Simultaneous Analysis of All SNPs in Genome-Wide and Re-Sequencing Association Studies

Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants, which is a plausible scenario for many complex diseases. We show that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods. We used a Bayesian-inspired penalised maximum likelihood approach in which every SNP can be considered for additive, dominant, and recessive contributions to disease risk. Posterior mode estimates were obtained for regression coefficients that were each assigned a prior with a sharp mode at zero. A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. We investigated two prior distributions and show that the normal-exponential-gamma prior leads to improved SNP selection in comparison with single-SNP tests. We also derived an explicit approximation for type-I error that avoids the need to use permutation procedures. As well as genome-wide analyses, our method is well-suited to fine mapping with very dense SNP sets obtained from re-sequencing and/or imputation. It can accommodate quantitative as well as case-control phenotypes, covariate adjustment, and can be extended to search for interactions. Here, we demonstrate the power and empirical type-I error of our approach using simulated case-control data sets of up to 500 K SNPs, a real genome-wide data set of 300 K SNPs, and a sequence-based dataset, each of which can be analysed in a few hours on a desktop workstation

Application of two machine learning algorithms to genetic association studies in the presence of covariates

BACKGROUND: Population-based investigations aimed at uncovering genotype-trait associations often involve high-dimensional genetic polymorphism data as well as information on multiple environmental and clinical parameters. Machine learning (ML) algorithms offer a straightforward analytic approach for selecting subsets of these inputs that are most predictive of a pre-defined trait. The performance of these algorithms, however, in the presence of covariates is not well characterized. METHODS AND RESULTS: In this manuscript, we investigate two approaches: Random Forests (RFs) and Multivariate Adaptive Regression Splines (MARS). Through multiple simulation studies, the performance under several underlying models is evaluated. An application to a cohort of HIV-1 infected individuals receiving anti-retroviral therapies is also provided. CONCLUSION: Consistent with more traditional regression modeling theory, our findings highlight the importance of considering the nature of underlying gene-covariate-trait relationships before applying ML algorithms, particularly when there is potential confounding or effect mediation

Effectiveness of YouRAction, an Intervention to Promote Adolescent Physical Activity Using Personal and Environmental Feedback: A Cluster RCT

Background: In this study the one and six months effects of the computer-tailored YouRAction (targeting individual level determinants) and YouRAction+e (targeting in addition perceived environmental determinants) on compliance with the moderate-to-vigorous physical activity (MVPA) guideline and weight status are examined. In addition the use and appreciation of both interventions are studied. Methods: A three-armed cluster randomized trial was conducted in 2009-2010 with measurements at baseline, one and six months post intervention. School classes were assigned to one of the study arms (YouRaction, YouRAction+e and Generic Information (GI) control group). MVPA was derived from self-reports at baseline, one and six months post intervention. Body Mass Index and waist circumference were measured at baseline and six months post intervention in a random sub-sample of the population. Use of the interventions was measured by webserver logs and appreciation by self-reports. Multilevel regression analyses were conducted to study the effects of the intervention against the GI control group. ANOVA's and chi-square tests were used to describe differences in use and appreciation between study arms. Results: There were no statistically significant intervention effects on compliance with the MVPA guideline, overweight or WC. Access to the full intervention was significantly lower for YouRAction (24.0%) and YouRAction+e (21.7%) compared to the GI (54.4%). Conclusion: This study could not demonstrate that the YouRAction and YouRAction+e interventions were effective in promoting MVPA or improve anthropometric outcomes among adolescents, compared to generic information. Insufficient use and exposure to the intervention content may be an explanation for the lack of effects

Defining eye-fixation sequences across individuals and tasks: the Binocular-Individual Threshold (BIT) algorithm

We propose a new fully automated velocity-based algorithm to identify fixations from eye-movement records of both eyes, with individual-specific thresholds. The algorithm is based on robust minimum determinant covariance estimators (MDC) and control chart procedures, and is conceptually simple and computationally attractive. To determine fixations, it uses velocity thresholds based on the natural within-fixation variability of both eyes. It improves over existing approaches by automatically identifying fixation thresholds that are specific to (a) both eyes, (b) x- and y- directions, (c) tasks, and (d) individuals. We applied the proposed Binocular-Individual Threshold (BIT) algorithm to two large datasets collected on eye-trackers with different sampling frequencies, and compute descriptive statistics of fixations for larger samples of individuals across a variety of tasks, including reading, scene viewing, and search on supermarket shelves. Our analysis shows that there are considerable differences in the characteristics of fixations not only between these tasks, but also between individuals

Predicting climate change impacts on polar bear litter size

Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40–73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55–100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22–67% and 44–100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population

Was Dinosaurian Physiology Inherited by Birds? Reconciling Slow Growth in Archaeopteryx

Archaeopteryx is the oldest and most primitive known bird (Avialae). It is believed that the growth and energetic physiology of basalmost birds such as Archaeopteryx were inherited in their entirety from non-avialan dinosaurs. This hypothesis predicts that the long bones in these birds formed using rapidly growing, well-vascularized woven tissue typical of non-avialan dinosaurs. We report that Archaeopteryx long bones are composed of nearly avascular parallel-fibered bone. This is among the slowest growing osseous tissues and is common in ectothermic reptiles. These findings dispute the hypothesis that non-avialan dinosaur growth and physiology were inherited in totality by the first birds. Examining these findings in a phylogenetic context required intensive sampling of outgroup dinosaurs and basalmost birds. Our results demonstrate the presence of a scale-dependent maniraptoran histological continuum that Archaeopteryx and other basalmost birds follow. Growth analysis for Archaeopteryx suggests that these animals showed exponential growth rates like non-avialan dinosaurs, three times slower than living precocial birds, but still within the lowermost range for all endothermic vertebrates. The unexpected histology of Archaeopteryx and other basalmost birds is actually consistent with retention of the phylogenetically earlier paravian dinosaur condition when size is considered. The first birds were simply feathered dinosaurs with respect to growth and energetic physiology. The evolution of the novel pattern in modern forms occurred later in the group's history

Twenty two cases of canine neural angiostronglyosis in eastern Australia (2002-2005) and a review of the literature

Cases of canine neural angiostrongylosis (NA) with cerebrospinal fluid (CSF) evaluations in the peer-reviewed literature were tabulated. All cases were from Australia. A retrospective cohort of 59 dogs was contrasted with a series of 22 new cases where NA was diagnosed by the presence of both eosinophilic pleocytosis and anti-Angiostrongylus cantonensis immunloglobulins (IgG) in CSF, determined by ELISA or Western blot. Both cohorts were drawn from south east Queensland and Sydney. The retrospective cohort comprised mostly pups presented for hind limb weakness with hyperaesthesia, a mixture of upper motor neurone (UMN) and lower motor neurone (LMN) signs in the hind limbs and urinary incontinence. Signs were attributed to larval migration through peripheral nerves, nerve roots, spinal cord and brain associated with an ascending eosinophilic meningo-encephomyelitis. The contemporary cohort consisted of a mixture of pups, young adult and mature dogs, with a wider range of signs including (i) paraparesis/proprioceptive ataxia (ii) lumbar and tail base hyperaesthesia, (iii) multi-focal central nervous system dysfunction, or (iv) focal disease with neck pain, cranial neuropathy and altered mentation. Cases were seen throughout the year, most between April and July (inclusive). There was a preponderance of large breeds. Often littermates, or multiple animals from the same kennel, were affected simultaneously or sequentially. A presumptive diagnosis was based on consistent signs, proximity to rats, ingestion/chewing of slugs or snails and eosinophilic pleocytosis. NA was diagnosed by demonstrating anti-A. cantonensis IgG in CSF. Detecting anti-A. cantonensis IgG in serum was unhelpful because many normal dogs (20/21 lb dogs; 8/22 of a hospital population) had such antibodies, often at substantial titres. Most NA cases in the contemporary series (19/22) and many pups (16/38) in the retrospective cohort were managed successfully using high doses of prednisolone and opioids. Treatment often included antibiotics administered in case protozoan encephalomyelitis or translocated bacterial meningitis was present. Supportive measures included bladder care and physiotherapy. Several dogs were left with permanent neural deficits. Dogs are an important sentinel species for NA. Human cases and numerous cases in tawny frogmouths were reported from the same regions as affected dogs over the study period