Breast Cancer Now. Grant Number: 2015MayPR515National Institute for Health Research. Grant Numbers: IS‐BRC‐1215‐20007, NF‐SI‐0513‐10076Prevent Breast Cancer. Grant Numbers: GA09‐002, GA11‐002Cancer Research UK. Grant Numbers: C1287/A10118, C1287/A16563, C569/A16891National Institutes of Health. Grant Numbers: X01HG007492, U19 CA148065Canadian Institutes of Health Research. Grant Number: GPH‐129344Horizon 2020 Research and Innovation Programme. Grant Numbers: 634935, 633784European Union. Grant Number: HEALTH‐F2‐2009‐22317

Astley, SM

Brentnall, AR

Byers, H

Cuzick, J

Evans, DGR

Harkness, EF

Howell, A

Newman, WG

Rafiq, S

Sampson, S

van Veen, EM

International Journal of Cancer

English

Panels 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 (1668 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 pre-defined polygenic risk score based on 143 SNPs was calculated (SNP143). The odds ratio (and 95% confidence interval, CI) per inter-quartile range (IQ-OR) of SNP143 was estimated unadjusted and adjusted for Tyrer-Cuzick and breast density. Secondary analysis assessed risk by estrogen-receptor status. The primary polygenic risk score was well calibrated (O/E odds ratio 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%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 estrogen-receptor positive and negative disease

Brentnall, Adam R

Van Veen, Elke

Harkness, Elaine

Rafiq, Saijad

Byers, Helen

Astley, Susan

Sampson, Sarah

Howell, Anthony

Newman, William

Cuzick, Jack

Evans, D Gareth

The University of Manchester - Institutional Repository

A case-control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density

Queen Mary Research Online

Duffy SW

Evans DG

NICE

R Core Team

Crossref

A case–control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density

https://qmro.qmul.ac.uk/xmlui/bitstream/handle/123456789/59200/Brentnall_case%e2%80%93control%20evaluation%20of%20143_accepted-ms_2019.doc?sequence=2&isAllowed=y

A case-control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density

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The University of Manchester - Institutional Repository

Queen Mary Research Online

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