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循环代谢标志物与胶质瘤之间的因果关系:一项双向、双样本、贝叶斯加权孟德尔随机化研究

Causal effect between circulating metabolic markers and glioma: a bidirectional, two-sample, Bayesian weighted Mendelian randomization.

作者信息

Wang Jiachen, Wang Chengzhuo, Li Shenglan, Huang Mengqian, Zhang Rong, Chen Yuxiao, Kang Zhuang, Li Wenbin

机构信息

Department of Neuro-Oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical University, No.119, West Nan Si Huan Road, Fengtai District, Beijing, 100071, China.

Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100071, China.

出版信息

Discov Oncol. 2025 Mar 14;16(1):315. doi: 10.1007/s12672-025-02050-z.

Abstract

Glioma is the most common malignant tumor in the central nervous system with significant challenges for its treatment and prognosis. Based on publicly available genome-wide association study data, this study employed a bidirectional, two-sample Mendelian randomization (MR) analysis, combined with Bayesian weighted MR, to investigate the causal effect of 233 circulating metabolic traits on glioma and its subtypes, with the expectation of discovering new diagnostic and therapeutic targets. The MR study revealed that the Total cholesterol to total lipids ratio in large VLDL and the Ratio of polyunsaturated fatty acids to total fatty acids (PUFAbyFA) are risk factors for glioma, while free cholesterol or phospholipids in small HDL are protective against glioma. The free cholesterol to total lipids ratio in IDL, the ratios of total cholesterol or cholesteryl esters to total lipids in small or medium VLDL, as well as linoleic acid (LA 18:2), phosphatidylcholine, and sphingomyelins levels are risk factors for non-GBM glioma. Free cholesterol in small HDL is identified as a protective factor for non-GBM glioma. The results were robust to sensitivity analyses and Bayesian weighted mendelian randomization. The causal effects of glioma on circulating metabolites were explored through reverse mendelian randomization. The results provide potential biomarkers for the early diagnosis and treatment of glioma.

摘要

胶质瘤是中枢神经系统中最常见的恶性肿瘤,其治疗和预后面临重大挑战。基于公开的全基因组关联研究数据,本研究采用双向两样本孟德尔随机化(MR)分析,并结合贝叶斯加权MR,以研究233种循环代谢特征对胶质瘤及其亚型的因果效应,期望发现新的诊断和治疗靶点。MR研究表明,大极低密度脂蛋白(VLDL)中的总胆固醇与总脂质之比以及多不饱和脂肪酸与总脂肪酸之比(PUFAbyFA)是胶质瘤的危险因素,而小高密度脂蛋白(HDL)中的游离胆固醇或磷脂对胶质瘤具有保护作用。中间密度脂蛋白(IDL)中的游离胆固醇与总脂质之比、小或中极低密度脂蛋白中的总胆固醇或胆固醇酯与总脂质之比,以及亚油酸(LA 18:2)、磷脂酰胆碱和鞘磷脂水平是非胶质母细胞瘤(GBM)的危险因素。小HDL中的游离胆固醇被确定为非GBM胶质瘤的保护因素。结果在敏感性分析和贝叶斯加权孟德尔随机化中具有稳健性。通过反向孟德尔随机化探索了胶质瘤对循环代谢物的因果效应。这些结果为胶质瘤的早期诊断和治疗提供了潜在的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b99c/11909308/282e91892880/12672_2025_2050_Fig1_HTML.jpg

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