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Exploring genetic loci linked to COVID-19 severity and immune response through multi-trait GWAS analyses.

Authors :
Meng, Ziang
Zhang, Chumeng
Liu, Shuai
Li, Wen
Wang, Yue
Zhang, Qingyi
Peng, Bichen
Ye, Weiyi
Jiang, Yue
Song, Yingchao
Guo, Miao
Chang, Xiao
Shao, Lei
Source :
Frontiers in Genetics; 2025, p1-11, 11p
Publication Year :
2025

Abstract

Introduction: COVID-19 severity has been linked to immune factors, with excessive immune responses like cytokine storms contributing to mortality. However, the genetic basis of these immune responses is not well understood. This study aimed to explore the genetic connection between COVID-19 severity and blood cell traits, given their close relationship with immunity. Materials and methods: GWAS summary statistics for COVID-19 and blood cell counts were analyzed using Linkage Disequilibrium Score Regression (LDSC) to estimate genetic correlations and heritabilities. For traits with significant correlations, a Multi-Trait GWAS Analysis (MTAG) was performed to identify pleiotropic loci shared between COVID-19 and blood cell counts. Results: Our MTAG analysis identified four pleiotropic loci associated with COVID-19 severity, five loci linked to hospitalized cases, and one locus related to general patients. Among these, two novel loci were identified in the high-risk population, with rs55779981 located near RAVER1 and rs73009538 near CARM1. In hospitalized patients, two previously unrecognized loci were detected, namely, rs115545251 near GFI1 and rs3181049 near RAVER1 , while in general patients, rs11065822 near CUX2 emerged as a newly identified locus. We also identified potential target genes, including those involved in inflammation signaling (CARM1), endothelial dysfunction (INTS12), and antiviral immune response (RAVER1), which may require further investigation. Conclusion: Our study offers insights into the genetic overlap between COVID-19 and immune factors, suggesting potential directions for future research and clinical exploration. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16648021
Database :
Complementary Index
Journal :
Frontiers in Genetics
Publication Type :
Academic Journal
Accession number :
183410677
Full Text :
https://doi.org/10.3389/fgene.2025.1502839