Genome-wide association studies (GWASs) have revealed increased breast cancer risk associated with multiple genetic variants at 5p12. Here, we report the fine mapping of this locus using data from 104,660 subjects from 50 case-control studies in the Breast Cancer Association Consortium (BCAC). With data for 3,365 genotyped and imputed SNPs across a 1 Mb region (positions 44,394,495-45,364,167; NCBI build 37), we found evidence for at least three independent signals: the strongest signal, consisting of a single SNP rs10941679, was associated with risk of estrogen-receptor-positive (ER+) breast cancer (per-g allele OR ER+ = 1.15; 95% CI 1.13-1.18; p = 8.35 × 10-30). After adjustment for rs10941679, we detected signal 2, consisting of 38 SNPs more strongly associated with ER-negative (ER-) breast cancer (lead SNP rs6864776: per-a allele OR ER- = 1.10; 95% CI 1.05-1.14; p conditional = 1.44 × 10-12), and a single signal 3 SNP (rs200229088: per-t allele OR ER+ = 1.12; 95% CI 1.09-1.15; p conditional = 1.12 × 10-05). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed that the g (risk) allele of rs10941679 was associated with increased expression of FGF10 and MRPS30. Functional assays demonstrated that SNP rs10941679 maps to an enhancer element that physically interacts with the FGF10 and MRPS30 promoter regions in breast cancer cell lines. FGF10 is an oncogene that binds to FGFR2 and is overexpressed in ∼10% of human breast cancers, whereas MRPS30 plays a key role in apoptosis. These data suggest that the strongest signal of association at 5p12 is mediated through coordinated activation of FGF10 and MRPS30, two candidate genes for breast cancer pathogenesis.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

In a systematic sequencing screen of the coding exons of the X chromosome in 250 families with X-linked mental retardation (XLMR), we identified two nonsense mutations and one consensus splice-site mutation in the AP1S2 gene on Xp22 in three families. Affected individuals in these families showed mild-to-profound mental retardation. Other features included hypotonia early in life and delay in walking. AP1S2 encodes an adaptin protein that constitutes part of the adaptor protein complex found at the cytoplasmic face of coated vesicles located at the Golgi complex. The complex mediates the recruitment of clathrin to the vesicle membrane. Aberrant endocytic processing through disruption of adaptor protein complexes is likely to result from the AP1S2 mutations identified in the three XLMR-affected families, and such defects may plausibly cause abnormal synaptic development and function. AP1S2 is the first reported XLMR gene that encodes a protein directly involved in the assembly of endocytic vesicles.

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.

The 10q26 locus in the second intron of FGFR2 is the locus most strongly associated with estrogen-receptor-positive breast cancer in genome-wide association studies. We conducted fine-scale mapping in case-control studies genotyped with a custom chip (iCOGS), comprising 41 studies (n = 89,050) of European ancestry, 9 Asian ancestry studies (n = 13,983), and 2 African ancestry studies (n = 2,028) from the Breast Cancer Association Consortium. We identified three statistically independent risk signals within the locus. Within risk signals 1 and 3, genetic analysis identified five and two variants, respectively, highly correlated with the most strongly associated SNPs. By using a combination of genetic fine mapping, data on DNase hypersensitivity, and electrophoretic mobility shift assays to study protein-DNA binding, we identified rs35054928, rs2981578, and rs45631563 as putative functional SNPs. Chromatin immunoprecipitation showed that FOXA1 preferentially bound to the risk-associated allele (C) of rs2981578 and was able to recruit ERα to this site in an allele-specific manner, whereas E2F1 preferentially bound the risk variant of rs35054928. The risk alleles were preferentially found in open chromatin and bound by Ser5 phosphorylated RNA polymerase II, suggesting that the risk alleles are associated with changes in transcription. Chromatin conformation capture demonstrated that the risk region was able to interact with the promoter of FGFR2, the likely target gene of this risk region. A role for FOXA1 in mediating breast cancer susceptibility at this locus is consistent with the finding that the FGFR2 risk locus primarily predisposes to estrogen-receptor-positive disease.

The genetic basis of many common human diseases is expected to be highly heterogeneous, with multiple causative loci and multiple alleles at some of the causative loci. Analyzing the association of disease with one genetic marker at a time can have weak power, because of relatively small genetic effects and the need to correct for multiple testing. Testing the simultaneous effects of multiple markers by multivariate statistics might improve power, but they too will not be very powerful when there are many markers, because of the many degrees of freedom. To overcome some of the limitations of current statistical methods for case-control studies of candidate genes, we develop a new class of nonparametric statistics that can simultaneously test the association of multiple markers with disease, with only a single degree of freedom. Our approach, which is based on U-statistics, first measures a score over all markers for pairs of subjects and then compares the averages of these scores between cases and controls. Genetic scoring for a pair of subjects is measured by a "kernel" function, which we allow to be fairly general. However, we provide guidelines on how to choose a kernel for different types of genetic effects. Our global statistic has the advantage of having only one degree of freedom and achieves its greatest power advantage when the contrasts of average genotype scores between cases and controls are in the same direction across multiple markers. Simulations illustrate that our proposed methods have the anticipated type I-error rate and that they can be more powerful than standard methods. Application of our methods to a study of candidate genes for prostate cancer illustrates their potential merits, and offers guidelines for interpretation.

We have identified one frameshift mutation, one splice-site mutation, and two missense mutations in highly conserved residues in ZDHHC9 at Xq26.1 in 4 of 250 families with X-linked mental retardation (XLMR). In three of the families, the mental retardation phenotype is associated with a Marfanoid habitus, although none of the affected individuals meets the Ghent criteria for Marfan syndrome. ZDHHC9 is a palmitoyltransferase that catalyzes the posttranslational modification of NRAS and HRAS. The degree of palmitoylation determines the temporal and spatial location of these proteins in the plasma membrane and Golgi complex. The finding of mutations in ZDHHC9 suggests that alterations in the concentrations and cellular distribution of target proteins are sufficient to cause disease. This is the first XLMR gene to be reported that encodes a posttranslational modification enzyme, palmitoyltransferase. Furthermore, now that the first palmitoyltransferase that causes mental retardation has been identified, defects in other palmitoylation transferases become good candidates for causing other mental retardation syndromes.

Mutation screening of the breast and ovarian cancer-predisposition genes BRCA1 and BRCA2 is becoming an increasingly important part of clinical practice. Classification of rare nontruncating sequence variants in these genes is problematic, because it is not known whether these subtle changes alter function sufficiently to predispose cells to cancer development. Using data from the Myriad Genetic Laboratories database of nearly 70,000 full-sequence tests, we assessed the clinical significance of 1,433 sequence variants of unknown significance (VUSs) in the BRCA genes. Three independent measures were employed in the assessment: co-occurrence in trans of a VUS with known deleterious mutations; detailed analysis, by logistic regression, of personal and family history of cancer in VUS-carrying probands; and, in a subset of probands, an analysis of cosegregation with disease in pedigrees. For each of these factors, a likelihood ratio was computed under the hypothesis that the VUSs were equivalent to an "average" deleterious mutation, compared with neutral, with respect to risk. The likelihood ratios derived from each component were combined to provide an overall assessment for each VUS. A total of 133 VUSs had odds of at least 100 : 1 in favor of neutrality with respect to risk, whereas 43 had odds of at least 20 : 1 in favor of being deleterious. VUSs with evidence in favor of causality were those that were predicted to affect splicing, fell at positions that are highly conserved among BRCA orthologs, and were more likely to be located in specific domains of the proteins. In addition to their utility for improved genetics counseling of patients and their families, the global assessment reported here will be invaluable for validation of functional assays, structural models, and in silico analyses.

Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.

A recent meta-analysis of multiple genome-wide association and follow-up endometrial cancer case-control datasets identified a novel genetic risk locus for this disease at chromosome 14q32.33. To prioritize the functional SNP(s) and target gene(s) at this locus, we employed an in silico fine-mapping approach using genotyped and imputed SNP data for 6,608 endometrial cancer cases and 37,925 controls of European ancestry. Association and functional analyses provide evidence that the best candidate causal SNP is rs2494737. Multiple experimental analyses show that SNP rs2494737 maps to a silencer element located within AKT1, a member of the PI3K/AKT/MTOR intracellular signaling pathway activated in endometrial tumors. The rs2494737 risk A allele creates a YY1 transcription factor-binding site and abrogates the silencer activity in luciferase assays, an effect mimicked by transfection of YY1 siRNA. Our findings suggest YY1 is a positive regulator of AKT1, mediating the stimulatory effects of rs2494737 increasing endometrial cancer risk. Identification of an endometrial cancer risk allele within a member of the PI3K/AKT signaling pathway, more commonly activated in tumors by somatic alterations, raises the possibility that well tolerated inhibitors targeting this pathway could be candidates for evaluation as chemopreventive agents in individuals at high risk of developing endometrial cancer.

RAD51 is an important component of double-stranded DNA-repair mechanisms that interacts with both BRCA1 and BRCA2. A single-nucleotide polymorphism (SNP) in the 5' untranslated region (UTR) of RAD51, 135G-->C, has been suggested as a possible modifier of breast cancer risk in BRCA1 and BRCA2 mutation carriers. We pooled genotype data for 8,512 female mutation carriers from 19 studies for the RAD51 135G-->C SNP. We found evidence of an increased breast cancer risk in CC homozygotes (hazard ratio [HR] 1.92 [95% confidence interval {CI} 1.25-2.94) but not in heterozygotes (HR 0.95 [95% CI 0.83-1.07]; P=.002, by heterogeneity test with 2 degrees of freedom [df]). When BRCA1 and BRCA2 mutation carriers were analyzed separately, the increased risk was statistically significant only among BRCA2 mutation carriers, in whom we observed HRs of 1.17 (95% CI 0.91-1.51) among heterozygotes and 3.18 (95% CI 1.39-7.27) among rare homozygotes (P=.0007, by heterogeneity test with 2 df). In addition, we determined that the 135G-->C variant affects RAD51 splicing within the 5' UTR. Thus, 135G-->C may modify the risk of breast cancer in BRCA2 mutation carriers by altering the expression of RAD51. RAD51 is the first gene to be reliably identified as a modifier of risk among BRCA1/2 mutation carriers.

The DNA-damage-signaling pathway has been implicated in all human cancers. However, the genetic defects and the mechanisms of this pathway in prostate carcinogenesis remain poorly understood. In this study, we analyzed CHEK2, the upstream regulator of p53 in the DNA-damage-signaling pathway, in several groups of patients with prostate cancer. A total of 28 (4.8%) germline CHEK2 mutations (16 of which were unique) were found among 578 patients. Additional screening for CHEK2 mutations in 149 families with familial prostate cancer revealed 11 mutations (5 unique) in nine families. These mutations included two frameshift and three missense mutations. Importantly, 16 of 18 unique CHEK2 mutations identified in both sporadic and familial cases were not detected among 423 unaffected men, suggesting a pathological effect of CHEK2 mutations in prostate cancer development. Analyses of the two frameshift mutations in Epstein Barr virus-transformed cell lines, using reverse-transcriptase polymerase chain reaction and western blot analysis, revealed abnormal splicing for one mutation and dramatic reduction of CHEK2 protein levels in both cases. Overall, our data suggest that mutations in CHEK2 may contribute to prostate cancer risk and that the DNA-damage-signaling pathway may play an important role in the development of prostate cancer.

Many sequence variants in predisposition genes are of uncertain clinical significance, and classification of these variants into high- or low-risk categories is an important problem in clinical genetics. Classification of such variants can be performed by direct epidemiological observations, including cosegregation with disease in families and degree of family history of the disease, or by indirect measures, including amino acid conservation, severity of amino acid change, and evidence from functional assays. In this study, we have developed an approach to the synthesis of such evidence in a multifactorial likelihood-ratio model. We applied this model to the analysis of three unclassified variants in BRCA1 and three in BRCA2. The evidence strongly suggests that two variants (C1787S in BRCA1 and D2723H in BRCA2) are deleterious, three (R841W in BRCA1 and Y42C and P655R in BRCA2) are neutral, and one (R1699Q in BRCA1) remains of uncertain significance. These results provide a demonstration of the utility of the model.

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.

We have identified three truncating, two splice-site, and three missense variants at conserved amino acids in the CUL4B gene on Xq24 in 8 of 250 families with X-linked mental retardation (XLMR). During affected subjects' adolescence, a syndrome emerged with delayed puberty, hypogonadism, relative macrocephaly, moderate short stature, central obesity, unprovoked aggressive outbursts, fine intention tremor, pes cavus, and abnormalities of the toes. This syndrome was first described by Cazebas et al., in a family that was included in our study and that carried a CUL4B missense variant. CUL4B is a ubiquitin E3 ligase subunit implicated in the regulation of several biological processes, and CUL4B is the first XLMR gene that encodes an E3 ubiquitin ligase. The relatively high frequency of CUL4B mutations in this series indicates that it is one of the most commonly mutated genes underlying XLMR and suggests that its introduction into clinical diagnostics should be a high priority.

Genome-wide association studies (GWASs) have revealed SNP rs889312 on 5q11.2 to be associated with breast cancer risk in women of European ancestry. In an attempt to identify the biologically relevant variants, we analyzed 909 genetic variants across 5q11.2 in 103,991 breast cancer individuals and control individuals from 52 studies in the Breast Cancer Association Consortium. Multiple logistic regression analyses identified three independent risk signals: the strongest associations were with 15 correlated variants (iCHAV1), where the minor allele of the best candidate, rs62355902, associated with significantly increased risks of both estrogen-receptor-positive (ER(+): odds ratio [OR] = 1.24, 95% confidence interval [CI] = 1.21-1.27, ptrend = 5.7 × 10(-44)) and estrogen-receptor-negative (ER(-): OR = 1.10, 95% CI = 1.05-1.15, ptrend = 3.0 × 10(-4)) tumors. After adjustment for rs62355902, we found evidence of association of a further 173 variants (iCHAV2) containing three subsets with a range of effects (the strongest was rs113317823 [pcond = 1.61 × 10(-5)]) and five variants composing iCHAV3 (lead rs11949391; ER(+): OR = 0.90, 95% CI = 0.87-0.93, pcond = 1.4 × 10(-4)). Twenty-six percent of the prioritized candidate variants coincided with four putative regulatory elements that interact with the MAP3K1 promoter through chromatin looping and affect MAP3K1 promoter activity. Functional analysis indicated that the cancer risk alleles of four candidates (rs74345699 and rs62355900 [iCHAV1], rs16886397 [iCHAV2a], and rs17432750 [iCHAV3]) increased MAP3K1 transcriptional activity. Chromatin immunoprecipitation analysis revealed diminished GATA3 binding to the minor (cancer-protective) allele of rs17432750, indicating a mechanism for its action. We propose that the cancer risk alleles act to increase MAP3K1 expression in vivo and might promote breast cancer cell survival.

The high-grade serous ovarian cancer (HGSOC) risk locus at chromosome 1p34.3 resides within a frequently amplified genomic region signifying the presence of an oncogene. Here, we integrate in silico variant-to-function analysis with functional studies to characterize the oncogenic potential of candidate genes in the 1p34.3 locus. Fine mapping of genome-wide association statistics identified candidate causal SNPs local to H3K27ac-demarcated enhancer regions that exhibit allele-specific binding for CTCF in HGSOC and normal fallopian tube secretory epithelium cells (FTSECs). SNP risk associations colocalized with eQTL for six genes (DNALI1, GNL2, RSPO1, SNIP1, MEAF6, and LINC01137) that are more highly expressed in carriers of the risk allele, and three (DNALI1, GNL2, and RSPO1) were upregulated in HGSOC compared to normal ovarian surface epithelium cells and/or FTSECs. Increased expression of GNL2 and MEAF6 was associated with shorter survival in HGSOC with 1p34.3 amplifications. Despite its activation of β-catenin signaling, RSPO1 overexpression exerted no effects on proliferation or colony formation in our study of ovarian cancer and FTSECs. Instead, GNL2, MEAF6, and SNIP1 silencing impaired in vitro ovarian cancer cell growth. Additionally, GNL2 silencing diminished xenograft tumor formation, whereas overexpression stimulated proliferation and colony formation in FTSECs. GNL2 influences 60S ribosomal subunit maturation and global protein synthesis in ovarian cancer and FTSECs, providing a potential mechanism of how GNL2 upregulation might promote ovarian cancer development and mediate genetic susceptibility of HGSOC.