradigm changes and emerging paradoxes.

Garraud O, Vuk T, Lozano M, Tissot J Transfus Clin Biol. 2020; 27(4):262-267.

PMID: 33035654 PMC: 7537623. DOI: 10.1016/j.tracli.2020.10.001.

Visualizing metabolic network dynamics through time-series metabolomic data.

Buchweitz L, Yurkovich J, Blessing C, Kohler V, Schwarzkopf F, King Z BMC Bioinformatics. 2020; 21(1):130.

PMID: 32245365 PMC: 7119163. DOI: 10.1186/s12859-020-3415-z.

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