Although familial susceptibility to glioma is known, the genetic basis for this susceptibility remains unidentified in the majority of glioma-specific families. An alternative approach to identifying such genes is to examine cancer pedigrees, which include glioma as one of several cancer phenotypes, to determine whether common chromosomal modifications might account for the familial aggregation of glioma and other cancers.
Germline rearrangements in 146 glioma families (from the Gliogene Consortium; http://www.gliogene.org/) were examined using multiplex ligation-dependent probe amplification. These families all had at least 2 verified glioma cases and a third reported or verified glioma case in the same family or 2 glioma cases in the family with at least one family member affected with melanoma, colon, or breast cancer.The genomic areas covering TP53, CDKN2A, MLH1, and MSH2 were selected because these genes have been previously reported to be associated with cancer pedigrees known to include glioma.
We detected a single structural rearrangement, a deletion of exons 1-6 in MSH2, in the proband of one family with 3 cases with glioma and one relative with colon cancer.
Large deletions and duplications are rare events in familial glioma cases, even in families with a strong family history of cancers that may be involved in known cancer syndromes.
CDKN2A/B; family history; glioma; MLH1; MSH2; TP53
Glioma is a rare, but highly fatal, cancer that accounts for the majority of malignant primary brain tumors. Inherited predisposition to glioma has been consistently observed within non-syndromic families. Our previous studies, which involved non-parametric and parametric linkage analyses, both yielded significant linkage peaks on chromosome 17q. Here, we use data from next generation and Sanger sequencing to identify familial glioma candidate genes and variants on chromosome 17q for further investigation. We applied a filtering schema to narrow the original list of 4830 annotated variants down to 21 very rare (<0.1% frequency), non-synonymous variants. Our findings implicate the MYO19 and KIF18B genes and rare variants in SPAG9 and RUNDC1 as candidates worthy of further investigation. Burden testing and functional studies are planned.
We conducted imputation to the 1000 Genomes Project of four genome-wide association studies of lung cancer in populations of European ancestry (11,348 cases and 15,861 controls) and genotyped an additional 10,246 cases and 38,295 controls for follow-up. We identified large-effect genome-wide associations for squamous lung cancer with the rare variants of BRCA2-K3326X (rs11571833; odds ratio [OR]=2.47, P=4.74×10−20) and of CHEK2-I157T (rs17879961; OR=0.38 P=1.27×10−13). We also showed an association between common variation at 3q28 (TP63; rs13314271; OR=1.13, P=7.22×10−10) and lung adenocarcinoma previously only reported in Asians. These findings provide further evidence for inherited genetic susceptibility to lung cancer and its biological basis. Additionally, our analysis demonstrates that imputation can identify rare disease-causing variants having substantive effects on cancer risk from pre-existing GWAS data.
To identify predisposition loci for classical Hodgkin Lymphoma (cHL) we conducted a genome-wide association study of 589 cHL cases and 5,199 controls with validation in 4 independent samples totaling 2,057 cases and 3,416 controls. We identified three new susceptibility loci at 2p16.1 (rs1432295, REL; odds ratio [OR]=1.22, Pcombined=1.91×10−8), 8q24.21 (rs2019960, PVT1; OR=1.33, Pcombined=1.26×10−13) and 10p14 (rs501764, GATA3; OR=1.25, Pcombined=7.05×10−8). Furthermore, we confirmed the role of the MHC in disease etiology by revealing a strong HLA association (rs6903608; OR=1.70, Pcombined=2.84×10−50). These data provide new insight into the pathogenesis of cHL.
Recent genome-wide association studies (GWASs) have identified common variants at 16 autosomal regions influencing the risk of developing colorectal cancer (CRC). To decipher the genetic basis of the association signals at these loci, we performed a meta-analysis of data from five GWASs, totalling 5626 cases and 7817 controls, using imputation to recover un-typed genotypes. To enhance our ability to discover low-frequency risk variants, in addition to using 1000 Genomes Project data as a reference panel, we made use of high-coverage sequencing data on 253 individuals, 199 with early-onset familial CRC. For 13 of the regions, it was possible to refine the association signal identifying a smaller region of interest likely to harbour the functional variant. Our analysis did not provide evidence that any of the associations at the 16 loci being a consequence of synthetic associations rather than linkage disequilibrium with a common risk variant.
We present VISual Plotting Interface for Genetics (visPIG; http://vispig.icr.ac.uk), a web application to produce multi-track, multi-scale, multi-region plots of genetic data. visPIG has been designed to allow users not well versed with mathematical software packages and/or programming languages such as R , Matlab®, Python, etc., to integrate data from multiple sources for interpretation and to easily create publication-ready figures. While web tools such as the UCSC Genome Browser  or the WashU Epigenome Browser  allow custom data uploads, such tools are primarily designed for data exploration. This is also true for the desktop-run Integrative Genomics Viewer (IGV) ,. Other locally run data visualisation software such as Circos  require significant computer skills of the user. The visPIG web application is a menu-based interface that allows users to upload custom data tracks and set track-specific parameters. Figures can be downloaded as PDF or PNG files. For sensitive data, the underlying R  code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…). It also allows annotation of genes and other custom features in the plotted region(s). Data tracks can be plotted individually or on a single figure. visPIG is multi-region: it supports plotting multiple regions, be they kilo- or megabases apart or even on different chromosomes. Finally, visPIG is multi-scale: a sub-region of particular interest can be 'zoomed' in. We describe the various features of visPIG and illustrate its utility with examples. visPIG is freely available through http://vispig.icr.ac.uk under a GNU General Public License (GPLv3).
Genome sequencing is now a sufficiently mature and affordable technology for clinical use. Its application promises not only to transform clinicians’ diagnostic and predictive ability, but also to improve preventative therapies, surveillance regimes, and tailor patient treatment to an individual’s genetic make-up. However, as with any technological advance, there are associated fresh challenges. While some of the ethical, legal and social aspects resulting from the generation of data from genome sequencing are generic, several nuances are unique. Since the UK government recently announced plans to sequence the genomes of 100,000 Health Service patients, and similar initiatives are being considered elsewhere, a discussion of these nuances is timely and needs to go hand in hand with formulation of guidelines and public engagement activities around implementation of sequencing in clinical practice.
genome sequencing; clinical practice; incidental findings; consent; disclosure
We have previously identified tagSNPs at 8q24.21 influencing glioma risk. We have sought to fine-map the location of the functional basis of this association using data from four genome-wide association studies, comprising a total of 4147 glioma cases and 7435 controls. To improve marker density across the 700 kb region, we imputed genotypes using 1000 Genomes Project data and high-coverage sequencing data generated on 253 individuals. Analysis revealed an imputed low-frequency SNP rs55705857 (P = 2.24 × 10−38) which was sufficient to fully capture the 8q24.21 association. Analysis by glioma subtype showed the association with rs55705857 confined to non-glioblastoma multiforme (non-GBM) tumours (P = 1.07 × 10−67). Validation of the non-GBM association was shown in three additional datasets (625 non-GBM cases, 2412 controls; P = 1.41 × 10−28). In the pooled analysis, the odds ratio for low-grade glioma associated with rs55705857 was 4.3 (P = 2.31 × 10−94). rs55705857 maps to a highly evolutionarily conserved sequence within the long non-coding RNA CCDC26 raising the possibility of direct functionality. These data provide additional insights into the aetiological basis of glioma development.
Identification of single nucleotide polymorphisms (SNPs) associated with development of advanced colorectal adenomas.
Discovery Phase: 1,406 Caucasian patients (139 advanced adenoma cases and 1,267 controls) from the Adenoma Prevention with Celecoxib (APC) trial were included in a genome-wide association study (GWAS) to identify variants associated with post-polypectomy disease recurrence. Genome-wide significance was defined as false discovery rate < 0.05, unadjusted p=7.4×10−7. Validation Phase: Results were further evaluated using 4,175 familial colorectal adenoma or CRC cases and 5,036 controls from patients of European ancestry (COloRectal Gene Identification consortium, Scotland, Australia and VQ58).
Our study identified eight SNPs associated with advanced adenoma risk in the APC trial (rs2837156, rs7278863, rs2837237, rs2837241, rs2837254, rs741864 at 21q22.2, and rs1381392 and rs17651822 at 3p24.1, at p<10–7 level with odds ratio – OR>2). Five variants in strong pairwise linkage disequilbrium (rs7278863, rs2837237, rs741864, rs741864 and rs2837241, r2=0.8–1) are in or near the coding region for the tight junction adhesion protein, IGSF5. An additional variant associated with advanced adenomas, rs1535989 (minor allele frequency 0.11; OR 2.09; 95% confidence interval 1.50–2.91), also predicted CRC development in a validation analysis (p=0.019) using a series of adenoma cases or CRC (CORGI study) and 3 sets of CRC cases and controls (Scotland, VQ58 and Australia, N=9,211).
Our results suggest that common polymorphisms contribute to the risk of developing advanced adenomas and might also contribute to the risk of developing CRC. The variant at rs1535989 may identify patients whose risk for neoplasia warrants increased colonoscopic surveillance.
Colorectal adenomas; colorectal cancer screening; genetic predisposition
This review looks back at five decades of research into genetic susceptibility to colorectal cancer (CRC) and the insights these studies have provided. Initial evidence of a genetic basis of CRC stems from epidemiological studies in the 1950s and is further provided by the existence of multiple dominant predisposition syndromes. Genetic linkage and positional cloning studies identified the first high-penetrance genes for CRC in the 1980s and 1990s. More recent genome-wide association studies have identified common low-penetrance susceptibility loci and provide support for a polygenic model of disease susceptibility. These observations suggest a high proportion of CRC may arise in a group of susceptible individuals as a consequence of the combined effects of common low-penetrance risk alleles and rare variants conferring moderate CRC risks. Despite these advances, however, currently identified loci explain only a small fraction of the estimated heritability to CRC. It is hoped that a new generation of sequencing projects will help explain this missing heritability.
colorectal cancer; genetics; susceptibility
Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) at 7 loci influencing glioma risk: rs2736100 (TERT), rs11979158 and rs2252586 (EGFR), rs4295627 (CCDC26), rs4977756 (CDKN2A/CDKN2B), rs498872 (PHLDB1), and rs6010620 (RTEL1).
Materials and methods
We studied the relationship among these 7 glioma-risk SNPs and characteristics of tumors from 1374 patients, including grade, IDH (ie IDH1 or IDH2) mutation, EGFR amplification, CDKN2A-p16-INK4a homozygous deletion, 9p and 10q loss, and 1p-19q codeletion.
rs2736100 (TERT) and rs6010620 (RTEL1) risk alleles were associated with high-grade disease, EGFR amplification, CDKN2A-p16-INK4a homozygous deletion, and 9p and 10q deletion; rs4295627 (CCDC26) and rs498872 (PHLDB1) were associated with low-grade disease, IDH mutation, and 1p-19q codeletion. In contrast, rs4977756 (CDKN2A/B), rs11979158 (EGFR), and to a lesser extent, rs2252586 (EGFR) risk alleles were independent of tumor grade and genetic profile. Adjusting for tumor grade showed a significant association between rs2736100 and IDH status (P = .01), 10q loss (P = .02); rs4295627 and 1p-19q codeletion (P = .04), rs498872 and IDH (P = .02), 9p loss (P = .04), and 10q loss (P = .02). Case-control analyses stratified into 4 molecular classes (defined by 1p-19q status, IDH mutation, and EGFR amplification) showed an association of rs4295627 and rs498872 with IDH-mutated gliomas (P < 10−3) and rs2736100 and rs6010620 with IDH wild-type gliomas (P < 10−3 and P = .03).
The frequency of EGFR and CDKN2A/B risk alleles were largely independent of tumor genetic profile, whereas TERT, RTEL1, CCDC26, and PHLDB1 variants were associated with different genetic profiles that annotate distinct molecular pathways. Our findings provide further insight into the biological basis of glioma etiology.
etiology; glioma; pathology; SNP
Invasive lobular breast cancer (ILC) accounts for 10–15% of all invasive breast carcinomas. It is generally ER positive (ER+) and often associated with lobular carcinoma in situ (LCIS). Genome-wide association studies have identified more than 70 common polymorphisms that predispose to breast cancer, but these studies included predominantly ductal (IDC) carcinomas. To identify novel common polymorphisms that predispose to ILC and LCIS, we pooled data from 6,023 cases (5,622 ILC, 401 pure LCIS) and 34,271 controls from 36 studies genotyped using the iCOGS chip. Six novel SNPs most strongly associated with ILC/LCIS in the pooled analysis were genotyped in a further 516 lobular cases (482 ILC, 36 LCIS) and 1,467 controls. These analyses identified a lobular-specific SNP at 7q34 (rs11977670, OR (95%CI) for ILC = 1.13 (1.09–1.18), P = 6.0×10−10; P-het for ILC vs IDC ER+ tumors = 1.8×10−4). Of the 75 known breast cancer polymorphisms that were genotyped, 56 were associated with ILC and 15 with LCIS at P<0.05. Two SNPs showed significantly stronger associations for ILC than LCIS (rs2981579/10q26/FGFR2, P-het = 0.04 and rs889312/5q11/MAP3K1, P-het = 0.03); and two showed stronger associations for LCIS than ILC (rs6678914/1q32/LGR6, P-het = 0.001 and rs1752911/6q14, P-het = 0.04). In addition, seven of the 75 known loci showed significant differences between ER+ tumors with IDC and ILC histology, three of these showing stronger associations for ILC (rs11249433/1p11, rs2981579/10q26/FGFR2 and rs10995190/10q21/ZNF365) and four associated only with IDC (5p12/rs10941679; rs2588809/14q24/RAD51L1, rs6472903/8q21 and rs1550623/2q31/CDCA7). In conclusion, we have identified one novel lobular breast cancer specific predisposition polymorphism at 7q34, and shown for the first time that common breast cancer polymorphisms predispose to LCIS. We have shown that many of the ER+ breast cancer predisposition loci also predispose to ILC, although there is some heterogeneity between ER+ lobular and ER+ IDC tumors. These data provide evidence for overlapping, but distinct etiological pathways within ER+ breast cancer between morphological subtypes.
Invasive lobular breast cancer (ILC) accounts for 10–15% of invasive breast cancer and is generally ER positive (ER+). To date, none of the genome-wide association studies that have identified loci that predispose to breast cancer in general or to ER+ or ER-negative breast cancer have focused on lobular breast cancer. In this lobular breast cancer study we identified a new variant that appears to be specific to this morphological subtype. We also ascertained which of the known variants predisposes specifically to lobular breast cancer and show for the first time that some of these loci are also associated with lobular carcinoma in situ, a non-obligate precursor of breast cancer and also a risk factor for contralateral breast cancer. Our study shows that the genetic pathways of invasive lobular cancer and ER+ ductal carcinoma mostly overlap, but there are important differences that are likely to provide insights into the biology of lobular breast tumors.
While certain inherited syndromes (e.g. Neurofibromatosis or Li-Fraumeni) are associated with an increased risk of glioma, most familial gliomas are non-syndromic. This study describes the demographic and clinical characteristics of the largest series of non-syndromic glioma families ascertained from 14 centres in the United States (US), Europe and Israel as part of the Gliogene Consortium.
Families with 2 or more verified gliomas were recruited between January 2007 and February 2011. Distributions of demographic characteristics and clinical variables of gliomas in the families were described based on information derived from personal questionnaires.
The study population comprised 841 glioma patients identified in 376 families (9797 individuals). There were more cases of glioma among males, with a male to female ratio of 1.25. In most families (83%), 2 gliomas were reported, with 3 and 4 gliomas in 13% and 3% of the families, respectively. For families with 2 gliomas, 57% were among 1st-degree relatives, and 31.5% among 2nd-degree relatives. Overall, the mean (±standard deviation [SD]) diagnosis age was 49.4 (±18.7) years. In 48% of families with 2 gliomas, at least one was diagnosed at <40 y, and in 12% both were diagnosed under 40 y of age. Most of these families (76%) had at least one grade IV glioblastoma multiforme (GBM), and in 32% both cases were grade IV gliomas. The most common glioma subtype was GBM (55%), followed by anaplastic astrocytoma (10%) and oligodendroglioma (8%). Individuals with grades I–II were on average 17 y younger than those with grades III–IV.
Familial glioma cases are similar to sporadic cases in terms of gender distribution, age, morphology and grade. Most familial gliomas appear to comprise clusters of two cases suggesting low penetrance, and that the risk of developing additional gliomas is probably low. These results should be useful in the counselling and clinical management of individuals with a family history of glioma.
Glioma; Familial glioma; Clinical characteristics; Genetic counselling
Genome-wide association studies have identified hundreds of genetic variants associated with specific cancers. A few of these risk regions have been associated with more than one cancer site; however, a systematic evaluation of the associations between risk variants for other cancers and lung cancer risk has yet to be performed.
We included 18023 patients with lung cancer and 60543 control subjects from two consortia, Population Architecture using Genomics and Epidemiology (PAGE) and Transdisciplinary Research in Cancer of the Lung (TRICL). We examined 165 single-nucleotide polymorphisms (SNPs) that were previously associated with at least one of 16 non–lung cancer sites. Study-specific logistic regression results underwent meta-analysis, and associations were also examined by race/ethnicity, histological cell type, sex, and smoking status. A Bonferroni-corrected P value of 2.5×10–5 was used to assign statistical significance.
The breast cancer SNP LSP1 rs3817198 was associated with an increased risk of lung cancer (odds ratio [OR] = 1.10; 95% confidence interval [CI] = 1.05 to 1.14; P = 2.8×10–6). This association was strongest for women with adenocarcinoma (P = 1.2×10–4) and not statistically significant in men (P = .14) with this cell type (P
het by sex = .10). Two glioma risk variants, TERT rs2853676 and CDKN2BAS1 rs4977756, which are located in regions previously associated with lung cancer, were associated with increased risk of adenocarcinoma (OR = 1.16; 95% CI = 1.10 to 1.22; P = 1.1×10–8) and squamous cell carcinoma (OR = 1.13; CI = 1.07 to 1.19; P = 2.5×10–5), respectively.
Our findings demonstrate a novel pleiotropic association between the breast cancer LSP1 risk region marked by variant rs3817198 and lung cancer risk.
Genome-wide association studies (GWASs) of renal cell cancer (RCC) have identified four susceptibility loci thus far. To identify an additional RCC common susceptibility locus, we conducted a GWAS and performed a meta-analysis with published GWASs (totalling 2215 cases and 8566 controls of European background) and followed up the most significant association signals [nine single nucleotide polymorphisms (SNPs) in eight genomic regions] in 3739 cases and 8786 controls. A combined analysis identified a novel susceptibility locus mapping to 2q22.3 marked by rs12105918 (P = 1.80 × 10−8; odds ratio 1.29, 95% CI: 1.18–1.41). The signal localizes to intron 2 of the ZEB2 gene (zinc finger E box-binding homeobox 2). Our findings suggest that genetic variation in ZEB2 influences the risk of RCC. This finding provides further insights into the genetic and biological basis of inherited genetic susceptibility to RCC.
Despite extensive research on the topic, glioma etiology remains largely unknown. Exploration of potential interactions between single-nucleotide polymorphisms (SNPs) of immune genes is a promising new area of glioma research. The case-only study design is a powerful and efficient design for exploring possible multiplicative interactions between factors that are independent of one another. The purpose of our study was to use this exploratory design to identify potential pair wise SNP-SNP interactions from genes involved in several different immune-related pathways for investigation in future studies.
The study population consisted of two case groups: 1224 histological-confirmed, non-Hispanic white glioma cases from the U.S. and a validation population of 634 glioma cases from the U.K. Polytomous logistic regression, in which one SNP was coded as the outcome and the other SNP was included as the exposure, was utilized to calculate the odds ratios of the likelihood of cases simultaneously having the variant alleles of two different SNPs. Potential interactions were examined only between SNPs located in different genes or chromosomes.
Using this data-mining strategy, we found 396 significant SNP-SNP interactions among polymorphisms of immune-related genes that were present in both the U.S. and U.K. study populations.
This exploratory study was conducted for the purpose of hypothesis generation, and thus has provided several new hypotheses that can be tested using traditional case-control study designs to obtain estimates of risk.
This is the first study, to our knowledge, to take this novel approach to identifying SNP-SNP interactions relevant to glioma etiology.
We propose a two-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma.
First, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N=281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N=74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are re-estimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis.
Using the best fitting segregation models in model-based multipoint linkage analysis, we identified two separate peaks on chromosome 17; the first agreed with a region identified by Shete et al. who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum log of the odds (LOD).
Our approach has the advantage of not requiring markers to be in linkage equilibrium unless the minor allele frequency is small (markers which tend to be uninformative for linkage), and of using more of the available information for LOD-based linkage analysis.
Glioma; model-based linkage; segregation; age of onset; prevalence constraint
Many individuals with multiple or large colorectal adenomas, or early-onset colorectal cancer (CRC), have no detectable germline mutations in the known cancer predisposition genes. Using whole-genome sequencing, supplemented by linkage and association analysis, we identified specific heterozygous POLE or POLD1 germline variants in several multiple adenoma and/or CRC cases, but in no controls. The susceptibility variants appear to have high penetrance. POLD1 is also associated with endometrial cancer predisposition. The mutations map to equivalent sites in the proof-reading (exonuclease) domain of DNA polymerases ε and δ, and are predicted to impair correction of mispaired bases inserted during DNA replication. In agreement with this prediction, mutation carriers’ tumours were microsatellite-stable, but tended to acquire base substitution mutations, as confirmed by yeast functional assays. Further analysis of published data showed that the recently-described group of hypermutant, microsatellite-stable CRCs is likely to be caused by somatic POLE exonuclease domain mutations.
Gliomas account for approximately 80% of all primary malignant brain tumors, and despite improvements in clinical care over the last 20 years remain among the most lethal tumors, underscoring the need for gaining new insights that could translate into clinical advances. Recent genome-wide association studies (GWAS) have identified seven new susceptibility regions. We conducted a new independent GWAS of glioma using 1,856 cases and 4,955 controls (from 14 cohort studies, 3 casecontrol studies, and 1 population-based case only study) and found evidence of strong replication for three of the seven previously reported associations at 20q13.33 (RTEL), 5p15.33 (TERT), and 9p21.3 (CDKN2BAS), and consistent association signals for the remaining four at 7p11.2 (EGFR both loci), 8q24.21 (CCDC26) and 11q23.3 (PHLDB1). The direction and magnitude of the signal were consistent for samples from cohort and case-control studies, but the strength of the association was more pronounced for loci rs6010620 (20q,13.33; RTEL) and rs2736100 (5p15.33, TERT) in cohort studies despite the smaller number of cases in this group, likely due to relatively more higher grade tumors being captured in the cohort studies. We further examined the 85 most promising single nucleotide polymorphism (SNP) markers identified in our study in three replication sets (5,015 cases and 11,601 controls), but no new markers reached genome-wide significance. Our findings suggest that larger studies focusing on novel approaches as well as specific tumor subtypes or subgroups will be required to identify additional common susceptibility loci for glioma risk.
Improved sequencing technologies offer unprecedented opportunities for investigating the role of rare genetic variation in common disease. However, there are considerable challenges with respect to study design, data analysis and replication1. Here, using pooled next-generation sequencing of 507 genes implicated in the repair of DNA in 1,150 samples, an analytical strategy focussed on protein truncating variants (PTVs) and a large-scale sequencing case-control replication experiment in 13,642 individuals, we show that rare PTVs in the p53 inducible protein phosphatase PPM1D are associated with predisposition to breast cancer and to ovarian cancer. PPM1D PTV mutations were present in 25/7781 cases vs 1/5861 controls; P=1.12×10−5, which included 18 mutations in 6,912 individuals with breast cancer; P = 2.42×10−4 and 12 mutations in 1,121 individuals with ovarian cancer; P = 3.10×10−9. Notably, all the identified PPM1D PTVs were mosaic in lymphocyte DNA and clustered within a 370 bp region in the final exon of the gene, C-terminal to the phosphatase catalytic domain. Functional studies demonstrated that the mutations result in enhanced suppression of p53 in response to ionising radiation exposure, suggesting the mutant alleles encode hyperactive PPM1D isoforms. Thus, although the mutations cause premature protein truncation, they do not result in the simple loss-of-function typically associated with this class of variant, but instead likely have a gain-of-function effect. Our results have implications for the detection and management of breast and ovarian cancer risk. More generally, these data provide new insights into the role of rare and of mosaic genetic variants in common conditions, and the utility of sequencing in their identification.
The risk of glioma has consistently been shown to be increased two-fold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23.
To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations.
In the discovery study, 12 SNPs showed significant associations with family history of PBT (P < 0.001). In the replication study, two of the 12 SNPs were confirmed: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.031) and 17q12-21.32 SPOP rs650461 (P = 0.025). In the combined analysis of discovery and replication studies, the strongest associations were attained at four SNPs: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.0001), SOX5 rs7305773 (P = 0.0001) and STKY1 rs2418087 (P = 0.0003), and 17q12-21.32 SPOP rs6504618 (P = 0.0006). Further, a significant gene-dosage effect was found for increased risk of family history of PBT with these four SNPs in the combined data set (Ptrend < 1.0 ×10−8).
The results support the linkage finding that some loci in the 12p13.33-12.1 and 17q12-q21.32 may contribute to gliomagenesis and suggest potential target genes underscoring linkage signals.
Association; Polymorphisms; Glioma; Family history of primary brain tumor; Linkage analysis
We conducted a genome-wide association study of male breast cancer using 823 cases and 2,795 controls of European ancestry with validation in independent sample sets totalling 438 cases and 474 controls. A novel variant in RAD51B (14q24.1) was significantly associated with male breast cancer risk (P = 3.02 ×10−13, odds ratio (OR) = 1.57). TOX3 (16q12.1) was also a susceptibility locus (P = 3.87 ×10−15, OR = 1.50).
Breast cancer is the most common cancer in women in developed countries. To identify common breast cancer susceptibility alleles, we conducted a genome-wide association study in which 582,886 SNPs were genotyped in 3,659 cases with a family history of the disease and 4,897 controls. Promising associations were evaluated in a second stage, comprising 12,576 cases and 12,223 controls. We identified five new susceptibility loci, on chromosomes 9, 10 and 11 (P = 4.6 × 10−7 to P = 3.2 × 10−15). We also identified SNPs in the 6q25.1 (rs3757318, P = 2.9 × 10−6), 8q24 (rs1562430, P = 5.8 × 10−7) and LSP1 (rs909116, P = 7.3 × 10−7) regions that showed more significant association with risk than those reported previously. Previously identified breast cancer susceptibility loci were also found to show larger effect sizes in this study of familial breast cancer cases than in previous population-based studies, consistent with polygenic susceptibility to the disease.
Many colorectal cancers (CRCs) develop in genetically susceptible individuals most of whom are not carriers of germ line mismatch repair or APC gene mutations and much of the heritable risk of CRC appears to be attributable to the co-inheritance of multiple low-risk variants. The accumulated experience to date in identifying this class of susceptibility allele has highlighted the need to conduct statistically and methodologically rigorous studies and the need for the multi-centre collaboration. This has been the motivation for establishing the COGENT (COlorectal cancer GENeTics) consortium which now includes over 20 research groups in Europe, Australia, the Americas, China and Japan actively working on CRC genetics. Here, we review the rationale for identifying low-penetrance variants for CRC and the current and future challenges for COGENT.
Gliomas, which generally have a poor prognosis, are the most common primary malignant brain tumors in adults. Recent genome-wide association studies have demonstrated that inherited susceptibility plays a role in the development of glioma. Although first-degree relatives of patients exhibit a two-fold increased risk of glioma, the search for susceptibility loci in familial forms of the disease has been challenging because the disease is relatively rare, fatal, and heterogeneous, making it difficult to collect sufficient biosamples from families for statistical power. To address this challenge, the Genetic Epidemiology of Glioma International Consortium (Gliogene) was formed to collect DNA samples from families with two or more cases of histologically confirmed glioma. In this study, we present results obtained from 46 U.S. families in which multipoint linkage analyses were undertaken using nonparametric (model-free) methods. After removal of high linkage disequilibrium SNPs, we obtained a maximum nonparametric linkage score (NPL) of 3.39 (P=0.0005) at 17q12–21.32 and the Z-score of 4.20 (P=0.000007). To replicate our findings, we genotyped 29 independent U.S. families and obtained a maximum NPL score of 1.26 (P=0.008) and the Z-score of 1.47 (P=0.035). Accounting for the genetic heterogeneity using the ordered subset analysis approach, the combined analyses of 75 families resulted in a maximum NPL score of 3.81 (P=0.00001). The genomic regions we have implicated in this study may offer novel insights into glioma susceptibility, focusing future work to identify genes that cause familial glioma.
Glioma; family studies; linkage; haplotype pattern; NPL