Drivers of severe Covid-19 disease in patients under 50 without comorbidities

patients without comorbidities progress to critical illness whereas others do not, a phenomenon that has been exacerbated with new viral variants in current epidemic waves across the globe.

In particular, knowledge of the molecular drivers of critical Covid-19 disease is needed in order to identify predictive biomarkers and more efficient therapeutic targets that function through drivers of critical Covid-19 disease. By using machine learning, artificial intelligence, and probabilistic programming strategies to analyze the multiomic data generated for the cases and controls, the research team found higher-than-usual levels of inflammation and coagulation factors in the critical Covid-19 disease cohort, as well as altered lymphoid and myeloid cell activation and molecular features related to viral activity. Taken together, the results indicate that critical illness was characterized by a proinflammatory cytokine storm and notable changes in the T-cell, B-cell , dendritic cell, and monocyte cell compartments. These specific changes were independent from the extent of viral infection, as both the global anti-SARS-CoV-2 antibody concentrations and their neutralizing activity were not different in critical versus non-critical patients. When researchers analysed the set of genes that were differentially expressed in samples from the critical Covid-19 disease cases, non-critical cases, and uninfected controls, the researchers found a gene signature associated with severe infection that also coincided with critical cases in a follow-up analysis of 81 more individuals with critical SARS-CoV-2 infections and another 73 individuals who had recovered from Covid-19 disease. Upon these analyses, the team found within the candidate potential driver genes. Of those, the top candidate was ADAM9, a gene encoding a metalloprotease and disintegrin that had elevated expression in the severe cases.