What do all viral pandemics have in common?
That’s the question Debashis Sahoo, PhD, an assistant professor of pediatrics at UC San Diego School of Medicine and of computer science and engineering at Jacobs School of Engineering, grappled with through a study, recently published in eBiomedicine, that led to the development of an AI algorithm that can identify “signature genes” that reveal how the human immune system responds to viral infections.
"When the COVID-19 pandemic began, I wanted to use my computer science background to find something that all viral pandemics have in common—some universal truth we could use as a guide as we try to make sense of a novel virus," Sahoo in a press release. "This coronavirus may be new to us, but there are only so many ways our bodies can respond to an infection."
For the study, UC San Diego researchers analyzed over 45,000 transcriptomic datasets from viral pandemics among humans, mice, and rats. From those sets, they identified a 166-gene signature that sheds light on how the immune system reacts to viral infections, as well as a signature of 20 genes that can predict the severity of a patient’s condition.
The data used to test and train the algorithm came from publicly available sources of patient gene expression data -- all the RNA transcribed from patients' genes and detected in tissue or blood samples. Each time a new set of data from patients with COVID-19 became available, the team tested it in their model. They saw the same signature gene expression patterns every time.
"In other words, this was what we call a prospective study, in which participants were enrolled into the study as they developed the disease and we used the gene signatures we found to navigate the uncharted territory of a completely new disease," Sahoo said.
"These viral pandemic-associated signatures tell us how a person's immune system responds to a viral infection and how severe it might get, and that gives us a map for this and future pandemics," explained Pradipta Ghosh, MD, one of the study’s authors and a professor of cellular and molecular medicine at UC San Diego School of Medicine and Moores Cancer Center.
As the study’s report summed it up, the gene signatures “provide a quantitative and qualitative framework for titrating the immune response in viral pandemics and may serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs.”
The study noted that as new COVID-19 datasets emerge, the AI model will become even more effective and accurate.
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