Pooja Middha, Xiaoliang Wang, Sabine Behrens, Manjeet K Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J Aronson, Paul L Auer, Annelie Augustinsson, Thaïs Baert, Laura E Beane Freeman, Heiko Becher, Matthias W Beckmann, Javier Benitez, Stig E Bojesen, Hiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Daniele Campa, Federico Canzian, Angel Carracedo, Jose E Castelao, Stephen J Chanock, Georgia Chenevix-Trench, Emilie Cordina-Duverger, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Laure Dossus, Pierre-Antoine Dugué, A Heather Eliassen, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Jonine D Figueroa, Olivia Fletcher, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Graham G Giles, Anna González-Neira, Felix Grassmann, Anne Grundy, Pascal Guénel, Christopher A Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Susan E Hankinson, Elaine F Harkness, Bernd Holleczek, Reiner Hoppe, John L Hopper, Richard S Houlston, Anthony Howell, David J Hunter, Christian Ingvar, Karolin Isaksson, Helena Jernström, Esther M John, Michael E Jones, Rudolf Kaaks, Renske Keeman, Cari M Kitahara, Yon-Dschun Ko, Stella Koutros, Allison W Kurian, James V Lacey, Diether Lambrechts, Nicole L Larson, Susanna Larsson, Loic Le Marchand, Flavio Lejbkowicz, Shuai Li, Martha Linet, Jolanta Lissowska, Maria Elena Martinez, Tabea Maurer, Anna Marie Mulligan, Claire Mulot, Rachel A Murphy, William G Newman, Sune F Nielsen, Børge G Nordestgaard, Aaron Norman, Katie M O'Brien, Janet E Olson, Alpa V Patel, Ross Prentice, Erika Rees-Punia, Gad Rennert, Valerie Rhenius, Kathryn J Ruddy, Dale P Sandler, Christopher G Scott, Mitul Shah, Xiao-Ou Shu, Ann Smeets, Melissa C Southey, Jennifer Stone, Rulla M Tamimi, Jack A Taylor, Lauren R Teras, Katarzyna Tomczyk, Melissa A Troester, Thérèse Truong, Celine M Vachon, Sophia S Wang, Clarice R Weinberg, Hans Wildiers, Walter Willett, Stacey J Winham, Alicja Wolk, Xiaohong R Yang, M Pilar Zamora, Wei Zheng, Argyrios Ziogas, Alison M Dunning, Paul D P Pharoah, Montserrat García-Closas, Marjanka K Schmidt, Peter Kraft, Roger L Milne, Sara Lindström, Douglas F Easton, Jenny Chang-Claude
{"title":"欧洲血统女性乳腺癌风险的全基因组基因-环境相互作用研究。","authors":"Pooja Middha, Xiaoliang Wang, Sabine Behrens, Manjeet K Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J Aronson, Paul L Auer, Annelie Augustinsson, Thaïs Baert, Laura E Beane Freeman, Heiko Becher, Matthias W Beckmann, Javier Benitez, Stig E Bojesen, Hiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Daniele Campa, Federico Canzian, Angel Carracedo, Jose E Castelao, Stephen J Chanock, Georgia Chenevix-Trench, Emilie Cordina-Duverger, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Laure Dossus, Pierre-Antoine Dugué, A Heather Eliassen, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Jonine D Figueroa, Olivia Fletcher, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Graham G Giles, Anna González-Neira, Felix Grassmann, Anne Grundy, Pascal Guénel, Christopher A Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Susan E Hankinson, Elaine F Harkness, Bernd Holleczek, Reiner Hoppe, John L Hopper, Richard S Houlston, Anthony Howell, David J Hunter, Christian Ingvar, Karolin Isaksson, Helena Jernström, Esther M John, Michael E Jones, Rudolf Kaaks, Renske Keeman, Cari M Kitahara, Yon-Dschun Ko, Stella Koutros, Allison W Kurian, James V Lacey, Diether Lambrechts, Nicole L Larson, Susanna Larsson, Loic Le Marchand, Flavio Lejbkowicz, Shuai Li, Martha Linet, Jolanta Lissowska, Maria Elena Martinez, Tabea Maurer, Anna Marie Mulligan, Claire Mulot, Rachel A Murphy, William G Newman, Sune F Nielsen, Børge G Nordestgaard, Aaron Norman, Katie M O'Brien, Janet E Olson, Alpa V Patel, Ross Prentice, Erika Rees-Punia, Gad Rennert, Valerie Rhenius, Kathryn J Ruddy, Dale P Sandler, Christopher G Scott, Mitul Shah, Xiao-Ou Shu, Ann Smeets, Melissa C Southey, Jennifer Stone, Rulla M Tamimi, Jack A Taylor, Lauren R Teras, Katarzyna Tomczyk, Melissa A Troester, Thérèse Truong, Celine M Vachon, Sophia S Wang, Clarice R Weinberg, Hans Wildiers, Walter Willett, Stacey J Winham, Alicja Wolk, Xiaohong R Yang, M Pilar Zamora, Wei Zheng, Argyrios Ziogas, Alison M Dunning, Paul D P Pharoah, Montserrat García-Closas, Marjanka K Schmidt, Peter Kraft, Roger L Milne, Sara Lindström, Douglas F Easton, Jenny Chang-Claude","doi":"10.1186/s13058-023-01691-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.</p><p><strong>Methods: </strong>Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.</p><p><strong>Results: </strong>Assuming a 1 × 10<sup>-5</sup> prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (OR<sub>int</sub> = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (OR<sub>int</sub> = 0.91, 95% CI 0.88-0.94).</p><p><strong>Conclusions: </strong>Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.</p>","PeriodicalId":9283,"journal":{"name":"Breast Cancer Research : BCR","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10411002/pdf/","citationCount":"0","resultStr":"{\"title\":\"A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry.\",\"authors\":\"Pooja Middha, Xiaoliang Wang, Sabine Behrens, Manjeet K Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J Aronson, Paul L Auer, Annelie Augustinsson, Thaïs Baert, Laura E Beane Freeman, Heiko Becher, Matthias W Beckmann, Javier Benitez, Stig E Bojesen, Hiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Daniele Campa, Federico Canzian, Angel Carracedo, Jose E Castelao, Stephen J Chanock, Georgia Chenevix-Trench, Emilie Cordina-Duverger, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Laure Dossus, Pierre-Antoine Dugué, A Heather Eliassen, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Jonine D Figueroa, Olivia Fletcher, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Graham G Giles, Anna González-Neira, Felix Grassmann, Anne Grundy, Pascal Guénel, Christopher A Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Susan E Hankinson, Elaine F Harkness, Bernd Holleczek, Reiner Hoppe, John L Hopper, Richard S Houlston, Anthony Howell, David J Hunter, Christian Ingvar, Karolin Isaksson, Helena Jernström, Esther M John, Michael E Jones, Rudolf Kaaks, Renske Keeman, Cari M Kitahara, Yon-Dschun Ko, Stella Koutros, Allison W Kurian, James V Lacey, Diether Lambrechts, Nicole L Larson, Susanna Larsson, Loic Le Marchand, Flavio Lejbkowicz, Shuai Li, Martha Linet, Jolanta Lissowska, Maria Elena Martinez, Tabea Maurer, Anna Marie Mulligan, Claire Mulot, Rachel A Murphy, William G Newman, Sune F Nielsen, Børge G Nordestgaard, Aaron Norman, Katie M O'Brien, Janet E Olson, Alpa V Patel, Ross Prentice, Erika Rees-Punia, Gad Rennert, Valerie Rhenius, Kathryn J Ruddy, Dale P Sandler, Christopher G Scott, Mitul Shah, Xiao-Ou Shu, Ann Smeets, Melissa C Southey, Jennifer Stone, Rulla M Tamimi, Jack A Taylor, Lauren R Teras, Katarzyna Tomczyk, Melissa A Troester, Thérèse Truong, Celine M Vachon, Sophia S Wang, Clarice R Weinberg, Hans Wildiers, Walter Willett, Stacey J Winham, Alicja Wolk, Xiaohong R Yang, M Pilar Zamora, Wei Zheng, Argyrios Ziogas, Alison M Dunning, Paul D P Pharoah, Montserrat García-Closas, Marjanka K Schmidt, Peter Kraft, Roger L Milne, Sara Lindström, Douglas F Easton, Jenny Chang-Claude\",\"doi\":\"10.1186/s13058-023-01691-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.</p><p><strong>Methods: </strong>Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.</p><p><strong>Results: </strong>Assuming a 1 × 10<sup>-5</sup> prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (OR<sub>int</sub> = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (OR<sub>int</sub> = 0.91, 95% CI 0.88-0.94).</p><p><strong>Conclusions: </strong>Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. 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引用次数: 0
摘要
背景:基因-环境相互作用的全基因组研究(G×E)可能会发现与生活方式/环境暴露相关的疾病风险变异。我们进行了一项全基因组G×E分析，分析了约760万个常见变异和乳腺癌总体风险和雌激素受体阳性(ER +)乳腺癌的七种生活方式/环境风险因素。方法:对来自乳腺癌协会联盟的72,285例乳腺癌病例和80,354例欧洲血统的对照进行了分析。使用标准的无条件逻辑回归模型和乳腺癌总体风险和ER +乳腺癌的似然比检验评估基因-环境相互作用。采用贝叶斯错误发现概率评估各snp风险因素对的可注意性。结果:假设每个snp风险因素对的真实关联的先验概率为1 × 10-5，贝叶斯错误发现概率为int = 0.94, 95% CI 0.92-0.96)， rs4770552(13q12)-SPATA13和初月经年龄对ER +乳腺癌风险的影响(ORint = 0.91, 95% CI 0.88-0.94)。结论:总体而言，G×E相互作用对乳腺癌遗传力的贡献很小。在人群水平上，乘法G×E相互作用对乳腺癌的风险预测没有重要贡献。
A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry.
Background: Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.
Methods: Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.
Results: Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94).
Conclusions: Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.
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