UKB.COVID19: an R package for UK Biobank COVID-19 data processing and analysis

Area of Science:

• Genomics
• Epidemiology
• Bioinformatics

Background:

• The COVID-19 pandemic necessitates rapid analysis of large-scale health data.
• The UK Biobank (UKBB) provides a valuable resource for studying disease risk factors, including genetic and environmental influences.
• Frequent updates of COVID-19, death, and hospital data in UKBB require efficient analytical tools.

Purpose of the Study:

• To develop an R package for analyzing UK Biobank COVID-19 data.
• To identify risk factors associated with COVID-19 susceptibility, severity, and mortality.
• To generate input files for genome-wide association studies (GWAS) and replicate genetic findings.

Main Methods:

• Development of a specialized R package for UKBB COVID-19 data processing.
• Association testing for risk factors (age, sex, blood type, comorbidities) and COVID-19 outcomes.
• Genome-wide association studies (GWAS) to identify genetic risk loci.

Main Results:

• Age, body mass index, socioeconomic status, and smoking are positively associated with COVID-19 susceptibility, severity, and mortality.
• Males exhibit a higher risk of COVID-19 infection compared to females.
• Replication of the 3p21.31 genetic association with COVID-19 susceptibility and severity.

Conclusions:

• The R package enables rapid analysis of frequently updated UKBB COVID-19 data.
• Identified risk factors provide insights into COVID-19 pathogenesis and prevention strategies.
• The study underscores the importance of genetic and environmental factors in COVID-19 outcomes.