Improved methods for the analysis of circadian rhythms in correlated gene expression data

Circadian clocks regulate biological behaviours, such as sleeping and waking times, that recur naturally on an approximately 24-hour cycle. These clocks tend to be influenced by a variety of external factors, sometimes to the extent that it can have an impact on health. As an example in pharmacology, the effects of chemicals on the circadian rhythm in patients can be key in clarifying the relationship of drug efficacy and toxicity with dosing times. While pre-clinical experiments conducted to elucidate these effects may produce correlated data measured over time, such as gene expression profiles, existing methods for fitting parametric nonlinear regression models are however inadequate and can lead to unreliable, inconsistent parameter estimates and invalid inference. A de-trending method is widely used as a pre-processing step to address the non-stationary problem in the data before fitting models based on the assumption of independence. However, as it is unclear that this approach properly accounts for the correlation structure, alternative methods that specifically model the correlation in the data based on conditional least squares and a two-stage estimation procedure are proposed and evaluated. A simulation study covering a wide range of scenarios and models show that the proposed methods more efficient and robust to model mis-specification than de-trending and, furthermore, they lead to reduced bias in estimation of the circadian period and more reliable confidence intervals

The efficiency of single SNP and SNP-set analysis in genome-wide association studies

The objective of this research is to compare and identify effective methods for the identification of gene loci associated with a disease outcome in the analysis of genome-wide data. We evaluate three methods which are single SNP analysis, Sequence Kernel Association Test (SKAT) and the recently proposed Generalized Higher Criticism (GHC). The simulated data used in this research were constructed from a control data set in a study of Crohn's disease. True positive (TP) and false positive rate (FP) were evaluated under different genetic models for disease with significant thresholds adjusted for multiple hypothesis testing based on the permutation method. The findings are mixed with all three methods giving similar TP rates under some disease models and different rates for other models. Overall, GHC is shown to be preferable in terms of error rates but it is disadvantageous in terms of computational efficiency

RhD blood type significantly influences susceptibility to contract COVID-19 among a study population in Iraq

The ABO blood type has been reported to be associated with several diseases such as hepatitis and malaria. Recently, some studies have reported that people with O blood type are protected against COVID-19, while people with A blood type are more susceptible to contract this disease. Here, we analysed data from 5668 COVID-19 patients along with the same number of control samples in a study population in Iraq. Our analysis confirms that people with O blood type are protected partially against COVID-19. Notably, we demonstrate that people with RhD- are more susceptible to contract COVID-19 than people with RhD+ blood type. The blood types are associated with some clinical symptoms such as headache and asthenia of COVID-19, but there is no association with other symptoms. There is no association between blood types and deaths among COVID-19 patients. This study suggests that in addition to ABO, RhD blood type influences the susceptibility to contract COVID-19. Overall, we conclude that susceptibility/protection against COVID-19 may not be determined based only on blood types among the global population as this might vary based on a number of other factors such as ethnicity, geographical locations, occupation and the level of exposure to infected people

Snakebite and its socio-economic impact on the rural population of Tamil Nadu, India

BACKGROUND: Snakebite represents a significant health issue worldwide, affecting several million people each year with as many as 95,000 deaths. India is considered to be the country most affected, but much remains unknown about snakebite incidence in this country, its socio-economic impact and how snakebite management could be improved. METHODS/PRINCIPAL FINDINGS: We conducted a study within rural villages in Tamil Nadu, India, which combines a household survey (28,494 people) of snakebite incidence with a more detailed survey of victims in order to understand the health and socio-economic effects of the bite, the treatments obtained and their views about future improvements. Our survey suggests that snakebite incidence is higher than previously reported. 3.9% of those surveyed had suffered from snakebite and the number of deaths corresponds to 0.45% of the population. The socio-economic impact of this is very considerable in terms of the treatment costs and the long-term effects on the health and ability of survivors to work. To reduce this, the victims recommended improvements to the accessibility and affordability of antivenom treatment. CONCLUSIONS: Snakebite has a considerable and disproportionate impact on rural populations, particularly in South Asia. This study provides an incentive for researchers and the public to work together to reduce the incidence and improve the outcomes for snake bite victims and their families

Genetic analysis of a major international collection of cultivated apple varieties reveals previously unknown historic heteroploid and inbred relationships

Domesticated apple (Malus x domestica Borkh.) is a major global crop and the genetic diversity held within the pool of cultivated varieties is important for the development of future cultivars. The aim of this study was to investigate the diversity held within the domesticated form, through the analysis of a major international germplasm collection of cultivated varieties, the UK National Fruit Collection, consisting of over 2,000 selections of named cultivars and seedling varieties. We utilised Diversity Array Technology (DArT) markers to assess the genetic diversity within the collection. Clustering attempts, using the software STRUCTURE revealed that the accessions formed a complex and historically admixed group for which clear clustering was challenging. Comparison of accessions using the Jaccard similarity coefficient allowed us to identify clonal and duplicate material as well as revealing pairs and groups that appeared more closely related than a standard parent-offspring or full-sibling relations. From further investigation, we were able to propose a number of new pedigrees, which revealed that some historically important cultivars were more closely related than previously documented and that some of them were partially inbred. We were also able to elucidate a number of parent-offspring relationships that had resulted in a number of important polyploid cultivars. This included reuniting polyploid cultivars that in some cases dated as far back as the 18th century, with diploid parents that potentially date back as far as the 13th century

A randomised controlled trial of positive memory training for the treatment of depression within schizophrenia

Abstract Background: Depression is highly prevalent within individuals diagnosed with schizophrenia, and is associated with an increased risk of suicide. There are no current evidence based treatments for low mood within this group. The specific targeting of co-morbid conditions within complex mental health problems lends itself to the development of short-term structured interventions which are relatively easy to disseminate within health services. A brief cognitive intervention based on a competitive memory theory of depression, is being evaluated in terms of its effectiveness in reducing depression within this group. Methods/Design: This is a single blind, intention-to-treat, multi-site, randomized controlled trial comparing Positive Memory Training plus Treatment as Usual with Treatment as Usual alone. Participants will be recruited from two NHS Trusts in Southern England. In order to be eligible, participants must have a DSM-V diagnosis of schizophrenia or schizo-affective disorder and exhibit at least a mild level of depression. Following baseline assessment eligible participants will be randomly allocated to either the Positive Memory Training plus Treatment as Usual group or the Treatment as Usual group. Outcome will be assessed at the end of treatment (3-months) and at 6-month and 9-month post randomization by assessors blind to group allocation. The primary outcome will be levels of depression and secondary outcomes will be severity of psychotic symptoms and cost-effectiveness. Semi-structured interviews will be conducted with all participants who are allocated to the treatment group so as to explore the acceptability of the intervention. Discussion: Cognitive behaviour therapy is recommended for individuals diagnosed with schizophrenia. However, the number of sessions and length of training required to deliver this intervention has caused a limit in availability. The current trial will evaluate a short-term structured protocol which targets a co-morbid condition often considered of primary importance by service users. If successful the intervention will be an important addition to current initiatives aimed at increasing access to psychological therapies for people diagnosed with severe mental health problems. Trial registration: Current Controlled Trials. ISRCTN99485756. Registered 13 March 2014

An extension of an over-dispersion test for count data

While over-dispersion in capture–recapture studies is well known to lead to poor estimation of population size, current diagnostic tools to detect the presence of heterogeneity have not been specifically developed for capture–recapture studies. To address this, a simple and efficient method of testing for over-dispersion in zero-truncated count data is developed and evaluated. The proposed method generalizes an over-dispersion test previously suggested for un-truncated count data and may also be used for testing residual over-dispersion in zero-inflation data. Simulations suggest that the asymptotic distribution of the test statistic is standard normal and that this approximation is also reasonable for small sample sizes. The method is also shown to be more efficient than an existing test for over-dispersion adapted for the capture–recapture setting. Studies with zero-truncated and zero-inflated count data are used to illustrate the test procedures

Influence of carbon dioxide dilution on soot formation in diffusive combustion

Peer reviewed: YesNRC publication: Ye

Sequential methods for pharmacogenetic studies

A study or experiment can be described as sequential if its design includes one or more interim analyses at which it is possible to stop the study, having reached a definitive conclusion concerning the primary question of interest. The potential of the sequential study to terminate earlier than the equivalent fixed sample size study means that, typically, there are ethical and economic advantages to be gained from using a sequential design. These advantages have secured a place for the methodology in the conduct of many clinical trials of novel therapies. Recently, there has been increasing interest in pharmacogenetics: the study of how DNA variation in the human genome affects the safety and efficacy of drugs. The potential for using sequential methodology in pharmacogenetic studies is considered and the conduct of candidate gene association studies, family-based designs and genome-wide association studies within the sequential setting is explored. The objective is to provide a unified framework for the conduct of these types of studies as sequential designs and hence allow experimenters to consider using sequential methodology in their future pharmacogenetic studies