Abstract P4-09-04: Associations between clinical factors in v7.02 of the Tyrer-Cuzick model and a SNP-based residual risk score
Authors: ER Hughes, E Rosenthal, B Morris, S Wagner, JS Lanchbury, A Gutin
Journal: Cancer Research (2019)

Abstract Background: Genome-wide association studies (GWAS) have identified common variants, primarily single-nucleotide polymorphisms (SNPs), that individually confer modest risk but together explain a significant proportion of genetic breast cancer (BC) predisposition. GWAS have also demonstrated that SNPs cannot replace family history evaluation: familial BC assessment captures a large magnitude of risk information that is not captured by SNPs. Thus, improved BC risk stratification may be achieved by combining family history assessment with SNP markers. However, to avoid double-counting shared risk information, familial and/or SNP-based risks must be adjusted for confounding. Additional clinical and biological factors that contribute to BC risk are included in version 7.02 of the Tyrer-Cuzick model. These include height; weight; BMI; age of menarche; parity and age of first childbirth; menopausal status and age of onset; and use of hormonal replacement therapy (HRT). Confounding of SNPs with these factors is not well understood. Here we present an analysis of associations between an 86-SNP Residual Risk Score (RRS) and factors included in version 7.02 of the Tyrer-Cuzick model. Methods: De-identified clinical records and genotypes were collected from a consecutive series of patients referred for hereditary cancer testing with a multigene panel. Study subjects included unaffected women age 18-84 who reported European ancestry and tested negative for mutations in 11 genes associated with BC (BRCA1, BRCA2, TP53, PTEN, STK11, CDH1, PALB2, CHEK2, ATM, NBN, BARD1). For each risk factor, we constructed a univariate linear regression model with RRS as the dependent variable and the clinical factor as the independent variable. From these models, we examined regression coefficients, p-values based on F-statistics, and Pearson correlation coefficients. Scatterplots and boxplots were used to visually assess associations. All analyses were conducted using R version 3.4.4. P-values were reported as two-sided with no corrections for multiple testing. Results: 5,489 patients met the study selection criteria. The median age at hereditary cancer testing was 42 years. Nearly one third (33.1%) of women reported a BC diagnosis in a first degree relative. The RRS was significantly associated with familial BC (p&amp;lt;10-08). We observed marginal evidence of association between the RRS and HRT use (p=0.04). However, this association would not survive a multiple testing correction, and was not significant after multivariate adjustment for family cancer history. We found no evidence for association of the RRS with height, weight, BMI, menopausal stage, age of menarche, age of menopause, duration of menarche, parity, age of first live birth, HRT type, or HRT length of use. Conclusions: The RRS is largely independent from the non-familial risk factors in version 7.02 of the Tyrer-Cuzick model, but is significantly associated with BC family history. Risk assessment based on Tyrer-Cuzick and SNPs must be adjusted for confounding to avoid double-counting familial risk. Citation Format: Hughes ER, Rosenthal E, Morris B, Wagner S, Lanchbury JS, Gutin A. Associations between clinical factors in v7.02 of the Tyrer-Cuzick model and a SNP-based residual risk score [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-09-04.