COVID-19 Flare-up Predicted by Artificial Intelligence

Artificial Intelligence predicts how patients with viral infections, including COVID-19, will fare using gene expression patterns that help define immune responses, measure disease severity, predict outcomes, and test therapies for current and future pandemics, as per a study at the University of California - San Diego School of Medicine, published in eBiomedicine. The algorithm's utility was validated using lung tissues collected at autopsies from deceased patients with COVID-19 and animal models of the infection.

Two telltale signatures emerged from the study – one, a set of 166 genes, reveals how the human immune system responds to viral infections. A second set of 20 signature genes predicts the severity of a patient's disease. For example, the need to hospitalize or use a mechanical ventilator.

"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," says Pradipta Ghosh, MD, professor of cellular and molecular medicine at UC San Diego School of Medicine and Moores Cancer Center.

Artificial Intelligence and COVID-19

The immune system releases small proteins called cytokines into the blood during a viral infection. These proteins guide immune cells to the site of infection to help get rid of the infection.

Sometimes, the body may release too many cytokines that attack its healthy tissue, known as a cytokine storm. This predicts the severity of the infection in a patient. However, the nature, extent, and source of fatal cytokine storms are unclear.

"We could see and show the world that the alveolar cells in our lungs that are normally designed to allow gas exchange and oxygenation of our blood, are one of the major sources of the cytokine storm, and hence, serve as the eye of the cytokine storm. Next, our HUMANOID Center team is modeling human lungs in the context of COVID-19 infection in order to examine both acute and post-COVID-19 effects," says Soumita Das, Ph.D., associate professor of pathology at UC San Diego School of Medicine.

The study thereby speculates that this information might also help guide treatment approaches for patients experiencing a cytokine storm by providing cellular targets and benchmarks to measure improvement.



Source-Medindia