Neonatal sepsis is an irregular immune response to a severe infection that occurs within the first 28 days of life. It affects around 1.3 million babies annually, with the highest rates generally seen in low- and middle-income countries. Because sepsis has non-specific symptoms, its diagnosis can be challenging and lengthy, leading to delays in administering life-saving antibiotics.
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Conducted by the Expanded Program for Immunization Consortium – Human Immunology Project Consortium (EPIC-HIPC), the study analyzed blood samples from 720 healthy, full-term newborns in The Gambia, ultimately identifying 21 infants who later developed sepsis within their first month of life. Neonates who eventually developed early-onset sepsis (EOS) displayed approximately 1,000 differently expressed genes at birth compared with those who did not develop sepsis or had only localized infections.
Using machine learning techniques, a four-gene signature – comprising HSPH1, BORA, NCAPG2, and PRIM1 – was developed to predict EOS. In an initial test, this gene signature achieved an area under the curve (AUC) of 0.94, with a sensitivity of 0.93 and specificity of 0.92. Validation in an external cohort showed an AUC of 0.72, indicating robust prediction capability, though it decreased somewhat across different patient populations.
The team also examined how sepsis disrupts typical gene expression pathways related to immune and metabolic development during the neonatal period. Babies with EOS showed marked changes in immune system and cell cycle gene expression trajectories in their first week, indicating that neonatal sepsis disrupts normal physiological development.
The research highlights the potential for implementing gene expression-based diagnostics in neonatal sepsis screening; corresponding author, Amy Lee, comments, “The larger implication is that we can potentially predict, when a baby is born, if they will be at a higher risk of developing neonatal sepsis or not. However, we need to test this out in a new cohort to validate the signature we found.”
Such screening could also inform treatment decisions to improve outcomes for neonatal sepsis. “Knowing that a newborn child will likely acquire neonatal sepsis would allow doctors to assign precious medical resources to prevent the severe consequences of this disease,” says EPIC Consortium member, Bob Hancock. “Identifying our gene expression signature in the blood will provide that information to physicians.”
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