Background: The aetiology of glioma is poorly understood. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to search for glioma risk factors. Methods: We performed an MR-PheWAS analysing 316 phenotypes, proxied by 8387 genetic variants, and summary genetic data from a GWAS of 12,488 glioma cases and 18,169 controls. Causal effects were estimated under a random-effects inverse-variance-weighted (IVW-RE) model, with robust adjusted profile score (MR-RAPS), weighted median and mode-based estimates computed to assess the robustness of findings. Odds ratios per one standard deviation increase in each phenotype were calculated for all glioma, glioblastoma (GBM) and non-GBM tumours. Results: No significant associations (P < 1.58 × 10⁻⁴) were observed between phenotypes and glioma under the IVW-RE model. Suggestive associations (1.58 × 10⁻⁴ < P < 0.05) were observed between leukocyte telomere length (LTL) with all glioma (OR_SD = 3.91, P = 9.24 × 10⁻³) and GBM (OR_SD = 4.86, P = 3.23 × 10⁻²), but the association was primarily driven by the TERT variant rs2736100. Serum low-density lipoprotein cholesterol and plasma HbA1C showed suggestive associations with glioma (OR_SD = 1.11, P = 1.39 × 10⁻² and OR_SD = 1.28, P = 1.73 × 10⁻², respectively), both associations being reliant on single genetic variants. Conclusions: Our study provides further insight into the aetiological basis of glioma for which published data have been mixed.