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Background <p>The cerebrospinal fluid (CSF) metabolites could potentially direct reflecting the biochemical processes involved in central nervous system metabolism. This study aims to delineate the potential causal relationships between CSF metabolites and Glioblastoma (GBM) using Mendelian Randomization (MR) analysis.</p> Methods <p>This research employs a two-sample MR framework, utilizing genetic instrumental variables derived from GWAS datasets corresponding to CSF and plasma metabolites, and GBM. Data from separate samples for the exposure and outcome were analyzed using specialized R packages designed for two-sample MR and Bayesian weighted MR analyses.</p> Results <p>Significant causal relationships were identified between GBM and several CSF metabolites through two-sample MR analysis mainly using the IVW method. Notably, associations were observed with 3-methoxytyramine sulfate (OR 1.039, 95% CI 1.010 to 1.070, p-value 0.009), caffeine (OR 1.132, 95% CI 1.021 to 1.255, p-value 0.018), dimethyl sulfone (OR 1.087, 95% CI 1.002 to 1.178, p-value 0.043), fructose (OR 0.985, 95% CI 0.969 to 0.998, p-value 0.049), and phenol sulfate (OR 1.074, 95% CI 1.020 to 1.131, p-value 0.007). An inverse causal relationship was also observed between CSF fructose levels (as exposure) and GBM (OR 0.255, 95% CI 0.089 to 0.725, p-value = 0.010), suggesting protective effects. These findings were substantiated through Bayesian MR analysis.</p> Conclusion <p>The study highlights significant links between specific CSF metabolites and GBM, suggesting that these metabolites may influence tumor biology and could serve as potential biomarkers for GBM diagnosis and progression.</p>

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Elucidating the causal relationships between cerebrospinal fluid metabolites and glioblastoma insights from mendelian randomization study

  • 期刊论文

  • 发表日期：

    2026年2月7日

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  • Chengrui Yan,
  • Bin Wang,
  • Guangchao Shi,
  • Wenbin Ma,
  • Kai Li

摘要

Background

The cerebrospinal fluid (CSF) metabolites could potentially direct reflecting the biochemical processes involved in central nervous system metabolism. This study aims to delineate the potential causal relationships between CSF metabolites and Glioblastoma (GBM) using Mendelian Randomization (MR) analysis.

Methods

This research employs a two-sample MR framework, utilizing genetic instrumental variables derived from GWAS datasets corresponding to CSF and plasma metabolites, and GBM. Data from separate samples for the exposure and outcome were analyzed using specialized R packages designed for two-sample MR and Bayesian weighted MR analyses.

Results

Significant causal relationships were identified between GBM and several CSF metabolites through two-sample MR analysis mainly using the IVW method. Notably, associations were observed with 3-methoxytyramine sulfate (OR 1.039, 95% CI 1.010 to 1.070, p-value 0.009), caffeine (OR 1.132, 95% CI 1.021 to 1.255, p-value 0.018), dimethyl sulfone (OR 1.087, 95% CI 1.002 to 1.178, p-value 0.043), fructose (OR 0.985, 95% CI 0.969 to 0.998, p-value 0.049), and phenol sulfate (OR 1.074, 95% CI 1.020 to 1.131, p-value 0.007). An inverse causal relationship was also observed between CSF fructose levels (as exposure) and GBM (OR 0.255, 95% CI 0.089 to 0.725, p-value = 0.010), suggesting protective effects. These findings were substantiated through Bayesian MR analysis.

Conclusion

The study highlights significant links between specific CSF metabolites and GBM, suggesting that these metabolites may influence tumor biology and could serve as potential biomarkers for GBM diagnosis and progression.