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Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study
BACKGROUND: Whilst epidemiological studies have provided evidence of associations between certain risk factors and glioma onset, inferring causality has proven challenging. Using Mendelian randomization (MR), we assessed whether associations of 36 reported glioma risk factors showed evidence of a ca...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268455/ https://www.ncbi.nlm.nih.gov/pubmed/32493226 http://dx.doi.org/10.1186/s12885-020-06967-2 |
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author | Howell, A. E. Robinson, J. W. Wootton, R. E. McAleenan, A. Tsavachidis, S. Ostrom, Q. T. Bondy, M. Armstrong, G. Relton, C. Haycock, P. Martin, R. M. Zheng, J. Kurian, K. M. |
author_facet | Howell, A. E. Robinson, J. W. Wootton, R. E. McAleenan, A. Tsavachidis, S. Ostrom, Q. T. Bondy, M. Armstrong, G. Relton, C. Haycock, P. Martin, R. M. Zheng, J. Kurian, K. M. |
author_sort | Howell, A. E. |
collection | PubMed |
description | BACKGROUND: Whilst epidemiological studies have provided evidence of associations between certain risk factors and glioma onset, inferring causality has proven challenging. Using Mendelian randomization (MR), we assessed whether associations of 36 reported glioma risk factors showed evidence of a causal relationship. METHODS: We performed a systematic search of MEDLINE from inception to October 2018 to identify candidate risk factors and conducted a meta-analysis of two glioma genome-wide association studies (5739 cases and 5501 controls) to form our exposure and outcome datasets. MR analyses were performed using genetic variants to proxy for candidate risk factors. We investigated whether risk factors differed by subtype diagnosis (either glioblastoma (n = 3112) or non-glioblastoma (n = 2411)). MR estimates for each risk factor were determined using multiplicative random effects inverse-variance weighting (IVW). Sensitivity analyses investigated potential pleiotropy using MR-Egger regression, the weighted median estimator, and the mode-based estimator. To increase power, trait-specific polygenic risk scores were used to test the association of a genetically predicated increase in each risk factor with glioma onset. RESULTS: Our systematic search identified 36 risk factors that could be proxied using genetic variants. Using MR, we found evidence that four genetically predicted traits increased risk of glioma, glioblastoma or non-glioblastoma: longer leukocyte telomere length, liability to allergic disease, increased alcohol consumption and liability to childhood extreme obesity (> 3 standard deviations from the mean). Two traits decreased risk of non-glioblastoma cancers: increased low-density lipoprotein cholesterol (LDLc) and triglyceride levels. Our findings were similar across sensitivity analyses that made allowance for pleiotropy (genetic confounding). CONCLUSIONS: Our comprehensive investigation provides evidence of a causal link between both genetically predicted leukocyte telomere length, allergic disease, alcohol consumption, childhood extreme obesity, and LDLc and triglyceride levels, and glioma. The findings from our study warrant further research to uncover mechanisms that implicate these traits in glioma onset. |
format | Online Article Text |
id | pubmed-7268455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72684552020-06-07 Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study Howell, A. E. Robinson, J. W. Wootton, R. E. McAleenan, A. Tsavachidis, S. Ostrom, Q. T. Bondy, M. Armstrong, G. Relton, C. Haycock, P. Martin, R. M. Zheng, J. Kurian, K. M. BMC Cancer Research Article BACKGROUND: Whilst epidemiological studies have provided evidence of associations between certain risk factors and glioma onset, inferring causality has proven challenging. Using Mendelian randomization (MR), we assessed whether associations of 36 reported glioma risk factors showed evidence of a causal relationship. METHODS: We performed a systematic search of MEDLINE from inception to October 2018 to identify candidate risk factors and conducted a meta-analysis of two glioma genome-wide association studies (5739 cases and 5501 controls) to form our exposure and outcome datasets. MR analyses were performed using genetic variants to proxy for candidate risk factors. We investigated whether risk factors differed by subtype diagnosis (either glioblastoma (n = 3112) or non-glioblastoma (n = 2411)). MR estimates for each risk factor were determined using multiplicative random effects inverse-variance weighting (IVW). Sensitivity analyses investigated potential pleiotropy using MR-Egger regression, the weighted median estimator, and the mode-based estimator. To increase power, trait-specific polygenic risk scores were used to test the association of a genetically predicated increase in each risk factor with glioma onset. RESULTS: Our systematic search identified 36 risk factors that could be proxied using genetic variants. Using MR, we found evidence that four genetically predicted traits increased risk of glioma, glioblastoma or non-glioblastoma: longer leukocyte telomere length, liability to allergic disease, increased alcohol consumption and liability to childhood extreme obesity (> 3 standard deviations from the mean). Two traits decreased risk of non-glioblastoma cancers: increased low-density lipoprotein cholesterol (LDLc) and triglyceride levels. Our findings were similar across sensitivity analyses that made allowance for pleiotropy (genetic confounding). CONCLUSIONS: Our comprehensive investigation provides evidence of a causal link between both genetically predicted leukocyte telomere length, allergic disease, alcohol consumption, childhood extreme obesity, and LDLc and triglyceride levels, and glioma. The findings from our study warrant further research to uncover mechanisms that implicate these traits in glioma onset. BioMed Central 2020-06-03 /pmc/articles/PMC7268455/ /pubmed/32493226 http://dx.doi.org/10.1186/s12885-020-06967-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Howell, A. E. Robinson, J. W. Wootton, R. E. McAleenan, A. Tsavachidis, S. Ostrom, Q. T. Bondy, M. Armstrong, G. Relton, C. Haycock, P. Martin, R. M. Zheng, J. Kurian, K. M. Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study |
title | Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study |
title_full | Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study |
title_fullStr | Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study |
title_full_unstemmed | Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study |
title_short | Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study |
title_sort | testing for causality between systematically identified risk factors and glioma: a mendelian randomization study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268455/ https://www.ncbi.nlm.nih.gov/pubmed/32493226 http://dx.doi.org/10.1186/s12885-020-06967-2 |
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