| Title: | Estimating the correlation of various genetic and non-genetic factors with severity and outcome of COVID-19. |
| Lead Institution: | Beijing Institute of Genomics |
| Principal investigator: | Professor Fan Liu |
Application 67076
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About
Estimating the correlation of various genetic and non-genetic factors with severity and outcome of COVID-19. The aim of this project is to 1. Systematically evaluate the genetic and non-genetic factors affecting COVID-19. 2. Develop methods to detect gene-environment interactions in large samples. 3. Build a gene-environment interaction network to help analyze the occurrence and development of COVID-19. 4. Enhance disease risk prediction ability and improve the health management system, which is in line with the purpose of UK Biobank. Diseases are the result of the interaction between the genetics and environment. If we only estimate the individual contribution of genes or environment to disease, and ignore the interaction between them, then we will incorrectly estimate the proportion of diseases explained by genes, environment and their combined effects. In the context of medical genetics and epidemiology, the study of the interaction between genes and the environment is of great significance, especially in the severe situation of the global epidemic of COVID-19. Understanding the interaction between genes and the environment may allow us to provide personalized preventive advice before a disease is diagnosed, and personalized treatment after diagnosing. Unlike the research that only focuses on genetic or environmental effects, the study of genetic and environmental interaction requires a larger sample size. Therefore, research on the interaction between genetics and environment needs to improve the ability to discover associations. There are many models that describe the degree of risk combined with genetic and environmental factors.Such as including case study only, empirical Bayes, Bayesian model average, joint test, case parent method and two-step method, etc.Thankfully, UK Biobank provides a perfect opportunity because of its large data sets and standardized phenotype measuring process.The optimal study design depends on the interaction that is being examined. Our research can firstly establish a method for detecting gene-environment interactions based on large samples. We can systematically assess the influencing factors of COVID-19 and provide help in analyzing the mechanism of COVID-19. Finally, our research can enhance disease risk prediction ability and improve health management systems. The duration for this proposed project is 15 months.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 10927 | Genome-wide epistasis study highlights genetic interactions influencing severity of COVID-19 | Shiqi Lin (+16) | 2023 | European Journal of Epidemiology |
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