Causal effects of the gut microbiome on COVID-19 susceptibility and severity: a two-sample Mendelian randomization study

• Published in: Frontiers in immunology Vol. 14; p. 1173974
• Main Authors: Zhong, Meng-Mei, Xie, Jia-Hao, Feng, Yao, Zhang, Shao-Hui, Xia, Jiang-Nan, Tan, Li, Chen, Ning-Xin, Su, Xiao-Lin, Zhang, Qian, Feng, Yun-Zhi, Guo, Yue
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 01.09.2023
• Subjects: COVID-19; gut microbiome; Immunology; Mendelian randomization; severity; susceptibility
• ISSN: 1664-3224; 1664-3224
• DOI: 10.3389/fimmu.2023.1173974

The coronavirus disease 2019 (COVID-19) caused a global pandemic, with potential severity. We aimed to investigate whether genetically predicted gut microbiome is associated with susceptibility and severity of COVID-19 risk.BackgroundThe coronavirus disease 2019 (COVID-19) caused a global pandemic, with potential severity. We aimed to investigate whether genetically predicted gut microbiome is associated with susceptibility and severity of COVID-19 risk.Mendelian randomization (MR) analysis of two sets with different significance thresholds was carried out to infer the causal relationship between the gut microbiome and COVID-19. SNPs associated with the composition of the gut microbiome (n = 5,717,754) and with COVID-19 susceptibility (n = 14,328,058), COVID-19 severity (n = 11,707,239), and COVID-19 hospitalization (n = 12,018,444) from publicly available genome-wide association studies (GWAS). The random-effect inverse variance weighted (IVW) method was used to determine causality. Three more MR techniques-MR Egger, weighted median, and weighted mode-and a thorough sensitivity analysis were also used to confirm the findings.MethodsMendelian randomization (MR) analysis of two sets with different significance thresholds was carried out to infer the causal relationship between the gut microbiome and COVID-19. SNPs associated with the composition of the gut microbiome (n = 5,717,754) and with COVID-19 susceptibility (n = 14,328,058), COVID-19 severity (n = 11,707,239), and COVID-19 hospitalization (n = 12,018,444) from publicly available genome-wide association studies (GWAS). The random-effect inverse variance weighted (IVW) method was used to determine causality. Three more MR techniques-MR Egger, weighted median, and weighted mode-and a thorough sensitivity analysis were also used to confirm the findings.IVW showed that 18 known microbial taxa were causally associated with COVID-19. Among them, six microbial taxa were causally associated with COVID-19 susceptibility; seven microbial taxa were causally associated with COVID-19 severity ; five microbial taxa were causally associated with COVID-19 hospitalization. Sensitivity analyses showed no evidence of pleiotropy or heterogeneity. Then, the predicted 37 species of the gut microbiome deserve further study.ResultsIVW showed that 18 known microbial taxa were causally associated with COVID-19. Among them, six microbial taxa were causally associated with COVID-19 susceptibility; seven microbial taxa were causally associated with COVID-19 severity ; five microbial taxa were causally associated with COVID-19 hospitalization. Sensitivity analyses showed no evidence of pleiotropy or heterogeneity. Then, the predicted 37 species of the gut microbiome deserve further study.This study found that some microbial taxa were protective factors or risky factors for COVID-19, which may provide helpful biomarkers for asymptomatic diagnosis and potential therapeutic targets for COVID-19.ConclusionThis study found that some microbial taxa were protective factors or risky factors for COVID-19, which may provide helpful biomarkers for asymptomatic diagnosis and potential therapeutic targets for COVID-19.