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探讨 COVID-19 和肥胖之间的共享遗传结构:一项大规模的全基因组跨性状分析。

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

机构信息

Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, Hunan, China.

Clinical Research Center for Medical Imaging in Hunan Province, Changsha, Hunan, China.

出版信息

Front Endocrinol (Lausanne). 2024 Jan 30;15:1325939. doi: 10.3389/fendo.2024.1325939. eCollection 2024.

DOI:10.3389/fendo.2024.1325939
PMID:38352709
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10862482/
Abstract

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.

摘要

观察性研究报告称肥胖症和严重 COVID-19 之间存在高度共病性。本研究旨在探讨遗传因素是否参与了这两种特征的共同发生。基于现有的全基因组关联研究(GWAS)汇总统计数据,我们探索了遗传相关性,并进行了跨性状荟萃分析(CPASSOC)和共定位分析(COLOC),以检测多效性单核苷酸多态性(SNP)。在遗传水平上,我们使用功能映射和注释(FUMA)和基因组注释的多标记分析(MAGMA)检测到基因。通过基于汇总数据的孟德尔随机化(SMR)进一步研究潜在的功能基因。最后,使用潜在因果变量模型(LCV)识别因果关系。肥胖症和 COVID-19 之间存在显著的正遗传相关性。通过 CPASSOC 我们发现了 331 个共享的遗传 SNP,通过 COLOC 发现了 13 个共享的风险位点。在遗传水平上,我们获得了 3546 个多效性基因,其中 SMR 发现 107 个基因表达显著。最后,我们观察到这些基因主要富集在免疫途径和信号转导中。这些发现为共病的病因学提供了新的见解,并对未来的治疗试验具有启示意义。

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