Background: Neonatal sepsis is a complex infection-induced systemic inflammatory response syndrome and it is a main cause of mortality and neurologic sequelae in newborns. An early and accurate detection of sepsis is mandatory in neonates, since the clinical course of the infectious process can be fulminant, leading to septic shock and death within hours after the first clinical symptoms. The gold standard for diagnosis of neonatal sepsis is blood culture, but it is time-consuming and false negative results are not rare. To date, there is still no reliable biochemical marker of neonatal sepsis. Aim of the study: To compare the metabolic profile of urine collected within 72 hours of birth between preterm neonates affected by early onset sepsis (EOS) and healthy preterm infants, searching for a specific metabolite or metabolic profile enabling the early identification of preterm newborns prone to develop EOS. Materials and Methods: Each preterm neonate admitted to the Neonatal Intensive Care Unit was eligible for recruitment. Infants who developed a septic episode within 72 hours of birth were enrolled as cases. Infants who did not developed a septic episode were enrolled as controls. For each subject, a urine sample was collected within 72 hours of birth. The urine samples underwent untargeted metabolomic analysis using mass spectrometry combined with ultra-performance liquid chromatography. The data obtained were analyzed using multivariate and univariate statistical data analysis tools. Results: One-hundred and twenty-three subjects were enrolled in the study. Seventeenth neonates were affected by EOS. Seventeenth gestational age-matched newborns were enrolled as controls. Metabolomic untargeted analysis on urine samples collected within 24 hours of birth revealed an evident clustering of subjects (septic versus non-septic neonates). The diagnostic performance of urine metabolome resulted comparable to those of PCR, as documented by ROC curves. Conclusions: Neonates with EOS showed a specific metabolic profile compared to those of newborns not affected by sepsis at the onset of infection, allowing their clear discrimination with the use of untargeted metabolomics analysis. Results of this research support the effectiveness of metabolomics in exploring biochemical pathways of neonatal sepsis, potentially providing novel putative biomarkers for early diagnosis, guide to antibiotic therapy, and monitoring of disease progression. Future perspectives will be addressed to introduce these novel metabolomics biomarkers in clinical routine practice, ensuring short laboratory turnaround time and 24 hours bedside availability.

Metabolomics and neonatal sepsis: a new approach for early biomarkers discovery / Mardegan, Veronica. - (2018 Aug 18).

Metabolomics and neonatal sepsis: a new approach for early biomarkers discovery

Mardegan, Veronica
2018

Abstract

Background: Neonatal sepsis is a complex infection-induced systemic inflammatory response syndrome and it is a main cause of mortality and neurologic sequelae in newborns. An early and accurate detection of sepsis is mandatory in neonates, since the clinical course of the infectious process can be fulminant, leading to septic shock and death within hours after the first clinical symptoms. The gold standard for diagnosis of neonatal sepsis is blood culture, but it is time-consuming and false negative results are not rare. To date, there is still no reliable biochemical marker of neonatal sepsis. Aim of the study: To compare the metabolic profile of urine collected within 72 hours of birth between preterm neonates affected by early onset sepsis (EOS) and healthy preterm infants, searching for a specific metabolite or metabolic profile enabling the early identification of preterm newborns prone to develop EOS. Materials and Methods: Each preterm neonate admitted to the Neonatal Intensive Care Unit was eligible for recruitment. Infants who developed a septic episode within 72 hours of birth were enrolled as cases. Infants who did not developed a septic episode were enrolled as controls. For each subject, a urine sample was collected within 72 hours of birth. The urine samples underwent untargeted metabolomic analysis using mass spectrometry combined with ultra-performance liquid chromatography. The data obtained were analyzed using multivariate and univariate statistical data analysis tools. Results: One-hundred and twenty-three subjects were enrolled in the study. Seventeenth neonates were affected by EOS. Seventeenth gestational age-matched newborns were enrolled as controls. Metabolomic untargeted analysis on urine samples collected within 24 hours of birth revealed an evident clustering of subjects (septic versus non-septic neonates). The diagnostic performance of urine metabolome resulted comparable to those of PCR, as documented by ROC curves. Conclusions: Neonates with EOS showed a specific metabolic profile compared to those of newborns not affected by sepsis at the onset of infection, allowing their clear discrimination with the use of untargeted metabolomics analysis. Results of this research support the effectiveness of metabolomics in exploring biochemical pathways of neonatal sepsis, potentially providing novel putative biomarkers for early diagnosis, guide to antibiotic therapy, and monitoring of disease progression. Future perspectives will be addressed to introduce these novel metabolomics biomarkers in clinical routine practice, ensuring short laboratory turnaround time and 24 hours bedside availability.
18-ago-2018
Metabolomics; sepsis; infant/newborn
Metabolomics and neonatal sepsis: a new approach for early biomarkers discovery / Mardegan, Veronica. - (2018 Aug 18).
File in questo prodotto:
File Dimensione Formato  
TESTO_TESI_COMPLETO_MardeganV.pdf

accesso aperto

Tipologia: Tesi di dottorato
Licenza: Non specificato
Dimensione 758.95 kB
Formato Adobe PDF
758.95 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3427177
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
  • OpenAlex ND
social impact