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Will GWAS eventually allow the identification of genomic biomarkers for COVID-19 severity and mortality?
Colona, Vito Luigi; Biancolella, Michela; Novelli, Antonio; Novelli, Giuseppe.
  • Colona VL; Department of Biomedicine and Prevention and.
  • Biancolella M; Department of Biology, Tor Vergata University of Rome, Rome, Italy.
  • Novelli A; Laboratory of Medical Genetics, IRCCS Bambino Gesù Children's Hospital, Rome, Italy.
  • Novelli G; Department of Biomedicine and Prevention and.
J Clin Invest ; 131(23)2021 12 01.
Article in English | MEDLINE | ID: covidwho-1484167
ABSTRACT
GWAS involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have enabled the identification of numerous genomic biomarkers in various complex human diseases, including infectious ones. However, few of these studies are relevant for clinical practice or at the bedside. In this issue of the JCI, Nakanishi et al. characterized the clinical implications of a major genetic risk factor for COVID-19 severity and its age-dependent effect, using individual-level data in a large international multicenter consortium. This study indicates that a common COVID-19 genetic risk factor (rs10490770) associates with increased risks of morbidity and mortality, suggesting potential implications for future clinical risk management. How can the genomic biomarkers identified by GWAS be associated with the clinical outcomes of an infectious disease? In this Commentary, we evaluate the advantages and limitations of this approach.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genome-Wide Association Study / COVID-19 Type of study: Experimental Studies / Prognostic study Topics: Variants Limits: Humans Language: English Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genome-Wide Association Study / COVID-19 Type of study: Experimental Studies / Prognostic study Topics: Variants Limits: Humans Language: English Year: 2021 Document Type: Article