Fine-scale mapping in case-control samples using locus scoring and haplotype-sharing methods

Both haplotype-based and locus-based methods have been proposed as the most powerful methods to employ when fine mapping by association. Although haplotype-based methods utilize more information, they may lose power as a result of overparameterization, given the large number of haplotypes possible over even a few loci. Recently methods have been developed that cluster haplotypes with similar structure in the hope that this reflects shared genealogical ancestry. The aim is to reduce the number of parameters while retaining the genotype information relating to disease susceptibility. We have compared several haplotype-based methods with locus-based methods. We utilized 2 regions (D2 and D4) simulated to be in linkage disequilibrium and to be associated with disease susceptibility, combining 5 replicates at a time to produce 4 datasets that were analyzed. We found little difference in the performance of the haplotype-based methods and the locus-based methods in this dataset

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-

Wafer bonding and layer transfer processes for 4-junction high efficiency solar cells

A four-junction cell design consisting of InGaAs, InGeAsP, GaAs, and Ga0.5In0.5P subcells could reach 1 x AMO efficiencies of 35.4%. but relies on the integration of non-lattice-matched materials. Wafer bonding and layer transfer processes show promise in the fabrication of InP/Si epitaxial templates for growth of the bottom InGaAs and InGaAsP subcells on a Si support substrate. Subsequent wafer bonding and layer transfer of a thin Ge layer onto the lower subcell stack can serve as an epitaxial template for GaAs and Ga0.5In0.5P subcelis. Present results indicate that optically active III/V compound semiconductors can be grown on both Ge/Si and InP/Si heterostructures. Current-voltage electrical characterization of the interfaces of these structures indicates that both InP/Si and Ge/Si interfaces have specific resistances lower than 0.1 Ωcm^2 for heavily doped wafer bonded interfaces, enabling back surface power extraction from the finished cell structure

Citizen-led sampling to monitor phosphate levels in freshwater environments using a simple paper microfluidic device

Contamination of waterways is of increasing concern, with recent studies demonstrating elevated levels of antibiotics, antidepressants, household, agricultural and industrial chemicals in freshwater systems. Thus, there is a growing demand for methods to rapidly and conveniently monitor contaminants in waterways. Here we demonstrate how a combination of paper microfluidic devices and handheld mobile technology can be used by citizen scientists to carry out a sustained water monitoring campaign. We have developed a paper-based analytical device and a 3 minute sampling workflow that requires no more than a container, a test device and a smartphone app. The contaminant measured in these pilots are phosphates, detectable down to 3 mg L-1. Together these allow volunteers to successfully carry out cost-effective, high frequency, phosphate monitoring over an extended geographies and periods

Linkage disequilibrium mapping of CHEK2: Common variation and breast cancer risk

10.1371/journal.pmed.0030168PLoS Medicine360895-090

An Overview of Strategies for Detecting Genotype-Phenotype Associations Across Ancestrally Diverse Populations

Genome-wide association studies (GWAS) have been very successful at identifying genetic variants influencing a large number of traits. Although the great majority of these studies have been performed in European-descent individuals, it has been recognised that including populations with differing ancestries enhances the potential for identifying causal SNPs due to their differing patterns of linkage disequilibrium. However, when individuals from distinct ethnicities are included in a GWAS, it is necessary to implement a number of control steps to ensure that the identified associations are real genotype-phenotype relationships. In this Review, we discuss the analyses that are required when performing multi-ethnic studies, including methods for determining ancestry at the global and local level for sample exclusion, controlling for ancestry in association testing, and post-GWAS interrogation methods such as genomic control and meta-analysis. We hope that this overview provides a primer for those researchers interested in including distinct populations in their studies

Sticky knowledge: A possible model for investigating implementation in healthcare contexts

<p>Abstract</p> <p>Background</p> <p>In health care, a well recognized gap exists between what we know should be done based on accumulated evidence and what we actually do in practice. A body of empirical literature shows organizations, like individuals, are difficult to change. In the business literature, knowledge management and transfer has become an established area of theory and practice, whilst in healthcare it is only starting to establish a firm footing. Knowledge has become a business resource, and knowledge management theorists and practitioners have examined how knowledge moves in organisations, how it is shared, and how the return on knowledge capital can be maximised to create competitive advantage. New models are being considered, and we wanted to explore the applicability of one of these conceptual models to the implementation of evidence-based practice in healthcare systems.</p> <p>Methods</p> <p>The application of a conceptual model called sticky knowledge, based on an integration of communication theory and knowledge transfer milestones, into a scenario of attempting knowledge transfer in primary care.</p> <p>Results</p> <p>We describe Szulanski's model, the empirical work he conducted, and illustrate its potential applicability with a hypothetical healthcare example based on improving palliative care services. We follow a doctor through two different posts and analyse aspects of knowledge transfer in different primary care settings. The factors included in the sticky knowledge model include: causal ambiguity, unproven knowledge, motivation of source, credibility of source, recipient motivation, recipient absorptive capacity, recipient retentive capacity, barren organisational context, and arduous relationship between source and recipient. We found that we could apply all these factors to the difficulty of implementing new knowledge into practice in primary care settings.</p> <p>Discussion</p> <p>Szulanski argues that knowledge factors play a greater role in the success or failure of a knowledge transfer than has been suspected, and we consider that this conjecture requires further empirical work in healthcare settings.</p

A comprehensive re-assessment of the association between vitamin D and cancer susceptibility using Mendelian randomization.

Previous Mendelian randomization (MR) studies on 25-hydroxyvitamin D (25(OH)D) and cancer have typically adopted a handful of variants and found no relationship between 25(OH)D and cancer; however, issues of horizontal pleiotropy cannot be reliably addressed. Using a larger set of variants associated with 25(OH)D (74 SNPs, up from 6 previously), we perform a unified MR analysis to re-evaluate the relationship between 25(OH)D and ten cancers. Our findings are broadly consistent with previous MR studies indicating no relationship, apart from ovarian cancers (OR 0.89; 95% C.I: 0.82 to 0.96 per 1 SD change in 25(OH)D concentration) and basal cell carcinoma (OR 1.16; 95% C.I.: 1.04 to 1.28). However, after adjustment for pigmentation related variables in a multivariable MR framework, the BCC findings were attenuated. Here we report that lower 25(OH)D is unlikely to be a causal risk factor for most cancers, with our study providing more precise confidence intervals than previously possible

Germline variants are associated with increased primary melanoma tumor thickness at diagnosis

Germline genetic variants have been identified, which predispose individuals and families to develop melanoma. Tumor thickness is the strongest predictor of outcome for clinically localized primary melanoma patients. We sought to determine whether there is a heritable genetic contribution to variation in tumor thickness. If confirmed, this will justify the search for specific genetic variants influencing tumor thickness. To address this, we estimated the proportion of variation in tumor thickness attributable to genome-wide genetic variation (variant-based heritability) using unrelated patients with measured primary cutaneous melanoma thickness. As a secondary analysis, we conducted a genome-wide association study (GWAS) of tumor thickness. The analyses utilized 10 604 individuals with primary cutaneous melanoma drawn from nine GWAS datasets from eight cohorts recruited from the general population, primary care and melanoma treatment centers. Following quality control and filtering to unrelated individuals with study phenotypes, 8125 patients were used in the primary analysis to test whether tumor thickness is heritable. An expanded set of 8505 individuals (47.6% female) were analyzed for the secondary GWAS meta-analysis. Analyses were adjusted for participant age, sex, cohort and ancestry. We found that 26.6% (SE 11.9%, P = 0.0128) of variation in tumor thickness is attributable to genome-wide genetic variation. While requiring replication, a chromosome 11 locus was associated (P < 5 × 10-8) with tumor thickness. Our work indicates that sufficiently large datasets will enable the discovery of genetic variants associated with greater tumor thickness, and this will lead to the identification of host biological processes influencing melanoma growth and invasion.E.M. was supported by the Malaysian Ministry of Higher Education and Universiti Sains Malaysia to study for a PhD at the University of Leeds. A.E.C. was supported by a National Health and Medical Research Council (NHMRC) of Australia Career Development Fellowship (1147843). K.K. was supported by an NHMRC Career Development Fellowship (1125290). M.M.I. was supported by Cancer Research UK (c588/a19167) and the NIH (ca083115). R.A.S. and G.V.L. are supported by NHMRC Practitioner Fellowships; R.A.S. and J.F.T. also acknowledge support from an NHMRC program grant. D.C.W., S.M. and N.K.H were supported by NHMRC Research Fellowships (1058522, 1155413, 1154543 and 1117663). We thank Nicholas G. Martin for assistance with access to data from the Q-MEGA cohort and with manuscript writing. This work was conducted using the UK Biobank Resource (application number 25331)

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes