A case-control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density
van Veen, E
Evans, D Gareth R
AffiliationCentre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Charterhouse Square, Barts and The London, Queen Mary University of London, London
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AbstractPanels of single nucleotide polymorphisms (SNPs) stratify risk for breast cancer in women from the general population, but studies are needed assess their use in a fully comprehensive model including classical risk factors, mammographic density and more than 100 SNPs associated with breast cancer. A case-control study was designed (1,668 controls, 405 cases) in women aged 47-73 years attending routine screening in Manchester UK, and enrolled in a wider study to assess methods for risk assessment. Risk from classical questionnaire risk factors was assessed using the Tyrer-Cuzick model; mean percentage visual mammographic density was scored by two independent readerS DNA extracted from saliva was genotyped at selected SNPs using the OncoArraY A predefined polygenic risk score based on 143 SNPs was calculated (SNP143). The odds ratio (OR, and 95% confidence interval, CI) per interquartile range (IQ-OR) of SNP143 was estimated unadjusted and adjusted for Tyrer-Cuzick and breast density. Secondary analysis assessed risk by oestrogen receptor (ER) statuS The primary polygenic risk score was well calibrated (O/E OR 1.10, 95% CI 0.86-1.34) and accuracy was retained after adjustment for Tyrer-Cuzick risk and mammographic density (IQ-OR unadjusted 2.12, 95% CI% 1.75-2.42; adjusted 2.06, 95% CI 1.75-2.42). SNP143 was a risk factor for ER+ and ER- breast cancer (adjusted IQ-OR, ER+ 2.11, 95% CI 1.78-2.51; ER- 1.81, 95% CI 1.16-2.84). In conclusion, polygenic risk scores based on a large number of SNPs improve risk stratification in combination with classical risk factors and mammographic density, and SNP143 was similarly predictive for ER-positive and ER-negative disease.
CitationBrentnall AR, van Veen EM, Harkness EF, Rafiq S, Byers H, Astley SM, et al. A case-control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density. Int J Cancer. 2019.
JournalInternational Journal of Cancer
- Long-term Accuracy of Breast Cancer Risk Assessment Combining Classic Risk Factors and Breast Density.
- Authors: Brentnall AR, Cuzick J, Buist DSM, Bowles EJA
- Issue date: 2018 Sep 1
- Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants.
- Authors: Evans DGR, Harkness EF, Brentnall AR, van Veen EM, Astley SM, Byers H, Sampson S, Southworth J, Stavrinos P, Howell SJ, Maxwell AJ, Howell A, Newman WG, Cuzick J
- Issue date: 2019 Jul
- Use of Single-Nucleotide Polymorphisms and Mammographic Density Plus Classic Risk Factors for Breast Cancer Risk Prediction.
- Authors: van Veen EM, Brentnall AR, Byers H, Harkness EF, Astley SM, Sampson S, Howell A, Newman WG, Cuzick J, Evans DGR
- Issue date: 2018 Apr 1
- Mammographic density adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening cohort.
- Authors: Brentnall AR, Harkness EF, Astley SM, Donnelly LS, Stavrinos P, Sampson S, Fox L, Sergeant JC, Harvie MN, Wilson M, Beetles U, Gadde S, Lim Y, Jain A, Bundred S, Barr N, Reece V, Howell A, Cuzick J, Evans DG
- Issue date: 2015 Dec 1
- The impact of a panel of 18 SNPs on breast cancer risk in women attending a UK familial screening clinic: a case-control study.
- Authors: Evans DG, Brentnall A, Byers H, Harkness E, Stavrinos P, Howell A, FH-risk study Group., Newman WG, Cuzick J
- Issue date: 2017 Feb