Published in
Nature Research, Nature Communications, 1(5), 2014
DOI: 10.1038/ncomms5649
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- [www.researchgate.net] | PDF
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Identification of a human neonatal immune-metabolic network associated with bacterial infection
,
Marie Craigon,
Alan Ross,
Mizanur R. Khondoker,
Rebecca France,
Alasdair Ivens ,
David J. Lynn,
Judith Orme,
Allan Jackson,
Paul Lacaze,
Katie L. Flanagan,
Ben Stenson,
Peter Ghazal
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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.