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A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women
Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for Cancer Research
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9604427/ https://www.ncbi.nlm.nih.gov/pubmed/36303815 http://dx.doi.org/10.1158/2767-9764.CRC-21-0119 |
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author | Wang, Xiaoliang Chen, Hongjie Kapoor, Pooja Middha Su, Yu-Ru Bolla, Manjeet K. Dennis, Joe Dunning, Alison M. Lush, Michael Wang, Qin Michailidou, Kyriaki Pharoah, Paul D.P. Hopper, John L. Southey, Melissa C. Koutros, Stella Freeman, Laura E. Beane Stone, Jennifer Rennert, Gad Shibli, Rana Murphy, Rachel A. Aronson, Kristan Guénel, Pascal Truong, Thérèse Teras, Lauren R. Hodge, James M. Canzian, Federico Kaaks, Rudolf Brenner, Hermann Arndt, Volker Hoppe, Reiner Lo, Wing-Yee Behrens, Sabine Mannermaa, Arto Kosma, Veli-Matti Jung, Audrey Becher, Heiko Giles, Graham G. Haiman, Christopher A. Maskarinec, Gertraud Scott, Christopher Winham, Stacey Simard, Jacques Goldberg, Mark S. Zheng, Wei Long, Jirong Troester, Melissa A. Love, Michael I. Peng, Cheng Tamimi, Rulla Eliassen, Heather García-Closas, Montserrat Figueroa, Jonine Ahearn, Thomas Yang, Rose Evans, D. Gareth Howell, Anthony Hall, Per Czene, Kamila Wolk, Alicja Sandler, Dale P. Taylor, Jack A. Swerdlow, Anthony J. Orr, Nick Lacey, James V. Wang, Sophia Olsson, Håkan Easton, Douglas F. Milne, Roger L. Hsu, Li Kraft, Peter Chang-Claude, Jenny Lindström, Sara |
author_facet | Wang, Xiaoliang Chen, Hongjie Kapoor, Pooja Middha Su, Yu-Ru Bolla, Manjeet K. Dennis, Joe Dunning, Alison M. Lush, Michael Wang, Qin Michailidou, Kyriaki Pharoah, Paul D.P. Hopper, John L. Southey, Melissa C. Koutros, Stella Freeman, Laura E. Beane Stone, Jennifer Rennert, Gad Shibli, Rana Murphy, Rachel A. Aronson, Kristan Guénel, Pascal Truong, Thérèse Teras, Lauren R. Hodge, James M. Canzian, Federico Kaaks, Rudolf Brenner, Hermann Arndt, Volker Hoppe, Reiner Lo, Wing-Yee Behrens, Sabine Mannermaa, Arto Kosma, Veli-Matti Jung, Audrey Becher, Heiko Giles, Graham G. Haiman, Christopher A. Maskarinec, Gertraud Scott, Christopher Winham, Stacey Simard, Jacques Goldberg, Mark S. Zheng, Wei Long, Jirong Troester, Melissa A. Love, Michael I. Peng, Cheng Tamimi, Rulla Eliassen, Heather García-Closas, Montserrat Figueroa, Jonine Ahearn, Thomas Yang, Rose Evans, D. Gareth Howell, Anthony Hall, Per Czene, Kamila Wolk, Alicja Sandler, Dale P. Taylor, Jack A. Swerdlow, Anthony J. Orr, Nick Lacey, James V. Wang, Sophia Olsson, Håkan Easton, Douglas F. Milne, Roger L. Hsu, Li Kraft, Peter Chang-Claude, Jenny Lindström, Sara |
author_sort | Wang, Xiaoliang |
collection | PubMed |
description | Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (P(GXE) = 4.44 × 10(−6)). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk. |
format | Online Article Text |
id | pubmed-9604427 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for Cancer Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-96044272022-10-26 A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women Wang, Xiaoliang Chen, Hongjie Kapoor, Pooja Middha Su, Yu-Ru Bolla, Manjeet K. Dennis, Joe Dunning, Alison M. Lush, Michael Wang, Qin Michailidou, Kyriaki Pharoah, Paul D.P. Hopper, John L. Southey, Melissa C. Koutros, Stella Freeman, Laura E. Beane Stone, Jennifer Rennert, Gad Shibli, Rana Murphy, Rachel A. Aronson, Kristan Guénel, Pascal Truong, Thérèse Teras, Lauren R. Hodge, James M. Canzian, Federico Kaaks, Rudolf Brenner, Hermann Arndt, Volker Hoppe, Reiner Lo, Wing-Yee Behrens, Sabine Mannermaa, Arto Kosma, Veli-Matti Jung, Audrey Becher, Heiko Giles, Graham G. Haiman, Christopher A. Maskarinec, Gertraud Scott, Christopher Winham, Stacey Simard, Jacques Goldberg, Mark S. Zheng, Wei Long, Jirong Troester, Melissa A. Love, Michael I. Peng, Cheng Tamimi, Rulla Eliassen, Heather García-Closas, Montserrat Figueroa, Jonine Ahearn, Thomas Yang, Rose Evans, D. Gareth Howell, Anthony Hall, Per Czene, Kamila Wolk, Alicja Sandler, Dale P. Taylor, Jack A. Swerdlow, Anthony J. Orr, Nick Lacey, James V. Wang, Sophia Olsson, Håkan Easton, Douglas F. Milne, Roger L. Hsu, Li Kraft, Peter Chang-Claude, Jenny Lindström, Sara Cancer Res Commun Research Article Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (P(GXE) = 4.44 × 10(−6)). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk. American Association for Cancer Research 2022-04-08 /pmc/articles/PMC9604427/ /pubmed/36303815 http://dx.doi.org/10.1158/2767-9764.CRC-21-0119 Text en © 2022 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by/4.0/This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. |
spellingShingle | Research Article Wang, Xiaoliang Chen, Hongjie Kapoor, Pooja Middha Su, Yu-Ru Bolla, Manjeet K. Dennis, Joe Dunning, Alison M. Lush, Michael Wang, Qin Michailidou, Kyriaki Pharoah, Paul D.P. Hopper, John L. Southey, Melissa C. Koutros, Stella Freeman, Laura E. Beane Stone, Jennifer Rennert, Gad Shibli, Rana Murphy, Rachel A. Aronson, Kristan Guénel, Pascal Truong, Thérèse Teras, Lauren R. Hodge, James M. Canzian, Federico Kaaks, Rudolf Brenner, Hermann Arndt, Volker Hoppe, Reiner Lo, Wing-Yee Behrens, Sabine Mannermaa, Arto Kosma, Veli-Matti Jung, Audrey Becher, Heiko Giles, Graham G. Haiman, Christopher A. Maskarinec, Gertraud Scott, Christopher Winham, Stacey Simard, Jacques Goldberg, Mark S. Zheng, Wei Long, Jirong Troester, Melissa A. Love, Michael I. Peng, Cheng Tamimi, Rulla Eliassen, Heather García-Closas, Montserrat Figueroa, Jonine Ahearn, Thomas Yang, Rose Evans, D. Gareth Howell, Anthony Hall, Per Czene, Kamila Wolk, Alicja Sandler, Dale P. Taylor, Jack A. Swerdlow, Anthony J. Orr, Nick Lacey, James V. Wang, Sophia Olsson, Håkan Easton, Douglas F. Milne, Roger L. Hsu, Li Kraft, Peter Chang-Claude, Jenny Lindström, Sara A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women |
title | A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women |
title_full | A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women |
title_fullStr | A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women |
title_full_unstemmed | A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women |
title_short | A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women |
title_sort | genome-wide gene-based gene–environment interaction study of breast cancer in more than 90,000 women |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9604427/ https://www.ncbi.nlm.nih.gov/pubmed/36303815 http://dx.doi.org/10.1158/2767-9764.CRC-21-0119 |
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