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 , and genes, as central components for SARS-CoV-2 infection, and on other molecules that modulate their expression such as , , and  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.