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Analysis of serum inflammatory mediators identifies unique dynamic networks associated with death and spontaneous survival in pediatric acute liver failure

Azhar, N and Ziraldo, C and Barclay, D and Rudnick, DA and Squires, RH and Vodovotz, Y (2013) Analysis of serum inflammatory mediators identifies unique dynamic networks associated with death and spontaneous survival in pediatric acute liver failure. PLoS ONE, 8 (11).

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Abstract

Background: Tools to predict death or spontaneous survival are necessary to inform liver transplantation (LTx) decisions in pediatric acute liver failure (PALF), but such tools are not available. Recent data suggest that immune/inflammatory dysregulation occurs in the setting of acute liver failure. We hypothesized that specific, dynamic, and measurable patterns of immune/inflammatory dysregulation will correlate with outcomes in PALF. Methods: We assayed 26 inflammatory mediators on stored serum samples obtained from a convenience sample of 49 children in the PALF study group (PALFSG) collected within 7 days after enrollment. Outcomes were assessed within 21 days of enrollment consisting of spontaneous survivors, non-survivors, and LTx recipients. Data were subjected to statistical analysis, patient-specific Principal Component Analysis (PCA), and Dynamic Bayesian Network (DBN) inference. Findings: Raw inflammatory mediator levels assessed over time did not distinguish among PALF outcomes. However, DBN analysis did reveal distinct interferon-gamma-related networks that distinguished spontaneous survivors from those who died. The network identified in LTx patients pre-transplant was more like that seen in spontaneous survivors than in those who died, a finding supported by PCA. Interpretation: The application of DBN analysis of inflammatory mediators in this small patient sample appears to differentiate survivors from non-survivors in PALF. Patterns associated with LTx pre-transplant were more like those seen in spontaneous survivors than in those who died. DBN-based analyses might lead to a better prediction of outcome in PALF, and could also have more general utility in other complex diseases with an inflammatory etiology. Copyright: © 2013 Azhar et al.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Azhar, N
Ziraldo, C
Barclay, Ddeb7@pitt.eduDEB7
Rudnick, DA
Squires, RHrhs8@pitt.eduRHS8
Vodovotz, Yvodovotz@pitt.eduVODOVOTZ
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorAndroulakis, Ioannis PUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Centers: Other Centers, Institutes, or Units > McGowan Institute for Regenerative Medicine
Date: 11 November 2013
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 8
Number: 11
DOI or Unique Handle: 10.1371/journal.pone.0078202
Schools and Programs: School of Medicine > Computational and Systems Biology
School of Medicine > Surgery
Refereed: Yes
Date Deposited: 30 Jan 2014 17:45
Last Modified: 04 Feb 2019 15:58
URI: http://d-scholarship.pitt.edu/id/eprint/20373

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