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Activity Number: 300 - Addressing Statistical Challenges of the COVID-19 Crisis
Type: Invited
Date/Time: Wednesday, August 11, 2021 : 3:30 PM to 5:20 PM
Sponsor: ENAR
Abstract #316800
Title: Genetic Variants Are Identified to Increase Risk of COVID-19-Related Mortality from UK Biobank Data
Author(s): Cai Li* and Jianchang Hu and Shiying Wang and Ting Li and Heping Zhang
Companies: Yale University and Yale University and Yale University and Yale University and Yale University
Keywords: COVID-19; GWAS; Host genetic factors; Mortality; SARS-CoV2; UK Biobank
Abstract:

The severity of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly heterogenous. Studies have reported that males and some ethnic groups are at increased risk of death from COVID-19, which implies that individual risk of death might be influenced by host genetic factors. In this project, we consider the mortality as the trait of interest and perform a genome-wide association study (GWAS) of data for 1,778 infected cases distributed by the UK Biobank. To enhance the power of GWAS and account for possible multi-loci interactions, we adopt the concept of super-variant for the detection of genetic factors. Eight genetic variants are identified to significantly increase risk of COVID-19 mortality. The identified risk factors contain genetic variants and genes related to cilia dysfunctions, cardiovascular diseases, thromboembolic disease, mitochondrial dysfunctions, and innate immune system. It is noteworthy that gene DNAH7 has been reported recently as the most downregulated gene after infecting human bronchial epithelial cells with SARS-CoV2.


Authors who are presenting talks have a * after their name.

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