Duke researchers, including DGHI faculty member Christopher W. Woods, are looking to genomic technologies – not the isolation of bacteria or viruses – to quickly detect and diagnose infectious diseases such as the flu and staph.
Two studies published Wednesday, both in the journal PLOS ONE, show how a pattern of genomic information among infected individuals can be used to accurately pinpoint the cause of infection.
“Traditional diagnostic tests for infectious diseases rely on detecting the specific illness-causing pathogens. So you only find what you’re looking for,” said Geoffrey Ginsburg, M.D., PhD, a senior author on both studies and director of genomic medicine at the Duke Institute for Genome Sciences & Policy and professor of medicine.
Identifying the culprit pathogen guides the selection of treatment for sick patients; however, these traditional tests for infectious diseases can take several days and have varying levels of accuracy.
“Given that humans already have robust systems that recognize and try to ward off infectious organisms, can we harness the systems’ response to distinguish between pathogens?” Ginsburg asked.
The body’s reaction to infection, or host response, can be measured using genome-wide technologies that analyze human genes responding to the infection. Scientists can use the resulting “genomic signatures” to classify and diagnose infectious diseases based on the host response, without needing to test for a specific pathogen. The approach is especially appealing for detecting influenza since a genomic signature could identify new flu strains, which emerge frequently but may not be detected with existing diagnostic tests.
“The 2009 H1N1 flu pandemic highlighted the limitations of traditional pathogen-based testing,” said Woods, M.D., MPH, associate professor of medicine, pathology, and global health at Duke and the flu study’s lead author. “A test that could identify individuals exposed to the flu before the onset of symptoms would be an important and useful tool for guiding treatment decisions, especially with limited antiviral medications.”
Woods and his colleagues set out to develop a test using two strains of flu. They inoculated 41 participants with either the H1N1 or H3N2 virus, and analyzed their blood samples to gauge the host response using a variety of genome-wide technologies.
See the full story on Duke Medicine’s website.