Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

Abstract

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10^-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Figure 1

Genomic region around the independent ER-negative risk-associated variants 11_108345515_G_A (rs11374964) and 11_108357137_G_A (rs74911261). A 1-Mb regional association plot shows the statistical significance of all genotyped and imputed SNPs with the genome-wide significance level (P = 5 × 10⁻⁸) represented by the dashed red line. The positions of candidate causal variants for two independent signals (depicted as red and blue ticks) are shown in relation to RefSeq genes. Missense variants are labeled with asterisks. Mammary cell enhancers overlapping candidate SNPs predicted to target nearby genes by IM-PET46 are depicted as black bars. Chromatin interactions from ENCODE ChIA-PET data in MCF7 cells overlapping candidate variants are shaded to reflect interaction confidence scores with darker shading indicating greater confidence. Epigenomic features (derived from publicly available ChIP–seq and DNase–seq data sets) that overlap candidate variants are shown as red or blue segments, depending on the intersected signal. Density tracks show the summed occurrence of ChIP–seq and DNase–seq peak signals at each position. Roadmap Epigenomics Project chromatin state models for HMECs and myoepithelial cells grouped into enhancer, promoter or transcribed annotations are shown as yellow, red and green segments, respectively. Transcript levels in MCF7 cells and HMECs are represented by histograms depicting mean normalized RNA-seq expression. All MCF7 ChIA-PET (ENCODE) and HMEC Hi-C47 chromatin interactions are represented by black and blue arcs, respectively. NHGRI GWAS catalog SNPs are shown as green ticks. All OncoArray SNPs (genotyped or imputed) are shown as black ticks, and uninterrogated, common SNPs (dbSNP138, European (EUR) MAF > 1%) are shown as red ticks. Features may be examined in detail via exploration of a custom UCSC Genome Browser session accessible via hyperlinks within Supplementary Table 5. TF, transcription factor; DHS, DNase I–hypersensitive site.