A new study reveals that a genetic signature in newborns can predict neonatal sepsis before any symptoms appear. This research, conducted by teams from the University of British Columbia (UBC) and Simon Fraser University (SFU), alongside the Medical Research Council (MRC) Unit in The Gambia, could lead to earlier diagnoses, especially in lower- and middle-income countries where neonatal sepsis is a significant issue. The findings were published today in eBiomedicine and are funded by the National Institutes of Health and the Canadian Institutes of Health Research.
Neonatal sepsis occurs when the body reacts improperly to a severe infection within the first 28 days of life. Each year, it affects about 1.3 million newborns worldwide, with the highest rates in low- and middle-income countries. In Canada, the risk is lower, affecting approximately one in 200 live births, but it is higher among premature babies.
Diagnosing sepsis is difficult because its symptoms can resemble those of many other conditions. Current tests can take days to yield results and are often limited to hospitals, which can delay necessary antibiotic treatment.
“An early warning of sepsis would give doctors more time to decide on the right treatment,” said Dr. Bob Hancock, co-senior author and a professor at UBC. “Given the severe consequences of neonatal sepsis, an early diagnosis can save lives.”
The researchers studied blood samples from 720 infants in The Gambia, identifying 15 who developed early-onset sepsis. Using machine learning, they examined gene expression to find biological markers that could indicate sepsis risk.
They discovered that four specific genes, when combined, could predict sepsis in newborns with 90% accuracy. “This study is unique because we analyzed the genes of all babies at birth, allowing us to identify markers before they became sick,” explained Dr. Amy Lee, co-senior author and an assistant professor at SFU.
Dr. Beate Kampmann, who led the clinical part of the study, emphasized the importance of early sepsis recognition for infant survival. Identifying at-risk babies could allow for targeted monitoring and treatment.
The researchers envision incorporating this genetic signature into portable testing devices, similar to those used for COVID-19 and influenza, which require only a drop of blood. “These devices could easily and cheaply be adapted to detect this signature,” Dr. Hancock noted.
The next steps for this research involve conducting a large prospective study to validate the signature’s effectiveness in predicting sepsis in various populations and to develop point-of-care tools for regulatory approval.
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