Krivov, SV, Fenton, H, Goldsmith, PJ et al. (3 more authors) (2014) Optimal reaction coordinate as a biomarker for the dynamics of recovery from kidney transplant. PLoS Computational Biology, 10 (6). e1003685. ISSN 1553-734X
Abstract
The evolution of disease or the progress of recovery of a patient is a complex process, which depends on many factors. A quantitative description of this process in real-time by a single, clinically measurable parameter (biomarker) would be helpful for early, informed and targeted treatment. Organ transplantation is an eminent case in which the evolution of the post-operative clinical condition is highly dependent on the individual case. The quality of management and monitoring of patients after kidney transplant often determines the long-term outcome of the graft. Using NMR spectra of blood samples, taken at different time points from just before to a week after surgery, we have shown that a biomarker can be found that quantitatively monitors the evolution of a clinical condition. We demonstrate that this is possible if the dynamics of the process is considered explicitly: the biomarker is defined and determined as an optimal reaction coordinate that provides a quantitatively accurate description of the stochastic recovery dynamics. The method, originally developed for the analysis of protein folding dynamics, is rigorous, robust and general, i.e., it can be applied in principle to analyze any type of biological dynamics. Such predictive biomarkers will promote improvement of long-term graft survival after renal transplantation, and have potentially unlimited applications as diagnostic tools.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 Krivov et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Keywords: | biomarkers; Disease dynamics; Free energy; NMR spectroscopy; Optimization; Reaction dynamics; Renal transplantation; Surgical and invasive medical procedures |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Molecular and Cellular Biology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Jul 2014 11:17 |
Last Modified: | 17 Aug 2015 13:36 |
Published Version: | http://dx.doi.org/10.1371/journal.pcbi.1003685 |
Status: | Published |
Publisher: | Public Library of Science |
Identification Number: | 10.1371/journal.pcbi.1003685 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:79641 |