Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Abstract

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57–1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628–0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

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

“…Third, although we considered some different risk scores based on different thresholds on which SNPs to include, we lacked power to assess small changes to risk score, such in our ER‐subtype risk scores that included SNPs in a PRS with p < 10 −5 . This has recently been investigated in a much larger study of women with European ancestry . Predictive performance of their larger panel of 313 SNPs was similar to here but drew on using wholly imputed SNPs that has important barriers for clinical use.…”

Breast cancer subtypes among Eastern‐African–born black women and other black women in the United States

“…6,[26][27][28] However, the relationship of the variation in breast cancer susceptibility loci with population differences in subtype prevalence is not clear. 6,[26][27][28] However, the relationship of the variation in breast cancer susceptibility loci with population differences in subtype prevalence is not clear.…”

Breast cancer risk in BRCA1/2 mutation carriers and noncarriers under prospective intensified surveillance

“…These genes might confer higher BC risks than observed in the group of women from BRCA1/2 ‐negative families. Likewise, we have currently no information on common genetic variants and the distribution of its polygenic combination, which might also have an impact on our risk estimates …”