PHIP – a novel candidate breast cancer susceptibility locus on 6q14.1

Most non-BRCA1/2 breast cancer families have no identified genetic cause. We used linkage and haplotype analyses in familial and sporadic breast cancer cases to identify a susceptibility locus on chromosome 6q. Two independent genome-wide linkage analysis studies suggested a 3 Mb locus on chromosome 6q and two unrelated Swedish families with a LOD >2 together seemed to share a haplotype in 6q14.1. We hypothesized that this region harbored a rare high-risk founder allele contributing to breast cancer in these two families. Sequencing of DNA and RNA from the two families did not detect any pathogenic mutations. Finally, 29 SNPs in the region were analyzed in 44,214 cases and 43,532 controls from BCAC, and the original haplotypes in the two families were suggested as low-risk alleles for European and Swedish women specifically. There was also some support for one additional independent moderate-risk allele in Swedish familial samples. The results were consistent with our previous findings in familial breast cancer and supported a breast cancer susceptibility locus at 6q14.1 around the PHIP gene.The study was supported by grants provided by the Swedish Cancer Society (Cancerfonden), the Stockholm County Council (ALF project), the Swedish Research Council (Vetenskapsrådet), the Stockholm Cancer Society (Radiumhemsfonderna) and Bert von Kantzows and Nilsson-Ehle’s foundations. BCAC is funded by Cancer Research UK (C1287/A16563, C1287/A10118), the European Union’s Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633784 for BRIDGES and B-CAST respectively), and by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). Funding for the iCOGS infrastructure came from: the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. Funding of individual BCAC studies is listed in the Supplemental Note

Is schizophrenia a risk factor for breast cancer? – Evidence from genetic data

Observational epidemiological studies have found an association between schizophrenia and breast cancer, but it is not known if the relationship is a causal one. We used summary statistics from very large genome-wide association studies of schizophrenia (n = 40,675 cases and 64,643 controls) and breast cancer (n = 122,977 cases and 105,974 controls) to investigate whether there is evidence that the association is partly due to shared genetic risk factors and whether there is evidence of a causal relationship. Using LD-score regression, we found that there is a small but significant genetic correlation between the two disorders (rG = 0.14, S.E = 0.03, p = 4.75 x 10-8), indicating shared genetic risk factors. Using 142 genetic variants associated with schizophrenia as instrumental variables that are a proxy for having schizophrenia, we estimated a causal effect of schizophrenia on breast cancer on the observed scale as bxy = 0.032 (S.E. = 0.009, p = 2.3 x 10-4). A one standard deviation increase in liability to schizophrenia increases risk of breast cancer 1.09-fold. In contrast, the estimated causal effect of breast cancer on schizophrenia from 191 instruments was not significantly different from zero (bxy = -0.005, S.E. = 0.012, p =0.67). No evidence for pleiotropy was found and adjusting for the effects of smoking or parity did not alter the results. These results provide evidence that the previously observed association is due to schizophrenia causally increasing risk for breast cancer. Genetic variants may provide an avenue to elucidating the mechanism underpinning this relationship

Fine-Scale mapping of the 11q13 breast cancer susceptibility locus

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799–121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000–120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Perallelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08–1.13, $\small \textit{P}$ = 1.49 x 10$^{-21}$). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity $\small \textit{P}$ $\leq$ 8.41 x 10$^{-5}$). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.Cancer Research UK (Grant IDs: C1287/A10118, C1287/A12014, C490/A10124, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), European Community's Seventh Framework Programme (Grant ID: HEALTH-F2-2009-223175), National Institutes of Health (Grant IDs: CA128978, CA116167, CA176785, CA116201, CA63464, CA54281, CA098758, CA132839, R01CA100374, R01CA64277, R01CA148667, R37CA70867, R01CA092447), National Institute for Health Research. See also Table K via http://dx.doi.org/10.1371/journal.pone.0160316.s003This is the final version of the article. It first appeared from the Public Library of Science via http://dx.doi.org/10.1371/journal.pone.016031

Oral contraceptive use and breast cancer risk: retrospective and prospective analyses from a BRCA1 and BRCA2 mutation carrier cohort study

Background For BRCA1 and BRCA2 mutation carriers, the association between oral contraceptive preparation (OCP) use and breast cancer (BC) risk is still unclear. Methods BC risk associations were estimated from OCP data on 6,030 BRCA1 and 3,809 BRCA2 mutation carriers using age-dependent Cox regression, stratified by study and birth cohort. Prospective, left-truncated retrospective and full-cohort retrospective analyses were performed. Results For BRCA1 mutation carriers, OCP use was not associated with BC risk from prospective analyses (Hazard Ratio (HR) 1.08;95% Confidence Interval (CI) 0.75-1.56), but from the left-truncated and full-cohort retrospective analyses risks were increased by 26% (95%CI 6%-51%) and 39% (95%CI 23%-58%), respectively. For BRCA2 mutation carriers, OCP use was associated with BC risk from prospective analyses (HR 1.75;95%CI 1.03-2.97), but retrospective analyses were inconsistent (left-truncated: HR 1.06;95%CI 0.85-1.33; full-cohort: HR 1.52;95%CI 1.28-1.81). There was evidence of increasing risk with duration of use, especially before first full-term pregnancy (BRCA1: both retrospective analyses, p<0.001 and p=0.001, respectively; BRCA2: full-retrospective analysis, p=0.002). Conclusions Prospective analyses did not show that past use of OCP is associated with an increased BC risk for BRCA1 mutation carriers in young middle age women (40-50 years). For BRCA2 mutation carriers, a causal association is also not likely at those ages. Findings between retrospective and prospective analyses were inconsistent and could be due to survival bias or a true association for younger women who were underrepresented in the prospective cohort. Given uncertain safety of OCP use for BRCA1/2 mutation carriers, indications other than contraception should be avoided and non-hormonal contraceptive methods discussed

Identification of nine new susceptibility loci for endometrial cancer

Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS) we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5,624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes and risk alleles at two of these loci that associate with decreased expression of genes which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study

Circulating vitamin D concentrations and risk of breast and prostate cancer: a Mendelian randomization study

Background: Observational studies have suggested an association between circulating vitamin D concentrations [25(OH)D] and risk of breast and prostate cancer, which was not supported by a recent Mendelian randomization analysis comprising 15,748 breast and 22,898 prostate cancer cases. Demonstrating causality has proven challenging, and one common limitation of MR studies is insufficient power. Methods: We aim to determine if circulating concentrations of vitamin D are causally associated with the risk of breast and prostate cancer, by using summary level data from the largest-ever genome-wide association studies conducted on vitamin D (N=73,699), breast cancer (Ncase=122,977) and prostate cancer (Ncase=79,148). We constructed a stronger instrument using six common genetic variants (as compared with the previous four variants), and applied several two-sample MR methods.This work was supported by the Veteskapsrådet International Postdoc grant (XJ), the World Cancer Research Fund International Regular Grant Programme (WCRF 2014/1180) (KKT), the World Cancer Research Fund International grant (WCRF 2015/1421) (SL), the National Cancer Institute Grant (R00 CA207848) (SWA), the Cancer Research UK Programme Grant, the Integrative Cancer Epidemiology Programme (C18281/A19169) (RMM), and the National Institute for Health Research (NIHR) Bristol Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol

A genome-wide association study to identify genetic markers associated with endometrial cancer grade

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A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al