Ontology highlight
ABSTRACT: 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?-4) were observed between phenotypes and glioma under the IVW-RE model. Suggestive associations (1.58?×?10-4?SD?=?3.91, P?=?9.24?×?10-3) and GBM (ORSD?=?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 (ORSD?=?1.11, P?=?1.39?×?10-2 and ORSD?=?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.
SUBMITTER: Saunders CN
PROVIDER: S-EPMC7852872 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Saunders Charlie N CN Cornish Alex J AJ Kinnersley Ben B Law Philip J PJ Houlston Richard S RS
British journal of cancer 20201006 2
<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-weigh ...[more]