[No authors listed]
There is considerable variation in disease course among individuals infected with SARS-CoV-2. Many of them do not exhibit any symptoms, while some others proceed to develop COVID-19; however, severity of COVID-19 symptoms greatly differs among individuals. Focusing on the early events related to SARS-CoV-2 entry to cells through the ACE2 pathway, we describe how variability in (epi)genetic factors can conceivably explain variability in disease course. We specifically focus on variations in ACE2, TMPRSS2 and FURIN genes, as central components for SARS-CoV-2 infection, and on other molecules that modulate their expression such as CALM, ADAM-17, AR and ESRs. We propose a genetic classifier for predicting SARS-CoV-2 infectivity potential as a preliminary tool for identifying the at-risk-population. This tool can serve as a dynamic scaffold being updated and adapted to validated (epi)genetic data. Overall, the proposed approach holds potential for better personalization of COVID-19 handling.
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