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

• DOI: 10.1186/s12879-022-07415-1
• Publication Date: 2022-06-19T18:02:36Z
• Authors: 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
• Keywords: Clade; 0301 basic medicine; Infectious and parasitic diseases; RC109-216; Infectious disease (medical specialty); FOS: Health sciences; PRS; Coronavirus Disease 2019; Computational biology; Pathology; Disease; Immunology and Microbiology; Host (biology); Life Sciences; COVID-19 severity; Medical microbiology; Profiling (computer programming); 3. Good health; Infectious Diseases; Vietnam; Medicine; Coronavirus Infections; Pneumonia, Viral; Immunology; Trained Immunity in Health and Disease; Coronavirus Disease 2019 Research; Betacoronavirus; 03 medical and health sciences; Virology; Health Sciences; Genetics; Humans; Biology; Corona Virus; Pandemic; SARS-CoV-2; Research; FOS: Clinical medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); COVID-19; Outbreak; Computer science; COVID-19 Drug Treatment; Coronavirus disease 2019 (COVID-19); Operating system; FOS: Biological sciences; Parasitology; 2019-20 coronavirus outbreak; Zoology; Genome-Wide Association Study

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.