Power Boosting in Genome-Wide Studies Via Methods for Multivariate Outcomes

Whole-genome studies are becoming a mainstay of biomedical research. Examples include expression array experiments, comparative genomic hybridization analyses and large case-control studies for detecting polymorphism/disease associations. The tactic of applying a regression model to every locus to obtain test statistics is useful in such studies. However, this approach ignores potential correlation structure in the data that could be used to gain power, particularly when a Bonferroni correction is applied to adjust for multiple testing. In this article, we propose using regression techniques for misspecified multivariate outcomes to increase statistical power over independence-based modeling at each locus. Even when the outcome is not ordinarily regarded as multivariate, it is mathematically valid to view the outcome as a set of (identical) repeated measurements, one associated with each genetic locus. Rather than joint modeling of all observations, we propose to apply joint modeling to subgroups of data. The primary example in this article focuses on the use of generalized estimating equations (GEE) software to apply the method. We describe conditions under which the proposed method provides more power than applying independence-based methods. In simulation studies of plausible and interesting scenarios, power gains are as large as 35% compared to modeling the outcomes univariately with a one genetic covariate. In contrast, modeling the outcome as univariate with multiple genetic covariates performs very poorly when data are correlated. The proposed method is easy to apply, allows adjustment for confounding and can be combined with other methods for increasing power in multiple testing situations

Practical Synthesis of Unsymmetrical Tetraarylethylenes and Their Application for the Preparation of [Triphenylethylene−Spacer−Triphenylethylene] Triads

We have demonstrated that reactions of diphenylmethyllithium with a variety of substituted benzophenones produces corresponding tertiary alcohols that are easily dehydrated, without any need for purification, to produce various unsymmetrical and symmetrical tetraarylethylenes in excellent yields. The simplicity of the method allows for the preparation of a variety of ethylenic derivatives in multigram (10−50 g) quantities with great ease. The methodology was successfully employed for the preparation of various triphenylethylene (TPE)-based triads (i.e., TPE−spacer−TPE) containing polyphenylene and fluoranyl-based spacers. The ready availability of various substituted tetraarylethylenes allowed us to shed light on the effect of substituents on the oxidation potentials (Eox) of various tetraarylethylenes. Moreover, the electronic coupling among the triphenylethylene moieties in various TPE−spacer−TPE triads was briefly probed by electrochemical and optical methods

A new mixture model approach to analyzing allelic-loss data using Bayes factors

BACKGROUND: Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor suppressor gene can lead to tumor development, one objective of these studies is to determine which, if any, chromosome arms harbor tumor suppressor genes. RESULTS: We propose a large class of mixture models for describing the data, and we suggest using Bayes factors to select a reasonable model from the class in order to classify the chromosome arms. Bayes factors are especially useful in the case of testing that the number of components in a mixture model is n(0 )versus n(1). In these cases, frequentist test statistics based on the likelihood ratio statistic have unknown distributions and are therefore not applicable. Our simulation study shows that Bayes factors favor the right model most of the time when tumor suppressor genes are present. When no tumor suppressor genes are present and background allelic-loss varies, the Bayes factors are often inconclusive, although this results in a markedly reduced false-positive rate compared to that of standard frequentist approaches. Application of our methods to three data sets of esophageal adenocarcinomas yields interesting differences from those results previously published. CONCLUSIONS: Our results indicate that Bayes factors are useful for analyzing allelic-loss data

Flow distortion investigation of wind velocity perturbations for two ocean meteorological platforms

A computational fluid dynamics (CFD) study was performed of the wind flow around two ocean buoys used to collect meteorological data from sensors mounted on the buoy tower. The CFD approach allowed wind velocity perturbations to be evaluated as a step towards quantifying the impacts of flow distortion on buoy wind measurements. The two buoys evaluated were the Wood Hole Oceanographic Institution WHOI Modular Ocean Buoy System and the University of New Hampshire (UNH) 2.1 m discus buoy. Engineering drawings were used to create a computational mesh for each buoy. Suitable solution methods were then developed and tested, CFD simulations were performed, and the results evaluated. Eleven CFD runs were performed, six for the WHOI buoy and five for the UNH buoy. Highlights of analysis for the WHOI buoy were that horizontal flow distortion was relatively small (<1%) for head-on flow, but that the tendency of the buoy to establish an angle of about 30 degrees relative to the flow resulted in acceleration at one anemometer location and deceleration at the other. Highlights of the analysis for the UNH buoy were that flow distortion of about 5% at the wind sensor location could be cut by about a factor of two by either raising the sensor by 2 ft or removing solar panels.Funding was provided by the National Oceanic and Atmospheric Administration under Grant No. NA17RJ1223 for the Cooperative Institute for Climate and Ocean Research (CICOR)

Which children and young people are excluded from school? Findings from the Avon Longitudinal Study of Parents and Children (ALSPAC) - poster abstract

Poster abstract presented at Spring Meeting for Clinician Scientists in Training 2015BACKGROUND: School exclusion is a disciplinary method used to remove a child from the school environment. It is known to affect certain groups disproportionately, including boys, some ethnic minorities, children in care, children in poverty, and children with special educational needs. Population-based studies on wider characteristics of excluded pupils are scarce. The aim of this study was to describe factors associated with school exclusion in the Avon Longitudinal Study of Parents and Children (ALSPAC), focussing on neurodevelopment and mental health. METHODS: ALSPAC is a prospective population-based British birth cohort study, with the initial sample consisting of 14 541 pregnancies. The study has data for whether a child has been permanently excluded from school up to the age of 8 years as reported by parents and also permanent and fixed period exclusions in the preceding 12 months as reported by parents and young people at age 16 years. Upstream risk factors were assessed for associations with exclusion on univariable analysis. The association with social communication difficulties was investigated with multivariable logistic regression. FINDINGS: Data for exclusions up to the age of 8 years were available for 8245 ALSPAC participants and 4482 participants for exclusion at age 16 years. 53 pupils (0·6%) were excluded from school by age 8 years, and 390 (8·7%) at age 16 years. The odds of exclusion by 8 years and at 16 years were increased with male sex (p=0·001 and p<0·0001, respectively), low family income (p=0·014 and p<0·0001), family adversity (p<0·0001 for both), maternal psychopathology (p=0·013 and p=0·004), low intelligence quotient (p=0·041 and p<0·0001), mental health difficulties (p<0·0001 for both), psychiatric disorder (p<0·0001 for both), social communication difficulties (p<0·0001 for both), antisocial activities (p=0·004 and p<0·0001), bullying or being bullied (p=0·005 and p<0·0001), low educational attainment (p<0·0001 for both), and increased special educational needs (p<0·0001 for both). On multivariable analysis, having social communication difficulties above a clinical threshold on the Social Communication Disorders Checklist was strongly associated with exclusion by 8 years (odds ratio 7·4, 95% CI 3·6-15·4) and at 16 years (2·3, 1·5-3·5), after adjustment for relevant confounders. INTERPRETATION: Although cohort attrition and small numbers of exclusions at 8 years are limitations, this study suggests that school exclusion is associated with numerous risk factors identifiable at or before primary school entry. Child health professionals have an important role in the holistic assessment of children who are excluded, or who are at risk of school exclusion. There is particular need to ensure that mental health and neurodevelopmental difficulties are appropriately recognised and supported. FUNDING: National Institute for Health Research Academic Clinical Fellowship

Comparison of the Use of a Physiologically Based Pharmacokinetic Model and a Classical Pharmacokinetic Model for Dioxin Exposure Assessments

In epidemiologic studies, exposure assessments of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) assume a fixed elimination rate. Recent data suggest a dose-dependent elimination rate for TCDD. A physiologically based pharmacokinetic (PBPK) model, which uses a body-burden–dependent elimination rate, was developed previously in rodents to describe the pharmacokinetics of TCDD and has been extrapolated to human exposure for this study. Optimizations were performed using data from a random selection of veterans from the Ranch Hand cohort and data from a human volunteer who was exposed to TCDD. Assessment of this PBPK model used additional data from the Ranch Hand cohort and a clinical report of two women exposed to TCDD. This PBPK model suggests that previous exposure assessments may have significantly underestimated peak blood concentrations, resulting in potential exposure misclassifications. Application of a PBPK model that incorporates an inducible elimination of TCDD may improve the exposure assessments in epidemiologic studies of TCDD

Is severity of motor coordination difficulties related to co-morbidity in children at risk for developmental coordination disorder?

Aim of the study was to investigate whether 7-9 year old children with severe motor difficulties are more at risk of additional difficulties in activities in daily living, academic skills, attention and social skills than children with moderate motor difficulties. Children (N=6959) from a population based cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC), were divided into three groups based on their scores on the ALSPAC Coordination Test at age 7: control children (scores above 15th centile; N=5719 [82.1%]); children with moderate (between 5th and 15th centile; N=951 [13.7%]); and children with severe motor difficulties (below 5th centile N=289 [4.2%]). Children with neurological disorders or an IQ<70 were excluded. Logistic regression was used to compare children with moderate and severe motor coordination difficulties with each other and with control children regarding their risk of co-morbidity defined as significant (<10th centile) difficulties with activities of daily living (ADL); academic skills (reading, spelling and handwriting); attention; social skills (social cognition and nonverbal skills). Children with severe motor difficulties demonstrated a higher risk of difficulties in ADL, handwriting, attention, reading, and social cognition than children with moderate motor difficulties, who in turn had a higher risk of difficulties than control children in five out of seven domains. Screening and intervention of co-morbid problems is recommended for children with both moderate and severe motor difficulties

Development of the Surgical Patient safety Observation Tool (SPOT)

Background: A Surgical Patient safety Observation Tool (SPOT) was developed and tested in a multicentre observational pilot study. The tool enables monitoring and benchmarking perioperative safety performance across departments and hospitals, covering international patient safety goals. Methods: Nineteen perioperative patient safety observation topics were selected from Dutch perioperative patient safety guidelines, which also cover international patient safety goals. All items that measured these selected topics were then extracted from available local observation checklists of the participating hospitals. Experts individually prioritized the best measurement items per topic in an initial written Delphi round. The second (face to face) Delphi round resulted in consensus on the content of SPOT, after which the measurable elements (MEs) per topic were defined. Finally, the tool was piloted in eight hospitals for measurability, applicability, improvement potential, discriminatory capacity and feasibility. Results: The pilot test showed good measurability for all 19 patient safety topics (range of 8-291 MEs among topics), with good applicability (median 97 (range 11.8-100) per cent). The overall improvement potential appeared to be good (median 89 (range 72.5-100) per cent), and at topic level the tool showed good discriminatory capacity (variation 27.5 per cent, range in compliance 72.5-100 per cent). Overall scores showed relatively little variation between the participating hospitals (variation 13 per cent, range in compliance 83-96 per cent). All eight auditors considered SPOT a straightforward and easy-to-use tracer tool. Conclusion: A comprehensive tool to measure safety of care was developed and validated using a systematic, stepwise method, enabling hospitals to monitor, benchmark and improve perioperative safety performance