BMC Infectious Diseases (Jun 2022)

Investigation of target sequencing of SARS-CoV-2 and immunogenic GWAS profiling in host cells of COVID-19 in Vietnam

  • Tham H. Hoang,
  • Giang M. Vu,
  • Mai H. Tran,
  • Trang T. H. Tran,
  • Quang D. Le,
  • Khanh V. Tran,
  • Tue T. Nguyen,
  • Lan T. N. Nguyen,
  • Thinh H. Tran,
  • Van T. Ta,
  • Nam S. Vo

DOI
https://doi.org/10.1186/s12879-022-07415-1
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 10

Abstract

Read online

Abstract Background A global pandemic has been declared for coronavirus disease 2019 (COVID-19), which has serious impacts on human health and healthcare systems in the affected areas, including Vietnam. None of the previous studies have a framework to provide summary statistics of the virus variants and assess the severity associated with virus proteins and host cells in COVID-19 patients in Vietnam. Method In this paper, we comprehensively investigated SARS-CoV-2 variants and immune responses in COVID-19 patients. We provided summary statistics of target sequences of SARS-CoV-2 in Vietnam and other countries for data scientists to use in downstream analysis for therapeutic targets. For host cells, we proposed a predictive model of the severity of COVID-19 based on public datasets of hospitalization status in Vietnam, incorporating a polygenic risk score. This score uses immunogenic SNP biomarkers as indicators of COVID-19 severity. Result We identified that the Delta variant of SARS-CoV-2 is most prevalent in southern areas of Vietnam and it is different from other areas in the world using various data sources. Our predictive models of COVID-19 severity had high accuracy (Random Forest AUC = 0.81, Elastic Net AUC = 0.7, and SVM AUC = 0.69) and showed that the use of polygenic risk scores increased the models’ predictive capabilities. Conclusion We provided a comprehensive analysis for COVID-19 severity in Vietnam. This investigation is not only helpful for COVID-19 treatment in therapeutic target studies, but also could influence further research on the disease progression and personalized clinical outcomes.

Keywords