Association analysis identifies 65 new breast cancer risk loci, predicts target genes for known risk loci and demonstrates a strong overlap with somatic driver genes in breast tumours. Genome-wide association studies for breast cancer have identified common genetic variation that influences susceptibility to this disease, but much of the genetic risk remains unexplained. Doug Easton and colleagues report a genome-wide association study for breast cancer in more than 122,000 cases and 105,000 controls. The authors genotyped a subset of these cases using OncoArray, a new, custom genome-wide single-nucleotide polymorphism (SNP) array for cancer genomics. Overall, they identify 65 loci newly associated with breast cancer susceptibility, and estimate that, together with 107 previously identified breast cancer susceptibility loci, these explain about 18 per cent of the familial relative risk of breast cancer. Polygenic risk scores may be used in risk prediction models and may improve early detection and targeted prevention of the disease. Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry1. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10−8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2–5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Genetic College: Many genomic elements in humans are associated with behavior, including educational attainment. In a genome-wide association study including more than 100,000 samples, Rietveld et al. (p. 1467 , published online 30 May; see the Perspective by Flint and Munafò ) looked for genes related to educational attainment in Caucasians. Small genetic effects at three loci appeared to impact educational attainment.

Doug Easton and colleagues report the results of a large-scale genome-wide association study of breast cancer. They discover 15 new susceptibility loci and highlight likely target genes in several of the newly associated regions. Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10−8. Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.

Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.