• Elisa Benetti, Rossella Tita, Ottavia Spiga, Andrea Ciolfi, Giovanni Birolo, Alessandro Bruselles, Gabriella Doddato, Annarita Giliberti, Caterina Marconi, Francesco Musacchia, Tommaso Pippucci, Annalaura Torella, Alfonso Trezza, Floriana Valentino, Margherita Baldassarri, Alfredo Brusco, Rosanna Asselta, Mirella Bruttini, Simone Furini, Marco Seri, Vincenzo Nigro, Giuseppe Matullo, Marco Tartaglia, Francesca Mari, GEN-COVID Multicenter Study, Alessandra Renieri, and Anna Maria Pinto.
• Department of Medical Biotechnologies, University of Siena, Siena, Italy.
• Eur. J. Hum. Genet. 2020 Nov 1; 28 (11): 1602-1614.

AbstractIn December 2019, an initial cluster of interstitial bilateral pneumonia emerged in Wuhan, China. A human-to-human transmission was assumed and a previously unrecognized entity, termed coronavirus disease-19 (COVID-19) due to a novel coronavirus (SARS-CoV-2) was described. The infection has rapidly spread out all over the world and Italy has been the first European country experiencing the endemic wave with unexpected clinical severity in comparison with Asian countries. It has been shown that SARS-CoV-2 utilizes angiotensin converting enzyme 2 (ACE2) as host receptor and host proteases for cell surface binding and internalization. Thus, a predisposing genetic background can give reason for interindividual disease susceptibility and/or severity. Taking advantage of the Network of Italian Genomes (NIG), here we mined whole-exome sequencing data of 6930 Italian control individuals from five different centers looking for ACE2 variants. A number of variants with a potential impact on protein stability were identified. Among these, three more common missense changes, p.(Asn720Asp), p.(Lys26Arg), and p.(Gly211Arg) were predicted to interfere with protein structure and stabilization. Rare variants likely interfering with the internalization process, namely p.(Leu351Val) and p.(Pro389His), predicted to interfere with SARS-CoV-2 spike protein binding, were also observed. Comparison of ACE2 WES data between a cohort of 131 patients and 258 controls allowed identifying a statistically significant (P value < 0.029) higher allelic variability in controls compared with patients. These findings suggest that a predisposing genetic background may contribute to the observed interindividual clinical variability associated with COVID-19, allowing an evidence-based risk assessment leading to personalized preventive measures and therapeutic options.

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