Searching for causal relationships of glioma: a phenome-wide Mendelian randomisation study

Collaborators, Christoffer Johansen (Member of study group)

13 Citations (Scopus)

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 < 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 (ORSD = 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.

Original languageEnglish
JournalBritish Journal of Cancer
Volume124
Issue number2
Pages (from-to)447-454
Number of pages8
ISSN0007-0920
DOIs
Publication statusPublished - 19 Jan 2021

Keywords

  • Brain Neoplasms/genetics
  • Genetic Variation
  • Genome-Wide Association Study
  • Glioma/genetics
  • Humans
  • Mendelian Randomization Analysis
  • Risk Factors

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