Abstract
We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88–0.92]; P-value = 1.58 × 10−25). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08–1.17]; P-value = 7.89 × 10−09) and rs13294895 (OR = 1.09 [1.06–1.12]; P-value = 2.97 × 10−11). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06–1.18]; P-value = 2.77 × 10−05). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.
Highlights
Breast cancer is the most common female cancer worldwide, in both developed and less developed regions, including Asia and Africa
We used statistical imputation of unobserved genotypes to increase the density of our finemapping analysis; a total of 2035 Single nucleotide polymorphism (SNP) and insertion/deletion polymorphisms were inferred using 1000 Genomes Project (1KGP) reference data, from which 1529 variants were imputed with high certainty (Impute2 [22] information measure ≥0.5) and included in subsequent association analyses
Because no imputed variant was more significantly associated with breast cancer risk than the highest ranked, directly genotyped SNPs, they were not considered in the following analyses unless explicitly stated
Summary
Breast cancer is the most common female cancer worldwide, in both developed and less developed regions, including Asia and Africa. Susceptibility to breast cancer involves contributions from genetic, environmental, lifestyle and hormonal factors. Rare germline variants in genes including CHEK2, PALB2 and ATM each confer moderately increased relative risks (RR) of breast cancer but make only small contributions to the excess FRR [3,4,5]. Genetic variants can be incorporated into risk prediction models that can stratify women by level of risk. The power of such models will improve as more variants are identified [20]. One productive approach to identifying additional susceptibility variants is through fine-mapping of regions known to harbour susceptibility alleles
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