Background: Symptoms of early-onset sepsis (EOS) in preterm infants are nonspecific, overlapping with normal postnatal physiological adaptations and noninfectious pathologies. This clinical uncertainty and the lack of reliable EOS diagnostics results in liberal use of antibiotics in the first days to weeks of life, leading to increased risk of antibiotic-related morbidities in infants who do not have an invasive infection.
Methods: To identify potential biomarkers for EOS in newborn infants, we used unlabelled tandem mass spectrometry proteomics to identify differentially abundant proteins in the umbilical cord blood of infants with and without culture-confirmed EOS. Proteins were then confirmed using immunoassay, and logistic regression and random forest models were built including both biomarker concentration and clinical variables to predict EOS.
Results: These data identified five proteins that were significantly upregulated in infants with EOS, three of which (serum amyloid A, C-reactive protein, and lipopolysaccharide-binding protein) were confirmed using a quantitative immunoassay. The random forest classifier for EOS was applied to a cohort of infants with culture-negative presumed sepsis (PS). Most PS infants were classified as resembling control infants, having low EOS biomarker concentrations.
Conclusion: These results suggest that cord blood biomarker screening may be useful for early stratification of EOS risk among neonates, improving targeted, evidence-based use of antibiotics early in life.
Funding: National Institutes of Health, Gerber Foundation, Friends of Prentice, Thrasher Research Fund, Ann & Robert H. Lurie Children's Hospital, Stanley Manne Children's Research Institute of Lurie Children's.
Keywords: Bacterial infections; Biomarkers; Immunology; Infectious disease; Proteomics.
