Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

Myrto Barrdahl; Anja Rudolph; John L Hopper; Melissa C Southey; Annegien Broeks; Peter A Fasching; Matthias W Beckmann; Manuela Gago-Dominguez; J Esteban Castelao; Pascal Guénel; Thérèse Truong; Stig E Bojesen; Susan M Gapstur; Mia M Gaudet; Hermann Brenner; Volker Arndt; Hiltrud Brauch; Ute Hamann; Arto Mannermaa; Diether Lambrechts; Lynn Jongen; Dieter Flesch-Janys; Kathrin Thoene; Fergus J Couch; Graham G Giles; Jacques Simard; Mark S Goldberg; Jonine Figueroa; Kyriaki Michailidou; Manjeet K Bolla; Joe Dennis; Qin Wang; Ursula Eilber; Sabine Behrens; Kamila Czene; Per Hall; Angela Cox; Simon Cross; Anthony Swerdlow; Minouk J Schoemaker; Alison M Dunning; Rudolf Kaaks; Paul D P Pharoah; Marjanka Schmidt; Montserrat Garcia-Closas; Douglas F Easton; Roger L Milne; Jenny Chang-Claude

doi:10.1002/ijc.30859

Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

Myrto Barrdahl, Anja Rudolph, John L Hopper, Melissa C Southey, Annegien Broeks, Peter A Fasching, Matthias W Beckmann, Manuela Gago-Dominguez, J Esteban Castelao, Pascal Guénel, Thérèse Truong, Stig E Bojesen, Susan M Gapstur, Mia M Gaudet, Hermann Brenner, Volker Arndt, Hiltrud Brauch, Ute Hamann, Arto Mannermaa, Diether LambrechtsLynn Jongen, Dieter Flesch-Janys, Kathrin Thoene, Fergus J Couch, Graham G Giles, Jacques Simard, Mark S Goldberg, Jonine Figueroa, Kyriaki Michailidou, Manjeet K Bolla, Joe Dennis, Qin Wang, Ursula Eilber, Sabine Behrens, Kamila Czene, Per Hall, Angela Cox, Simon Cross, Anthony Swerdlow, Minouk J Schoemaker, Alison M Dunning, Rudolf Kaaks, Paul D P Pharoah, Marjanka Schmidt, Montserrat Garcia-Closas, Douglas F Easton, Roger L Milne, Jenny Chang-Claude

Institut for Klinisk Medicin

14 Citationer (Scopus)

325 Downloads (Pure)

Abstract

Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene–environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER–) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene–environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (OR_int = 0.77, 95% CI: 0.67–0.88, p_int = 1.8 × 10⁻⁴). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (OR_int =1.36, 95% CI: 1.16–1.59, p_int = 1.9 × 10⁻⁵) in relation to ER– disease risk. The remaining two gene–environment interactions were also identified in relation to ER– breast cancer risk and were found between 3p21-rs6796502 and age at menarche (OR_int = 1.26, 95% CI: 1.12–1.43, p_int =1.8 × 10⁻⁴) and between 8q23-rs13267382 and age at first full-term pregnancy (OR_int = 0.89, 95% CI: 0.83–0.95, p_int = 5.2 × 10⁻⁴). While these results do not suggest any strong gene–environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

Originalsprog	Engelsk
Tidsskrift	International Journal of Cancer
Vol/bind	141
Udgave nummer	9
Sider (fra-til)	1830-1840
Antal sider	11
ISSN	0020-7136
DOI	https://doi.org/10.1002/ijc.30859
Status	Udgivet - 1 nov. 2017

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Gene–environment interactions involving functional variants:Results from the Breast Cancer Association ConsortiumForlagets udgivne version, 520 KBLicens: CC BY

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Barrdahl, M., Rudolph, A., Hopper, J. L., Southey, M. C., Broeks, A., Fasching, P. A., Beckmann, M. W., Gago-Dominguez, M., Castelao, J. E., Guénel, P., Truong, T., Bojesen, S. E., Gapstur, S. M., Gaudet, M. M., Brenner, H., Arndt, V., Brauch, H., Hamann, U., Mannermaa, A., ... Chang-Claude, J. (2017). Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium. International Journal of Cancer, 141(9), 1830-1840. https://doi.org/10.1002/ijc.30859

Barrdahl, M, Rudolph, A, Hopper, JL, Southey, MC, Broeks, A, Fasching, PA, Beckmann, MW, Gago-Dominguez, M, Castelao, JE, Guénel, P, Truong, T, Bojesen, SE, Gapstur, SM, Gaudet, MM, Brenner, H, Arndt, V, Brauch, H, Hamann, U, Mannermaa, A, Lambrechts, D, Jongen, L, Flesch-Janys, D, Thoene, K, Couch, FJ, Giles, GG, Simard, J, Goldberg, MS, Figueroa, J, Michailidou, K, Bolla, MK, Dennis, J, Wang, Q, Eilber, U, Behrens, S, Czene, K, Hall, P, Cox, A, Cross, S, Swerdlow, A, Schoemaker, MJ, Dunning, AM, Kaaks, R, Pharoah, PDP, Schmidt, M, Garcia-Closas, M, Easton, DF, Milne, RL & Chang-Claude, J 2017, 'Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium', International Journal of Cancer, bind 141, nr. 9, s. 1830-1840. https://doi.org/10.1002/ijc.30859

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title = "Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium",

abstract = "Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene–environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER–) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene–environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (ORint = 0.77, 95% CI: 0.67–0.88, pint = 1.8 × 10−4). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16–1.59, pint = 1.9 × 10−5) in relation to ER– disease risk. The remaining two gene–environment interactions were also identified in relation to ER– breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint = 1.26, 95% CI: 1.12–1.43, pint =1.8 × 10−4) and between 8q23-rs13267382 and age at first full-term pregnancy (ORint = 0.89, 95% CI: 0.83–0.95, pint = 5.2 × 10−4). While these results do not suggest any strong gene–environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.",

keywords = "Alcohol Drinking, Breast Neoplasms, CASP8 and FADD-Like Apoptosis Regulating Protein, Estrogen Receptor alpha, Female, Gene-Environment Interaction, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Polymorphism, Single Nucleotide, Risk Factors, Smoking, Journal Article",

author = "Myrto Barrdahl and Anja Rudolph and Hopper, {John L} and Southey, {Melissa C} and Annegien Broeks and Fasching, {Peter A} and Beckmann, {Matthias W} and Manuela Gago-Dominguez and Castelao, {J Esteban} and Pascal Gu{\'e}nel and Th{\'e}r{\`e}se Truong and Bojesen, {Stig E} and Gapstur, {Susan M} and Gaudet, {Mia M} and Hermann Brenner and Volker Arndt and Hiltrud Brauch and Ute Hamann and Arto Mannermaa and Diether Lambrechts and Lynn Jongen and Dieter Flesch-Janys and Kathrin Thoene and Couch, {Fergus J} and Giles, {Graham G} and Jacques Simard and Goldberg, {Mark S} and Jonine Figueroa and Kyriaki Michailidou and Bolla, {Manjeet K} and Joe Dennis and Qin Wang and Ursula Eilber and Sabine Behrens and Kamila Czene and Per Hall and Angela Cox and Simon Cross and Anthony Swerdlow and Schoemaker, {Minouk J} and Dunning, {Alison M} and Rudolf Kaaks and Pharoah, {Paul D P} and Marjanka Schmidt and Montserrat Garcia-Closas and Easton, {Douglas F} and Milne, {Roger L} and Jenny Chang-Claude",

note = "{\textcopyright} 2017 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.",

year = "2017",

month = nov,

day = "1",

doi = "10.1002/ijc.30859",

language = "English",

volume = "141",

pages = "1830--1840",

journal = "International Journal of Cancer",

issn = "0020-7136",

publisher = "JohnWiley & Sons, Inc.",

number = "9",

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TY - JOUR

T1 - Gene-environment interactions involving functional variants

T2 - Results from the Breast Cancer Association Consortium

AU - Barrdahl, Myrto

AU - Rudolph, Anja

AU - Hopper, John L

AU - Southey, Melissa C

AU - Broeks, Annegien

AU - Fasching, Peter A

AU - Beckmann, Matthias W

AU - Gago-Dominguez, Manuela

AU - Castelao, J Esteban

AU - Guénel, Pascal

AU - Truong, Thérèse

AU - Bojesen, Stig E

AU - Gapstur, Susan M

AU - Gaudet, Mia M

AU - Brenner, Hermann

AU - Arndt, Volker

AU - Brauch, Hiltrud

AU - Hamann, Ute

AU - Mannermaa, Arto

AU - Lambrechts, Diether

AU - Jongen, Lynn

AU - Flesch-Janys, Dieter

AU - Thoene, Kathrin

AU - Couch, Fergus J

AU - Giles, Graham G

AU - Simard, Jacques

AU - Goldberg, Mark S

AU - Figueroa, Jonine

AU - Michailidou, Kyriaki

AU - Bolla, Manjeet K

AU - Dennis, Joe

AU - Wang, Qin

AU - Eilber, Ursula

AU - Behrens, Sabine

AU - Czene, Kamila

AU - Hall, Per

AU - Cox, Angela

AU - Cross, Simon

AU - Swerdlow, Anthony

AU - Schoemaker, Minouk J

AU - Dunning, Alison M

AU - Kaaks, Rudolf

AU - Pharoah, Paul D P

AU - Schmidt, Marjanka

AU - Garcia-Closas, Montserrat

AU - Easton, Douglas F

AU - Milne, Roger L

AU - Chang-Claude, Jenny

PY - 2017/11/1

Y1 - 2017/11/1

N2 - Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene–environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER–) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene–environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (ORint = 0.77, 95% CI: 0.67–0.88, pint = 1.8 × 10−4). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16–1.59, pint = 1.9 × 10−5) in relation to ER– disease risk. The remaining two gene–environment interactions were also identified in relation to ER– breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint = 1.26, 95% CI: 1.12–1.43, pint =1.8 × 10−4) and between 8q23-rs13267382 and age at first full-term pregnancy (ORint = 0.89, 95% CI: 0.83–0.95, pint = 5.2 × 10−4). While these results do not suggest any strong gene–environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

AB - Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene–environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER–) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene–environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (ORint = 0.77, 95% CI: 0.67–0.88, pint = 1.8 × 10−4). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16–1.59, pint = 1.9 × 10−5) in relation to ER– disease risk. The remaining two gene–environment interactions were also identified in relation to ER– breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint = 1.26, 95% CI: 1.12–1.43, pint =1.8 × 10−4) and between 8q23-rs13267382 and age at first full-term pregnancy (ORint = 0.89, 95% CI: 0.83–0.95, pint = 5.2 × 10−4). While these results do not suggest any strong gene–environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

KW - Alcohol Drinking

KW - Breast Neoplasms

KW - CASP8 and FADD-Like Apoptosis Regulating Protein

KW - Estrogen Receptor alpha

KW - Female

KW - Gene-Environment Interaction

KW - Genetic Association Studies

KW - Genetic Predisposition to Disease

KW - Humans

KW - Polymorphism, Single Nucleotide

KW - Risk Factors

KW - Smoking

KW - Journal Article

U2 - 10.1002/ijc.30859

DO - 10.1002/ijc.30859

M3 - Journal article

C2 - 28670784

SN - 0020-7136

VL - 141

SP - 1830

EP - 1840

JO - International Journal of Cancer

JF - International Journal of Cancer

IS - 9

ER -

Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

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