Dataset Information

Association between viral infections and glioma risk: a two-sample bidirectional Mendelian randomization analysis.

ABSTRACT:

Background

Glioma is one of the leading types of brain tumor, but few etiologic factors of primary glioma have been identified. Previous observational research has shown an association between viral infection and glioma risk. In this study, we used Mendelian randomization (MR) analysis to explore the direction and magnitude of the causal relationship between viral infection and glioma.

Methods

We conducted a two-sample bidirectional MR analysis using genome-wide association study (GWAS) data. Summary statistics data of glioma were collected from the largest meta-analysis GWAS, involving 12,488 cases and 18,169 controls. Single-nucleotide polymorphisms (SNPs) associated with exposures were used as instrumental variables to estimate the causal relationship between glioma and twelve types of viral infections from corresponding GWAS data. In addition, sensitivity analyses were performed.

Results

After correcting for multiple tests and sensitivity analysis, we detected that genetically predicted herpes zoster (caused by Varicella zoster virus (VZV) infection) significantly decreased risk of low-grade glioma (LGG) development (OR = 0.85, 95% CI: 0.76-0.96, P = 0.01, FDR = 0.04). No causal effects of the other eleven viral infections on glioma and reverse causality were detected.

Conclusions

This is one of the first and largest studies in this field. We show robust evidence supporting that genetically predicted herpes zoster caused by VZV infection reduces risk of LGG. The findings of our research advance understanding of the etiology of glioma.

SUBMITTER: Zhong S

PROVIDER: S-EPMC10698979 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Association between viral infections and glioma risk: a two-sample bidirectional Mendelian randomization analysis.

Zhong Sheng S Yang Wenzhuo W Zhang Zhiyun Z Xie Yangyiran Y Pan Lin L Ren Jiaxin J Ren Fei F Li Yifan Y Xie Haoqun H Chen Hongyu H Deng Davy D Lu Jie J Li Hui H Wu Bo B Chen Youqi Y Peng Fei F Puduvalli Vinay K VK Sai Ke K Li Yunqian Y Cheng Ye Y Mou Yonggao Y

BMC medicine 20231205 1

<h4>Background</h4>Glioma is one of the leading types of brain tumor, but few etiologic factors of primary glioma have been identified. Previous observational research has shown an association between viral infection and glioma risk. In this study, we used Mendelian randomization (MR) analysis to explore the direction and magnitude of the causal relationship between viral infection and glioma.<h4>Methods</h4>We conducted a two-sample bidirectional MR analysis using genome-wide association study ...[more]

PMID: 38053181

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Project description:BackgroundPrevious observational studies have indicated a correlation between the gut microbiota and influenza; however, the exact nature of the bidirectional causal connection remains uncertain.MethodA two-way, two-sample Mendelian randomization (MR) study was conducted to evaluate the possible causal connection between the gut microbiota and the two outcomes of influenza (pneumonia without influenza and influenza pneumonia). The statistical analysis of gut microbiota is derived from the information of the most extensive meta-analysis (GWAS) conducted by the MiBioGen Alliance, encompassing a sample size of 18,340.The summary statistical data for influenza (not pneumonia, n = 291,090) and influenza pneumonia (n = 342,499) are from GWAS data published by FinnGen consortium R8.Estimate and summarize Single-nucleotide polymorphisms (SNPs) using Inverse variance weighted (IVW), MR Egger, and Weighted median (WM) in bidirectional MR analysis. To assess the heterogeneity, horizontal pleiotropy, and stability of SNPs, we employed Cochran's Q test, MR Egger intercept test, and sensitivity analysis.ResultThe IVW analysis indicated that there was a significant association between influenza infection and five bacterial taxa. Additionally, the abundance changes of seven gut microbiota were found to be causally related to influenza infection. In addition, seven bacterial taxa showed a significant association with the occurrence of influenza pneumonia. The findings from the WM analysis largely support the outcomes of IVW, however, the results of MR egger analysis do not align with IVW. Furthermore, there is no proof to substantiate the cause-and-effect relationship between influenza pneumonia and the composition of gut microbiota.ConclusionThis analysis demonstrates a possible bidirectional causal connection between the prevalence of particular gut microbiota and the occurrence of influenza infection. The presence of certain gut microbiota may potentially contribute to the development of pneumonia caused by influenza. Additional investigation into the interaction between particular bacterial communities and influenza can enhance efforts in preventing, monitoring, and treating influenza.

Project description:ObjectivesTo assess the association between thyroid dysfunction and diabetic retinopathy (DR), a two-sample bidirectional Mendelian randomization (MR) study utilizing the Genome-wide Association Study (GWAS) database was conducted to investigate the causal relationship between these two variables.MethodsIn this study, GWAS of 48,328,151 single nucleotide polymorphisms(SNP) in the European population from the IEU open GWAS database were utilized as genetic tools for investigating thyroid dysfunction. The total sample size for the study on hyperthyroidism was 460,499 (case group: 3557; control group: 456,942). The total sample size for hypothyroidism was 410,141 (case group: 30,155; control group: 37,986). In addition, the data on DR were extracted from the FinnGen Biobank, comprising a total sample size of 319,046 individuals (10,413 cases and 308,633 controls). For the forward MR analysis, hyperthyroidism and hypothyroidism were considered as exposures with DR as the outcome. Reverse MR analysis was conducted using DR as exposure and hyperthyroidism and hypothyroidism as outcomes.MethodsThe main analytical approach employed inverse variance weighting(IVW), supplemented by MR-Egger, Weighted mode method, weighted median, and Simple mode. Cochran's Q test, MR-PRESSO, MR-Egger and leave-one-out analysis were used to evaluate the sensitivity and pleiotropy.ResultsTwo-sample bidirectional MR analysis revealed a significant association between the presence of hyperthyroidism and hypothyroidism and an increased risk of DR in the forward MR analysis (IVW: OR = 1.29, 95% [CI] = 1.12-1.49, P < 0.001; OR = 1.17, 95% CI = 1.10-1.25, P < 0.001). In the reverse MR analysis, DR was found to be associated with an elevated risk of developing hyperthyroidism and hypothyroidism (IVW: OR = 1.56, 95% CI 1.38-1.76, P < 0.001; OR = 1.41, 95% CI 1.25-1.59, P < 0.001). Furthermore, most supplementary MR methods also demonstrated statistically significant differences and exhibited effect sizes consistent with those obtained from IVW. The sensitivity analysis confirmed the relative reliability of our causal findings.ConclusionsOur findings provide genetic evidence supporting a bidirectional causal relationship between thyroid function and DR.

Dataset Information

Association between viral infections and glioma risk: a two-sample bidirectional Mendelian randomization analysis.

Background

Methods

Results

Conclusions

Publications

Association between viral infections and glioma risk: a two-sample bidirectional Mendelian randomization analysis.

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