Association analysis identifies 65 new breast cancer risk loci.

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.

Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus.

BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.

Functional variants at the 11q13 risk locus for breast cancer regulate cyclin D1 expression through long-range enhancers.

Analysis of 4,405 variants in 89,050 European subjects from 41 case-control studies identified three independent association signals for estrogen-receptor-positive tumors at 11q13. The strongest signal maps to a transcriptional enhancer element in which the G allele of the best candidate causative variant rs554219 increases risk of breast cancer, reduces both binding of ELK4 transcription factor and luciferase activity in reporter assays, and may be associated with low cyclin D1 protein levels in tumors. Another candidate variant, rs78540526, lies in the same enhancer element. Risk association signal 2, rs75915166, creates a GATA3 binding site within a silencer element. Chromatin conformation studies demonstrate that these enhancer and silencer elements interact with each other and with their likely target gene, CCND1.

Identification of a BRCA2-specific modifier locus at 6p24 related to breast cancer risk.

Common genetic variants contribute to the observed variation in breast cancer risk for BRCA2 mutation carriers; those known to date have all been found through population-based genome-wide association studies (GWAS). To comprehensively identify breast cancer risk modifying loci for BRCA2 mutation carriers, we conducted a deep replication of an ongoing GWAS discovery study. Using the ranked P-values of the breast cancer associations with the imputed genotype of 1.4 M SNPs, 19,029 SNPs were selected and designed for inclusion on a custom Illumina array that included a total of 211,155 SNPs as part of a multi-consortial project. DNA samples from 3,881 breast cancer affected and 4,330 unaffected BRCA2 mutation carriers from 47 studies belonging to the Consortium of Investigators of Modifiers of BRCA1/2 were genotyped and available for analysis. We replicated previously reported breast cancer susceptibility alleles in these BRCA2 mutation carriers and for several regions (including FGFR2, MAP3K1, CDKN2A/B, and PTHLH) identified SNPs that have stronger evidence of association than those previously published. We also identified a novel susceptibility allele at 6p24 that was inversely associated with risk in BRCA2 mutation carriers (rs9348512; per allele HR = 0.85, 95% CI 0.80-0.90, P = 3.9 × 10(-8)). This SNP was not associated with breast cancer risk either in the general population or in BRCA1 mutation carriers. The locus lies within a region containing TFAP2A, which encodes a transcriptional activation protein that interacts with several tumor suppressor genes. This report identifies the first breast cancer risk locus specific to a BRCA2 mutation background. This comprehensive update of novel and previously reported breast cancer susceptibility loci contributes to the establishment of a panel of SNPs that modify breast cancer risk in BRCA2 mutation carriers. This panel may have clinical utility for women with BRCA2 mutations weighing options for medical prevention of breast cancer.

Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk.

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7 × 10(-8), HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4 × 10(-8), HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4 × 10(-8), HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10(-4)). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%-50% compared to 81%-100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.

Common genetic determinants of breast-cancer risk in East Asian women: a collaborative study of 23 637 breast cancer cases and 25 579 controls.

In a consortium including 23 637 breast cancer patients and 25 579 controls of East Asian ancestry, we investigated 70 single-nucleotide polymorphisms (SNPs) in 67 independent breast cancer susceptibility loci recently identified by genome-wide association studies (GWASs) conducted primarily in European-ancestry populations. SNPs in 31 loci showed an association with breast cancer risk at P < 0.05 in a direction consistent with that reported previously. Twenty-one of them remained statistically significant after adjusting for multiple comparisons with the Bonferroni-corrected significance level of <0.0015. Eight of the 70 SNPs showed a significantly different association with breast cancer risk by estrogen receptor (ER) status at P < 0.05. With the exception of rs2046210 at 6q25.1, the seven other SNPs showed a stronger association with ER-positive than ER-negative cancer. This study replicated all five genetic risk variants initially identified in Asians and provided evidence for associations of breast cancer risk in the East Asian population with nearly half of the genetic risk variants initially reported in GWASs conducted in European descendants. Taken together, these common genetic risk variants explain ~10% of excess familial risk of breast cancer in Asian populations.

Identification of susceptibility genes for complex diseases using pooling-based genome-wide association scans.

The success of genome-wide association studies (GWAS) to identify risk loci of complex diseases is now well-established. One persistent major hurdle is the cost of those studies, which make them beyond the reach of most research groups. Performing GWAS on pools of DNA samples may be an effective strategy to reduce the costs of these studies. In this study, we performed pooling-based GWAS with more than 550,000 SNPs in two case-control cohorts consisting of patients with Type II diabetes (T2DM) and with chronic rhinosinusitis (CRS). In the T2DM study, the results of the pooling experiment were compared to individual genotypes obtained from a previously published GWAS. TCF7L2 and HHEX SNPs associated with T2DM by the traditional GWAS were among the top ranked SNPs in the pooling experiment. This dataset was also used to refine the best strategy to correctly identify SNPs that will remain significant based on individual genotyping. In the CRS study, the top hits from the pooling-based GWAS located within ten kilobases of known genes were validated by individual genotyping of 1,536 SNPs. Forty-one percent (598 out of the 1,457 SNPs that passed quality control) were associated with CRS at a nominal P value of 0.05, confirming the potential of pooling-based GWAS to identify SNPs that differ in allele frequencies between two groups of subjects. Overall, our results demonstrate that a pooling experiment on high-density genotyping arrays can accurately determine the minor allelic frequency as compared to individual genotyping and produce a list of top ranked SNPs that captures genuine allelic differences between a group of cases and controls. The low cost associated with a pooling-based GWAS clearly justifies its use in screening for genetic determinants of complex diseases.

Genetic control of alternative splicing in the TAP2 gene: possible implication in the genetics of type 1 diabetes.

The transporter 2, ATP-binding cassette, subfamily B (TAP2) is involved in the transport of antigenic peptides to HLA molecules. Coding TAP2 polymorphisms shows a strong association with type 1 diabetes, but it is not clear whether this association may be entirely due to linkage disequilibrium with HLA DR and DQ. Functionally, rat Tap2 nonsynonymous single-nucleotide polymorphisms (nsSNPs) confer differential selectivity for antigenic peptides, but this was not shown to be the case for human TAP2 nsSNPs. In the human, differential peptide selectivity is rather conferred by two splicing isoforms with alternative carboxy terminals. Here, we tested the hypothesis that alleles at the coding SNPs favor different splicing isoforms, thus determining peptide selectivity indirectly. This may be the basis for independent contribution to the type 1 diabetes association. In RNA from heterozygous lymphoblastoid lines, we measured the relative abundance of each SNP haplotype in each isoform. In isoform NM_000544, the G (Ala) allele at 665 Thr>Ala (rs241447) is more than twice as abundant as A (Thr) (GA = 2.2 +/- 0.4, P = 1.5 x 10(-4)), while isoform NM_018833 is derived almost exclusively from chromosomes carrying A (AG = 18.1 +/- 5.6, P = 2.04 x 10(-7)). In 889 Canadian children with type 1 diabetes, differential transmission of parental TAP2 alleles persisted (P = 0.011) when analysis was confined to chromosomes carrying only DQ*02 alleles, which mark a conserved DR-DQ haplotype, thus eliminating most of the variation at DR-DQ. Thus, we present evidence of TAP2 association with type 1 diabetes that is independent of HLA DR-DQ and describe a plausible functional mechanism based on allele dependence of splicing into isoforms known to have differential peptide selectivities.

No association of type 1 diabetes with a functional polymorphism of the LRAP gene.

AIMS/HYPOTHESIS: In a recent linkage analysis of genome-wide gene-expression patterns in lymphoblastoid lines, the gene encoding the leukocyte-derived arginine aminopeptidase (LRAP) was identified as having its expression levels modulated by one of the most pronounced effects in cis, mapping to a single-nucleotide polymorphism (rs2762). As this enzyme has an important role in processing antigenic peptides for the HLA I molecules, a variant that drastically modulates its expression levels might affect risk of autoimmunity. This study was designed to confirm that LRAP expression in B-cell derived lines is controlled by a haplotype marked by rs2762 and to see whether this would be the basis of an association with type 1 diabetes (T1D). METHODS: Single-nucleotide primer extension (SNuPE) was adapted to determine the haplotype-specific expression. Genetic association was tested in 892 nuclear families with one T1D-affected offspring and two parents (2676 individuals). RESULTS: All nine heterozygous RNA samples showed an eight-fold higher level of one haplotype over the other (7.97+/-0.99, p=1.33x10(-9)). However, no association of rs2762 with T1D was found by the transmission disequilibrium test (transmission ratio A/G=377/388, p=0.69). CONCLUSIONS/INTERPRETATION: The genetically determined LRAP expression does not play significant roles in T1D. However, this dramatic genetic effect on LRAP expression justifies further investigation of association with other phenotypes, especially autoimmune and related to host defense to specific pathogens.

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

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.

The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers.

BACKGROUND: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. METHODS: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. RESULTS: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. CONCLUSIONS: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. IMPACT: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR.

Variations in 5-methylcytosine and 5-hydroxymethylcytosine among human brain, blood, and saliva using oxBS and the Infinium MethylationEPIC array.

Investigating 5-methylcytosine (5mC) has led to many hypotheses regarding molecular mechanism underlying human diseases and disorders. Many of these studies, however, utilize bisulfite conversion alone, which cannot distinguish 5mC from its recently discovered oxidative product, 5-hydroxymethylcytosine (5hmC). Furthermore, previous array-based technologies do not have the necessary probes to adequately investigate both modifications simultaneously. In this manuscript, we used technical replicates of DNA from human brain, human blood, and human saliva, in combination with oxidative bisulfite conversion and Illumina's Infinium MethylationEPIC array, to analyze 5mC and 5hmC at more than 650 000 and 450 000 relevant loci, respectively, in the human genome. We show the presence of loci with detectable 5mC and 5hmC to be equally distributed across chromosomes and genomic features, while also being present in genomic regions with transcriptional regulatory properties. We also describe 2528 5hmC sites common across tissue types that show a strong association with immune-related functions. Lastly, in human brain, we show that 5hmC accounts for one-third of the total signal from bisulfite-converted data. As such, not only do our results confirm the efficacy and sensitivity of pairing oxidative bisulfite conversion and the EPIC array to detect 5mC and 5hmC in all three tissue types, but they also highlight the importance of dissociating 5hmC from 5mC in future studies related to cytosine modifications.

Large-scale genotyping identifies 41 new loci associated with breast cancer risk.

Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping. These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC). The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs. We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P < 5 × 10(-8)). Further analyses suggest that more than 1,000 additional loci are involved in breast cancer susceptibility.

Identification and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31.

Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully characterized. Most identified common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3' untranslated region at putative microRNA (miRNA)-binding sites represent functional targets that influence EOC susceptibility. Here, we evaluate the association between 767 miRNA-related single-nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene-environment Study. We identify several miRSNPs associated with invasive serous EOC risk (odds ratio=1.12, P=10(-8)) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion (P=10(-10)). Variation at 17q21.31 is associated with neurological diseases, and our collaboration is the first to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes.

GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer.

Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have associations close to genome-wide significance and identified three loci newly associated with risk: two loci associated with all EOC subtypes at 8q21 (rs11782652, P = 5.5 × 10(-9)) and 10p12 (rs1243180, P = 1.8 × 10(-8)) and another locus specific to the serous subtype at 17q12 (rs757210, P = 8.1 × 10(-10)). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility and implicated CHMP4C in the pathogenesis of ovarian cancer.

Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia.

Genome-wide association studies have identified common variants that only partially explain the genetic risk for type 2 diabetes (T2D). Using genome-wide association data from 1,376 French individuals, we identified 16,360 SNPs nominally associated with T2D and studied these SNPs in an independent sample of 4,977 French individuals. We then selected the 28 best hits for replication in 7,698 Danish subjects and identified 4 SNPs showing strong association with T2D, one of which (rs2943641, P = 9.3 x 10(-12), OR = 1.19) was located adjacent to the insulin receptor substrate 1 gene (IRS1). Unlike previously reported T2D risk loci, which predominantly associate with impaired beta cell function, the C allele of rs2943641 was associated with insulin resistance and hyperinsulinemia in 14,358 French, Danish and Finnish participants from population-based cohorts; this allele was also associated with reduced basal levels of IRS1 protein and decreased insulin induction of IRS1-associated phosphatidylinositol-3-OH kinase activity in human skeletal muscle biopsies.