Genetic differences according to onset age and lung function in asthma: a cluster analysis

BACKGROUND: The extent of differences between genetic risks associated with various asthma subtypes is still unknown. To better understand the heterogeneity of asthma, we employed an unsupervised method to identify genetic variants specifically associated with asthma subtypes. Our goal was to gain insight into the genetic basis of asthma. METHODS: In this study, we utilized the UK Biobank dataset to select asthma patients (All asthma, n = 50,517) and controls (n = 283,410). We excluded 14,431 individuals who had no information on predicted values of forced expiratory volume in one second percent (FEV1%) and onset age, resulting in a final total of 36,086 asthma cases. We conducted k-means clustering based on asthma onset age and predicted FEV1% using these samples (n = 36,086). Cluster-specific genome-wide association studies were then performed, and heritability was estimated via linkage disequilibrium score regression. To further investigate the pathophysiology, we conducted eQTL analysis with GTEx and gene-set enrichment analysis with FUMA. RESULTS: Clustering resulted in four distinct clusters: early onset asthmanormalLF (early onset with normal lung function, n = 8172), early onset asthmareducedLF (early onset with reduced lung function, n = 8925), late-onset asthmanormalLF (late-onset with normal lung function, n = 12,481), and late-onset asthmareducedLF (late-onset with reduced lung function, n = 6508). Our GWASs in four clusters and in All asthma sample identified 5 novel loci, 14 novel signals, and 51 cluster-specific signals. Among clusters, early onset asthmanormalLF and late-onset asthmareducedLF were the least correlated (rg  = 0.37). Early onset asthmareducedLF showed the highest heritability explained by common variants (h2  = 0.212) and was associated with the largest number of variants (71 single nucleotide polymorphisms). Further, the pathway analysis conducted through eQTL and gene-set enrichment analysis showed that the worsening of symptoms in early onset asthma correlated with lymphocyte activation, pathogen recognition, cytokine receptor activation, and lymphocyte differentiation. CONCLUSIONS: Our findings suggest that early onset asthmareducedLF was the most genetically predisposed cluster, and that asthma clusters with reduced lung function were genetically distinct from clusters with normal lung function. Our study revealed the genetic variation between clusters that were segmented based on onset age and lung function, providing an important clue for the genetic mechanism of asthma heterogeneity

Determination of quantitative trait loci (QTL) for early maturation in rainbow trout (Oncorhynchus mykiss)

To identify quantitative trait loci (QTL) influencing early maturation (EM) in rainbow trout (Oncorhynchus mykiss), a genome scan was performed using 100 microsatellite loci across 29 linkage groups. Six inter-strain paternal half-sib families using three inter-strain F(1) brothers (approximately 50 progeny in each family) derived from two strains that differ in the propensity for EM were used in the study. Alleles derived from both parental sources were observed to contribute to the expression of EM in the progeny of the brothers. Four genome-wide significant QTL regions (i.e., RT-8, -17, -24, and -30) were observed. EM QTL detected on RT-8 and -24 demonstrated significant and suggestive QTL effects in both male and female progeny. Furthermore, within both male and female full-sib groupings, QTL on RT-8 and -24 were detected in two or more of the five parents used. Significant genome-wide and several strong chromosome-wide QTL for EM localized to different regions in males and females, suggesting some sex-specific control. Namely, QTL detected on RT-13, -15, -21, and -30 were associated with EM only in females, and those on RT-3, -17, and -19 were associated with EM only in males. Within the QTL regions identified, a comparison of syntenic EST markers from the rainbow trout linkage map with the zebrafish (Danio rerio) genome identified several putative candidate genes that may influence EM. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10126-008-9098-5) contains supplementary material, which is available to authorized users

Predicting sample size required for classification performance

<p>Abstract</p> <p>Background</p> <p>Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target.</p> <p>Methods</p> <p>We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method.</p> <p>Results</p> <p>A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p < 0.05).</p> <p>Conclusions</p> <p>This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.</p

Aldose reductase deficiency in mice protects from ragweed pollen extract (RWE)-induced allergic asthma

<p>Abstract</p> <p>Background</p> <p>Childhood hospitalization related to asthma remains at historically high levels, and its incidence is on the rise world-wide. Previously, we have demonstrated that aldose reductase (AR), a regulatory enzyme of polyol pathway, is a major mediator of allergen-induced asthma pathogenesis in mouse models. Here, using AR null (AR^-/-) mice we have investigated the effect of AR deficiency on the pathogenesis of ragweed pollen extract (RWE)-induced allergic asthma in mice and also examined the efficacy of enteral administration of highly specific AR inhibitor, fidarestat.</p> <p>Methods</p> <p>The wild type (WT) and AR^-/-mice were sensitized and challenged with RWE to induce allergic asthma. AR inhibitor, fidarestat was administered orally. Airway hyper-responsiveness was measured in unrestrained animals using whole body plethysmography. Mucin levels and Th2 cytokine in broncho-alveolar lavage (BAL) were determined using mouse anti-Muc5A/C ELISA kit and multiplex cytokine array, respectively. Eosinophils infiltration and goblet cells were assessed by H&E and periodic acid Schiff (PAS)-staining of formalin-fixed, paraffin-embedded lung sections. T regulatory cells were assessed in spleen derived CD4⁺CD25⁺T cells population.</p> <p>Results</p> <p>Deficiency of AR in mice led to significantly decreased PENH, a marker of airway hyper-responsiveness, metaplasia of airway epithelial cells and mucus hyper-secretion following RWE-challenge. This was accompanied by a dramatic decrease in infiltration of eosinophils into sub-epithelium of lung as well as in BAL and release of Th2 cytokines in response to RWE-challenge of AR^-/-mice. Further, enteral administration of fidarestat significantly prevented eosinophils infiltration, airway hyper-responsiveness and also markedly increased population of T regulatory (CD4⁺CD25⁺FoxP3⁺) cells as compared to RWE-sensitized and challenged mice not treated with fidarestat.</p> <p>Conclusion</p> <p>Our results using AR^-/-mice strongly suggest the role of AR in allergic asthma pathogenesis and effectiveness of oral administration of AR inhibitor in RWE-induced asthma in mice supports the use of AR inhibitors in the treatment of allergic asthma.</p

Interactivity and Reward-Related Neural Activation during a Serious Videogame

This study sought to determine whether playing a “serious” interactive digital game (IDG) – the Re-Mission videogame for cancer patients – activates mesolimbic neural circuits associated with incentive motivation, and if so, whether such effects stem from the participatory aspects of interactive gameplay, or from the complex sensory/perceptual engagement generated by its dynamic event-stream. Healthy undergraduates were randomized to groups in which they were scanned with functional magnetic resonance imaging (FMRI) as they either actively played Re-Mission or as they passively observed a gameplay audio-visual stream generated by a yoked active group subject. Onset of interactive game play robustly activated mesolimbic projection regions including the caudate nucleus and nucleus accumbens, as well as a subregion of the parahippocampal gyrus. During interactive gameplay, subjects showed extended activation of the thalamus, anterior insula, putamen, and motor-related regions, accompanied by decreased activation in parietal and medial prefrontal cortex. Offset of interactive gameplay activated the anterior insula and anterior cingulate. Between-group comparisons of within-subject contrasts confirmed that mesolimbic activation was significantly more pronounced in the active playgroup than in the passive exposure control group. Individual difference analyses also found the magnitude of parahippocampal activation following gameplay onset to correlate with positive attitudes toward chemotherapy assessed both at the end of the scanning session and at an unannounced one-month follow-up. These findings suggest that IDG-induced activation of reward-related mesolimbic neural circuits stems primarily from participatory engagement in gameplay (interactivity), rather than from the effects of vivid and dynamic sensory stimulation

A new pathway of glucocorticoid action for asthma treatment through the regulation of PTEN expression

<p>Abstract</p> <p>Background</p> <p>"Phosphatase and tensin homolog deleted on chromosome 10" (PTEN) is mostly considered to be a cancer-related gene, and has been suggested to be a new pathway of pathogenesis of asthma. The purpose of this study was to investigate the effects of the glucocorticoid, dexamethasone, on PTEN regulation.</p> <p>Methods</p> <p>OVA-challenged mice were used as an asthma model to investigate the effect of dexamethasone on PTEN regulation. Immunohistochemistry was used to detect expression levels of PTEN protein in lung tissues. The human A549 cell line was used to explore the possible mechanism of action of dexamethasone on human PTEN regulation <it>in vitro</it>. A luciferase reporter construct under the control of PTEN promoter was used to confirm transcriptional regulation in response to dexamethasone.</p> <p>Results</p> <p>PTEN protein was found to be expressed at low levels in lung tissues in asthmatic mice; but the expression was restored after treatment with dexamethasone. In A549 cells, human PTEN was up-regulated by dexamethasone treatment. The promoter-reporter construct confirmed that dexamethasone could regulate human PTEN transcription. Treatment with the histone deacetylase inhibitor, TSA, could increase PTEN expression in A549 cells, while inhibition of histone acetylase (HAT) by anacardic acid attenuated dexamethasone-induced PTEN expression.</p> <p>Conclusions</p> <p>Based on the data a new mechanism is proposed where glucocorticoids treat asthma partly through up-regulation of PTEN expression. The <it>in vitro </it>studies also suggest that the PTEN pathway may be involved in human asthma.</p

Single-Molecule Force Spectroscopy: Experiments, Analysis, and Simulations

International audienceThe mechanical properties of cells and of subcellular components are important to obtain a mechanistic molecular understanding of biological processes. The quantification of mechanical resistance of cells and biomolecules using biophysical methods matured thanks to the development of nanotechnologies such as optical and magnetic tweezers, the biomembrane force probe and atomic force microscopy (AFM). The quantitative nature of force spectroscopy measurements has converted AFM into a valuable tool in biophysics. Force spectroscopy allows the determination of the forces required to unfold protein domains and to disrupt individual receptor/ligand bonds. Molecular simulation as a computational microscope allows investigation of similar biological processes with an atomistic detail. In this chapter, we first provide a step-by-step protocol of force spectroscopy including sample preparation, measurement and analysis of force spectroscopy using AFM and its interpretation in terms of available theories. Next, we present the background for molecular dynamics (MD) simulations focusing on steered molecular dynamics (SMD) and the importance of bridging of computational tools with experimental technique

Enhancement of Vaccinia Virus Based Oncolysis with Histone Deacetylase Inhibitors

Histone deacetylase inhibitors (HDI) dampen cellular innate immune response by decreasing interferon production and have been shown to increase the growth of vesicular stomatitis virus and HSV. As attenuated tumour-selective oncolytic vaccinia viruses (VV) are already undergoing clinical evaluation, the goal of this study is to determine whether HDI can also enhance the potency of these poxviruses in infection-resistant cancer cell lines. Multiple HDIs were tested and Trichostatin A (TSA) was found to potently enhance the spread and replication of a tumour selective vaccinia virus in several infection-resistant cancer cell lines. TSA significantly decreased the number of lung metastases in a syngeneic B16F10LacZ lung metastasis model yet did not increase the replication of vaccinia in normal tissues. The combination of TSA and VV increased survival of mice harbouring human HCT116 colon tumour xenografts as compared to mice treated with either agent alone. We conclude that TSA can selectively and effectively enhance the replication and spread of oncolytic vaccinia virus in cancer cells

Molecular dynamics simulations and drug discovery

This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role