A mitotic recombination map proximal to the APC locus on chromosome 5q and assessment of influences on colorectal cancer risk

Mitotic recombination is important for inactivating tumour suppressor genes by copy-neutral loss of heterozygosity (LOH). Although meiotic recombination maps are plentiful, little is known about mitotic recombination. The APC gene (chr5q21) is mutated in most colorectal tumours and its usual mode of LOH is mitotic recombination.

Refinement of the associations between risk of colorectal cancer and polymorphisms on chromosomes 1q41 and 12q13.13

In genome-wide association studies (GWASs) of colorectal cancer, we have identified two genomic regions in which pairs of tagging-single nucleotide polymorphisms (tagSNPs) are associated with disease; these comprise chromosomes 1q41 (rs6691170, rs6687758) and 12q13.13 (rs7163702, rs11169552). We investigated these regions further, aiming to determine whether they contain more than one independent association signal and/or to identify the SNPs most strongly associated with disease. Genotyping of additional sample sets at the original tagSNPs showed that, for both regions, the two tagSNPs were unlikely to identify a single haplotype on which the functional variation lay. Conversely, one of the pair of SNPs did not fully capture the association signal in each region. We therefore undertook more detailed analyses, using imputation, logistic regression, genealogical analysis using the GENECLUSTER program and haplotype analysis. In the 1q41 region, the SNP rs11118883 emerged as a strong candidate based on all these analyses, sufficient to account for the signals at both rs6691170 and rs6687758. rs11118883 lies within a region with strong evidence of transcriptional regulatory activity and has been associated with expression of PDGFRB mRNA. For 12q13.13, a complex situation was found: SNP rs7972465 showed stronger association than either rs11169552 or rs7136702, and GENECLUSTER found no good evidence for a two-SNP model. However, logistic regression and haplotype analyses supported a two-SNP model, in which a signal at the SNP rs706793 was added to that at rs11169552. Post-GWAS fine-mapping studies are challenging, but the use of multiple tools can assist in identifying candidate functional variants in at least some cases

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression

The relationship between appetite and food preferences in British and Australian children

Background: Appetitive traits and food preferences are key determinants of children’s eating patterns but it is unclear how these behaviours relate to one another. This study explores relationships between appetitive traits and preferences for fruits and vegetables, and energy dense, nutrient poor (noncore) foods in two distinct samples of Australian and British preschool children. Methods: This study reports secondary analyses of data from families participating in the British GEMINI cohort study (n = 1044) and the control arm of the Australian NOURISH RCT (n = 167). Food preferences were assessed by parent-completed questionnaire when children were aged 3–4 years and grouped into three categories; vegetables, fruits and noncore foods. Appetitive traits; enjoyment of food, food responsiveness, satiety responsiveness, slowness in eating, and food fussiness were measured using the Children’s Eating Behaviour Questionnaire when children were 16 months (GEMINI) or 3–4 years (NOURISH). Relationships between appetitive traits and food preferences were explored using adjusted linear regression analyses that controlled for demographic and anthropometric covariates. Results: Vegetable liking was positively associated with enjoyment of food (GEMINI; β = 0.20 ± 0.03, p < 0.001, NOURISH; β = 0.43 ± 0.07, p < 0.001) and negatively related to satiety responsiveness (GEMINI; β = -0.19 ± 0.03, p < 0.001, NOURISH; β = -0.34 ± 0.08, p < 0.001), slowness in eating (GEMINI; β = -0.10 ± 0.03, p = 0.002, NOURISH; β = -0.30 ± 0.08, p < 0.001) and food fussiness (GEMINI; β = −0.30 ± 0.03, p < 0.001, NOURISH; β = -0.60 ± 0.06, p < 0.001). Fruit liking was positively associated with enjoyment of food (GEMINI; β = 0.18 ± 0.03, p < 0.001, NOURISH; β = 0.36 ± 0.08, p < 0.001), and negatively associated with satiety responsiveness (GEMINI; β = −0.13 ± 0.03, p < 0.001, NOURISH; β = −0.24 ± 0.08, p = 0.003), food fussiness (GEMINI; β = -0.26 ± 0.03, p < 0.001, NOURISH; β = −0.51 ± 0.07, p < 0.001) and slowness in eating (GEMINI only; β = -0.09 ± 0.03, p = 0.005). Food responsiveness was unrelated to liking for fruits or vegetables in either sample but was positively associated with noncore food preference (GEMINI; β = 0.10 ± 0.03, p = 0.001, NOURISH; β = 0.21 ± 0.08, p = 0.010). Conclusion: Appetitive traits linked with lower obesity risk were related to lower liking for fruits and vegetables, while food responsiveness, a trait linked with greater risk of overweight, was uniquely associated with higher liking for noncore foods

DNA polymerase ɛ and δ exonuclease domain mutations in endometrial cancer

Accurate duplication of DNA prior to cell division is essential to suppress mutagenesis and tumour development. The high fidelity of eukaryotic DNA replication is due to a combination of accurate incorporation of nucleotides into the nascent DNA strand by DNA polymerases, the recognition and removal of mispaired nucleotides (proofreading) by the exonuclease activity of DNA polymerases δ and ɛ, and post-replication surveillance and repair of newly synthesized DNA by the mismatch repair (MMR) apparatus. While the contribution of defective MMR to neoplasia is well recognized, evidence that faulty DNA polymerase activity is important in cancer development has been limited. We have recently shown that germline POLE and POLD1 exonuclease domain mutations (EDMs) predispose to colorectal cancer (CRC) and, in the latter case, to endometrial cancer (EC). Somatic POLE mutations also occur in 5–10% of sporadic CRCs and underlie a hypermutator, microsatellite-stable molecular phenotype. We hypothesized that sporadic ECs might also acquire somatic POLE and/or POLD1 mutations. Here, we have found that missense POLE EDMs with good evidence of pathogenic effects are present in 7% of a set of 173 endometrial cancers, although POLD1 EDMs are uncommon. The POLE mutations localized to highly conserved residues and were strongly predicted to affect proofreading. Consistent with this, POLE-mutant tumours were hypermutated, with a high frequency of base substitutions, and an especially large relative excess of G:C>T:A transversions. All POLE EDM tumours were microsatellite stable, suggesting that defects in either DNA proofreading or MMR provide alternative mechanisms to achieve genomic instability and tumourigenesis

Candidate locus analysis of the TERT-CLPTM1L cancer risk region on chromosome 5p15 identifies multiple independent variants associated with endometrial cancer risk.

Several studies have reported associations between multiple cancer types and single-nucleotide polymorphisms (SNPs) on chromosome 5p15, which harbours TERT and CLPTM1L, but no such association has been reported with endometrial cancer. To evaluate the role of genetic variants at the TERT-CLPTM1L region in endometrial cancer risk, we carried out comprehensive fine-mapping analyses of genotyped and imputed SNPs using a custom Illumina iSelect array which includes dense SNP coverage of this region. We examined 396 SNPs (113 genotyped, 283 imputed) in 4,401 endometrial cancer cases and 28,758 controls. Single-SNP and forward/backward logistic regression models suggested evidence for three variants independently associated with endometrial cancer risk (P = 4.9 × 10(-6) to P = 7.7 × 10(-5)). Only one falls into a haplotype previously associated with other cancer types (rs7705526, in TERT intron 1), and this SNP has been shown to alter TERT promoter activity. One of the novel associations (rs13174814) maps to a second region in the TERT promoter and the other (rs62329728) is in the promoter region of CLPTM1L; neither are correlated with previously reported cancer-associated SNPs. Using TCGA RNASeq data, we found significantly increased expression of both TERT and CLPTM1L in endometrial cancer tissue compared with normal tissue (TERT P = 1.5 × 10(-18), CLPTM1L P = 1.5 × 10(-19)). Our study thus reports a novel endometrial cancer risk locus and expands the spectrum of cancer types associated with genetic variation at 5p15, further highlighting the importance of this region for cancer susceptibility.This work was supported by the NHMRC Project Grant (ID#1031333). This work was also supported by Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692)This is the published version. It first appeared at http://link.springer.com/article/10.1007%2Fs00439-014-1515-4

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University