New York: COVID-19 patients have different immune responses that lead to disease outcomes ranging from asymptomatic SARS-CoV-2 infection to death.
After examining blood samples from nearly 200 patients with COVID-19, researchers discovered key metabolic changes that regulate how immune cells react to the disease.
These changes correlate with disease severity and can be used to predict patient survival. The results were published in the journal Nature Biotechnology.
“We analyzed thousands of biomarkers associated with metabolic pathways that underlie the immune system, and found some clues about the immune metabolic changes that may be pivotal in severe disease,” said Jihon Lee, a graduate student at the Fred Hutchinson Cancer Research Center.
“We hope that these observations of immune function will help others piece together the body’s response to COVID-19,” Lee added.
The researchers collected 374 blood samples — two drawn for each patient within the first week after they were diagnosed with SARS-CoV-2 infection — and analyzed individual plasma and immune cells.
The analysis included 1387 genes involved in metabolic pathways and 1050 metabolites in plasma.
In plasma samples, the team found that increased severity of COVID-19 correlated with metabolic changes, indicating increased immune-related activity.
Moreover, by single-cell sequencing, the researchers found that each of the major immune cell types has a distinct metabolic imprint.
“We found metabolic reprogramming very specific to individual immune cell classes (eg, ‘killer’ CD8+ T cells, ‘helper’ CD4+ T cells, antibody-secreting B cells, etc.) and even cell subtypes, The complex metabolic reprogramming of the immune system is linked to the global metabolite of plasma and is predictive of disease severity and even patient death, said Dr. Yaping Su, a research scientist at the Institute of Systems Biology.
“This work provides important insights for developing more effective treatments against COVID-19,” the researchers noted. “It also represents a major technological hurdle.”