How Gut Bacteria and Blood Chemicals May Influence Risk of Meningioma Brain Tumors

Meningioma is one of the most prevalent intracranial neoplasms, accounting for 40%–56% of primary central nervous system tumors, mostly affecting women aged 50–70 years (Degeneffe et al. 2023; CBTRUS 2024). The WHO categorization indicates that 80%–81% of meningiomas are benign (Grade I), 17%–18% are atypical (Grade II), and roughly 1.7% are malignant (Grade III) (Yarabarla et al. 2023). Grades II–III meningiomas have elevated recurrence rates, increased invasiveness, and worse prognosis (Sescu et al. 2023). Benign tumors may need surgical excision if situated in functionally essential regions or if they are of considerable size, which poses hazards including brain harm. Prevalent symptoms include headache (32.3%–50%), neurological impairments (e.g., hemiplegia, sensory abnormalities, aphasia, affecting around 17.3%), and visual or cranial nerve damage (13%–42.5%). Meningiomas located at the skull base or superior orbital fissure are more prone to impact cranial nerves (Mederer et al. 2022). Exploring the etiology of meningioma is essential for identifying therapeutic targets.

The exact etiology of meningioma remains unclear but may involve multiple factors. Recognized high‐risk factors include exposure to ionizing radiation, especially head and neck radiotherapy during childhood (Banerjee et al. 2009). Hormonal aspects are crucial; over 70% of meningiomas exhibit progesterone receptors (PR), with some also displaying estrogen receptors. The prolonged use of certain progestin medicines further elevates the risk (Roland et al. 2024; Wiemels et al. 2010). Inflammation and immunological responses contribute to the formation and pathological progression of meningioma. This is evidenced by irregularities in pro‐inflammatory metabolic pathways, including heightened arachidonic acid concentrations and enhanced activity of its enzymes COX and lipoxygenase, resulting in the production of tumor‐promoting eicosanoids and the infiltration of immune cells such as tumor‐associated macrophages (Nathoo et al. 2004; Roland et al. 2024). Metabolic disorders, including altered plasma levels of choline, indole, tryptophan, and lipids, together with family history and genetic diseases such as neurofibromatosis type 2, are related to the formation of meningiomas (Goutagny et al. 2012; Kökoğlu et al. 1998).

The brain, gastrointestinal system, and microbiome interact via the gut–brain axis to affect neurological health and disorders (Morais et al. 2021). The gut microbiota is involved not only in nutrient absorption but also in systemic regulation of immunity, inflammation, and metabolism (Staby et al. 2017). The gut microbiota composition in individuals with brain tumors, including meningioma, differs from that of healthy individuals, indicating that bacteria may promote brain tumor growth via immunological and inflammatory mechanisms (Jiang et al. 2022; Mehrian‐Shai et al. 2019). We posited a possible correlation between gut microbiota and meningioma risk and evaluated this notion by Mendelian randomization (MR) analysis. MR used genetic variations as instrumental factors to deduce causation in evaluating this hypothesis. This research seeks to investigate the pathogenic causes and possible treatment modalities for meningioma via the perspective of the gut–brain axis. A two‐step MR analysis was performed: first, to assess the causal relationships between the abundance of 473 fecal gut microbial taxa and 1,400 serum metabolites with meningioma; second, to examine the causal associations between gut microbiota and serum metabolites; and finally, to evaluate the mediating effects of serum metabolites in the relationship between gut microbiota and meningioma.

This research, using two‐sample MR analysis, revealed 19 gut microbial species that are causally linked to the risk of meningioma. Among them, ten taxa—including CAG‐873 sp001701165 from the order Bacteroidales, Enterobacteriaceae, Fusobacterium A from the family Fusobacteriaceae, Bifidobacterium, Enterococcus, Eubacterium F sp000434115, and CAG‐1000 from the order Bacteroidales—were linked to an increased risk of meningioma. The tumor‐promoting effects of these gut microbes on meningioma may involve mechanisms including the activation of inflammatory signaling pathways (e.g., TLR4/NF‐κB pathway), the release of pro‐inflammatory cytokines (IL‐6, TNF‐α), dysregulation of polyunsaturated fatty acid metabolism (notably the accumulation of arachidonic acid), and the reprogramming of the immune microenvironment.

CAG‐873 sp001701165 is a gut microbe belonging to the order Bacteroidales, whose members possess complex metabolic networks capable of regulating host fatty acid metabolism (Park et al. 2022; H. Zhang et al. 2024). The expression of proteins associated with fatty acid metabolism is significantly linked to meningioma grading and prognosis, and aberrant expression of these proteins may enhance tumor cell proliferation and survival (Shibuya 2015). Arachidonic acid, an ω‐6 polyunsaturated fatty acid, may be processed via the cyclooxygenase‐2 (COX‐2) route to generate prostaglandin E2 (PGE2), which facilitates tumor angiogenesis and immunological regulation (Cui et al. 2017; Jin et al. 2023). This study found a significant association between CAG‐873 sp001701165 and elevated Arachidonate (20:4n6) levels, with part of the tumor‐promoting mechanism mediated by Arachidonate (20:4n6) (mediation effect accounted for 8.41%, p = 0.027), suggesting that this microbe may participate in fatty acid metabolism and regulation through multiple pathways. Additionally, the cell walls of Bacteroidales bacteria typically contain components such as lipopolysaccharides (LPS), some of which exhibit pro‐inflammatory effects. The pro‐inflammatory activity of the LPS from CAG‐873 sp001701165 remains ambiguous; however, drawing from mechanisms observed in similar taxa, it may activate the Toll‐like Receptor 4 (TLR4)/NF‐κB pathway, thereby facilitating the release of pro‐inflammatory cytokines (e.g., IL‐6, TNF‐α) (Chen et al. 2023), which could amplify inflammatory signaling cascades associated with meningioma. Likewise, Fusobacterium A, a member of the Fusobacteriaceae family, may affect meningioma risk via the modulation of inflammation. Enterobacteriaceae may induce chronic intestinal mucosal inflammation and the production of reactive oxygen species (ROS), leading to increased genomic instability. (Jiang et al. 2024; Zhou et al. 2024). Consequently, Enterobacteriaceae may affect meningioma risk through similar mechanisms.

Conversely, nine microbial taxa—including Propionibacterium freudenreichii from the genus Propionibacterium, CAG‐170 sp003516765 and CAG‐177 from the genus Ruminococcus, UBA2658 sp002841545 from the phylum Firmicutes, Lachnospirales from the order Clostridiales, Holdemania sp900120005, and Parabacteroides sp000436495 from the genus Parabacteroides—were associated with a decreased risk of meningioma. The protective effects of these microbes may involve mechanisms such as short‐chain fatty acid (SCFA)‐mediated inhibition of histone deacetylases (HDAC), enhanced differentiation of regulatory T cells (Tregs), antioxidative stress, and modulation of secondary bile acid metabolism. Specifically, Propionibacterium freudenreichii, a member of the Propionibacterium genus, exhibits antitumor properties that are likely related to its secretion of SCFAs, such as propionate. SCFAs can inhibit HDAC activity, upregulate tumor suppressor genes (e.g., p21), and promote Treg differentiation, thereby suppressing tumor immune evasion (Luu et al. 2021; Ryu et al. 2022).

This study further identified 34 serum metabolites significantly associated with meningioma risk. Among them, Arachidonate (20:4n6) showed a potential causal relationship with meningioma (OR = 1.192, 95% CI: 1.048–1.355, p = 0.007). Arachidonic acid and its metabolites are known to regulate multiple mammalian processes, including inflammation, aging, ion channel function, and neuropsychiatric disorders (Chopra et al. 2012). Arachidonic acid is closely linked to various inflammatory mechanisms; as a precursor of prostaglandins, Arachidonic acid can be metabolized via the COX‐2 pathway to produce PGE2. PGE2 promotes tumor cell proliferation, angiogenesis, and the formation of an immunosuppressive microenvironment by activating EP2/EP4 receptors (Jin et al. 2023). Overexpression of COX‐2 and elevated PGE2 levels in meningioma tissues have been confirmed to correlate with poor prognosis (Aung et al. 2024; Kulesza et al. 2023), suggesting that this pathway may represent a therapeutic target. A MR research indicated that heightened levels of TNF‐β and CXCL1, together with diminished levels of IL‐9, correlate with an increased risk of meningioma (Z. Zhang et al. 2023). Arachidonic acid can amplify inflammatory responses and modulate other inflammatory mediators (Gorica and Calderone 2022; Regulska et al. 2021; Z. Zhang et al. 2023). Thus, the association between arachidonic acid and meningioma is closely related to inflammation regulation.

Levels of 16α‐hydroxy DHEA 3‐sulfate, 2,6‐dihydroxybenzoic acid, 2‐hydroxyglutarate, 4‐hydroxychlorothalonil, methylsuccinate, methylsuccinoylcarnitine, along with X‐11795, X‐11850, X‐12600, X‐23654, and tartronate (hydroxymalonate) are correlated with an elevated risk of meningioma. 2‐hydroxyglutarate, functioning as an oncometabolite, can competitively inhibit α‐ketoglutarate‐dependent dioxygenases such as TET2 and JMJD3, leading to genome‐wide DNA hypermethylation and stabilization of hypoxia‐inducible factor‐1α (HIF‐1α), thereby mimicking the “metabolic reprogramming” phenotype seen in gliomas (Kadiyala et al. 2021; Reiter‐Brennan et al. 2018; Tong et al. 2024). Furthermore, 2‐hydroxyglutarate may exacerbate oxidative stress and promote the accumulation of genomic mutations by disrupting the tricarboxylic acid (TCA) cycle and mitochondrial electron transport chain.

Conversely, serum metabolites—1‐(1‐enyl‐palmitoyl)‐GPE, 1‐stearoyl‐GPE, the arginine to ornithine ratio, plasma lactate levels, pregnenediol sulfate levels, and levels of X‐11308, X‐12484, X‐13507, and X‐21742—correlate with a reduced risk of meningioma. These metabolites may affect the incidence and advancement of meningioma by altering inflammatory responses, the immunological microenvironment, or hormone‐dependent mechanisms. 1‐stearoyl‐GPE may inhibit pro‐inflammatory signaling by altering membrane phospholipid metabolism; plasma lactate levels might reflect reduced glycolytic activity in the tumor microenvironment, correlated with benign tumor morphologies. Moreover, pregnenediol sulfate may impede the phosphorylation of PR via feedback mechanisms, hence hindering tumor proliferation associated with the MAPK/ERK pathway, consistent with the hormone‐dependent nature of meningiomas.

Our research demonstrated that CAG‐873 sp001701165 influences meningioma risk via the upregulation of Arachidonate (20:4n6) levels (mediation effect p = 0.027), indicating that gut microbiota might remotely modulate the central tumor microenvironment by altering metabolite levels. Previous research has shown that circulating PGE2 may disrupt blood‐brain barrier integrity, infiltrate meningioma tissue, and activate the STAT3 pathway to drive tumor stem cell self‐renewal (H. Q. Wang et al. 2022). These results support the “microbiota–gut–brain axis” paradigm, which posits that chemicals originating from gut microbiota affect central tumors via systemic inflammation and neuroendocrine mechanisms. This research first evaluates the causal relationship between fecal gut microbiota abundance, blood metabolites, and the risk of meningioma by MR analysis. However, the GWAS data used are mostly from North American and European populations, so further validation is needed for better generalizability to other populations. While larger sample sizes can boost MR analysis accuracy, obtaining large—scale datasets is challenging in practice. As MR analysis depends on genetic instruments to infer causality, additional research is required to enhance the reliability of the results. From the brain—gut axis perspective, the study explores arachidonate (20:4n6)'s mediating role between gut bacterium CAG ‐ 873 sp001701165 and meningioma. The remaining associated signals also deserve more exploration. Future studies should dissect the brain—gut axis metabolic regulatory network and employ multi—omics or complementary analytical approaches to elucidate its role in meningioma pathogenesis.

This study has several limitations. In this study, MR‐Egger and MR‐PRESSO were employed to assess horizontal pleiotropy; however, both methods rely on the InSIDE (Instrument Strength Independent of Direct Effect) assumption, which requires that the strength of the instruments for the exposure be independent of their direct effects on the outcome. This assumption cannot be empirically verified and may be violated due to factors such as pathway enrichment, LD, or the use of a relatively relaxed instrument selection threshold (p < 1 × 10⁻⁵), potentially leading to bias. Considering the complex, multi‐pathway biological characteristics of gut microbiota and metabolites, we interpret our findings with caution and recommend that future studies confirm these results using multi‐ancestry replication, stronger IVs, more robust MR approaches, and complementary experimental validation. Moreover, because the genetic architecture, allele frequencies, and LD patterns of gut microbiota and metabolites differ across populations—which may affect instrument strength and direction—the generalizability of our results is mainly limited to individuals of European ancestry. Future studies should therefore perform cross‐population validation and homogeneity tests to further strengthen the robustness of causal inferences.

This study rigorously assessed the causal relationships among gut microbiota, blood metabolites, and meningioma by MR analysis. MR mitigated the influence of confounding variables prevalent in conventional observational research, hence increasing the credibility of the results. Mediation analysis was used to elucidate the mediating function of serum metabolites in the gut microbiota‐meningioma relationship. This study offers novel insights into the pathophysiology and possible therapeutic targets of meningioma via the lens of the brain–gut axis. However, the intricate interactions between gut microbiota, serum metabolites, and meningioma need more exploration.

The project was managed by X.G., J.Z., and W.Z. Statistical analyses were conducted by J.Z., K.W., and X.G. Data extraction and literature review were performed by M.H. Figures and visualizations were created by X.Z. Methodological framework and sensitivity analyses were contributed by K.W. Manuscript drafting and writing were undertaken by X.G. and Y.Y. The study was supervised and critically revised by X.Z., Q.Z., and W.Z., who also served as the corresponding authors. The final manuscript was reviewed and approved by all authors.

The authors have nothing to report.

This research used publicly accessible summary‐level GWAS data. The first investigations obtained ethical clearance and informed permission from subjects. This secondary analysis does not need further ethical clearance.

The authors declare no conflicts of interests.