Utilizing biomarkers to forecast quantitative metabolite concentration profiles in human red blood cells

James T. Yurkovich, Laurence Yang, Bernhard O. Palsson*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

One of the major limitations in making experimental measurements of biological systems is the complexity of the network being investigated. Major efforts have been made to identify a subset of measurements ('biomarkers') that can be used to provide information about the rest of the system. For red blood cells under cold storage conditions in a blood bank, a set of metabolite biomarkers have been identified that can reliably define the qualitative trend of cellular metabolism. Recently, it was shown that these biomarkers could also be used to train a model that quantitatively predicts the concentrations of other metabolites in the network over a 45 day time course. Here, we extend the utility of these methods by using a linear blackbox model to forecast future values of these concentrations. We show that 57 of the 70 metabolites measured in the red blood cell metabolic network (81%) can be accurately forecasted after 8 days of storage (5 time points) with a global median error of 18.36%. The ability to forecast metabolite profiles by only requiring a subset of measurements for the first few days of storage makes these methods immediately applicable in a clinical setting to assess the metabolic health of stored blood.

Original languageEnglish
Title of host publication1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages961-966
Number of pages6
ISBN (Electronic)9781509021826
DOIs
Publication statusPublished - 6 Oct 2017
Event1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 - Kohala Coast, United States
Duration: 27 Aug 201730 Aug 2017

Publication series

Name1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
Volume2017-January

Conference

Conference1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
Country/TerritoryUnited States
CityKohala Coast
Period27/08/1730/08/17

Bibliographical note

Funding Information:
This research was supported by the US Department of Energy (award DE-SC0008701), and the National Institute of General Medical Sciences of the National Institutes of Health (awards U01-GM102098 and R01-GM057089).

Publisher Copyright:
© 2017 IEEE.

Other keywords

  • Biosystems
  • Biotechnology
  • Modeling

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