Brain and behavior · 2023
Association between COVID-19 and myasthenia gravis (MG): A genetic correlation and Mendelian randomization study.
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Sun Dongren, Tu Liangdan, Wang Xiaofei, Du Qin, Wang Rui, Shi Ziyan, Chen Hongxi, Zhou Hongyu
Аннотация
BACKGROUND: Observational studies have suggested an association between coronavirus disease 2019 (COVID-19) and myasthenia gravis (MG). Here, we aimed to estimate the genetic correlation and causal relationship between COVID-19 susceptibility, hospitalization, severity, and MG phenotypes using linkage disequilibrium score regression (LDSC) and Mendelian randomization (MR) approach.
METHODS: Summary statistics of COVID-19 susceptibility, hospitalization, and severity were used as instrumental variables for exposure traits. Large-scale genome-wide association study (GWAS) data for MG were used as outcome traits. The inverse variance weighted approach was used for the main MR analysis, complemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analysis was implemented using Cochran's Q test, MR-PRESSO method, and MR-Egger intercept test.
RESULTS: LDSC analysis did not reveal any genetic correlation among COVID-19 susceptibility, hospitalization, severity, and MG phenotypes, including MG, early-onset MG, and late-onset MG (p > .05). Our MR analysis did not provide evidence supporting a causal effect of COVID-19 susceptibility, hospitalization, or severity on MG phenotypes (p > .05). Extensive sensitivity analysis strengthened the robustness and consistency of the MR estimates.
CONCLUSION: Our study did not find evidence of a genetic correlation or causal relationship among COVID-19 susceptibility, hospitalization, severity, and MG. Future studies with more GWAS data are needed to evaluate the association between COVID-19 phenotypes and MG and its subgroups.
METHODS: Summary statistics of COVID-19 susceptibility, hospitalization, and severity were used as instrumental variables for exposure traits. Large-scale genome-wide association study (GWAS) data for MG were used as outcome traits. The inverse variance weighted approach was used for the main MR analysis, complemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analysis was implemented using Cochran's Q test, MR-PRESSO method, and MR-Egger intercept test.
RESULTS: LDSC analysis did not reveal any genetic correlation among COVID-19 susceptibility, hospitalization, severity, and MG phenotypes, including MG, early-onset MG, and late-onset MG (p > .05). Our MR analysis did not provide evidence supporting a causal effect of COVID-19 susceptibility, hospitalization, or severity on MG phenotypes (p > .05). Extensive sensitivity analysis strengthened the robustness and consistency of the MR estimates.
CONCLUSION: Our study did not find evidence of a genetic correlation or causal relationship among COVID-19 susceptibility, hospitalization, severity, and MG. Future studies with more GWAS data are needed to evaluate the association between COVID-19 phenotypes and MG and its subgroups.