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Published on: November 10, 2023
Host Genetic Factors, Comorbidities and the Risk of Severe COVID-19
Dongliang Zhu1, Renjia Zhao2, Huangbo Yuan2
1Department of Epidemiology & Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Insights
Host genetic factors, including two 3p21.31 genes, significantly increase severe COVID-19 risk. A predictive model combining genetics, demographics, and comorbidities accurately identifies high-risk patients.
Area of Science:
- Genetics
- Epidemiology
- Infectious Diseases
Background:
- Coronavirus disease 2019 (COVID-19) presents varied symptoms, influenced by host factors.
- Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) necessitates understanding genetic predispositions and comorbidities for severe disease risk.
Purpose of the Study:
- To explore the impact of host genetic factors on severe COVID-19 risk.
- To assess the combined effect of host genetics and comorbidities in predicting severe COVID-19 outcomes.
Main Methods:
- Genome-wide association analysis (GWAS) and polygenic risk score (PRS) construction using 86 SNPs in 20,320 UK Biobank COVID-19 patients.
- Colocalization and logistic regression analyses to evaluate associations between genetic factors, comorbidities, and COVID-19 severity.
- Development and validation of predictive models incorporating demographic data, comorbidities, and PRS, assessed by AUROC.
Main Results:
- A genome-wide significant association was found at rs73064425 (3p21.31), implicating SLC6A20 and LZTFL1 genes in COVID-19 progression.
- A predictive model integrating demographic characteristics, comorbidities, and genetic factors achieved high accuracy (AUROC = 82.1%).
- Genetic risk was found to contribute to nearly 20% of severe COVID-19 events.
Conclusions:
- Two 3p21.31 genes were identified as genetic susceptibility loci for severe COVID-19.
- A predictive model incorporating demographic, comorbidity, and genetic data effectively identifies COVID-19 patients at risk for critical illness.
Background:
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was varied in disease symptoms. We aim to explore the effect of host genetic factors and comorbidities on severe COVID-19 risk.
Methods:
A total of 20,320 COVID-19 patients in the UK Biobank cohort were included. Genome-wide association analysis (GWAS) was used to identify host genetic factors in the progression of COVID-19 and a polygenic risk score (PRS) consisted of 86 SNPs was constructed to summarize genetic susceptibility. Colocalization analysis and Logistic regression model were used to assess the association of host genetic factors and comorbidities with COVID-19 severity. All cases were randomly split into training and validation set (1:1). Four algorithms were used to develop predictive models and predict COVID-19 severity. Demographic characteristics, comorbidities and PRS were included in the model to predict the risk of severe COVID-19. The area under the receiver operating characteristic curve (AUROC) was applied to assess the models' performance.
Results:
We detected an association with rs73064425 at locus 3p21.31 reached the genome-wide level in GWAS (odds ratio: 1.55, 95% confidence interval: 1.36-1.78). Colocalization analysis found that two genes (SLC6A20 and LZTFL1) may affect the progression of COVID-19. In the predictive model, logistic regression models were selected due to simplicity and high performance. Predictive model consisting of demographic characteristics, comorbidities and genetic factors could precisely predict the patient's progression (AUROC = 82.1%, 95% CI 80.6-83.7%). Nearly 20% of severe COVID-19 events could be attributed to genetic risk.
Conclusion:
In this study, we identified two 3p21.31 genes as genetic susceptibility loci in patients with severe COVID-19. The predictive model includes demographic characteristics, comorbidities and genetic factors is useful to identify individuals who are predisposed to develop subsequent critical conditions among COVID-19 patients.
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