Menu
Currency
GWAS Study

Investigating the shared genetic architecture between COVID-19 and obesity: a large-scale genome wide cross-trait analysis.

Chen Y, Fan C, Liu J

38352709 PubMed ID
GWAS Study Type
2985505 Participants
39 Views
Scroll to explore
Chapter I

Publication Details

Comprehensive information about this research publication

Authors

CY
Chen Y
FC
Fan C
LJ
Liu J
Chapter II

Abstract

Summary of the research findings

Observational studies have reported high comorbidity between obesity and severe COVID-19. The aim of this study is to explore whether genetic factors are involved in the co-occurrence of the two traits. Based on the available genome-wide association studies (GWAS) summary statistics, we explored the genetic correlation and performed cross-trait meta-analysis (CPASSOC) and colocalization analysis (COLOC) to detect pleiotropic single nucleotide polymorphisms (SNPs). At the genetic level, we obtained genes detected by Functional mapping and annotation (FUMA) and the Multi-marker Analysis of GenoMic Annotation (MAGMA). Potential functional genes were further investigated by summary-data-based Mendelian randomization (SMR). Finally, the casualty was identiied using the latent causal variable model (LCV). A significant positive genetic correlation was revealed between obesity and COVID-19. We found 331 shared genetic SNPs by CPASSOC and 13 shared risk loci by COLOC. At the genetic level, We obtained 3546 pleiotropic genes, among which 107 genes were found to be significantly expressed by SMR. Lastly, we observed these genes were mainly enriched in immune pathways and signaling transduction. These indings could provide new insights into the etiology of comorbidity and have implications for future therapeutic trial.

387,649 European ancestry individuals with BMI measurements, 122,616 European ancestry COVID-19 cases, 2,475,240 controls

Chapter III

Study Statistics

Key metrics and study information

2985505
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
Chapter IV

AI-Generated Summary

AI-generated by DNAGENICS

Independent AI summary of health and genetic findings from the published study

Important: This summary is AI-generated by DNAGENICS for informational purposes only. It was not created by, affiliated with, or endorsed by the researchers behind the original publication, and is based solely on that published research. It may contain errors or omissions. DNAGENICS disclaims all liability for any inaccuracies or consequences arising from use of this information. Verify all information against the original publication. This is not professional scientific review or medical advice.

AI Summary In Progress

Our AI-generated summary of this publication is being prepared. Please check back soon.