Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated coronavirus disease 2019 (COVID-19) pandemic has been the subject of a large number of studies in recent times. Here, starting from the evidence that in Italy, the areas with the lowest number of COVID-19 cases were those with the highest incidence of malaria in the early 1900’s, we explore possible inverse relationships between malaria and COVID-19. Indeed, some genetic variants, which have been demonstrated to give an advantage against malaria, can also play a role in the incidence and severity of SARS-CoV-2 infections (e.g., the ACE2 receptor). To verify this scientific hypothesis, we here use public data from whole-genome sequencing (WGS) experiments to extrapolate the genetic information of 46 world populations with matched COVID-19 data. In particular, we focus on 47 genes, including ACE2 and genes which have previously been reported to play a role in malaria. Only common variants (>5%) in at least 30% of the selected populations were considered, and, for this subset, we correlate the intra-population allele frequency with the COVID-19 data (cases/million inhabitants), eventually pinpointing meaningful variants in 6 genes. This study allows us to distinguish between positive and negative correlations, i.e., variants whose frequency significantly increases with increasing or decreasing COVID-19 cases. Finally, we discuss the possible molecular mechanisms associated with these variants and advance potential therapeutic options, which may help fight and/or prevent COVID-19.
【저자키워드】 COVID-19, Epidemiology, Genomics, malaria, whole-genome sequencing analysis, 【초록키워드】 coronavirus disease, whole-genome sequencing, ACE2, coronavirus, pandemic, SARS-COV-2 infection, severity, allele frequency, variant, ACE2 receptor, Italy, molecular mechanism, Population, genetic variants, experiment, incidence, WGS, therapeutic options, Evidence, Hypothesis, Frequency, COVID-19 cases, acute respiratory syndrome, subject, COVID-19 case, help, correlations, genetic information, positive, Genes, Prevent, lowest, selected, highest, significantly, reported, increase, demonstrated, subset,