Systems biology as an emerging paradigm in transfusion medicine

James T Yurkovich,Bernhard O Palsson,Ólafur E Sigurjónsson,Aarash Bordbar

doi:10.1186/s12918-018-0558-x

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.

Highlights

The human red blood cell (RBC) has long been a starting point for the application of systems biology
Other models of the RBC have focused on various aspects of its physiology, from metabolism [6] to its structural properties [7]
Initial global characterization of the data was achieved using principal component analysis (PCA) of the raw metabolomics data, revealing two distinct metabolic shifts that occur during the 42 day shelf-life of a stored RBC unit

Summary

Introduction

The human red blood cell (RBC) has long been a starting point for the application of systems biology. Multivariate statistical analysis reveals a three-phase metabolic decay The first major step in a systems biology characterization of the storage process was to understand the baseline RBC metabolic behavior during storage [39].

Results

Conclusion