BioBuilder as a database development and functional annotation platform for proteins

BACKGROUND: The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development. RESULTS: BioBuilder is a Zope-based software tool that was developed to facilitate intuitive creation of protein databases. Protein data can be entered and annotated through web forms along with the flexibility to add customized annotation features to protein entries. A built-in review system permits a global team of scientists to coordinate their annotation efforts. We have already used BioBuilder to develop Human Protein Reference Database , a comprehensive annotated repository of the human proteome. The data can be exported in the extensible markup language (XML) format, which is rapidly becoming as the standard format for data exchange. CONCLUSIONS: As the proteomic data for several organisms begins to accumulate, BioBuilder will prove to be an invaluable platform for functional annotation and development of customizable protein centric databases. BioBuilder is open source and is available under the terms of LGPL

Investigation of the association of Apgar score with maternal socio-economic and biological factors: an analysis of German perinatal statistics

PURPOSE: To examine the relationship of 5-min Apgar score with maternal socio-economic and biological factors. METHODS: We analyzed data from 465,964 singleton pregnancies (37–41 weeks’ gestation) from the German perinatal statistics of 1998–2000. Using a logistic regression model we analyzed the incidence of low (0–6) 5-min Apgar scores in relation to these maternal factors: body mass index (BMI), age, previous live births, country of origin, occupation, single mother status, working during pregnancy, and smoking. RESULTS: A low Apgar score was more common in overweight [adjusted odds ratio (OR) 1.24; 95% confidence interval (CI) 1.10–1.40; P < 0.001] and obese [OR 1.92 (95% CI 1.67–2.20); P < 0.001] compared to normal weight women. A low Apgar score was also more common for women aged >35 years compared to those aged 20–35 years [OR 1.35 (95% CI 1.16–1.58); P < 0.001]. Furthermore, odds of a low Apgar score were higher for women with no previous live births compared to those with one or more previous live births [OR 1.52 (95% CI 1.37–1.70); P < 0.001]. Socio-economic factors did not convincingly influence Apgar scores. CONCLUSIONS: There was an influence of the biological maternal factors age, BMI, and parity on the 5-min Apgar score. There was no convincing effect of socio-economic factors on Apgar score in our study population. Possible reasons for this are discussed

A framework for the detection of de novo mutations in family-based sequencing data

Francioli LC, Cretu-Stancu M, Garimella KV, et al. A framework for the detection of de novo mutations in family-based sequencing data. European Journal of Human Genetics. 2016;25(2):227-233

Limiting weight gain in overweight and obese women during pregnancy to improve health outcomes: the LIMIT randomised controlled trial

Extent: 5p.Background: Obesity is a significant global health problem, with the proportion of women entering pregnancy with a body mass index greater than or equal to 25 kg/m2 approaching 50%. Obesity during pregnancy is associated with a well-recognised increased risk of adverse health outcomes both for the woman and her infant, however there is more limited information available regarding effective interventions to improve health outcomes. The aims of this randomised controlled trial are to assess whether the implementation of a package of dietary and lifestyle advice to overweight and obese women during pregnancy to limit gestational weight gain is effective in improving maternal, fetal and infant health outcomes. Methods/Design: Design: Multicentred randomised, controlled trial. Inclusion Criteria: Women with a singleton, live gestation between 10+0-20+0 weeks who are obese or overweight (defined as body mass index greater than or equal to 25 kg/m2), at the first antenatal visit. Trial Entry & Randomisation: Eligible, consenting women will be randomised between 10+0 and 20+0 weeks gestation using a central telephone randomisation service, and randomisation schedule prepared by non-clinical research staff with balanced variable blocks. Stratification will be according to maternal BMI at trial entry, parity, and centre where planned to give birth. Treatment Schedules: Women randomised to the Dietary and Lifestyle Advice Group will receive a series of inputs from research assistants and research dietician to limit gestational weight gain, and will include a combination of dietary, exercise and behavioural strategies. Women randomised to the Standard Care Group will continue to receive their pregnancy care according to local hospital guidelines, which does not currently include routine provision of dietary, lifestyle and behavioural advice. Outcome assessors will be blinded to the allocated treatment group. Primary Study Outcome: infant large for gestational age (defined as infant birth weight ≥ 90th centile for gestational age). Sample Size: 2,180 women to detect a 30% reduction in large for gestational age infants from 14.40% (p = 0.05, 80% power, two-tailed). Discussion This is a protocol for a randomised trial. The findings will contribute to the development of evidence based clinical practice guidelines.Jodie M Dodd, Deborah A Turnbull, Andrew J McPhee, Gary Wittert, Caroline A Crowther and Jeffrey S Robinso

Patterns and rates of exonic de novo mutations in autism spectrum disorders

Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified1,2. To identify further genetic risk factors, we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n= 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant and the overall rate of mutation is only modestly higher than the expected rate. In contrast, there is significantly enriched connectivity among the proteins encoded by genes harboring de novo missense or nonsense mutations, and excess connectivity to prior ASD genes of major effect, suggesting a subset of observed events are relevant to ASD risk. The small increase in rate of de novo events, when taken together with the connections among the proteins themselves and to ASD, are consistent with an important but limited role for de novo point mutations, similar to that documented for de novo copy number variants. Genetic models incorporating these data suggest that the majority of observed de novo events are unconnected to ASD, those that do confer risk are distributed across many genes and are incompletely penetrant (i.e., not necessarily causal). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5 to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favor of CHD8 and KATNAL2 as genuine autism risk factors

Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. © 2013 Liu et al

Can physical activity help to maintain cognitive functioning and psychosocial well-being among breast cancer patients treated with chemotherapy? A randomised controlled trial: study protocol

Background: Evidence suggests chemotherapy treatment for breast cancer is associated with side effects such as cognitive impairment in domains of memory, attention, concentration and executive function. Cognitive impairments reported by patients have been associated with higher levels of emotional distress. To date, intervention studies to alleviate cognitive impairment associated with chemotherapy have focused on psycho-educational techniques or cognitive training. Studies have not yet considered physical activity as a potential for alleviating cognitive problems. Physical activity interventions are reported to be effective in alleviating emotional distress and fatigue in those with breast cancer. They have also been reported to improve cognitive functioning in the elderly, in those suffering with dementia and in children. We propose that physical activity could also help to alleviate cognitive impairments in women diagnosed with breast cancer. The study has been designed using a recently developed taxonomy of behaviour change techniques to reliably report the content of the intervention to allow future replication. Method: This study will deliver a home-based moderate intensity walking intervention to women diagnosed with breast cancer mid-way through their chemotherapy treatment and will compare them to patients receiving usual care alone. The primary outcome measure for this intervention is changes in an objective measure of memory assessed using the Digit Span. Secondary outcome measures include: objective measures of executive function; attention; visual spatial skills; self report cognitive function; self-report fatigue; anxiety; depression; mood and self-esteem. As emotional distress has been associated with self-reporting of cognitive problems, this intervention will further test whether emotional distress mediates between the amount of walking undertaken during the intervention period and levels of self-reported cognitive functioning. Discussion: The development of an effective intervention for preventing difficulties in emotional and cognitive functioning of cancer patients’ post-treatment will help to guide health care professionals to improve patients’ overall quality of life. It will also provide direction for future research, ultimately to improve the day to day functioning of breast cancer survivors. Trial Registration: Current Controlled Trials ISRCTN50709297. Keywords: Intervention, Breast cancer, Chemotherapy, Physical activity, Exercise, Walking, Cognitive function, Emotional distress, Psychosocial well-bein