Childhood maltreatment and the medical morbidity in bipolar disorder: a case-control study.

BACKGROUND: Childhood maltreatment (abuse and neglect) can have long-term deleterious consequences, including increased risk for medical and psychiatric illnesses, such as bipolar disorder in adulthood. Emerging evidence suggests that a history of childhood maltreatment is linked to the comorbidity between medical illnesses and mood disorders. However, existing studies on bipolar disorder have not yet explored the specific influence of child neglect and have not included comparisons with individuals without mood disorders (controls). This study aimed to extend the existing literature by examining the differential influence of child abuse and child neglect on medical morbidity in a sample of bipolar cases and controls. METHODS: The study included 72 participants with bipolar disorder and 354 psychiatrically healthy controls (average age of both groups was 48 years), who completed the Childhood Trauma Questionnaire, and were interviewed regarding various medical disorders. RESULTS: A history of any type of childhood maltreatment was significantly associated with a diagnosis of any medical illness (adjusted OR = 6.28, 95% confidence intervals 1.70-23.12, p = 0.006) and an increased number of medical illnesses (adjusted OR = 3.77, 95% confidence intervals 1.34-10.57, p = 0.012) among adults with bipolar disorder. Exposure to child abuse was more strongly associated with medical disorders than child neglect. No association between childhood maltreatment and medical morbidity was detected among controls. CONCLUSIONS: To summarise, individuals with bipolar disorder who reported experiencing maltreatment during childhood, especially abuse, were at increased risk of suffering from medical illnesses and warrant greater clinical attention.The bipolar case–control genetic association study was funded by an unrestricted grant from GlaxoSmithKline Research and Development. Funding for the depression case–control study was provided by the UK Medical Research Council (MRC; G0701420). The BADGE study was supported by an Interdisciplinary Ph.D. studentship from the UK Economic Social Research Council (ESRC) and MRC to Dr. Hosang. Prof. Uher is supported by the Canada Research Chairs program (http://www.chairs-chaires.gc.ca/him) and Dr. Fisher is supported by an MQ Fellows Award (MQ14F40). The sources of funding had no involvement in the study design, data collection or decision to submit for publication

IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences

IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at: http://www.reading.ac.uk/bioinf/IntFOLD

Evaluation of two interaction techniques for visualization of dynamic graphs

Several techniques for visualization of dynamic graphs are based on different spatial arrangements of a temporal sequence of node-link diagrams. Many studies in the literature have investigated the importance of maintaining the user's mental map across this temporal sequence, but usually each layout is considered as a static graph drawing and the effect of user interaction is disregarded. We conducted a task-based controlled experiment to assess the effectiveness of two basic interaction techniques: the adjustment of the layout stability and the highlighting of adjacent nodes and edges. We found that generally both interaction techniques increase accuracy, sometimes at the cost of longer completion times, and that the highlighting outclasses the stability adjustment for many tasks except the most complex ones.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data

Are genetic risk factors for psychosis also associated with dimension-specific psychotic experiences in adolescence?

Psychosis has been hypothesised to be a continuously distributed quantitative phenotype and disorders such as schizophrenia and bipolar disorder represent its extreme manifestations. Evidence suggests that common genetic variants play an important role in liability to both schizophrenia and bipolar disorder. Here we tested the hypothesis that these common variants would also influence psychotic experiences measured dimensionally in adolescents in the general population. Our aim was to test whether schizophrenia and bipolar disorder polygenic risk scores (PRS), as well as specific single nucleotide polymorphisms (SNPs) previously identified as risk variants for schizophrenia, were associated with adolescent dimension-specific psychotic experiences. Self-reported Paranoia, Hallucinations, Cognitive Disorganisation, Grandiosity, Anhedonia, and Parent-rated Negative Symptoms, as measured by the Specific Psychotic Experiences Questionnaire (SPEQ), were assessed in a community sample of 2,152 16-year-olds. Polygenic risk scores were calculated using estimates of the log of odds ratios from the Psychiatric Genomics Consortium GWAS stage-1 mega-analysis of schizophrenia and bipolar disorder. The polygenic risk analyses yielded no significant associations between schizophrenia and bipolar disorder PRS and the SPEQ measures. The analyses on the 28 individual SNPs previously associated with schizophrenia found that two SNPs in TCF4 returned a significant association with the SPEQ Paranoia dimension, rs17512836 (p-value=2.57x10-4) and rs9960767 (p-value=6.23x10-4). Replication in an independent sample of 16-year-olds (N=3,427) assessed using the Psychotic-Like Symptoms Questionnaire (PLIKS-Q), a composite measure of multiple positive psychotic experiences, failed to yield significant results. Future research with PRS derived from larger samples, as well as larger adolescent validation samples, would improve the predictive power to test these hypotheses further. The challenges of relating adult clinical diagnostic constructs such as schizophrenia to adolescent psychotic experiences at a genetic level are discussed

The selectivity, voltage-dependence and acid sensitivity of the tandem pore potassium channel TASK-1 : contributions of the pore domains

We have investigated the contribution to ionic selectivity of residues in the selectivity filter and pore helices of the P1 and P2 domains in the acid sensitive potassium channel TASK-1. We used site directed mutagenesis and electrophysiological studies, assisted by structural models built through computational methods. We have measured selectivity in channels expressed in Xenopus oocytes, using voltage clamp to measure shifts in reversal potential and current amplitudes when Rb+ or Na+ replaced extracellular K+. Both P1 and P2 contribute to selectivity, and most mutations, including mutation of residues in the triplets GYG and GFG in P1 and P2, made channels nonselective. We interpret the effects of these—and of other mutations—in terms of the way the pore is likely to be stabilised structurally. We show also that residues in the outer pore mouth contribute to selectivity in TASK-1. Mutations resulting in loss of selectivity (e.g. I94S, G95A) were associated with slowing of the response of channels to depolarisation. More important physiologically, pH sensitivity is also lost or altered by such mutations. Mutations that retained selectivity (e.g. I94L, I94V) also retained their response to acidification. It is likely that responses both to voltage and pH changes involve gating at the selectivity filter

A comparison of common programming languages used in bioinformatics

<p>Abstract</p> <p>Background</p> <p>The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python.</p> <p>Results</p> <p>Implementations in C and C++ were fastest and used the least memory. Programs in these languages generally contained more lines of code. Java and C# appeared to be a compromise between the flexibility of Perl and Python and the fast performance of C and C++. The relative performance of the tested languages did not change from Windows to Linux and no clear evidence of a faster operating system was found.</p> <p>Source code and additional information are available from <url>http://www.bioinformatics.org/benchmark/</url></p> <p>Conclusion</p> <p>This benchmark provides a comparison of six commonly used programming languages under two different operating systems. The overall comparison shows that a developer should choose an appropriate language carefully, taking into account the performance expected and the library availability for each language.</p

Purification and functional characterisation of rhiminopeptidase A, a novel aminopeptidase from the venom of Bitis gabonica rhinoceros

This study describes the discovery and characterisation of a novel aminopeptidase A from the venom of B. g. rhinoceros and highlights its potential biological importance. Similar to mammalian aminopeptidases, rhiminopeptidase A might be capable of playing roles in altering the blood pressure and brain function of victims. Furthermore, it could have additional effects on the biological functions of other host proteins by cleaving their N-terminal amino acids. This study points towards the importance of complete analysis of individual components of snake venom in order to develop effective therapies for snake bites

Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations

Time spent with cats is never wasted: Lessons learned from feline acromegalic cardiomyopathy, a naturally occurring animal model of the human disease

<div><p>Background</p><p>In humans, acromegaly due to a pituitary somatotrophic adenoma is a recognized cause of increased left ventricular (LV) mass. Acromegalic cardiomyopathy is incompletely understood, and represents a major cause of morbidity and mortality. We describe the clinical, echocardiographic and histopathologic features of naturally occurring feline acromegalic cardiomyopathy, an emerging disease among domestic cats.</p><p>Methods</p><p>Cats with confirmed hypersomatotropism (IGF-1>1000ng/ml and pituitary mass; n = 67) were prospectively recruited, as were two control groups: diabetics (IGF-1<800ng/ml; n = 24) and healthy cats without known endocrinopathy or cardiovascular disease (n = 16). Echocardiography was performed in all cases, including after hypersomatotropism treatment where applicable. Additionally, tissue samples from deceased cats with hypersomatotropism, hypertrophic cardiomyopathy and age-matched controls (n = 21 each) were collected and systematically histopathologically reviewed and compared.</p><p>Results</p><p>By echocardiography, cats with hypersomatotropism had a greater maximum LV wall thickness (6.5mm, 4.1–10.1mm) than diabetic (5.9mm, 4.2–9.1mm; Mann Whitney, p<0.001) or control cats (5.2mm, 4.1–6.5mm; Mann Whitney, p<0.001). Left atrial diameter was also greater in cats with hypersomatotropism (16.6mm, 13.0–29.5mm) than in diabetic (15.4mm, 11.2–20.3mm; Mann Whitney, p<0.001) and control cats (14.0mm, 12.6–17.4mm; Mann Whitney, p<0.001). After hypophysectomy and normalization of IGF-1 concentration (n = 20), echocardiographic changes proved mostly reversible. As in humans, histopathology of the feline acromegalic heart was dominated by myocyte hypertrophy with interstitial fibrosis and minimal myofiber disarray.</p><p>Conclusions</p><p>These results demonstrate cats could be considered a naturally occurring model of acromegalic cardiomyopathy, and as such help elucidate mechanisms driving cardiovascular remodeling in this disease.</p></div