TY - JOUR

T1 - Searching for causal relationships of glioma

T2 - a phenome-wide Mendelian randomisation study

AU - Saunders, Charlie N.

AU - Cornish, Alex J.

AU - Kinnersley, Ben

AU - Law, Philip J.

AU - Houlston, Richard S.

AU - Claus, Elizabeth B.

AU - Il’yasova, Dora

AU - Schildkraut, Joellen

AU - Barnholtz-Sloan, Jill S.

AU - Olson, Sara H.

AU - Bernstein, Jonine L.

AU - Lai, Rose K.

AU - Chanock, Stephen

AU - Rajaraman, Preetha

AU - Johansen, Christoffer

AU - Jenkins, Robert B.

AU - Melin, Beatrice S.

AU - Wrensch, Margaret R.

AU - Sanson, Marc

AU - Bondy, Melissa L.

AU - Collaborators

N1 - Publisher Copyright: © 2020, The Author(s).

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

U2 - 10.1038/s41416-020-01083-1

DO - 10.1038/s41416-020-01083-1

M3 - Journal article

C2 - 33020596

AN - SCOPUS:85092192018

VL - 124

SP - 447

EP - 454

JO - The British journal of cancer. Supplement

JF - The British journal of cancer. Supplement

SN - 0007-0920

IS - 2

ER -