The causal relationship between CSF metabolites and GBM: a two-sample mendelian randomization analysis

Abstract

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.