A comprehensive model for familial breast cancer incorporating BRCA1, BRCA2 and other genes

In computing the probability that a woman is a BRCA1 or BRCA2 carrier for genetic counselling purposes, it is important to allow for the fact that other breast cancer susceptibility genes may exist. We used data from both a population based series of breast cancer cases and high risk families in the UK, with information on BRCA1 and BRCA2 mutation status, to investigate the genetic models that can best explain familial breast cancer outside BRCA1 and BRCA2 families. We also evaluated the evidence for risk modifiers in BRCA1 and BRCA2 carriers. We estimated the simultaneous effects of BRCA1, BRCA2, a third hypothetical gene ‘BRCA3’, and a polygenic effect using segregation analysis. The hypergeometric polygenic model was used to approximate polygenic inheritance and the effect of risk modifiers. BRCA1 and BRCA2 could not explain all the observed familial clustering. The best fitting model for the residual familial breast cancer was the polygenic, although a model with a single recessive allele produced a similar fit. There was also significant evidence for a modifying effect of other genes on the risks of breast cancer in BRCA1 and BRCA2 mutation carriers. Under this model, the frequency of BRCA1 was estimated to be 0.051% (95% CI: 0.021–0.125%) and of BRCA2 0.068% (95% CI: 0.033–0.141%). The breast cancer risk by age 70 years, based on the average incidence over all modifiers was estimated to be 35.3% for BRCA1 and 50.3% for BRCA2. The corresponding ovarian cancer risks were 25.9% for BRCA1 and 9.1% for BRCA2. The findings suggest that several common, low penetrance genes with multiplicative effects on risk may account for the residual non-BRCA1/2 familial aggregation of breast cancer. The modifying effect may explain the previously reported differences between population based estimates for BRCA1/2 penetrance and estimates based on high-risk families

Immune-Complex Mimics as a Molecular Platform for Adjuvant-Free Vaccine Delivery

Protein-based vaccine development faces the difficult challenge of finding robust yet non-toxic adjuvants suitable for humans. Here, using a molecular engineering approach, we have developed a molecular platform for generating self-adjuvanting immunogens that do not depend on exogenous adjuvants for induction of immune responses. These are based on the concept of Immune Complex Mimics (ICM), structures that are formed between an oligomeric antigen and a monoclonal antibody (mAb) to that antigen. In this way, the roles of antigens and antibodies within the structure of immune complexes are reversed, so that a single monoclonal antibody, rather than polyclonal sera or expensive mAb cocktails can be used. We tested this approach in the context of Mycobacterium tuberculosis (MTB) infection by linking the highly immunogenic and potentially protective Ag85B with the oligomeric Acr (alpha crystallin, HspX) antigen. When combined with an anti-Acr monoclonal antibody, the fusion protein formed ICM which bound to C1q component of the complement system and were readily taken up by antigen-presenting cells in vitro. ICM induced a strong Th1/Th2 mixed type antibody response, which was comparable to cholera toxin adjuvanted antigen, but only moderate levels of T cell proliferation and IFN-γ secretion. Unfortunately, the systemic administration of ICM did not confer statistically significant protection against intranasal MTB challenge, although a small BCG-boosting effect was observed. We conclude that ICM are capable of inducing strong humoral responses to incorporated antigens and may be a suitable vaccination approach for pathogens other than MTB, where antibody-based immunity may play a more protective role

Validation of Case-Finding Algorithms Derived from Administrative Data for Identifying Adults Living with Human Immunodeficiency Virus Infection

OBJECTIVE: We sought to validate a case-finding algorithm for human immunodeficiency virus (HIV) infection using administrative health databases in Ontario, Canada. METHODS: We constructed 48 case-finding algorithms using combinations of physician billing claims, hospital and emergency room separations and prescription drug claims. We determined the test characteristics of each algorithm over various time frames for identifying HIV infection, using data abstracted from the charts of 2,040 randomly selected patients receiving care at two medical practices in Toronto, Ontario as the reference standard. RESULTS: With the exception of algorithms using only a single physician claim, the specificity of all algorithms exceeded 99%. An algorithm consisting of three physician claims over a three year period had a sensitivity and specificity of 96.2% (95% CI 95.2%-97.9%) and 99.6% (95% CI 99.1%-99.8%), respectively. Application of the algorithm to the province of Ontario identified 12,179 HIV-infected patients in care for the period spanning April 1, 2007 to March 31, 2009. CONCLUSIONS: Case-finding algorithms generated from administrative data can accurately identify adults living with HIV. A relatively simple "3 claims in 3 years" definition can be used for assembling a population-based cohort and facilitating future research examining trends in health service use and outcomes among HIV-infected adults in Ontario

The quest for the solar g modes

Solar gravity modes (or g modes) -- oscillations of the solar interior for which buoyancy acts as the restoring force -- have the potential to provide unprecedented inference on the structure and dynamics of the solar core, inference that is not possible with the well observed acoustic modes (or p modes). The high amplitude of the g-mode eigenfunctions in the core and the evanesence of the modes in the convection zone make the modes particularly sensitive to the physical and dynamical conditions in the core. Owing to the existence of the convection zone, the g modes have very low amplitudes at photospheric levels, which makes the modes extremely hard to detect. In this paper, we review the current state of play regarding attempts to detect g modes. We review the theory of g modes, including theoretical estimation of the g-mode frequencies, amplitudes and damping rates. Then we go on to discuss the techniques that have been used to try to detect g modes. We review results in the literature, and finish by looking to the future, and the potential advances that can be made -- from both data and data-analysis perspectives -- to give unambiguous detections of individual g modes. The review ends by concluding that, at the time of writing, there is indeed a consensus amongst the authors that there is currently no undisputed detection of solar g modes.Comment: 71 pages, 18 figures, accepted by Astronomy and Astrophysics Revie

Beliefs about weight and breast cancer: An interview study with high risk women following a 12 month weight loss intervention

This is an Version of Record of an article published by BioMed Central in Hereditary Cancer in Clinical Practice on 9 January 2015, available online: http://www.hccpjournal.com/content/13/1/1 This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Breast cancer is the most common cancer in the UK. Lifestyle factors including excess weight contribute to risk of developing the disease. Whilst the exact links between weight and breast cancer are still emerging, it is imperative to explore how women understand these links and if these beliefs impact on successful behaviour change. Overweight/obese premenopausal women (aged 35–45) with a family history of breast cancer (lifetime risk 17–40%) were invited to a semi-structured interview following their participation in a 12 month weight loss intervention aimed at reducing their risk of breast cancer. Interviews were carried out with 9 women who successfully achieved ≥5% weight loss and 11 who were unsuccessful. Data were transcribed verbatim and analysed using thematic analysis. Three themes were developed from the analysis. The first theme how women construct and understand links between weight and breast cancer risk is composed of two subthemes, the construction of weight and breast cancer risk and making sense of weight and breast cancer risk. The second theme - motivation and adherence to weight loss interventions - explains that breast cancer risk can be a motivating factor for adherence to a weight loss intervention. The final theme, acceptance of personal responsibility for health is composed of two subthemes responsibility for one’s own health and responsibility for family health through making sensible lifestyle choices.Beliefs about weight and breast cancer risk were informed by social networks, media reports and personal experiences of significant others diagnosed with breast cancer. Our study has highlighted common doubts, anxieties and questions and the importance of providing a credible rationale for weight control and weight loss which addresses individual concerns

Fine mapping of the 9q31 Hirschsprung’s disease locus

Hirschsprung’s disease (HSCR) is a congenital disorder characterised by the absence of ganglia along variable lengths of the intestine. The RET gene is the major HSCR gene. Reduced penetrance of RET mutations and phenotypic variability suggest the involvement of additional modifying genes in the disease. A RET-dependent modifier locus was mapped to 9q31 in families bearing no coding sequence (CDS) RET mutations. Yet, the 9q31 causative locus is to be identified. To fine-map the 9q31 region, we genotyped 301 tag-SNPs spanning 7 Mb on 137 HSCR Dutch trios. This revealed two HSCR-associated regions that were further investigated in 173 Chinese HSCR patients and 436 controls using the genotype data obtained from a genome-wide association study recently conducted. Within one of the two identified regions SVEP1 SNPs were found associated with Dutch HSCR patients in the absence of RET mutations. This ratifies the reported linkage to the 9q31 region in HSCR families with no RET CDS mutations. However, this finding could not be replicated. In Chinese, HSCR was found associated with IKBKAP. In contrast, this association was stronger in patients carrying RET CDS mutations with p = 5.10 × 10−6 [OR = 3.32 (1.99, 5.59)] after replication. The HSCR-association found for IKBKAP in Chinese suggests population specificity and implies that RET mutation carriers may have an additional risk. Our finding is supported by the role of IKBKAP in the development of the nervous system

Oral contraceptive use and ovarian cancer risk among carriers of BRCA1 or BRCA2 mutations

Women with mutations of the genes BRCA1 or BRCA2 are at increased risk of ovarian cancer. Oral contraceptives protect against ovarian cancer in general, but it is not known whether they protect against the disease in carriers of these mutations. We obtained self-reported lifetime histories of oral contraceptive use from 451 women who carried mutations of BRCA1 or BRCA2. We used conditional logistic regression to estimate the odds ratios associated with oral contraceptive use, comparing the histories of 147 women with ovarian cancer (cases) to those of 304 women without ovarian cancer (controls) who were matched to cases on year of birth, country of residence and gene (BRCA1 vs BRCA2). Reference ages for controls had to exceed the ages at diagnosis of their matched cases. After adjusting for parity, the odds-ratio for ovarian cancer associated with use of oral contraceptives for at least 1 year was 0.85 (95 percent confidence interval, 0.53-1.36). The risk decreased by 5% (1-9%) with each year of use (P for trend=0.01). Use for 6 or more years was associated with an odds-ratio of 0.62 (0.35-1.09). These data support the hypothesis that long-term oral contraceptive use reduces the risk of ovarian cancer among women who carry mutations of BRCA1 or BRCA2

SNP-SNP interactions in breast cancer susceptibility

BACKGROUND: Breast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2) are responsible for less than 5% of all breast cancer cases. Many studies have shown that the cancer risks associated with individual commonly occurring single nucleotide polymorphisms (SNPs) are incremental. However, polygenic models suggest that multiple commonly occurring low to modestly penetrant SNPs of cancer related genes might have a greater effect on a disease when considered in combination. METHODS: In an attempt to identify the breast cancer risk conferred by SNP interactions, we have studied 19 SNPs from genes involved in major cancer related pathways. All SNPs were genotyped by TaqMan 5'nuclease assay. The association between the case-control status and each individual SNP, measured by the odds ratio and its corresponding 95% confidence interval, was estimated using unconditional logistic regression models. At the second stage, two-way interactions were investigated using multivariate logistic models. The robustness of the interactions, which were observed among SNPs with stronger functional evidence, was assessed using a bootstrap approach, and correction for multiple testing based on the false discovery rate (FDR) principle. RESULTS: None of these SNPs contributed to breast cancer risk individually. However, we have demonstrated evidence for gene-gene (SNP-SNP) interaction among these SNPs, which were associated with increased breast cancer risk. Our study suggests cross talk between the SNPs of the DNA repair and immune system (XPD-[Lys751Gln] and IL10-[G(-1082)A]), cell cycle and estrogen metabolism (CCND1-[Pro241Pro] and COMT-[Met108/158Val]), cell cycle and DNA repair (BARD1-[Pro24Ser] and XPD-[Lys751Gln]), and within carcinogen metabolism (GSTP1-[Ile105Val] and COMT-[Met108/158Val]) pathways. CONCLUSION: The importance of these pathways and their communication in breast cancer predisposition has been emphasized previously, but their biological interactions through SNPs have not been described. The strategy used here has the potential to identify complex biological links among breast cancer genes and processes. This will provide novel biological information, which will ultimately improve breast cancer risk management