Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

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., 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 10.1038/ncomms5649

Full text not available from this repository.

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
Date Type: Published Online
Status: Published
Schools: Medicine
Subjects: R Medicine > R Medicine (General)
Publisher: Nature Publishing Group
ISSN: 2041-1723
Date of Acceptance: 9 July 2014
Last Modified: 29 Mar 2018 08:08
URI: http://orca.cf.ac.uk/id/eprint/110316

Citation Data

Cited 36 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item