背景: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,其特征是进展迅速,预后不良,和高死亡率。了解脑脊液(CSF)代谢产物与GBM之间的关系对于确定这种破坏性疾病的发病机理中涉及的潜在生物标志物和途径至关重要。
方法:在本研究中,采用孟德尔随机化(MR)分析研究了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个个体的全基因组关联研究汇总数据集,GBM数据来自FinnGen,包括91例病例和174,006例欧洲血统对照。利用逆方差加权法估计因果效应。使用MR-Egger回归对CSF代谢物和GBM之间的因果效应进行补充综合评估,加权中位数,简单模式,和加权模式方法。此外,进行了异质性和多效性测试。
结果:通过MR分析,共发现12种已鉴定的代谢物和2种化学性质未知的代谢物与GBM有因果关系.1-棕榈酰基-2-硬脂酰基-gpc(16:0/18:0),7-α-羟基-3-氧代-4-胆烯酸酯,α-生育酚,Beenoyl鞘磷脂(d18:1/22:0),半胱氨酰甘氨酸,马来酸盐,Uracil,缬氨酸,X-12,101、X-12,104和丁酸酯(4:0)与GBM的风险增加相关。N1-甲基肌苷,水苏碱和琥珀酰肉碱(c4-dc)与降低GBM风险相关。
结论:结论:这项研究揭示了脑脊液代谢物和GBM之间复杂的相互作用,提供关于疾病机制和潜在治疗途径的新观点。通过阐明CSF代谢物在GBM发病机制中的作用,这项研究有助于提高这种侵袭性脑肿瘤的诊断能力和有针对性的治疗干预措施.对这些发现的进一步探索可能会改善GBM患者的管理策略和更好的预后。
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.