Searching for causal relationships of glioma: a phenome-wide Mendelian randomisation study.
MetadataShow full item record
<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>No significant associations (P < 1.58 × 10<sup>-4</sup>) were observed between phenotypes and glioma under the IVW-RE model. Suggestive associations (1.58 × 10<sup>-4</sup> < P < 0.05) were observed between leukocyte telomere length (LTL) with all glioma (OR<sub>SD</sub> = 3.91, P = 9.24 × 10<sup>-3</sup>) and GBM (OR<sub>SD</sub> = 4.86, P = 3.23 × 10<sup>-2</sup>), 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<sub>SD</sub> = 1.11, P = 1.39 × 10<sup>-2</sup> and OR<sub>SD</sub> = 1.28, P = 1.73 × 10<sup>-2</sup>, respectively), both associations being reliant on single genetic variants.<h4>Conclusions</h4>Our study provides further insight into the aetiological basis of glioma for which published data have been mixed.
Version of record
License start date
British journal of cancer, 2021, 124 (2), pp. 447 - 454