Can your chance of surviving SARS-Cov-2 be predicted? It sure can be due to recently combined research efforts by ISB, Fred Hutchinson Cancer Research Center, Stanford University, Swedish Medical Center St. John’s Cancer Institute at Saint John’s Health Center, the University of Washington, the Howard Hughes Medical Institute. It comes from studying your immune system and a special part of your endocrine system, your metabolism.
The researchers sampled the blood of nearly 200 COVID-19 patients. They took two draws per patient during the first week after being diagnosed with SARS-CoV-2 infection, totaling 374 blood samples. The researchers then analyzed their plasma and single immune cells. The analysis included 1,387 genes involved in metabolic pathways and 1,050 plasma metabolites.
“We analyzed thousands of biological markers linked to metabolic pathways that underlie the immune system and found some clues as to what immune-metabolic changes may be pivotal in severe disease,” says researcher and graduate student from Fred Hutchinson Cancer Research Center, Jihoon Lee. Well, what were these clues? The clue is the link between how certain metabolic changes regulate how immune cells react when it comes to disease severity and predicting patient survival. Basically, increased COVID-19 severity leads to increased immune-related activity.
With these new discoveries, researchers used single-cell sequencing to further investigate. They found that each major immune cell type has a distinct metabolic signature. “We have found metabolic reprogramming that is highly specific to individual immune cell classes (e.g. “killer” CD8+ T cells, “helper” CD4+ T cells, antibody-secreting B cells, etc.) and even cell subtypes, and the complex metabolic reprogramming of the immune system is associated with the plasma global metabolome and are predictive of disease severity and even patient death,” says Dr. Yapeng Su, a research scientist at Institute for Systems Biology.
Despite the need for more advanced single-cell multi-omic analysis, this research has proven to be very successful. It provides significant insights for developing more effective treatments against COVID-19. What do you think about this research being used for predicting survivability for other diseases to come?