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

Abstract

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 (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.

Keywords: SNPs; Tyrer-Cuzick; breast cancer; breast density; risk prediction; risk stratification.

Figure 1

Calibration of the primary polygenic risk score (unadjusted). Points are observed and expected odds ratios by decile, the fit from a logistic regression (—) is also shown (see Supporting Information Table S3). O/E OR: a calibration coefficient for the observed (O) divided by expected (E) odds ratio (OR), or fitted slope of the line (—).

Figure 2

Calibration (95% CI) of the primary polygenic risk score (unadjusted) split into subscores of 20 SNPs ordered by the overview p‐value for each SNP (1 = top 20 [SNP1–20] predictive SNPs, 2 = next 20 [SNP21–40], similarly 3–6 and 7 = least predictive SNPs [SNP121–143]).