Identification of a human neonatal immune-metabolic network associated with bacterial infection

Smith, Claire L., Dickinson, Paul, Forster, Thorsten, Craigon, Marie, Ross, Alan, Khondoker, Mizanur R. ORCID: https://orcid.org/0000-0002-1801-1635, France, Rebecca, Ivens, Alasdair, Lynn, David J., Orme, Judith, Jackson, Allan, Lacaze, Paul, Flanagan, Katie L., Stenson, Benjamin J. and Ghazal, Peter (2014) Identification of a human neonatal immune-metabolic network associated with bacterial infection. Nature Communications, 5. ISSN 2041-1723

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Abstract

Understanding how human neonates respond to infection remains incomplete. Here, a system-level investigation of neonatal systemic responses to infection shows a surprisingly strong but unbalanced homeostatic immune response; developing an elevated set-point of myeloid regulatory signalling and sugar-lipid metabolism with concomitant inhibition of lymphoid responses. Innate immune-negative feedback opposes innate immune activation while suppression of T-cell co-stimulation is coincident with selective upregulation of CD85 co-inhibitory pathways. By deriving modules of co-expressed RNAs, we identify a limited set of networks associated with bacterial infection that exhibit high levels of inter-patient variability. Whereas, by integrating immune and metabolic pathways, we infer a patient-invariant 52-gene-classifier that predicts bacterial infection with high accuracy using a new independent patient population. This is further shown to have predictive value in identifying infection in suspected cases with blood culture-negative tests. Our results lay the foundation for future translation of host pathways in advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis.

Item Type: Article
Additional Information: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: bacterial infection,biochemical networks,innate immunity,neonatal sepsis
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Faculty of Social Sciences > School of Education and Lifelong Learning
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Depositing User: Pure Connector
Date Deposited: 24 Sep 2016 00:39
Last Modified: 21 Oct 2022 06:32
URI: https://ueaeprints.uea.ac.uk/id/eprint/60164
DOI: 10.1038/ncomms5649

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