A pilot study characterizing the blood transcriptome of neonates during sepsis using RNA-sequencing — ASN Events
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  3. A pilot study characterizing the blood transcriptome of neonates during sepsis using RNA-sequencing

A pilot study characterizing the blood transcriptome of neonates during sepsis using RNA-sequencing (#194)

Sherrianne Ng 1 , Tobias Strunk 2 , Erin E. Gill 3 4 , Reza Falsafi 3 4 , Amy H. Lee 3 4 , Robert E. W. Hancock 3 4 , Andrew Currie 1
  1. School of Veterinary and Life Sciences, Murdoch University, Perth, Western Australia, Australia
  2. Centre for Neonatal Research and Education, The University of Western Australia, Perth, Western Australia, Australia
  3. Centre for Microbial Diseases and Immunity Research, University of British Columbia, Vancouver, British Columbia, Canada
  4. Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada

Neonatal sepsis causes significant morbidity and mortality in newborns, especially preterm infants (<37 weeks gestation). The pathophysiology of neonatal sepsis is complex and the leukocyte transcriptional response to sepsis is poorly understood. Characterizing the neonatal blood transcriptome could provide novel insight into complex immune system networks involved in host responses during sepsis. We present the first pilot study characterizing the transcriptomic responses of preterm infants during neonatal sepsis using RNA-sequencing.

We performed RNA-sequencing on 53 peripheral blood samples taken during septic screens from neonates (23.7–40.4 weeks gestation) born at King Edward Memorial Hospital, Perth, Australia. Patients were classified based on blood culture positivity and elevated CRP concentrations as confirmed sepsis (n=6), possible sepsis (n=11) or no sepsis (n=36).

We identified differentially expressed (DE) genes, conducted enrichment pathway analysis and visualized protein-protein interaction (PPI) networks between groups. Multi-factor analysis was conducted on the top 500 DE genes to generate clusters described by qualitative meta-data (positive blood culture and/or serial CRP measurement) independent of assigned clinical classifications. A total of 2889 genes were DE between confirmed sepsis and no sepsis patients, generating 2045 nodes in the zero-order PPI network with top enriched pathways associated with the innate and adaptive immune system; hemostasis; and cytokine signaling, where interferon-α/β signaling was the top gene-pair signature pathway. The transcriptomes of possible sepsis patients appeared more similar to no sepsis (64 DE genes) than confirmed sepsis (1596 DE genes) patients, suggesting a high rate of false positive sepsis calls. Separately, hierarchical clustering of genes based on qualitative factors showed two distinct clusters for confirmed sepsis and no sepsis, but not possible sepsis.

Our findings show that septic patients had significantly altered immune-related transcriptional signatures that may be useful in improving the diagnosis of neonatal sepsis.

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