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 language | English (US) |
|---|---|
| Article number | 68 |
| Journal | Breast Cancer Research |
| Volume | 21 |
| Issue number | 1 |
| DOIs | |
| State | Published - May 22 2019 |
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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 journal › Article
}
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
UR - http://www.scopus.com/inward/record.url?scp=85066484413&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85066484413&partnerID=8YFLogxK
U2 - 10.1186/s13058-019-1138-8
DO - 10.1186/s13058-019-1138-8
M3 - Article
C2 - 31118087
AN - SCOPUS:85066484413
VL - 21
JO - Breast Cancer Research
JF - Breast Cancer Research
SN - 1465-5411
IS - 1
M1 - 68
ER -