全基因组关联研究
遗传建筑学
特质
生物
遗传关联
连锁不平衡
数量性状位点
遗传变异
遗传学
遗传分析
基因
计算生物学
单核苷酸多态性
基因型
计算机科学
程序设计语言
作者
Xianqiang Liu,Dingchang Li,Wenxing Gao,Hao Liu,Peng Chen,Yingjie Zhao,Wen Zhao,Guanglong Dong
标识
DOI:10.3389/fimmu.2024.1442693
摘要
Background It has been reported that COVID-19 patients have an increased risk of developing IBS; however, the underlying genetic mechanisms of these associations remain largely unknown. The aim of this study was to investigate potential shared SNPs, genes, proteins, and biological pathways between COVID-19 and IBS by assessing pairwise genetic correlations and cross-trait genetic analysis. Materials and methods We assessed the genetic correlation between three COVID-19 phenotypes and IBS using linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL) methods. Two different sources of IBS data were combined using METAL, and the Multi-trait analysis of GWAS (MTAG) method was applied for multi-trait analysis to enhance statistical robustness and discover new genetic associations. Independent risk loci were examined using genome-wide complex trait analysis (GCTA)-conditional and joint analysis (COJO), multi-marker analysis of genomic annotation (MAGMA), and functional mapping and annotation (FUMA), integrating various QTL information and methods to further identify risk genes and proteins. Gene set variation analysis (GSVA) was employed to compute pleiotropic gene scores, and combined with immune infiltration algorithms, IBS patients were categorized into high and low immune infiltration groups. Results We found a positive genetic correlation between COVID-19 infection, COVID-19 hospitalization, and IBS. Subsequent multi-trait analysis identified nine significantly associated genomic loci. Among these, eight genetic variants were closely related to the comorbidity of IBS and COVID-19. The study also highlighted four genes and 231 proteins associated with the susceptibility to IBS identified through various analytical strategies and a stratification approach for IBS risk populations. Conclusions Our study reveals a shared genetic architecture between these two diseases, providing new insights into potential biological mechanisms and laying the groundwork for more effective interventions.
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