Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium

Anja Rudolph, Minsun Song, Mark N. Brook, Roger L. Milne, Nasim Mavaddat, Kyriaki Michailidou, Manjeet K. Bolla, Qin Wang, Joe Dennis, Amber N. Wilcox, John L. Hopper, Melissa C. Southey, Renske Keeman, Peter A. Fasching, Matthias W. Beckmann, Manuela Gago-Dominguez, Jose E. Castelao, Pascal Guénel, Thérèse Truong, Stig E. Bojesen & 31 others Henrik Flyger, Hermann Brenner, Volker Arndt, Hiltrud Brauch, Thomas Brüning, Arto Mannermaa, Veli Matti Kosma, Diether Lambrechts, Machteld Keupers, Fergus J. Couch, Celine Vachon, Graham G. Giles, Robert J. MacInnis, Jonine Figueroa, Louise Brinton, Kamila Czene, Judith S. Brand, Marike Gabrielson, Keith Humphreys, Angela Cox, Simon S. Cross, Alison M. Dunning, Nick Orr, Anthony Swerdlow, Per Hall, Paul D.P. Pharoah, Marjanka K. Schmidt, Douglas F. Easton, Nilanjan Chatterjee, Jenny Chang-Claude, Montserrat García-Closas

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Background: Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors. Methods: Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status. Results: The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction=0.009), adult height (P-interaction=0.025) and current use of combined MHT (P-interaction=0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P=0.013 for global and 0.18 for tail-based tests). Conclusions: The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.

Original languageEnglish
Pages (from-to)526-536
Number of pages11
JournalInternational Journal of Epidemiology
Volume47
Issue number2
DOIs
Publication statusPublished - 1 Apr 2018
Externally publishedYes

Keywords

  • Breast cancer
  • Epidemiology
  • Gene-environment interactions
  • Genetic susceptibility
  • Risk prediction

Cite this

Rudolph, Anja ; Song, Minsun ; Brook, Mark N. ; Milne, Roger L. ; Mavaddat, Nasim ; Michailidou, Kyriaki ; Bolla, Manjeet K. ; Wang, Qin ; Dennis, Joe ; Wilcox, Amber N. ; Hopper, John L. ; Southey, Melissa C. ; Keeman, Renske ; Fasching, Peter A. ; Beckmann, Matthias W. ; Gago-Dominguez, Manuela ; Castelao, Jose E. ; Guénel, Pascal ; Truong, Thérèse ; Bojesen, Stig E. ; Flyger, Henrik ; Brenner, Hermann ; Arndt, Volker ; Brauch, Hiltrud ; Brüning, Thomas ; Mannermaa, Arto ; Kosma, Veli Matti ; Lambrechts, Diether ; Keupers, Machteld ; Couch, Fergus J. ; Vachon, Celine ; Giles, Graham G. ; MacInnis, Robert J. ; Figueroa, Jonine ; Brinton, Louise ; Czene, Kamila ; Brand, Judith S. ; Gabrielson, Marike ; Humphreys, Keith ; Cox, Angela ; Cross, Simon S. ; Dunning, Alison M. ; Orr, Nick ; Swerdlow, Anthony ; Hall, Per ; Pharoah, Paul D.P. ; Schmidt, Marjanka K. ; Easton, Douglas F. ; Chatterjee, Nilanjan ; Chang-Claude, Jenny ; García-Closas, Montserrat. / Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium. In: International Journal of Epidemiology. 2018 ; Vol. 47, No. 2. pp. 526-536.
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title = "Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium",
abstract = "Background: Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors. Methods: Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status. Results: The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction=0.009), adult height (P-interaction=0.025) and current use of combined MHT (P-interaction=0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P=0.013 for global and 0.18 for tail-based tests). Conclusions: The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.",
keywords = "Breast cancer, Epidemiology, Gene-environment interactions, Genetic susceptibility, Risk prediction",
author = "Anja Rudolph and Minsun Song and Brook, {Mark N.} and Milne, {Roger L.} and Nasim Mavaddat and Kyriaki Michailidou and Bolla, {Manjeet K.} and Qin Wang and Joe Dennis and Wilcox, {Amber N.} and Hopper, {John L.} and Southey, {Melissa C.} and Renske Keeman and Fasching, {Peter A.} and Beckmann, {Matthias W.} and Manuela Gago-Dominguez and Castelao, {Jose E.} and Pascal Gu{\'e}nel and Th{\'e}r{\`e}se Truong and Bojesen, {Stig E.} and Henrik Flyger and Hermann Brenner and Volker Arndt and Hiltrud Brauch and Thomas Br{\"u}ning and Arto Mannermaa and Kosma, {Veli Matti} and Diether Lambrechts and Machteld Keupers and Couch, {Fergus J.} and Celine Vachon and Giles, {Graham G.} and MacInnis, {Robert J.} and Jonine Figueroa and Louise Brinton and Kamila Czene and Brand, {Judith S.} and Marike Gabrielson and Keith Humphreys and Angela Cox and Cross, {Simon S.} and Dunning, {Alison M.} and Nick Orr and Anthony Swerdlow and Per Hall and Pharoah, {Paul D.P.} and Schmidt, {Marjanka K.} and Easton, {Douglas F.} and Nilanjan Chatterjee and Jenny Chang-Claude and Montserrat Garc{\'i}a-Closas",
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month = "4",
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doi = "10.1093/IJE/DYX242",
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pages = "526--536",
journal = "International Journal of Epidemiology",
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Rudolph, A, Song, M, Brook, MN, Milne, RL, Mavaddat, N, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Wilcox, AN, Hopper, JL, Southey, MC, Keeman, R, Fasching, PA, Beckmann, MW, Gago-Dominguez, M, Castelao, JE, Guénel, P, Truong, T, Bojesen, SE, Flyger, H, Brenner, H, Arndt, V, Brauch, H, Brüning, T, Mannermaa, A, Kosma, VM, Lambrechts, D, Keupers, M, Couch, FJ, Vachon, C, Giles, GG, MacInnis, RJ, Figueroa, J, Brinton, L, Czene, K, Brand, JS, Gabrielson, M, Humphreys, K, Cox, A, Cross, SS, Dunning, AM, Orr, N, Swerdlow, A, Hall, P, Pharoah, PDP, Schmidt, MK, Easton, DF, Chatterjee, N, Chang-Claude, J & García-Closas, M 2018, 'Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium' International Journal of Epidemiology, vol. 47, no. 2, pp. 526-536. https://doi.org/10.1093/IJE/DYX242

Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium. / Rudolph, Anja; Song, Minsun; Brook, Mark N.; Milne, Roger L.; Mavaddat, Nasim; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Wilcox, Amber N.; Hopper, John L.; Southey, Melissa C.; Keeman, Renske; Fasching, Peter A.; Beckmann, Matthias W.; Gago-Dominguez, Manuela; Castelao, Jose E.; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E.; Flyger, Henrik; Brenner, Hermann; Arndt, Volker; Brauch, Hiltrud; Brüning, Thomas; Mannermaa, Arto; Kosma, Veli Matti; Lambrechts, Diether; Keupers, Machteld; Couch, Fergus J.; Vachon, Celine; Giles, Graham G.; MacInnis, Robert J.; Figueroa, Jonine; Brinton, Louise; Czene, Kamila; Brand, Judith S.; Gabrielson, Marike; Humphreys, Keith; Cox, Angela; Cross, Simon S.; Dunning, Alison M.; Orr, Nick; Swerdlow, Anthony; Hall, Per; Pharoah, Paul D.P.; Schmidt, Marjanka K.; Easton, Douglas F.; Chatterjee, Nilanjan; Chang-Claude, Jenny; García-Closas, Montserrat.

In: International Journal of Epidemiology, Vol. 47, No. 2, 01.04.2018, p. 526-536.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium

AU - Rudolph, Anja

AU - Song, Minsun

AU - Brook, Mark N.

AU - Milne, Roger L.

AU - Mavaddat, Nasim

AU - Michailidou, Kyriaki

AU - Bolla, Manjeet K.

AU - Wang, Qin

AU - Dennis, Joe

AU - Wilcox, Amber N.

AU - Hopper, John L.

AU - Southey, Melissa C.

AU - Keeman, Renske

AU - Fasching, Peter A.

AU - Beckmann, Matthias W.

AU - Gago-Dominguez, Manuela

AU - Castelao, Jose E.

AU - Guénel, Pascal

AU - Truong, Thérèse

AU - Bojesen, Stig E.

AU - Flyger, Henrik

AU - Brenner, Hermann

AU - Arndt, Volker

AU - Brauch, Hiltrud

AU - Brüning, Thomas

AU - Mannermaa, Arto

AU - Kosma, Veli Matti

AU - Lambrechts, Diether

AU - Keupers, Machteld

AU - Couch, Fergus J.

AU - Vachon, Celine

AU - Giles, Graham G.

AU - MacInnis, Robert J.

AU - Figueroa, Jonine

AU - Brinton, Louise

AU - Czene, Kamila

AU - Brand, Judith S.

AU - Gabrielson, Marike

AU - Humphreys, Keith

AU - Cox, Angela

AU - Cross, Simon S.

AU - Dunning, Alison M.

AU - Orr, Nick

AU - Swerdlow, Anthony

AU - Hall, Per

AU - Pharoah, Paul D.P.

AU - Schmidt, Marjanka K.

AU - Easton, Douglas F.

AU - Chatterjee, Nilanjan

AU - Chang-Claude, Jenny

AU - García-Closas, Montserrat

PY - 2018/4/1

Y1 - 2018/4/1

N2 - Background: Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors. Methods: Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status. Results: The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction=0.009), adult height (P-interaction=0.025) and current use of combined MHT (P-interaction=0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P=0.013 for global and 0.18 for tail-based tests). Conclusions: The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.

AB - Background: Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors. Methods: Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status. Results: The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction=0.009), adult height (P-interaction=0.025) and current use of combined MHT (P-interaction=0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P=0.013 for global and 0.18 for tail-based tests). Conclusions: The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.

KW - Breast cancer

KW - Epidemiology

KW - Gene-environment interactions

KW - Genetic susceptibility

KW - Risk prediction

UR - http://www.scopus.com/inward/record.url?scp=85048267311&partnerID=8YFLogxK

U2 - 10.1093/IJE/DYX242

DO - 10.1093/IJE/DYX242

M3 - Article

VL - 47

SP - 526

EP - 536

JO - International Journal of Epidemiology

JF - International Journal of Epidemiology

SN - 0300-5771

IS - 2

ER -