Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk

Celine M Vachon, Christopher G. Scott, Rulla M. Tamimi, Deborah J. Thompson, Peter A. Fasching, Jennifer Stone, Melissa C. Southey, Stacey J Winham, Sara Lindström, Jenna Lilyquist, Graham G. Giles, Roger L. Milne, Robert J. MacInnis, Laura Baglietto, Jingmei Li, Kamila Czene, Manjeet K. Bolla, Qin Wang, Joe Dennis, Lothar HaeberleMikael Eriksson, Peter Kraft, Robert Luben, Nick Wareham, Janet E Olson, Aaron Norman, Eric Polley, Gertraud Maskarinec, Loic Le Marchand, Christopher A. Haiman, John L. Hopper, Fergus J Couch, Douglas F. Easton, Per Hall, Nilanjan Chatterjee, Montse Garcia-Closas

Research output: Contribution to journalArticle

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Abstract

Background: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Methods: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Results: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusions: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.

Original languageEnglish (US)
Article number68
JournalBreast Cancer Research
Volume21
Issue number1
DOIs
StatePublished - May 22 2019

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Body Mass Index
Breast Neoplasms
Odds Ratio
Single Nucleotide Polymorphism
Breast Density
Logistic Models
Case-Control Studies
Software
Phenotype

Keywords

  • Breast cancer risk
  • Breast density
  • Genetic variation
  • Polygenic risk score
  • Risk models

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk. / Vachon, Celine M; Scott, Christopher G.; Tamimi, Rulla M.; Thompson, Deborah J.; Fasching, Peter A.; Stone, Jennifer; Southey, Melissa C.; Winham, Stacey J; Lindström, Sara; Lilyquist, Jenna; Giles, Graham G.; Milne, Roger L.; MacInnis, Robert J.; Baglietto, Laura; Li, Jingmei; Czene, Kamila; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Haeberle, Lothar; Eriksson, Mikael; Kraft, Peter; Luben, Robert; Wareham, Nick; Olson, Janet E; Norman, Aaron; Polley, Eric; Maskarinec, Gertraud; Le Marchand, Loic; Haiman, Christopher A.; Hopper, John L.; Couch, Fergus J; Easton, Douglas F.; Hall, Per; Chatterjee, Nilanjan; Garcia-Closas, Montse.

In: Breast Cancer Research, Vol. 21, No. 1, 68, 22.05.2019.

Research output: Contribution to journalArticle

Vachon, CM, Scott, CG, Tamimi, RM, Thompson, DJ, Fasching, PA, Stone, J, Southey, MC, Winham, SJ, Lindström, S, Lilyquist, J, Giles, GG, Milne, RL, MacInnis, RJ, Baglietto, L, Li, J, Czene, K, Bolla, MK, Wang, Q, Dennis, J, Haeberle, L, Eriksson, M, Kraft, P, Luben, R, Wareham, N, Olson, JE, Norman, A, Polley, E, Maskarinec, G, Le Marchand, L, Haiman, CA, Hopper, JL, Couch, FJ, Easton, DF, Hall, P, Chatterjee, N & Garcia-Closas, M 2019, 'Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk', Breast Cancer Research, vol. 21, no. 1, 68. https://doi.org/10.1186/s13058-019-1138-8
Vachon, Celine M ; Scott, Christopher G. ; Tamimi, Rulla M. ; Thompson, Deborah J. ; Fasching, Peter A. ; Stone, Jennifer ; Southey, Melissa C. ; Winham, Stacey J ; Lindström, Sara ; Lilyquist, Jenna ; Giles, Graham G. ; Milne, Roger L. ; MacInnis, Robert J. ; Baglietto, Laura ; Li, Jingmei ; Czene, Kamila ; Bolla, Manjeet K. ; Wang, Qin ; Dennis, Joe ; Haeberle, Lothar ; Eriksson, Mikael ; Kraft, Peter ; Luben, Robert ; Wareham, Nick ; Olson, Janet E ; Norman, Aaron ; Polley, Eric ; Maskarinec, Gertraud ; Le Marchand, Loic ; Haiman, Christopher A. ; Hopper, John L. ; Couch, Fergus J ; Easton, Douglas F. ; Hall, Per ; Chatterjee, Nilanjan ; Garcia-Closas, Montse. / Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk. In: Breast Cancer Research. 2019 ; Vol. 21, No. 1.
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abstract = "Background: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Methods: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Results: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95{\%} CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95{\%} CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95{\%} CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusions: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.",
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author = "Vachon, {Celine M} and Scott, {Christopher G.} and Tamimi, {Rulla M.} and Thompson, {Deborah J.} and Fasching, {Peter A.} and Jennifer Stone and Southey, {Melissa C.} and Winham, {Stacey J} and Sara Lindstr{\"o}m and Jenna Lilyquist and Giles, {Graham G.} and Milne, {Roger L.} and MacInnis, {Robert J.} and Laura Baglietto and Jingmei Li and Kamila Czene and Bolla, {Manjeet K.} and Qin Wang and Joe Dennis and Lothar Haeberle and Mikael Eriksson and Peter Kraft and Robert Luben and Nick Wareham and Olson, {Janet E} and Aaron Norman and Eric Polley and Gertraud Maskarinec and {Le Marchand}, Loic and Haiman, {Christopher A.} and Hopper, {John L.} and Couch, {Fergus J} and Easton, {Douglas F.} and Per Hall and Nilanjan Chatterjee and Montse Garcia-Closas",
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TY - JOUR

T1 - Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk

AU - Vachon, Celine M

AU - Scott, Christopher G.

AU - Tamimi, Rulla M.

AU - Thompson, Deborah J.

AU - Fasching, Peter A.

AU - Stone, Jennifer

AU - Southey, Melissa C.

AU - Winham, Stacey J

AU - Lindström, Sara

AU - Lilyquist, Jenna

AU - Giles, Graham G.

AU - Milne, Roger L.

AU - MacInnis, Robert J.

AU - Baglietto, Laura

AU - Li, Jingmei

AU - Czene, Kamila

AU - Bolla, Manjeet K.

AU - Wang, Qin

AU - Dennis, Joe

AU - Haeberle, Lothar

AU - Eriksson, Mikael

AU - Kraft, Peter

AU - Luben, Robert

AU - Wareham, Nick

AU - Olson, Janet E

AU - Norman, Aaron

AU - Polley, Eric

AU - Maskarinec, Gertraud

AU - Le Marchand, Loic

AU - Haiman, Christopher A.

AU - Hopper, John L.

AU - Couch, Fergus J

AU - Easton, Douglas F.

AU - Hall, Per

AU - Chatterjee, Nilanjan

AU - Garcia-Closas, Montse

PY - 2019/5/22

Y1 - 2019/5/22

N2 - Background: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Methods: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Results: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusions: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.

AB - Background: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Methods: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Results: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusions: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.

KW - Breast cancer risk

KW - Breast density

KW - Genetic variation

KW - Polygenic risk score

KW - Risk models

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