Telomere length and common disease: study design and analytical challenges.

Telomeres, the repetitive sequences that protect the ends of chromosomes, help to maintain genomic integrity and are of key importance to human health. The aim here is to give an overview of the evidence for the importance of telomere length (TL) to the risk of common disease, considering the strengths and weaknesses of different epidemiological study designs. Methods for measuring TL are described, all of which are subject to considerable measurement error. TL declines with age and varies in relation to factors such as smoking and obesity. It is also highly heritable (estimated heritability of ~40 to 50%), and genome-wide studies have identified a number of associated genetic variants. Epidemiological studies have shown shorter TL to be associated with risk of a number of common diseases, including cardiovascular disease and some cancers. The relationship with cancer appears complex, in that longer telomeres are associated with higher risk of some cancers. Prospective studies of the relationship between TL and disease, where TL is measured before diagnosis, have numerous advantages over retrospective studies, since they avoid the problems of reverse causality and differences in sample handling, but they are still subject to potential confounding. Studies of the genetic predictors of TL in relation to disease risk avoid these drawbacks, although they are not without limitations. Telomere biology is of major importance to the risk of common disease, but the complexities of the relationship are only now beginning to be understood.This research was supported by Cancer Research UK Programme Awards C588/A10589 and C588/A19167 (MMI and JHB) and C8197/A16565 (AMD and KAP) and the Isaac Newton Trust.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00439-015-1563-

Seq4SNPs: new software for retrieval of multiple, accurately annotated DNA sequences, ready formatted for SNP assay design.

BACKGROUND: In moderate-throughput SNP genotyping there was a gap in the workflow, between choosing a set of SNPs and submitting their sequences to proprietary assay design software, which was not met by existing software. Retrieval and formatting of sequences flanking each SNP, prior to assay design, becomes rate-limiting for more than about ten SNPs, especially if annotated for repetitive regions and adjacent variations. We routinely process up to 50 SNPs at once. IMPLEMENTATION: We created Seq4SNPs, a web-based, walk-away software that can process one to several hundred SNPs given rs numbers as input. It outputs a file of fully annotated sequences formatted for one of three proprietary design softwares: TaqMan's Primer-By-Design FileBuilder, Sequenom's iPLEX or SNPstream's Autoprimer, as well as unannotated fasta sequences. We found genotyping assays to be inhibited by repetitive sequences or the presence of additional variations flanking the SNP under test, and in multiplexes, repetitive sequence flanking one SNP adversely affects multiple assays. Assay design software programs avoid such regions if the input sequences are appropriately annotated, so we used Seq4SNPs to provide suitably annotated input sequences, and improved our genotyping success rate. Adjacent SNPs can also be avoided, by annotating sequences used as input for primer design. CONCLUSION: The accuracy of annotation by Seq4SNPs is significantly better than manual annotation (P < 1e-5).Using Seq4SNPs to incorporate all annotation for additional SNPs and repetitive elements into sequences, for genotyping assay designer software, minimizes assay failure at the design stage, reducing the cost of genotyping. Seq4SNPs provides a rapid route for replacement of poor test SNP sequences. We routinely use this software for assay sequence preparation. Seq4SNPs is available as a service at (http://moya.srl.cam.ac.uk/oncology/bio/s4shome.html) and (http://moya.srl.cam.ac.uk/cgi-bin/oncology/srl/ncbi/seq4snp1.pl), currently for human SNPs, but easily extended to include any species in dbSNP.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

Peer reviewe

Saliva samples are a viable alternative to blood samples as a source of DNA for high throughput genotyping.

BACKGROUND: The increasing trend for incorporation of biological sample collection within clinical trials requires sample collection procedures which are convenient and acceptable for both patients and clinicians. This study investigated the feasibility of using saliva-extracted DNA in comparison to blood-derived DNA, across two genotyping platforms: Applied Biosystems Taqman™ and Illumina Beadchip™ genome-wide arrays. METHOD: Patients were recruited from the Pharmacogenetics of Breast Cancer Chemotherapy (PGSNPS) study. Paired blood and saliva samples were collected from 79 study participants. The Oragene DNA Self-Collection kit (DNAgenotek®) was used to collect and extract DNA from saliva. DNA from EDTA blood samples (median volume 8 ml) was extracted by Gen-Probe, Livingstone, UK. DNA yields, standard measures of DNA quality, genotype call rates and genotype concordance between paired, duplicated samples were assessed. RESULTS: Total DNA yields were lower from saliva (mean 24 μg, range 0.2-52 μg) than from blood (mean 210 μg, range 58-577 μg) and a 2-fold difference remained after adjusting for the volume of biological material collected. Protein contamination and DNA fragmentation measures were greater in saliva DNA. 78/79 saliva samples yielded sufficient DNA for use on Illumina Beadchip arrays and using Taqman assays. Four samples were randomly selected for genotyping in duplicate on the Illumina Beadchip arrays. All samples were genotyped using Taqman assays. DNA quality, as assessed by genotype call rates and genotype concordance between matched pairs of DNA was high (>97%) for each measure in both blood and saliva-derived DNA. CONCLUSION: We conclude that DNA from saliva and blood samples is comparable when genotyping using either Taqman assays or genome-wide chip arrays. Saliva sampling has the potential to increase participant recruitment within clinical trials, as well as reducing the resources and organisation required for multicentre sample collection.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Common ERBB2 polymorphisms and risk of breast cancer in a white British population: a case-control study.

INTRODUCTION: About two-thirds of the excess familial risk associated with breast cancer is still unaccounted for and may be explained by multiple weakly predisposing alleles. A gene thought to be involved in low-level predisposition to the disease is ERBB2 (HER2). This gene is involved in cell division, differentiation, and apoptosis and is frequently amplified in breast tumours. Its amplification correlates with poor prognosis. Moreover, the coding polymorphism I655V has previously been associated with an increased risk of breast cancer. METHODS: We aimed to determine if common polymorphisms (frequency >or= 5%) in ERBB2 were associated with breast cancer risk in a white British population. Five single-nucleotide polymorphisms (SNPs) were selected for study: SNP 1 near the promoter, SNP 2 in intron 1, SNP 3 in intron 4, SNP 4 in exon 17 (I655V), and SNP 5 in exon 27 (A1170P). We tested their association with breast cancer in a large case-control study (n = 2192 cases and 2257 controls). RESULTS: There were no differences in genotype frequencies between cases and controls for any of the SNPs examined. To investigate the possibility that a common polymorphism not included in our study might be involved in breast cancer predisposition, we also constructed multilocus haplotypes. Our set of SNPs generated all existing (n = 6) common haplotypes and no differences were seen in haplotype frequencies between cases and controls (P = 0.44). CONCLUSIONS: In our population, common ERBB2 polymorphisms are not involved in predisposition to breast cancer

Validation of loci at 2q14.2 and 15q21.3 as risk factors for testicular cancer.

Testicular germ cell tumor (TGCT), the most common cancer in men aged 18 to 45 years, has a strong heritable basis. Genome-wide association studies (GWAS) have proposed single nucleotide polymorphisms (SNPs) at a number of loci influencing TGCT risk. To further evaluate the association of recently proposed risk SNPs with TGCT at 2q14.2, 3q26.2, 7q36.3, 10q26.13 and 15q21.3, we analyzed genotype data on 3,206 cases and 7,422 controls. Our analysis provides independent replication of the associations for risk SNPs at 2q14.2 (rs2713206 at P = 3.03 × 10-2; P-meta = 3.92 × 10-8; nearest gene, TFCP2L1) and rs12912292 at 15q21.3 (P = 7.96 × 10-11; P-meta = 1.55 × 10-19; nearest gene PRTG). Case-only analyses did not reveal specific associations with TGCT histology. TFCP2L1 joins the growing list of genes located within TGCT risk loci with biologically plausible roles in developmental transcriptional regulation, further highlighting the importance of this phenomenon in TGCT oncogenesis

CYP2D6 gene variants: association with breast cancer specific survival in a cohort of breast cancer patients from the United Kingdom treated with adjuvant tamoxifen.

INTRODUCTION: Tamoxifen is one of the most effective adjuvant breast cancer therapies available. Its metabolism involves the phase I enzyme, cytochrome P4502D6 (CYP2D6), encoded by the highly polymorphic CYP2D6 gene. CYP2D6 variants resulting in poor metabolism of tamoxifen are hypothesised to reduce its efficacy. An FDA-approved pre-treatment CYP2D6 gene testing assay is available. However, evidence from published studies evaluating CYP2D6 variants as predictive factors of tamoxifen efficacy and clinical outcome are conflicting, querying the clinical utility of CYP2D6 testing. We investigated the association of CYP2D6 variants with breast cancer specific survival (BCSS) in breast cancer patients receiving tamoxifen. METHODS: This was a population based case-cohort study. We genotyped known functional variants (n = 7; minor allele frequency (MAF) > 0.01) and single nucleotide polymorphisms (SNPs) (n = 5; MAF > 0.05) tagging all known common variants (tagSNPs), in CYP2D6 in 6640 DNA samples from patients with invasive breast cancer from SEARCH (Studies of Epidemiology and Risk factors in Cancer Heredity); 3155 cases had received tamoxifen therapy. There were 312 deaths from breast cancer, in the tamoxifen treated patients, with over 18000 years of cumulative follow-up. The association between genotype and BCSS was evaluated using Cox proportional hazards regression analysis. RESULTS: In tamoxifen treated patients, there was weak evidence that the poor-metaboliser variant, CYP2D6*6 (MAF = 0.01), was associated with decreased BCSS (P = 0.02; HR = 1.95; 95% CI = 1.12-3.40). No other variants, including CYP2D6*4 (MAF = 0.20), previously reported to be associated with poorer clinical outcomes, were associated with differences in BCSS, in either the tamoxifen or non-tamoxifen groups. CONCLUSIONS: CYP2D6*6 may affect BCSS in tamoxifen-treated patients. However, the absence of an association with survival in more frequent variants, including CYP2D6*4, questions the validity of the reported association between CYP2D6 genotype and treatment response in breast cancer. Until larger, prospective studies confirming any associations are available, routine CYP2D6 genetic testing should not be used in the clinical setting.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Association between Common Variation in 120 Candidate Genes and Breast Cancer Risk

Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran–Armitage trend test (p-trend) and a two-degrees of freedom χ(2) test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 × 10(−5)) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty

Common variants in the ATM, BRCA1, BRCA2, CHEK2 and TP53 cancer susceptibility genes are unlikely to increase breast cancer risk.

INTRODUCTION: Certain rare, familial mutations in the ATM, BRCA1, BRCA2, CHEK2 or TP53 genes increase susceptibility to breast cancer but it has not, until now, been clear whether common polymorphic variants in the same genes also increase risk. METHODS: We have attempted a comprehensive, single nucleotide polymorphism (SNP)- and haplotype-tagging association study on each of these five genes in up to 4,474 breast cancer cases from the British, East Anglian SEARCH study and 4,560 controls from the EPIC-Norfolk study, using a two-stage study design. Nine tag SNPs were genotyped in ATM, together with five in BRCA1, sixteen in BRCA2, ten in CHEK2 and five in TP53, with the aim of tagging all other known, common variants. SNPs generating the common amino acid substitutions were specifically forced into the tagging set for each gene. RESULTS: No significant breast cancer associations were detected with any individual or combination of tag SNPs. CONCLUSION: It is unlikely that there are any other common variants in these genes conferring measurably increased risks of breast cancer in our study population.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

STROGAR – STrengthening the Reporting Of Genetic Association studies in Radiogenomics

AbstractDespite publication of numerous radiogenomics studies to date, positive single nucleotide polymorphism (SNP) associations have rarely been reproduced in independent validation studies. A major reason for these inconsistencies is a high number of false positive findings because no adjustments were made for multiple comparisons. It is also possible that some validation studies were false negatives due to methodological shortcomings or a failure to reproduce relevant details of the original study. Transparent reporting is needed to ensure these flaws do not hamper progress in radiogenomics. In response to the need for improving the quality of research in the area, the Radiogenomics Consortium produced an 18-item checklist for reporting radiogenomics studies. It is recognised that not all studies will have recorded all of the information included in the checklist. However, authors should report on all checklist items and acknowledge any missing information. Use of STROGAR guidelines will advance the field of radiogenomics by increasing the transparency and completeness of reporting