Identification of a human neonatal immune-metabolic network associated with bacterial infection.
Nat Commun, 2014/8/14;5:4649.
Smith CL[1], Dickinson P[2], Forster T[3], Craigon M[4], Ross A[4], Khondoker MR[5], France R[4], Ivens A[6], Lynn DJ[7], Orme J[8], Jackson A[8], Lacaze P[4], Flanagan KL[9], Stenson BJ[8], Ghazal P[3]
Affiliations
PMID: 25120092DOI: 10.1038/ncomms5649
Impact factor: 17.694
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.
MeSH terms
Antigens, CD; Bacterial Infections; Glucose; Homeostasis; Humans; Immunity, Innate; Infant, Newborn; Leukocyte Immunoglobulin-like Receptor B1; Lipid Metabolism; Metabolic Networks and Pathways; Receptors, Immunologic; T-Lymphocytes
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