Association analysis identifies 65 new breast cancer risk loci

Abstract

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 ancestry. 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.

Extended data Figure 1. Global mapping of biofeatures across novel loci associated with overall breast cancer risk.

The overlaps between potential genomic predictors in relevant breast cell lines and candidate causal risk variants (CRVs) within each locus. On the x-axis, each column represents a CRV (see Online Methods). The most significant SNPs are identified in each region. On the y-axis, biofeatures are grouped into five functional categories: genomic structure (red), enhancer marks (dark green), histone marks (blue), open chromatin marks (dark blue) and transcription factor binding sites (dark violet). Colored elements indicate SNPs for which the feature is present. For data sources, see Online Methods (“In-Silico Analysis of CRVs”).

Extended data Figure 2. Pathway enrichment map for susceptibility loci based on summary association statistics.

Each circle (node) represents a pathway (gene set), coloured by enrichment score (ES) where redder nodes indicate lower FDRs. Larger nodes indicate pathways with more genes. Green lines connect pathways with overlapping genes (minimum overlap 0.55). Pathways are grouped by similarity and organized into major themes (large labelled circles).

Extended data Figure 3. Heatmap showing patterns of cell type-specific enrichments for breast tissue across three histone marks (H3K4me1, H3K4me3 and H3K9ac) for breast cancer overall, ER-positive breast cancer and ER-negative breast cancer as well as 16 other traits.

Extended data Figure 4. Heatmap showing patterns of cell type-specific enrichments for histone mark H3K27ac in breast cancer overall, ER+ and ER- breast cancer as well as 16 other traits.

Extended data Figure 5. Heatmap showing patterns of cell type-specific enrichments for histone mark H3K4me1 in breast cancer overall, ER+ and ER- breast cancer as well as 16 other traits.

Extended data Figure 6. Heatmap showing patterns of cell type-specific enrichments for histone mark H3K4me3 in breast cancer overall, ER+ and ER- breast cancer as well as 16 other traits.

Extended data Figure 7. Heatmap showing patterns of cell type-specific enrichments for histone mark H3K9ac in breast cancer overall, ER-positive and ER-negative breast cancer as well as 16 other traits.

Extended data Figure 8. Functional assessment of regulatory variants at 1p36, 11p15 and 1p34 risk loci.

a, The KLHDC7A or b, PIDD1 promoter regions containing the reference (prom-Ref) or risk alleles (prom-Hap), were cloned upstream of the pGL3 luciferase reporter gene. MCF7 or Bre-80 cells were transfected with constructs and assayed for luciferase activity after 24 h. Error bars denote 95% CI (n=3). P-values were determined by two-way ANOVA followed by Dunnett’s multiple comparisons test (*P<0.05, **P<0.01, ***P<0.001). c, 3C assays. A physical map of the region interrogated by 3C is shown first. Grey boxes depict the putative regulatory elements (PREs), blue vertical lines indicate the risk-associated SNPs and black dotted line represents chromatin looping. The graphs represent three independent 3C interaction profiles. 3C libraries were generated with EcoRI, grey vertical boxes indicate the interacting restriction fragment (containing PRE1 and PRE2). Error bars denote SD. d, PRE1 or PRE2 containing the reference (PRE-ref) or risk (PRE-Hap) haplotypes were cloned downstream of a CITED4 promoter-driven luciferase construct (CITED4 prom). MCF7 or Bre-80 cells were transfected with constructs and assayed for luciferase activity after 24 h. Error bars denote 95% CI (n=3). P-values were determined by two-way ANOVA followed by Dunnett’s multiple comparisons test (**P<0.01, ***P<0.001).

Extended data Figure 9. Functional assessment of regulatory variants at the 7q22 risk locus.

a-e, 3C assays. A physical map of the region interrogated by 3C is shown first. Grey horizontal boxes depict the putative regulatory elements (PREs), blue vertical lines indicate the risk-associated SNPs and black dotted line represents chromatin looping. The graphs represent three independent 3C interaction profiles between the a, CUX1, b, d, PRKRIP1 or c, e, RASA4 promoter regions and PREs. 3C libraries were generated with EcoRI, grey vertical boxes indicate the interacting restriction fragment (containing PRE1 and/or PRE2). Error bars denote SD. f, g, Allele-specific 3C. 3C followed by Sanger sequencing for the f, PRKRIP1-PRE2 or g, RASA4-PRE1 or -PRE2 in heterozygous MDA-MB-231 breast cancer cells.

Figure 1

(a) Manhattan plot showing log₁₀P-values for SNP associations with overall breast cancer (b) Manhattan plot after excluding previously identified associated regions. The red line denotes “genome-wide” significance (P<5x10^-8); the blue line denotes P<10^-5.