We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
LGC Clinical Diagnostics

Download Mobile App




Genetic Signature in Newborns Predicts Neonatal Sepsis Before Symptoms Appear

By LabMedica International staff writers
Posted on 29 Oct 2024
Print article
Image: Scientists have developed tool to predict sepsis in apparently healthy newborns (Photo courtesy of 123RF)
Image: Scientists have developed tool to predict sepsis in apparently healthy newborns (Photo courtesy of 123RF)

Neonatal sepsis, which occurs due to the body’s abnormal response to severe infection within the first 28 days of life, results in approximately 200,000 deaths globally each year. This condition affects around 1.3 million infants worldwide annually, with even higher rates reported in lower- and middle-income countries (LMICs). Diagnosing sepsis poses significant challenges for both healthcare providers and families. The symptoms can resemble those of various other illnesses, and tests to determine the presence of sepsis can take several days, may not always be accurate, and are largely confined to hospital settings. This uncertainty can lead to delays in administering urgent antibiotic treatment. Furthermore, even if treatment is successful, sepsis can cause lifelong consequences, including developmental delays in children, cognitive deficits, and long-term health issues. A new study has now revealed that a genetic signature in newborns can predict neonatal sepsis before any symptoms appear, offering the potential to assist healthcare professionals in diagnosing affected infants earlier, especially in LMICs where neonatal sepsis is a critical issue.

The extensive study was conducted by researchers at The University of British Columbia (UBC, Vancouver, BC, Canada) and Simon Fraser University (SFU, Burnaby, BC, Canada) in The Gambia, where blood samples were collected from 720 infants at birth. Among this cohort, 15 infants developed early-onset sepsis. The researchers employed machine learning techniques to analyze the expression of genes active at birth, seeking biological markers capable of predicting sepsis. The findings, published in eBiomedicine, indicate that the researchers identified four genes that, when combined into a 'signature', could accurately predict sepsis in newborns with a success rate of 90%.

This study presented a unique opportunity, as samples from all infants in the cohort were available on the day of their birth, allowing researchers to investigate the gene expressions in those who later developed sepsis before they exhibited any illness. Most previous studies have only reported markers detected after the infants had already fallen ill, making those findings less useful for prediction. The next phase of this research involves conducting a large prospective study to validate the predictive capability of the signature in other populations and to establish its methodology. Following this, the aim will be to develop point-of-care tools for approval by relevant regulatory bodies. The researchers hope that this genetic signature will eventually be integrated not only into PCR tests in hospitals but also into portable, point-of-care devices.

“There are point-of-care devices available that can test for gene expression, for instance, COVID-19 and influenza, with a single drop of blood. They can operate anywhere with a power source including batteries and can be used by anyone, not just trained healthcare providers,” said co-senior author Dr. Bob Hancock, professor in the UBC department of microbiology and immunology. “These portable devices could be retooled to recognize this ‘signature’ relatively easily and inexpensively.”

Gold Member
Flocked Fiber Swabs
Puritan® Patented HydraFlock®
Antipsychotic TDM AssaysSaladax Antipsychotic Assays
New
Thyroxine ELISA
T4 ELISA
New
Urine Strips
11 Parameter Urine Strips

Print article

Channels

Clinical Chemistry

view channel
Image: The new saliva-based test for heart failure measures two biomarkers in about 15 minutes (Photo courtesy of Trey Pittman)

POC Saliva Testing Device Predicts Heart Failure in 15 Minutes

Heart failure is a serious condition where the heart muscle is unable to pump sufficient oxygen-rich blood throughout the body. It ranks as a major cause of death globally and is particularly fatal for... Read more

Hematology

view channel
Image: The smartphone technology measures blood hemoglobin levels from a digital photo of the inner eyelid (Photo courtesy of Purdue University)

First-Of-Its-Kind Smartphone Technology Noninvasively Measures Blood Hemoglobin Levels at POC

Blood hemoglobin tests are among the most frequently conducted blood tests, as hemoglobin levels can provide vital insights into various health conditions. However, traditional tests are often underutilized... Read more

Immunology

view channel
Image: Under a microscope, DNA repair is visible as bright green spots (“foci”) in the blue-stained cell DNA. Orange highlights actively growing cancer cells (Photo courtesy of WEHI)

Simple Blood Test Could Detect Drug Resistance in Ovarian Cancer Patients

Every year, hundreds of thousands of women across the world are diagnosed with ovarian and breast cancer. PARP inhibitors (PARPi) therapy has been a major advancement in treating these cancers, particularly... Read more

Microbiology

view channel
Image: HNL Dimer can be a novel and potentially useful clinical tool in antibiotic stewardship in sepsis (Photo courtesy of Shutterstock)

Unique Blood Biomarker Shown to Effectively Monitor Sepsis Treatment

Sepsis remains a growing problem across the world, linked to high rates of mortality and morbidity. Timely and accurate diagnosis, along with effective supportive therapy, is essential in reducing sepsis-related... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.