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 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.
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Change history
08 March 2018
The link to Supplementary Table 20 was corrected.
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Acknowledgements
We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. Genotyping of the OncoArray was principally funded from three sources: the PERSPECTIVE project, funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome Québec, and the Quebec Breast Cancer Foundation; the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH Grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118 and C1287/A16563). BCAC is funded by Cancer Research UK (C1287/A16563), by the European Community’s Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast Cancer’ program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combining of the GWAS data was supported in part by The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant U19 CA 148065 (DRIVE, part of the GAME-ON initiative). For a full description of funding and acknowledgments, see Supplementary Note.
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Writing group: K.Mi., S.Li., J.Bee., S.Hu., S.Ka., P.So., S.L.E., G.D.B., G.C.-T., J.Si., P.K. and D.F.E. Conceived the OncoArray and obtained financial support: C.I.A., J.Si., P.K. and D.F.E. Designed the OncoArray: J.D., E.D., A. Lee, Z.W., A.C.A., C.I.A., S.J.C., P.K. and D.F.E. Led the COGS project: P.Hal. Led the DRIVE project: D.J.H. Led the PERSPECTIVE project: J.Si. Led the working groups of BCAC: A.C.A., I.L.A., P.D.P.P., J.C.-C., R.L.M., M.G.-C., M.K.S. and A.M.D. Data management: J.D., M.K.B., Q.Wan., R.Ke., U.E., S.B., J.C.-C. and M.K.S. Bioinformatics analysis: J.D., J.Bee., A.Lem., P.So., J.A., M.Gh., J.C., A.D., A.E.M.R., S.R.L. Statistical analysis: K.Mi., S.Li., S.Hu., S.Ka., A.Ros., J.T., X.Q.C., L.Fa., X.J., H.Fi., G.D.B., P.K. and D.F.E. Functional analysis: D.G., X.Q.C., J.Bee., J.D.F., K.Mc., S.L.E. and G.C.-T. OncoArray genotyping: M.A., F.B., C.Ba., D.M.C., J.M.C., K.F.D., N.Ha., B.H., K.J., C.L., J.Me., E.P., J.R., G.S., D.C.T., D.V.D.B., D.V., J.V., L.X., B.Z. and A.M.D. Provided DNA samples and/or phenotypic data: M.A.A., H.A., K.A., H.A.-C., N.N.A., V.A., K.J.A., B.A., P.L.A., M.Ba., M.W.B., J.Ben., M.Be., L.Be., C.Bl., N.V.B., S.E.B., B.Bo., A.-L.B.-D., J.S.B., H.Bra., P.Bre., H.Bre., L.Br., P.Bro., I.W.B., A.B., A.B.-W., S.Y.B., T.B., B.Bu., K.B., H.Ca., Q.C., T.C., F.C., A.Ca., B.D.C., J.E.C., T.L.C., T.-Y.D.C., K.S.C., J.-Y.C., H.Ch., C.L.C., M.C., E.C.-D., S.C., A.Co., D.G.C., S.S.C., K.C., M.B.D., P.D., T.D., I.d.-S.-S., M.Du., L.D., M.Dw., D.M.E., A.B.E., A.H.E., C.El., M.El., C.En., M.Er., P.A.F., J.F., D.F.-J., O.F., H.Fl., L.Fr., V.Ga., M.Ga., M.G.-D., Y.-T.G., S.M.G., J.A.G.-S., M.M.G., V.Ge., G.G.G., G.G., M.S.G., D.E.G., A.G.-N., G.I.G.A., M.Gr., J.G., A.G., P.G., L.H., E.H., C.A.H., N.Hå., U.H., S.Ha., P.Har., S.N.H., J.M.H., M.H., A.He., J.H., P.Hi., D.N.H., A.Ho., M.J.H., R.N.H., J.L.H., M.-F.H., C.-N.H., G.H., K.H., J.I., H.It., M.I., H.Iw., A.J., W.J., E.M.J., N.J., M.J., A.J.-V., R.Ka., M.K., K.K., D.K., Y.K., M.J.K., S.Kh., E.K., J.I.K., S.-W.K., J.A.K., V.-M.K., I.M.K., V.N.K., U.K., A.K., D.L., L.L.M., C.N.L., E.L., J.W.L., M.H.L., F.L., J. Li, J.Lil., A.Li., J.Lis., R.L., W.-Y.L., S.Lo., J.Lo., A.Lo., J.Lu., M.P.L., E.S.K.M., R.J.M., T.M., E.M., K.E.M., A.Ma., S.Man., J.E.M., S.Marg., S.Mari., M.E.M., K.Ma., D.M., J.Mc., C.Mc., H.M.-H., A.Me., P.M., U.M., H.M., N.M., K.Mu., A.M.M., C.Mu., S.L.N., H.N., P.N., S.F.N., D.-Y.N., B.G.N., A.N., O.I.O., J.E.O., H.O., C.O., N.O., V.S.P., S.K.P., T.-W.P.-S., J.I.A.P., P.P., J.P., K.-A.P., M.P., D.P.-K., R.P., N.P., D.P., K.P., B.R., P.R., N.R., G.R., H.S.R., V.R., A.Rom., K.J.R., T.R., A.Ru., M.R., E.J.T.R., E.S., D.P.S., S.Sa., E.J.S., D.F.S., R.K.S., A.Sc., M.J.Sc., F.S., P.Sc., C.Sc., R.J.S., S.Se., C.Se., M.S., P.Sh., C.-Y.S., M.E.S., M.J.Sh., X.-O.S., A.Sm., C.So., M.C.S., J.J.S., C.St., S.S.-B., J.St., D.O.S., H.S., A.Sw., N.A.M.T., R.T., J.A.T., M.T., S.H.T., M.B.T., S.Th., K.T., R.A.E.M.T., I.T., L.T., D.T., T.T., C.-C.T., S.Ts., H.-U.U., M.U., G.U., C.V., C.J.v.A., A.M.W.v.d.O., L.v.d.K., R.B.v.d.L., Q.Wai., S.W.-G., C.R.W., C.W., A.S.W., H.W., W.W., R.W., A.W., A.H.W., T.Y., X.R.Y., C.H.Y., K.-Y.Y., J.-C.Y., W.Z., Y.Z., A.Z., E.Z., ABCTB Investigators, kConFab/AOCS Investigators, NBCS Collaborators, A.C.A., I.L.A., F.J.C., P.D.P.P., J.C.-C., P.Hal., D.J.H., R.L.M., M.G.-C., M.K.S., G.D.B., J.Si., P.K. and D.F.E. All authors read and approved the final version of the manuscript.
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Extended data figures and tables
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 credible risk variants (CRVs) within each locus. On the x axis, each column represents a CRV (see 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 markers (dark green), histone markers (blue), open chromatin markers (dark blue) and transcription factor binding sites (dark violet). Coloured elements indicate SNPs for which the feature is present. For data sources, see Methods (In silico analysis of CRVs).
Extended Data Figure 2 Pathway enrichment map for susceptibility loci based on summary association statistics.
Each coloured circle (node) represents a pathway (gene set), coloured by enrichment score 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 Heat map showing patterns of cell-type-specific enrichments for breast tissue across three histone marks (H3K4me1, H3K4me3 and H3K9ac) for all breast cancer types, ER-positive breast cancer and ER-negative breast cancer as well as 16 other traits.
BC_ERneg, ER-negative breast cancer; BC_ERpos, ER-positive breast cancer; BC_overall, all breast cancer types; BMI, body mass index; CAD, cardiovascular disease; CD, Crohn’s disease; HDL, high-density lipoprotein; LDL, low-density lipoprotein; RA, rheumatoid arthritis; T2D, type 2 diabetes; TG, triglycerides; UC, ulcerative colitis; vHMEC, variant human mammary epithelial cells.
Extended Data Figure 8 Functional assessment of regulatory variants at 1p36, 11p15 and 1p34 risk loci.
a, b, The KLHDC7A (a) or PIDD1 (b) 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. The means and 95% confidence intervals are shown. (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. Top, a physical map of the region analysed by 3C. Grey boxes depict the PREs, blue vertical lines indicate the risk-associated SNPs and the black dotted line represents chromatin looping. Bottom, graphs representing three independent 3C interaction profiles. 3C libraries were generated with EcoRI, grey vertical boxes indicate the interacting restriction fragment (containing PRE1 and PRE2). Means and standard deviations are shown. 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. Top, a physical map of the region interrogated by 3C. Grey horizontal boxes depict the putative regulatory elements (PREs), blue vertical lines indicate the risk-associated SNPs and the black dotted line represents chromatin looping. Bottom, graphs represent three independent 3C interaction profiles between the CUX1 (a), PRKRIP1 (b, d) or RASA4 (c, e) promoter regions and PREs. 3C libraries were generated with EcoRI, grey vertical boxes indicate the interacting restriction fragment (containing PRE1 and/or PRE2). Means and standard deviations are shown. f, g, Allele-specific 3C. 3C followed by Sanger sequencing for the PRKRIP1-PRE2 (f) or RASA4-PRE1 or -PRE2 (g) in heterozygous MDA-MB-231 breast cancer cells.
Supplementary information
Supplementary Information
This file contains Supplementary Tables 1, 2 and 24, a Supplementary Note, Funding Information, Study Acknowledgments, Members of Consortia listed as Authors, Supplementary References and a Supplementary Table Guide. (PDF 659 kb)
Supplementary Data
This file contains Supplementary Tables 3–5, 7, 9–12, 14–17, 21–23 and 25–33 – see the Supplementary Table Guide in the Supplementary Information document for full descriptions. (XLSX 1115 kb)
Supplementary Table 6
This table contains sixty-five newly identified susceptibility loci for overall breast cancer. (XLSX 17 kb)
Supplementary Table 8
This table contains summary statistics for all variants for which the association with overall breast cancer in the combined dataset was significant at P<0.00001. (XLSX 17279 kb)
Supplementary Table 13
This table contains a list of 2,221 credible variants at 65 novel loci, with annotations, UCSC Genome Browser links, and sources for genomic annotation data. (XLSX 684 kb)
Supplementary Table 18
This table displays eQTL associations significant at P<0.05 in the TCGA and METABRIC datasets, for credible risk variants from the analyses for overall breast cancer (see Methods), together with the corresponding results for the most significant eQTL association in the region for the same gene. (XLSX 3630 kb)
Supplementary Table 19
This table contains summary INQUISIT gene prediction scores. (XLSX 52 kb)
Supplementary Table 20
This table contains detailed INQUISIT gene prediction scores. (XLSX 102 kb)
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Michailidou, K., Lindström, S., Dennis, J. et al. Association analysis identifies 65 new breast cancer risk loci. Nature 551, 92–94 (2017). https://doi.org/10.1038/nature24284
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DOI: https://doi.org/10.1038/nature24284
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