COVID-19 pandemic represented a worldwide challenge in the past 3 years. Even if the emergency is ending, the identification of the main prognostic factors that determine the clinical outcome still remain one of the major challenges, to implement effective preventive and therapeutic strategies also useful for other infectious diseases and complex diseases. Retrospective analysis of epidemiologic data has revealed that male sex, older age, and underlying metabolic diseases such as obesity pose high risks for fatal COVID-19. It is now well known that also host genetics factors play a crucial role in causing the COVID-19 clinical outcome and various common and rare variants have been described in association with susceptibility and severity. In particular, within the GEN-COVID Multicenter study, from March 2020, we have enrolled more than 5000 Sars-CoV-2 positive subjects, collected their clinical data and performed WES analysis. Through data-mining from clinical and molecular data, during these three years of my PhD course, we have discovered that common, rare and ultra-rare variants in genes such as TLR7, CFTR, AR, TLR3, SELP and ADAMTS13 are associated with the severity of COVID-19 disease through different mechanisms. Moreover, in order to better understand the genetic basis of COVID-19, as a complex, polygenic disease, it was therefore necessary to apply new approaches capable of identifying the entire genetic variability of the host and combining common and rare variants in a single model. For this reason, we proposed a new model, the post-Mendelian model, for a genetic characterization of the disorder based on an adapted Poly-genic Risk Score (PRS), called Integrated PolyGenic Score (IPGS). This allowed us to reach a more precise disease severity prediction than that based on sex and age alone. Modelling precisely the role of the entire range of host genomics affecting disease susceptibility and severity in COVID-19 is critical to obtaining a complete biological understanding of the aetiology and pathogenicity of COVID-19 as well as other severe complex diseases The knowledge that will be acquired with our data will allow us to develop a new therapeutic approach, which acts through the host-mediated response to pathogens rather than acting directly on the pathogen, as standard therapy traditionally addresses.
Baldassarri, M. (2023). Host genetic basis of COVID-19: from phenotype to genes. [10.25434/baldassarri-margherita_phd2023].
Host genetic basis of COVID-19: from phenotype to genes.
Baldassarri, Margherita
2023-01-01
Abstract
COVID-19 pandemic represented a worldwide challenge in the past 3 years. Even if the emergency is ending, the identification of the main prognostic factors that determine the clinical outcome still remain one of the major challenges, to implement effective preventive and therapeutic strategies also useful for other infectious diseases and complex diseases. Retrospective analysis of epidemiologic data has revealed that male sex, older age, and underlying metabolic diseases such as obesity pose high risks for fatal COVID-19. It is now well known that also host genetics factors play a crucial role in causing the COVID-19 clinical outcome and various common and rare variants have been described in association with susceptibility and severity. In particular, within the GEN-COVID Multicenter study, from March 2020, we have enrolled more than 5000 Sars-CoV-2 positive subjects, collected their clinical data and performed WES analysis. Through data-mining from clinical and molecular data, during these three years of my PhD course, we have discovered that common, rare and ultra-rare variants in genes such as TLR7, CFTR, AR, TLR3, SELP and ADAMTS13 are associated with the severity of COVID-19 disease through different mechanisms. Moreover, in order to better understand the genetic basis of COVID-19, as a complex, polygenic disease, it was therefore necessary to apply new approaches capable of identifying the entire genetic variability of the host and combining common and rare variants in a single model. For this reason, we proposed a new model, the post-Mendelian model, for a genetic characterization of the disorder based on an adapted Poly-genic Risk Score (PRS), called Integrated PolyGenic Score (IPGS). This allowed us to reach a more precise disease severity prediction than that based on sex and age alone. Modelling precisely the role of the entire range of host genomics affecting disease susceptibility and severity in COVID-19 is critical to obtaining a complete biological understanding of the aetiology and pathogenicity of COVID-19 as well as other severe complex diseases The knowledge that will be acquired with our data will allow us to develop a new therapeutic approach, which acts through the host-mediated response to pathogens rather than acting directly on the pathogen, as standard therapy traditionally addresses.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1252215