Fine‐scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

Abstract

Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. We conducted a fine-mapping study across 2.06 Mb (chr8:127,561,724 −129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium. We found three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional P = 5.8 × 10−6), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional P = 1.1 × 10−6), and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional P = 1.1 × 10−4). Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas, and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r2 = 0.77), were putatively functional variants for two of the five independent association signals. Our results highlight multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.

Fine‐mapping of a novel premenopausal breast cancer susceptibility locus at Chr4q31.22 in Caucasian women and validation in African and Chinese women

“…The fine‐mapped variants in our study are common polymorphisms (MAF 18%). A higher sample size might have enabled the identification of low frequency putative causal variants within the susceptibility locus to gain additional biological insights . Due to the challenges in the functional characterization of the fine‐mapped loci, only a limited number of breast cancer studies successfully identified the target genes ( FGFR2 , CCND1 , MAP3K1 , TERT , IGFBP5 , TET2 , STXBP4 ) with role in breast cancer etiology.…”

“…While fine‐mapping approaches are well described in the literature, it is challenging to elucidate the functional relevance of GWAS SNPs, which are predominantly from noncoding regions conferring potential gene regulatory roles. Thus far, 15 breast cancer associated GWAS variants have been fine‐mapped and characterized for putative biological roles …”

“…Thus far, 15 breast cancer associated GWAS variants have been fine-mapped and characterized for putative biological roles. [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] We previously reported six putative risk variants 21 for breast cancer from a GWAS in European populations (Alberta, Canada), hereafter described also as Caucasian populations, of which four SNPs were from different chromosomes showing association with sporadic (age of disease onset, >40 Years of age and no family history) breast cancer risk. One SNP rs1429142 on Chr4q31.22, showed consistent associations in three independent cohorts for overall risk (Stages 1-3, p = 1.5 × 10 −7 adjusted for body mass index [BMI]; OR 1.28).…”

Gene–environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

“…To improve SNP density, imputation of the respective regions was performed using the March 2012 release of the 1000 Genomes as reference panel. The functional follow‐up work was not carried out centrally for all regions but divided between the different working groups of BCAC and thus the methods used varied somewhat . In addition, imputed genotypes for 15 new susceptibility loci identified through a meta‐analysis of 11 GWAS with genotypes SNPs generated by imputation using the 1000 Genomes Project March 2012 release as the reference panel were used .…”

“…The functional follow-up work was not carried out centrally for all regions but divided between the different working groups of BCAC and thus the methods used varied somewhat. [4][5][6][7][8][9][10][11][12][13][14][15][16][17] In addition, imputed genotypes for 15 new susceptibility loci identified through a meta-analysis of 11 GWAS with genotypes SNPs generated by imputation using the 1000 Genomes Project March 2012 release as the reference panel were used. 5 A list of the 70 SNPs included in the analyses for this report can be found in Supporting Information Table S2.…”