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BMC Syst Biol. 2018 Mar 7;12(1):31. doi: 10.1186/s12918-018-0558-x.

Systems biology as an emerging paradigm in transfusion medicine.

Author information

1
Department Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, 92093, USA.
2
Bioinformatics and Systems Biology Program, University of California, San Diego, 9500 Gilman Drive, La Jolla, 92093, USA.
3
Sinopia Biosciences, 600 W Broadway Suite 700, San Diego, 92101, USA.
4
School of Science and Engineering, Reykjavík University, Hringbraut 101, Reykjavík, 101, Iceland.
5
The Blood Bank, Landspítali-University Hospital, 9500 Gilman Drive, Reykjavík, 101, Iceland.
6
Department Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, 92093, USA. palsson@ucsd.edu.
7
Bioinformatics and Systems Biology Program, University of California, San Diego, 9500 Gilman Drive, La Jolla, 92093, USA. palsson@ucsd.edu.
8
Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, 92093, USA. palsson@ucsd.edu.

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.

KEYWORDS:

Metabolism; Red blood cell; Storage lesion; Systems biology; Transfusion medicine

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