An accurate test for homogeneity of odds ratios based on Cochran's Q-statistic

Background: A frequently used statistic for testing homogeneity in a meta-analysis of K independent studies is Cochran's Q. For a standard test of homogeneity the Q statistic is referred to a chi-square distribution with K - 1 degrees of freedom. For the situation in which the effects of the studies are logarithms of odds ratios, the chi-square distribution is much too conservative for moderate size studies, although it may be asymptotically correct as the individual studies become large. Methods: Using a mixture of theoretical results and simulations, we provide formulas to estimate the shape and scale parameters of a gamma distribution to t the distribution of Q. Results: Simulation studies show that the gamma distribution is a good approximation to the distribution for Q. Conclusions: : Use of the gamma distribution instead of the chi-square distribution for Q should eliminate inaccurate inferences in assessing homogeneity in a meta-analysis. (A computer program for implementing this test is provided.) This hypothesis test is competitive with the Breslow-Day test both in accuracy of level and in power

The National Women's Health Study: assembly and description of a population-based reproductive cohort

BACKGROUND: Miscarriage is a common event but is remarkably difficult to measure in epidemiological studies. Few large-scale population-based studies have been conducted in the UK. METHODS: This was a population-based two-stage postal survey of reproductive histories of adult women living in the United Kingdom in 2001, sampled from the electronic electoral roll. In Stage 1 a short "screening" questionnaire was sent to over 60,000 randomly selected women in order to identify those aged 55 and under who had ever been pregnant or ever attempted to achieve a pregnancy, from whom a brief reproductive history was requested. Stage 2 involved a more lengthy questionnaire requesting detailed information on every pregnancy (and fertility problems), and questions relating to socio-demographic, behavioural and other factors for the most recent pregnancy in order to examine risk factors for miscarriage. Data on stillbirth, multiple birth and maternal age are compared to national data in order to assess response bias. RESULTS: The response rate was 49% for Stage 1 and 73% for the more targeted Stage 2. A total of 26,050 questionnaires were returned in Stage 1. Of the 17,748 women who were eligible on the grounds of age, 27% reported that they had never been pregnant and had never attempted to conceive a child. The remaining 13,035 women reported a total of 30,661 pregnancies. Comparison of key reproductive indicators (stillbirth and multiple birth rates and maternal age at first birth) with national statistics showed that the data look remarkably similar to the general population. CONCLUSIONS: This study has enabled the assembly of a large population-based dataset of women's reproductive histories which appears unbiased compared to the general UK population and which will enable investigation of hard-to-measure outcomes such as miscarriage and infertility

The yeast P5 type ATPase, Spf1, regulates manganese transport into the endoplasmic reticulum

The endoplasmic reticulum (ER) is a large, multifunctional and essential organelle. Despite intense research, the function of more than a third of ER proteins remains unknown even in the well-studied model organism Saccharomyces cerevisiae. One such protein is Spf1, which is a highly conserved, ER localized, putative P-type ATPase. Deletion of SPF1 causes a wide variety of phenotypes including severe ER stress suggesting that this protein is essential for the normal function of the ER. The closest homologue of Spf1 is the vacuolar P-type ATPase Ypk9 that influences Mn2+ homeostasis. However in vitro reconstitution assays with Spf1 have not yielded insight into its transport specificity. Here we took an in vivo approach to detect the direct and indirect effects of deleting SPF1. We found a specific reduction in the luminal concentration of Mn2+ in ∆spf1 cells and an increase following it’s overexpression. In agreement with the observed loss of luminal Mn2+ we could observe concurrent reduction in many Mn2+-related process in the ER lumen. Conversely, cytosolic Mn2+-dependent processes were increased. Together, these data support a role for Spf1p in Mn2+ transport in the cell. We also demonstrate that the human sequence homologue, ATP13A1, is a functionally conserved orthologue. Since ATP13A1 is highly expressed in developing neuronal tissues and in the brain, this should help in the study of Mn2+-dependent neurological disorders

Women's knowledge and beliefs regarding breast cancer

Approximately 20–30% of women delay for 12 weeks or more from self-discovery of a breast symptom to presentation to a health care provider, and such delay intervals are associated with poorer survival. Understanding the factors that influence patient delay is important for the development of an effective, targeted health intervention programme to shorten patient delay. The aim of the study was to elicit knowledge and beliefs about breast cancer among a sample of the general female population, and examine age and socio-economic variations in responses. Participants were randomly selected through the Postal Address File, and data were collected through the Office of National Statistics. Geographically distributed throughout the UK, 996 women participated in a short structured interview to elicit their knowledge of breast cancer risk, breast cancer symptoms, and their perceptions of the management and outcomes associated with breast cancer. Women had limited knowledge of their relative risk of developing breast cancer, of associated risk factors and of the diversity of potential breast cancer-related symptoms. Older women were particularly poor at identifying symptoms of breast cancer, risk factors associated with breast cancer and their personal risk of developing the disease. Poorer knowledge of symptoms and risks among older women may help to explain the strong association between older age and delay in help-seeking. If these findings are confirmed they suggest that any intervention programme should target older women in particular, given that advancing age is a risk factor for both developing breast cancer and for subsequent delayed presentation

A prospective study of the relationship between prediagnostic Human Papillomavirus seropositivity and HPV DNA in subsequent cervical carcinomas

Several prospective studies with invasive carcinoma as endpoint have supported Human Papillomavirus as a cause of cervical carcinoma. However, the largest study used seroepidemiology and did not analyse presence of Human Papillomavirus DNA in the subsequent tumour. Linkage of serum bank registries and cancer registries had identified 196 women with a registered cervical carcinoma after donation of a serum sample. For the present study, biopsies for 127 cases could be located, verified to contain invasive carcinoma and be amplified by PCR. Three control women who had remained alive and without cervical carcinoma during an equal length of follow-up had been matched to each of the case women and tested for HPV antibodies. Presence of Human Papillomavirus DNA in the tumours was analysed by general primer and type specific PCR. HPV16-seropositive women had a relative risk of 4.4 (95% CI: 2.2–8.8) to develop cervical carcinoma carrying HPV16 DNA. By contrast, there was no excess risk for Human Papillomavirus 16-seropositive women to develop cervical carcinoma devoid of HPV16 DNA. Prediagnostic HPV16 seropositivity was strongly correlated with later HPV16 DNA positivity of the tumour (P<0.001) and prediagnostic HPV18 seropositivity correlated with HPV18 DNA in the tumour (P<0.03). The link between prediagnostic seropositivity and type of viral DNA in the cancer implies that the carcinogenic effect of infection with these viruses is dependent on persistent presence of type-specific viral DNA

Quantitative Epistasis Analysis and Pathway Inference from Genetic Interaction Data

Inferring regulatory and metabolic network models from quantitative genetic interaction data remains a major challenge in systems biology. Here, we present a novel quantitative model for interpreting epistasis within pathways responding to an external signal. The model provides the basis of an experimental method to determine the architecture of such pathways, and establishes a new set of rules to infer the order of genes within them. The method also allows the extraction of quantitative parameters enabling a new level of information to be added to genetic network models. It is applicable to any system where the impact of combinatorial loss-of-function mutations can be quantified with sufficient accuracy. We test the method by conducting a systematic analysis of a thoroughly characterized eukaryotic gene network, the galactose utilization pathway in Saccharomyces cerevisiae. For this purpose, we quantify the effects of single and double gene deletions on two phenotypic traits, fitness and reporter gene expression. We show that applying our method to fitness traits reveals the order of metabolic enzymes and the effects of accumulating metabolic intermediates. Conversely, the analysis of expression traits reveals the order of transcriptional regulatory genes, secondary regulatory signals and their relative strength. Strikingly, when the analyses of the two traits are combined, the method correctly infers ∼80% of the known relationships without any false positives

The Complete Spectrum of Yeast Chromosome Instability Genes Identifies Candidate CIN Cancer Genes and Functional Roles for ASTRA Complex Components

Chromosome instability (CIN) is observed in most solid tumors and is linked to somatic mutations in genome integrity maintenance genes. The spectrum of mutations that cause CIN is only partly known and it is not possible to predict a priori all pathways whose disruption might lead to CIN. To address this issue, we generated a catalogue of CIN genes and pathways by screening ∼2,000 reduction-of-function alleles for 90% of essential genes in Saccharomyces cerevisiae. Integrating this with published CIN phenotypes for other yeast genes generated a systematic CIN gene dataset comprised of 692 genes. Enriched gene ontology terms defined cellular CIN pathways that, together with sequence orthologs, created a list of human CIN candidate genes, which we cross-referenced to published somatic mutation databases revealing hundreds of mutated CIN candidate genes. Characterization of some poorly characterized CIN genes revealed short telomeres in mutants of the ASTRA/TTT components TTI1 and ASA1. High-throughput phenotypic profiling links ASA1 to TTT (Tel2-Tti1-Tti2) complex function and to TORC1 signaling via Tor1p stability, consistent with the role of TTT in PI3-kinase related kinase biogenesis. The comprehensive CIN gene list presented here in principle comprises all conserved eukaryotic genome integrity pathways. Deriving human CIN candidate genes from the list allows direct cross-referencing with tumor mutational data and thus candidate mutations potentially driving CIN in tumors. Overall, the CIN gene spectrum reveals new chromosome biology and will help us to understand CIN phenotypes in human disease

Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform

Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies