TY - JOUR
T1 - Searching for causal relationships of glioma
T2 - a phenome-wide Mendelian randomisation study
AU - Collaborators
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.
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2021/1/19
Y1 - 2021/1/19
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.
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U2 - 10.1038/s41416-020-01083-1
DO - 10.1038/s41416-020-01083-1
M3 - Article
C2 - 33020596
AN - SCOPUS:85092192018
SN - 0007-0920
VL - 124
SP - 447
EP - 454
JO - British journal of cancer
JF - British journal of cancer
IS - 2
ER -