How Genetics Might Explain the Unusual Link Between Malaria and COVID-19

Marta Rusmini; Paolo Uva; Antonio Amoroso; Manlio Tolomeo; Andrea Cavalli

doi:10.3389/fmed.2021.650231

How Genetics Might Explain the Unusual Link Between Malaria and COVID-19

Front Med (Lausanne). 2021 Apr 26:8:650231. doi: 10.3389/fmed.2021.650231. eCollection 2021.

Authors

Marta Rusmini^{1

2}, Paolo Uva^{1

2}, Antonio Amoroso³, Manlio Tolomeo⁴, Andrea Cavalli^{1

5}

Affiliations

¹ Computational and Chemical Biology, Italian Institute of Technology, Genova, Italy.
² Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) G. Gaslini, Genova, Italy.
³ Department of Medical Sciences, University of Turin, Turin, Italy.
⁴ Department of Health Promotion Sciences, Azienda Ospedaliera Universitaria Policlinico Paolo Giaccone, Palermo, Italy.
⁵ Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.

Abstract

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.

Keywords: COVID-19; epidemiology; genomics; malaria; whole-genome sequencing analysis.