Complex causal relationships between genetic predictions of 731 immune cell phenotypes and novel coronavirus: A two-sample Mendelian randomization analysis

731种免疫细胞表型的遗传预测与新型冠状病毒之间复杂的因果关系:一项双样本孟德尔随机化分析

阅读:1

Abstract

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a significant impact on global health. While the virus primarily affects the respiratory system, the intricate interplay between immune cells and the virus remains poorly understood. This study investigates the causal relationship between 731 immune cell phenotypes and COVID-19 using Mendelian randomization (MR) analysis. METHODS: A bidirectional two-sample MR analysis was conducted using genetic variants strongly associated with immune cell phenotypes as instrumental variables. Data for 731 immune cell phenotypes were sourced from the Genome-Wide Association Study (GWAS) catalog, while data for COVID-19 susceptibility were obtained from the OPEN GWAS database. Five MR methods (inverse variance weighted [IVW], MR-Egger, weighted median, simple mode, and weighted mode) were used to estimate causal effects, with IVW as the primary analysis method. RESULTS: The study identified 57 immune cell phenotypes causally associated with COVID-19 risk across two independent GWAS datasets. Five immune cell phenotypes were consistently associated with COVID-19 risk across both datasets: CD3- lymphocyte %lymphocyte (protective), CD27 on CD20- (protective), CD20 on IgD+ CD38- unsw mem (increased risk), CD27 on IgD- CD38- (increased risk), and CD19 on B cell (increased risk). Sensitivity analyses confirmed the robustness of the findings. CONCLUSION: This study provides compelling evidence for a causal relationship between specific immune cell phenotypes and COVID-19 risk. These findings highlight the potential for targeting these immune cell phenotypes as novel therapeutic targets for COVID-19 treatment and prevention.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。