Vascular endothelial growth factor and risk of malignant brain tumor: A genetic correlation and two-sample Mendelian randomization study

Qiaoyun Zhang; Guangheng Wu; Xiaoyu Zhang; Jie Zhang; Mengyang Jiang; Yiqiang Zhang; Lixiang Ding; Youxin Wang

doi:10.3389/fonc.2023.991825

Vascular endothelial growth factor and risk of malignant brain tumor: A genetic correlation and two-sample Mendelian randomization study

Front Oncol. 2023 Feb 23:13:991825. doi: 10.3389/fonc.2023.991825. eCollection 2023.

Authors

Qiaoyun Zhang^{1

2}, Guangheng Wu¹, Xiaoyu Zhang^{1

2}, Jie Zhang¹, Mengyang Jiang², Yiqiang Zhang², Lixiang Ding³, Youxin Wang¹

Affiliations

¹ Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China.
² Department of Anesthesiology, Beijing Sanbo Brain Hospital, Capital Medical University, Beijing, China.
³ Department of Spine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.

Abstract

Objective: The relationship between vascular endothelial growth factor (VEGF) and the risk of malignant brain tumors has always been a concern in the medical field. However, the causal inferences from published observational studies on this issue may be affected by confounders, coinheritability and reverse causality. We aimed to investigate the causal relationship between VEGF and different types of malignant brain tumors.

Methods: Using publicly available summary data from genome-wide association studies (GWAS) of VEGF (n=16,112) and different types of malignant brain tumors (n=174,097-174,646), we adopted a standard two-sample bidirectional Mendelian randomization (MR) to estimate potential causal associations of circulating VEGF levels and the risk of malignant brain tumors. Inverse variance weighted (IVW) was used as the primary analysis method to estimate causality. MR-Egger regression, weighted median (WM), penalty weighted median (PWM), MR robust adjusted profile score (MR.RAPS) and causal analysis using summary effect estimates (CAUSE) methods were used in sensitivity analyses to verify the robustness of the findings. Meanwhile, we applied the MR pleiotropy residual sum and outlier (MR-PRESSO) test and PhenoScanner tool to identify and remove potential horizontal pleiotropic single nucleotide polymorphisms (SNPs). Additionally, linkage disequilibrium score regression (LDSC) analysis was conducted to assess the coinheritability of exposure and outcome.

Results: A total of 6 (VEGF), 12 (malignant brain tumor), 13 (brain glioblastoma) and 12 (malignant neoplasm of meninges) SNPs were identified as valid instrumental variables. No evidence supported a causal relationship between circulating VEGF levels and the risk of malignant brain tumors (forwards: odds ratio (OR) = 1.277, 95% confidence interval (CI), 0.812~2.009; reversed: β = 0.005, 95% CI, -0.029~0.038), brain glioblastoma (forwards: OR (95% CI) = 1.278(0.463~3.528); reversed: β = 0.010, 95% CI, -0.002~0.022) and malignant neoplasm of meninges (forwards: OR (95% CI) = 0.831(0.486~1.421); reversed: β = 0.010, 95% CI, -0.030~0.050) using the main IVW method. Outliers and pleiotropy bias were not detected by sensitivity analyses and pleiotropy-robust methods in any estimates. LDSC failed to identify genetic correlations between VEGF and different types of malignant brain tumors.

Conclusions: Our findings reported no coinheritability and failed to provide evidence for causal associations between VEGF and the risk of different types of malignant brain tumors. However, certain subtypes of VEGF for which genetic predictors have not been identified may play a role and need to be further investigated.

Keywords: Mendelian randomization; causal inference; genetic correlation; malignant brain tumor; vascular endothelial growth factor.

Grants and funding

This work was supported by the National Key R&D Program of China (2018YFC2000704). The funder had no role in the design and conduct of the study, the collection and analysis of the data, or the writing and submission of the manuscript.