Matthew Frampton

Common variation near CDKN1A , POLD3 and SHROOM2 influences colorectal cancer risk

We performed a meta-analysis of five genome-wide association studies to identify common variants influencing colorectal cancer (CRC) risk comprising 8,682 cases and 9,649 controls. Replication analysis was performed in case-control sets totaling 21,096 cases and 19,555 controls. We identified three new CRC risk loci at 6p21 (rs1321311, near CDKN1A; P = 1.14 × 10−10), 11q13.4 (rs3824999, intronic to POLD3; P = 3.65 × 10−10) and Xp22.2 (rs5934683, near SHROOM2; P = 7.30 × 10−10) This brings the number of independent loci associated with CRC risk to 20 and provides further insight into the genetic architecture of inherited susceptibility to CRC.

Variation at 3p24.1 and 6q23.3 influences the risk of Hodgkin’s lymphoma

In addition to HLA, recent genome-wide association studies (GWASs) of Hodgkin’s Lymphoma (HL) have identified susceptibility loci for HL at 2p16.1, 8q24.21 and 10p14. In this study, we perform a GWAS meta-analysis with published GWAS (totaling 1,465 cases and 6,417 controls of European background), and follow up the most significant association signals in 2,024 cases and 1,853 controls. A combined analysis identifies new HL susceptibility loci mapping to 3p24.1 (rs3806624; P=1.14×10-12, odds ratio [OR]=1.26) and 6q23.3 (rs7745098; P=3.42×10-9, OR=1.21). rs3806624 localizes 5’ to the EOMES (eomesodermin) gene within a p53 response element affecting p53 binding. rs7745098 maps intergenic to HBS1L and MYB, a region previously associated with hematopoiesis. These findings provide further insight into the genetic and biological basis of inherited susceptibility to HL.

Genetic Diagnosis of High-Penetrance Susceptibility for Colorectal Cancer (CRC) Is Achievable for a High Proportion of Familial CRC by Exome Sequencing

PURPOSE Knowledge of the contribution of high-penetrance susceptibility to familial colorectal cancer (CRC) is relevant to the counseling, treatment, and surveillance of CRC patients and families. PATIENTS AND METHODS To quantify the impact of germline mutation to familial CRC, we sequenced the mismatch repair genes (MMR) APC, MUTYH, and SMAD4/BMPR1A in 626 early-onset familial CRC cases ascertained through a population-based United Kingdom national registry. In addition, we evaluated the contribution of mutations in the exonuclease domain (exodom) of POLE and POLD1 genes that have recently been reported to confer CRC risk. RESULTS Overall mutations (pathogenic, likely pathogenic) in MMR genes make the highest contribution to familial CRC (10.9%). Mutations in the other established CRC genes account for 3.3% of cases. POLE/POLD1 exodom mutations were identified in three patients with family histories consistent with dominant transmission of CRC. Collectively, mutations in the known genes account for 14.2% of familial CRC (89 of 626 cases; 95% CI = 11.5, 17.2). CONCLUSION A genetic diagnosis is feasible in a high proportion of familial CRC. Mainstreaming such analysis in clinical practice should enable the medical management of patients and their families to be optimized. Findings suggest CRC screening of POLE and POLD1 mutation carriers should be comparable to that afforded to those at risk of HNPCC. Although the risk of CRC associated with unexplained familial CRC is in general moderate, in some families the risk is substantive and likely to be the consequence of unidentified genes, as exemplified by POLE and POLD1. Our findings have utility in the design of genetic analyses to identify such novel CRC risk genes.

Common variation at 2q22.3 (ZEB2) influences the risk of renal cancer

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.

Rare disruptive mutations and their contribution to the heritable risk of colorectal cancer.

Colorectal cancer (CRC) displays a complex pattern of inheritance. It is postulated that much of the missing heritability of CRC is enshrined in high-impact rare alleles, which are mechanistically and clinically important. In this study, we assay the impact of rare germline mutations on CRC, analysing high-coverage exome sequencing data on 1,006 early-onset familial CRC cases and 1,609 healthy controls, with additional sequencing and array data on up to 5,552 cases and 6,792 controls. We identify highly penetrant rare mutations in 16% of familial CRC. Although the majority of these reside in known genes, we identify POT1, POLE2 and MRE11 as candidate CRC genes. We did not identify any coding low-frequency alleles (1–5%) with moderate effect. Our study clarifies the genetic architecture of CRC and probably discounts the existence of further major high-penetrance susceptibility genes, which individually account for >1% of the familial risk. Our results inform future study design and provide a resource for contextualizing the impact of new CRC genes.

Generation of Artificial FASTQ Files to Evaluate the Performance of Next-Generation Sequencing Pipelines

Pipelines for the analysis of Next-Generation Sequencing (NGS) data are generally composed of a set of different publicly available software, configured together in order to map short reads of a genome and call variants. The fidelity of pipelines is variable. We have developed ArtificialFastqGenerator, which takes a reference genome sequence as input and outputs artificial paired-end FASTQ files containing Phred quality scores. Since these artificial FASTQs are derived from the reference genome, it provides a gold-standard for read-alignment and variant-calling, thereby enabling the performance of any NGS pipeline to be evaluated. The user can customise DNA template/read length, the modelling of coverage based on GC content, whether to use real Phred base quality scores taken from existing FASTQ files, and whether to simulate sequencing errors. Detailed coverage and error summary statistics are outputted. Here we describe ArtificialFastqGenerator and illustrate its implementation in evaluating a typical bespoke NGS analysis pipeline under different experimental conditions. ArtificialFastqGenerator was released in January 2012. Source code, example files and binaries are freely available under the terms of the GNU General Public License v3.0. from https://sourceforge.net/projects/artfastqgen/.

Implications of polygenic risk for personalised colorectal cancer screening

BACKGROUND We modelled the utility of applying a personalised screening approach for colorectal cancer (CRC) when compared with standard age-based screening. In this personalised screening approach, eligibility is determined by absolute risk which is calculated from age and polygenic risk score (PRS), where the PRS is relative risk attributable to common genetic variation. In contrast, eligibility in age-based screening is determined only by age. DESIGN We calculated absolute risks of CRC from UK population age structure, incidence and mortality rate data, and a PRS distribution which we derived for the 37 known CRC susceptibility variants. We compared the number of CRC cases potentially detectable by personalised and age-based screening. Using Genome-Wide Complex Trait Analysis to calculate the heritability attributable to common variation, we repeated the analysis assuming all common CRC risk variants were known. RESULTS Based on the known CRC variants, individuals with a PRS in the top 1% have a 2.9-fold increased CRC risk over the population median. Compared with age-based screening (aged 60: 10-year absolute risk 1.96% in men, 1.19% in women, as per the UK NHS National Bowel Screening Programme), personalised screening of individuals aged 55-69 at the same risk would lead to 16% fewer men and 17% fewer women being eligible for screening with 10% and 8%, respectively, fewer screen-detected cases. If all susceptibility variants were known, individuals with a PRS in the top 1% would have an estimated 7.7-fold increased risk. Personalised screening would then result in 26% fewer men and women being eligible for screening with 7% and 5% fewer screen-detected cases. CONCLUSION Personalised screening using PRS has the potential to optimise population screening for CRC and to define those likely to maximally benefit from chemoprevention. There are however significant technical and operational details to be addressed before any such programme is introduced.

Common variation at 1q24.1 (ALDH9A1) is a potential risk factor for renal cancer

So far six susceptibility loci for renal cell carcinoma (RCC) have been discovered by genome-wide association studies (GWAS). To identify additional RCC common risk loci, we performed a meta-analysis of published GWAS (totalling 2,215 cases and 8,566 controls of Western-European background) with imputation using 1000 Genomes Project and UK10K Project data as reference panels and followed up the most significant association signals [22 single nucleotide polymorphisms (SNPs) and 3 indels in eight genomic regions] in 383 cases and 2,189 controls from The Cancer Genome Atlas (TCGA). A combined analysis identified a promising susceptibility locus mapping to 1q24.1 marked by the imputed SNP rs3845536 (P combined =2.30x10-8). Specifically, the signal maps to intron 4 of the ALDH9A1 gene (aldehyde dehydrogenase 9 family, member A1). We further evaluated this potential signal in 2,461 cases and 5,081 controls from the International Agency for Research on Cancer (IARC) GWAS of RCC cases and controls from multiple European regions. In contrast to earlier findings no association was shown in the IARC series (P=0.94; P combined =2.73x10-5). While variation at 1q24.1 represents a potential risk locus for RCC, future replication analyses are required to substantiate our observation.

Modeling the prevention of colorectal cancer from the combined impact of host and behavioral risk factors

Purpose:This study investigated the utility of modeling modifiable lifestyle risk factors in addition to genetic variation in colorectal cancer (CRC) screening/prevention.Methods:We derived a polygenic risk score for CRC susceptibility variants in combination with the established nongenetic risk factors of inflammatory bowel disease (IBD), adiposity, alcohol, red meat, fruit, vegetables, smoking, physical activity, and aspirin. We used the 37 known risk variants and 50 and 100% of all risk variants as calculated from a heritability estimate. We derived absolute risk from UK population age structure, incidence, and mortality rate data.Results:Taking into account all risk factors (known variants), 42.2% of 55- to 59-year-old men with CRC have a risk at least as high as that of an average 60-year-old, the minimum eligible age for the UK NHS National Bowel Cancer Screening Program. If the male population is stratified by known variants and IBD status, then risk-difference estimates imply that for 10,000 50-year-old men in the 99th percentile, 760 cases could be prevented over a 25-year period through the modifiable risk factors, but in the lowest percentile, only 90 could be prevented.Conclusion:CRC screening and prevention centered on modifiable risk factors could be optimized if targeted at individuals at higher polygenic risk.Genet Med 19 3, 314–321.

Correspondence: SEMA4A variation and risk of colorectal cancer

Sill and co-workers1 report that germline variation in semaphorin 4A (SEMA4A) influences colorectal cancer (CRC) risk. This stems from identifying the SEMA4A p.Val78Met variant in one kindred with familial colorectal cancer type X (FCCTX) and subsequently p.Gly484Ala (c.1451G>C, rs148744804) and p.Ser326Phe (c.977C>T) mutations along with the single nucleotide polymorphism (SNP) p.Pro682Ser (c.2044C>T, rs76381440) among an additional 53 FCCTX cases. In comparing the frequency of rs76381440 genotype in 47 FCCTX cases and 1,138 controls, c.2044T carrier status was reported to be associated with 6.79-fold increased CRC risk1. Here, we report a well-powered study that casts doubt on SEMA4A as a CRC predisposition gene. This has important implications for clinical genetics because inappropriate screening or intervention might be recommended to carriers. First, we studied the contribution of the recurrent variants, rs148744804 and rs76381440, to CRC analysing 6,856 CRC cases and 10,090 controls from six European populations as previously described2,3. These comprised (1) 3,666 English case patients (n=250 from the CORGI study; n=957 from the QUASAR study; n=1,168 from NSCCG; n=1,291 from a Leeds case–control series) and 6,140 control patients (n=5,694 from the 1958 Birth Cohort; n=446 from the Leeds series); (2) 2,052 Scottish CRC cases and 2,004 Scottish controls (n=1,452 from the 1935 and 1928 Lothian birth cohorts; n=552 from generation Scotland); (3) 276 Spanish cases and 284 controls; (4) 800 Dutch samples (n=337 Leiden cases and n=337 controls; n=74 Groningen cases and n=52 controls); (5) 199 Portuguese cases and 186 controls and (6) 1,339 German samples (n=77 Heidelberg cases and n=88 controls; n=175 Kiel cases and n=999 controls). Collectively these samples provide >99% power (α=0.05) to detect the lower limit of the point estimate reported by Sill and co-workers for the association between p.Pro682Ser and CRC1) (odds ratio [OR]=2.6). We used Infinium HumanExome BeadChips (Illumina San Diego, CA) to genotype our samples as previously described2,3 and extracted the genotypes for rs148744804 and rs76381440. We validated genotyping by sequencing 541 random samples, providing very strong concordance (r2=1.0 and 0.99 for rs148744804 and rs76381440, respectively; Supplementary Table 1). We used principal component analysis to confirm ancestral comparability of cases and controls (Supplementary Figure 1). None of the six series showed a statistically significant difference in frequency of rs148744804 or rs76381440 genotype between cases and controls (Table 1). In a meta-analysis of data from all studies, we found no association between c.1451C or c.2044T carrier status and CRC (OR=1.14, 95% confidence interval [CI]: 0.58–2.24, Pheterogenity=0.87, I2=0% and OR=1.04, 95% CI: 0.89–1.22, Pheterogenity=0.36, I2=9%, respectively; Fig. 1). Principal component analysis adjustment had no impact on findings. Figure 1 Forest plot of association between rs148744804 and rs76381440 SEMA4A genotypes and colorectal cancer risk. Table 1 SEMA4A rs76381440 (p.Pro682Ser, c.2044C>T) and rs148744804 (p.Gly484Ala, c.1451G>C) genotype counts and association statistics for the six colorectal cancer case–control studies. Following on from these analyses we examined the mutational spectra of SEMA4A in 1,006 familial early-onset CRC cases (≥1 first-degree relative with CRC, <56yrs; 158 with FCCTX) from the National Study of Colorectal Cancer Genetics (NSCCG) and 1,609 1958 BC controls sequenced using Illumina Truseq exome capture in conjunction with HiSeq2000 technology (Supplementary Figure 2, Supplementary Table 2). Over 99% of the SEMA4A transcript was covered at a depth greater than 10 reads (average coverage 38 ×, Supplementary Figure 2). We identified 28 protein changing variants in 354 samples. Of these variants, there were three unique frameshifts present in two controls and one case. Overall, 13% of CRC cases (16% FCCTX) had a protein changing variant in SEMA4A in comparison with 14% of controls. There are a number of possible explanations for the disparity between our findings and those reported by Sill and co-workers1. Population stratification can lead to spurious associations, and this is especially important with rare variants. The study by Sill and co-workers did not account for this and indeed in comparing the frequency of rs14874408 included cases from both the US and Germany, whereas we ensured ancestral comparability of case patients and control subjects from single nucleotide polymorphism genotypes, thereby excluding this as a source of bias. Generalisability is central to establishing a mutation–phenotype relationship. The evidence for p.Val78Met being causative in FCCTX is based on incomplete segregation in the family reported by Schulz et al. Hence there is the issue of type 1 error. Much of the missing heritability of CRC is likely to be a result of high/moderate penetrance mutations and rare variants. As illustrated by the recent identification of POLE and POLD1 as a cause of familial CRC4, this class of susceptibility is especially important in understanding cancer biology and for clinical practice. Hence there is a strong rationale for seeking to identify additional such genes. Given the high frequency of deleterious mutations carried by the healthy population, it is becoming increasingly clear that robust and well-powered studies are required to prevent erroneous findings from exome-sequencing projects being asserted to be causal of disease. In conclusion, in this well-powered study, we find no evidence to support variation in SEMA4A as a determinant of CRC risk. Given that a priori SEMA4A is not a strong candidate CRC predisposition gene, having previously been shown to cause eye disease, we feel that caution should be exercised before SEMA4A is considered as a cause of CRC.