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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 |
| 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: | |
| Depositing User: | Pure Connector |
| Date Deposited: | 24 Sep 2016 00:39 |
| Last Modified: | 19 Oct 2023 01:46 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/60164 |
| DOI: | 10.1038/ncomms5649 |
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