Abstract

Albeit the pathogenesis of COVID-19 remains unclear, host’s genetic polymorphisms in genes involved in infection and reinfection, inflammation, or immune stimulation could play a role in determining the course and outcome. We studied in the early phase of pandemic consecutive patients (N = 383) with SARS-CoV-2 infection, whose subsequent clinical course was classified as mild or severe, the latter being characterized by admission to intensive therapy unit or death. Five host gene polymorphisms (MERTK rs4374383, PNPLA3 rs738409, TLL-1 rs17047200, IFNL3 rs1297860, and INFL4 rs368234815) were assessed by using whole nucleic acids extracted from nasopharyngeal swabs. Specific protease cleavage sites of TLL-1 on the SARS-CoV-2 Spike protein were predicted in silico. Male subjects and older patients were significantly at higher risk for a severe outcome (p = 0.02 and p < 0.001, respectively). By considering patients ≤65 years, after adjusting for potential confounding due to sex, an increased risk of severe outcome was found in subjects with the GG genotype of PNPLA3 (adj-OR: 4.69; 95% CI = 1.01–22.04) or TT genotype of TLL-1 (adj-OR=9.1; 95% CI = 1.45–57.3). In silico evaluation showed that TLL-1 is potentially involved in the Spike protein cleavage which is essential for viral binding and entry into the host cells using the host receptor angiotensin-converting enzyme 2 (ACE2). Subjects carrying a GG genotype in PNPLA3 gene might have a constitutive upregulation of the NLRP3 inflammasome and be more prone to tissue damage when infected by SARS-CoV-2. The TT genotype in TLL-1 gene might affect its protease activity on the SARS-CoV-2 Spike protein, enhancing the ability to infect or re-infect host’s cells. The untoward effect of these variants on disease course is evident in younger patients due to the relative absence of comorbidities as determinants of prognosis. In the unresolved pathogenetic scenery of COVID-19, the identification of genetic variants associates with more prolonged course or with a severe outcome of infection would support the development of predictive tools useful to stratify subjects by risk class at presentation. Moreover, the individuation of key genes could contribute to a better understanding of the pathways involved in the pathogenesis, giving the basis for rational therapeutic approaches.

Highlights

  • More than 140 million cases of infection with Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported worldwide by April 19, 2021, with over 3 million deaths due to the virus

  • Since family clustering of severe cases was reported starting from the first phase of the pandemic, supporting the possibility of a genetic predisposition (Chan et al, 2020), it is conceivable that the complexity of host genetic background in terms of polymorphisms, may play a key role in pathogenesis and outcome of COVID-19

  • One of the five investigated polymorphisms had an uncommon genotype (TT in Tolloid Like-1 (TLL-1) rs17047200; N = 11, 2.96%), whereas low frequency genotypes were found in IFNL3 rs12979860 (TT N = 41, 10.7%), INFL4 rs368234815 (DG/DG 34, 11.30%), Mer tyrosine kinase (MERTK) rs4374383 (AA in 44, 15.12%), and patatin-like phospholipase domain-containing 3 (PNPLA3) rs738409 (GG 29, 7.82%), respectively

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Summary

Introduction

More than 140 million cases of infection with Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported worldwide by April 19, 2021, with over 3 million deaths due to the virus Since family clustering of severe cases was reported starting from the first phase of the pandemic, supporting the possibility of a genetic predisposition (Chan et al, 2020), it is conceivable that the complexity of host genetic background in terms of polymorphisms, may play a key role in pathogenesis and outcome of COVID-19 In this perspective, the COVID-19 Host Genetics Initiative, 2020 (available at COVID-19 HGI2) is currently leading a public effort worldwide to analyze COVID-19 information for millions of individuals in relation with genotype data to identify genetic variants associated with SARS-CoV-2 infection as well as COVID-19 hospitalization and disease severity (COVID-19 Host Genetics Initiative, 2020)

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