Department of Forensic Medicine, First College for Clinical Medicine, Xuzhou Medical University, 84 West Huaihai Rd, Xuzhou, Jiangsu, 221000, China.
Jiangsu Medical Engineering Research Center of Gene Detection, Xuzhou, Jiangsu, China.
BMC Cancer. 2024 Sep 9;24(1):1119. doi: 10.1186/s12885-024-12901-7.
Glioblastoma multiforme (GBM) is a highly aggressive primary malignant brain tumor characterized by rapid progression, poor prognosis, and high mortality rates. Understanding the relationship between cerebrospinal fluid (CSF) metabolites and GBM is crucial for identifying potential biomarkers and pathways involved in the pathogenesis of this devastating disease.
In this study, Mendelian randomization (MR) analysis was employed to investigate the causal relationship between 338 CSF metabolites and GBM. The data for metabolites were obtained from a genome-wide association study summary dataset based on 291 individuals, and the GBM data was derived from FinnGen included 91 cases and 174,006 controls of European descent. The Inverse Variance Weighted method was utilized to estimate the causal effects. Supplementary comprehensive assessments of causal effects between CSF metabolites and GBM were conducted using MR-Egger regression, Weighted Median, Simple Mode, and Weighted Mode methods. Additionally, tests for heterogeneity and pleiotropy were performed.
Through MR analysis, a total of 12 identified metabolites and 2 with unknown chemical properties were found to have a causal relationship with GBM. 1-palmitoyl-2-stearoyl-gpc (16:0/18:0), 7-alpha-hydroxy-3-oxo-4-cholestenoate, Alpha-tocopherol, Behenoyl sphingomyelin (d18:1/22:0), Cysteinylglycine, Maleate, Uracil, Valine, X-12,101, X-12,104 and Butyrate (4:0) are associated with an increased risk of GBM. N1-methylinosine, Stachydrine and Succinylcarnitine (c4-dc) are associated with decreased GBM risk.
In conclusion, this study sheds light on the intricate interplay between CSF metabolites and GBM, offering novel perspectives on disease mechanisms and potential treatment avenues. By elucidating the role of CSF metabolites in GBM pathogenesis, this research contributes to the advancement of diagnostic capabilities and targeted therapeutic interventions for this aggressive brain tumor. Further exploration of these findings may lead to improved management strategies and better outcomes for patients with GBM.
多形性胶质母细胞瘤（GBM）是一种高度侵袭性的原发性恶性脑肿瘤，其特征为快速进展、预后不良和高死亡率。了解脑脊液（CSF）代谢物与 GBM 之间的关系对于鉴定潜在的生物标志物和参与这种毁灭性疾病发病机制的途径至关重要。
在这项研究中，我们采用孟德尔随机化（MR）分析来研究 338 种 CSF 代谢物与 GBM 之间的因果关系。代谢物的数据来自基于 291 个人的全基因组关联研究汇总数据集，而 GBM 数据源自包含 91 例病例和 174006 例欧洲裔对照的芬兰遗传（FinnGen）研究。我们采用逆方差加权法来估计因果效应。此外，我们还使用 MR-Egger 回归、加权中位数、简单模式和加权模式方法对 CSF 代谢物与 GBM 之间的因果关系进行了综合评估。同时，还进行了异质性和多效性检验。
通过 MR 分析，我们共鉴定出 12 种具有因果关系的代谢物和 2 种代谢物具有未知化学性质与 GBM 相关。1-棕榈酰-2-硬脂酰基-gpc（16:0/18:0）、7α-羟基-3-氧代-4-胆甾烯酸、α-生育酚、二十二烷酰基神经鞘氨醇（d18:1/22:0）、半胱氨酰甘氨酸、马来酸、尿嘧啶、缬氨酸、X-12,101、X-12,104 和丁酸盐（4:0）与 GBM 风险增加相关。N1-甲基肌苷、水苏碱和琥珀酰肉碱（c4-dc）与 GBM 风险降低相关。
总之，本研究揭示了 CSF 代谢物与 GBM 之间复杂的相互作用，为疾病机制和潜在治疗途径提供了新的视角。通过阐明 CSF 代谢物在 GBM 发病机制中的作用，本研究为这种侵袭性脑肿瘤的诊断能力和靶向治疗干预提供了新的思路。进一步探索这些发现可能会为胶质母细胞瘤患者带来更好的管理策略和更好的预后。
