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Genomic and ancestral variation underlies the severity of covid-19 clinical manifestation in individuals of european descent

  • Priyanka Upadhyai
  • , Gokul Suresh
  • , Rahul Parit
  • , Ranajit Das*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The coronavirus disease (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by a wide spectrum of clinical phenotypes ranging from asymptomatic to symptomatic with mild or moderate presentation and severe disease. COVID-19 susceptibility, severity and recovery have demonstrated high variability worldwide. Variances in the host genetic architecture may underlie the inter-individual and population-scale differences in COVID-19 presentation. We performed a genome-wide association analysis employing the genotyp-ing data from AncestryDNA for COVID-19 patients of European descent and used asymptomatic subjects as the control group. We identified 621 genetic variants that were significantly distinct between asymptomatic and acutely symptomatic COVID-19 patients (multiple-testing corrected p-value < 0.001). These variants were found to be associated with pathways governing host immunity, such as interferon, interleukin and cytokine signalling, and known COVID-19 comorbidities, such as obesity and cholesterol metabolism. Further, our ancestry analysis revealed that the asymp-tomatic COVID-19 patients possess discernibly higher proportions of the Ancestral North Eurasian (ANE) and Eastern Hunter-Gatherer (EHG) ancestry, which was introduced to Europe through Bell Beaker culture (Yamnaya related) and lower fractions of Western Hunter-Gatherer (WHG) ancestry, while severely symptomatic patients have higher fractions of WHG and lower ANE/EHG ancestral components, thereby delineating the likely ancestral differences between the two groups.

Original languageEnglish
Article number921
JournalLife
Volume11
Issue number9
DOIs
Publication statusPublished - 09-2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • General Biochemistry,Genetics and Molecular Biology
  • Space and Planetary Science
  • Palaeontology

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