Dataset Information

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.

SUBMITTER: Rudolph A

PROVIDER: S-EPMC5913605 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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

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

International journal of epidemiology 20180401 2

<h4>Background</h4>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.<h4>Methods</h4>Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer ...[more]

PMID: 29315403

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Project description:BackgroundMammographic 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.MethodsUsing 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.ResultsAdjusted 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.ConclusionsThe 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.

Project description:BackgroundPrevious studies have suggested that breast cancer risk factors are associated with estrogen receptor (ER) and progesterone receptor (PR) expression status of the tumors.MethodsWe pooled tumor marker and epidemiological risk factor data from 35,568 invasive breast cancer case patients from 34 studies participating in the Breast Cancer Association Consortium. Logistic regression models were used in case-case analyses to estimate associations between epidemiological risk factors and tumor subtypes, and case-control analyses to estimate associations between epidemiological risk factors and the risk of developing specific tumor subtypes in 12 population-based studies. All statistical tests were two-sided.ResultsIn case-case analyses, of the epidemiological risk factors examined, early age at menarche (?12 years) was less frequent in case patients with PR(-) than PR(+) tumors (P = .001). Nulliparity (P = 3 × 10(-6)) and increasing age at first birth (P = 2 × 10(-9)) were less frequent in ER(-) than in ER(+) tumors. Obesity (body mass index [BMI] ? 30 kg/m(2)) in younger women (?50 years) was more frequent in ER(-)/PR(-) than in ER(+)/PR(+) tumors (P = 1 × 10(-7)), whereas obesity in older women (>50 years) was less frequent in PR(-) than in PR(+) tumors (P = 6 × 10(-4)). The triple-negative (ER(-)/PR(-)/HER2(-)) or core basal phenotype (CBP; triple-negative and cytokeratins [CK]5/6(+) and/or epidermal growth factor receptor [EGFR](+)) accounted for much of the heterogeneity in parity-related variables and BMI in younger women. Case-control analyses showed that nulliparity, increasing age at first birth, and obesity in younger women showed the expected associations with the risk of ER(+) or PR(+) tumors but not triple-negative (nulliparity vs parity, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.75 to 1.19, P = .61; 5-year increase in age at first full-term birth, OR = 0.95, 95% CI = 0.86 to 1.05, P = .34; obesity in younger women, OR = 1.36, 95% CI = 0.95 to 1.94, P = .09) or CBP tumors.ConclusionsThis study shows that reproductive factors and BMI are most clearly associated with hormone receptor-positive tumors and suggest that triple-negative or CBP tumors may have distinct etiology.

Dataset Information

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

Publications

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

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