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

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Smith, Claire L., Dickinson, Paul, Forster, Thorsten, Craigon, Marie, Ross, Alan, Khondoker, Mizanur R., 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
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Groups > Epidemiology and Public Health Faculty of Medicine and Health Sciences > Research Groups > Public Health and Health Services Research (former - to 2023) Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Centres > Population Health
Related URLs:	http://www.nature.com/articles/ncomms564...
Depositing User:	Pure Connector
Date Deposited:	24 Sep 2016 00:39
Last Modified:	06 Feb 2025 06:38
URI:	https://ueaeprints.uea.ac.uk/id/eprint/60164
DOI:	10.1038/ncomms5649

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