Host genetic basis of COVID-19: from methodologies to genes

Abstract

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is having a massive impact on public health, societies, and economies worldwide. Despite the ongoing vaccination program, treating COVID-19 remains a high priority; thus, a better understanding of the disease is urgently needed. Initially, susceptibility was associated with age, sex, and other prior existing comorbidities. However, as these conditions alone could not explain the highly variable clinical manifestations of SARS-CoV-2 infection, the attention was shifted toward the identification of the genetic basis of COVID-19. Thanks to international collaborations like The COVID-19 Host Genetics Initiative, it became possible the elucidation of numerous genetic markers that are not only likely to help in explaining the varied clinical outcomes of COVID-19 patients but can also guide the development of novel diagnostics and therapeutics. Within this framework, this review delineates GWAS and Burden test as traditional methodologies employed so far for the discovery of the human genetic basis of COVID-19, with particular attention to recently emerged predictive models such as the post-Mendelian model. A summary table with the main genome-wide significant genomic loci is provided. Besides, various common and rare variants identified in genes like TLR7, CFTR, ACE2, TMPRSS2, TLR3, and SELP are further described in detail to illustrate their association with disease severity.

Host Genetic Variants Linked to COVID-19 Neurological Complications and Susceptibility in Young Adults—A Preliminary Analysis

“…The effect of the SARS-CoV-2 virus on the respiratory system, cardiovascular system, and gastrointestinal tract has been repeatedly demonstrated [ 1 , 2 ]. Together with epidemiological data on disease severity related to anthropometric parameters and concomitant chronic pathology [ 1 ], the role of genetic factors in COVID-19 illness and disease severity has been reported (for review, see [ 2 , 3 , 4 ]). Twin studies have elucidated a substantial genetic influence for predicted COVID-19, with a concordance rate of 80% in MZ twins [ 4 ].…”

“…Together with epidemiological data on disease severity related to anthropometric parameters and concomitant chronic pathology [ 1 ], the role of genetic factors in COVID-19 illness and disease severity has been reported (for review, see [ 2 , 3 , 4 ]). Twin studies have elucidated a substantial genetic influence for predicted COVID-19, with a concordance rate of 80% in MZ twins [ 4 ]. The largest study was conducted by the COVID-19 Host Genetics Initiative (COVID19 HGI) (released on 15 June 2021) [ 5 ], which established a link between host genes and three COVID-19 outcomes in a genome-wide association study (GWAS) meta-analysis.…”

COVID-19: a challenge and an opportunity

“…COVID-19 is the first disease in which environmental factors are well defined, misurabile and weighable. Heritability (h2) as calculated by gV/gV+aV is very high in COVID-19, similarly to psychiatric disorders [1]. While media are taking care mainly of the viral genome, the host genome is the real discriminant between severe COVID-19 and asymptomatic SARS-CoV-2 infection.…”

“…While media are taking care mainly of the viral genome, the host genome is the real discriminant between severe COVID-19 and asymptomatic SARS-CoV-2 infection. Therefore, while COVID-19 is representing a challenge for the health systems and society, it is the first real opportunity to move forward on understanding mechanisms and new rules useful in clinical practice of complex disorders, as described in the papers of this issue [1][2][3][4][5][6][7][8][9].…”

“…Finally, Zguro et al focus on new methods for understanding the host genetics determinants of COVID-19 [1]. A new method named "post-Mendelian model" has been developed combining for the first time both common and rare genetic variability and using a gene-based machine learning approach with the support of GEN-COVID (https://sites.google.com/dbm.unisi.it/gen-covid).…”