The GSK-3β-FBXL21 Axis Contributes to Circadian TCAP Degradation and Skeletal Muscle Function.

FBXL21 is a clock-controlled E3 ligase modulating circadian periodicity via subcellular-specific CRYPTOCHROME degradation. How FBXL21 regulates tissue-specific circadian physiology and what mechanism operates upstream is poorly understood. Here we report the sarcomere component TCAP as a cytoplasmic substrate of FBXL21. FBXL21 interacts with TCAP in a circadian manner antiphasic to TCAP accumulation in skeletal muscle, and circadian TCAP oscillation is disrupted in Psttm mice with an Fbxl21 hypomorph mutation. GSK-3β phosphorylates FBXL21 and TCAP to activate FBXL21-mediated, phosphodegron-dependent TCAP degradation. GSK-3β inhibition or knockdown diminishes FBXL21-Cul1 complex formation and delays FBXL21-mediated TCAP degradation. Finally, Psttm mice show significant skeletal muscle defects, including impaired fiber size, exercise tolerance, grip strength, and response to glucocorticoid-induced atrophy, in conjunction with cardiac dysfunction. These data highlight a circadian regulatory pathway where a GSK-3β-FBXL21 functional axis controls TCAP degradation via SCF complex formation and regulates skeletal muscle function

Glioblastoma Subclasses Can Be Defined by Activity among Signal Transduction Pathways and Associated Genomic Alterations

Glioblastoma multiforme (GBM) is an umbrella designation that includes a heterogeneous group of primary brain tumors. Several classification strategies of GBM have been reported, some by clinical course and others by resemblance to cell types either in the adult or during development. From a practical and therapeutic standpoint, classifying GBMs by signal transduction pathway activation and by mutation in pathway member genes may be particularly valuable for the development of targeted therapies.We performed targeted proteomic analysis of 27 surgical glioma samples to identify patterns of coordinate activation among glioma-relevant signal transduction pathways, then compared these results with integrated analysis of genomic and expression data of 243 GBM samples from The Cancer Genome Atlas (TCGA). In the pattern of signaling, three subclasses of GBM emerge which appear to be associated with predominance of EGFR activation, PDGFR activation, or loss of the RAS regulator NF1. The EGFR signaling class has prominent Notch pathway activation measured by elevated expression of Notch ligands, cleaved Notch receptor, and downstream target Hes1. The PDGF class showed high levels of PDGFB ligand and phosphorylation of PDGFRbeta and NFKB. NF1-loss was associated with lower overall MAPK and PI3K activation and relative overexpression of the mesenchymal marker YKL40. These three signaling classes appear to correspond with distinct transcriptomal subclasses of primary GBM samples from TCGA for which copy number aberration and mutation of EGFR, PDGFRA, and NF1 are signature events.Proteomic analysis of GBM samples revealed three patterns of expression and activation of proteins in glioma-relevant signaling pathways. These three classes are comprised of roughly equal numbers showing either EGFR activation associated with amplification and mutation of the receptor, PDGF-pathway activation that is primarily ligand-driven, or loss of NF1 expression. The associated signaling activities correlating with these sentinel alterations provide insight into glioma biology and therapeutic strategies

CCL3L1 copy number, CCR5 genotype and susceptibility to tuberculosis

Background: Tuberculosis is a major infectious disease and functional studies have provided evidence that both the chemokine MIP-1α and its receptor CCR5 play a role in susceptibility to TB. Thus by measuring copy number variation of CCL3L1, one of the genes that encode MIP-1α, and genotyping a functional promoter polymorphism -2459A > G in CCR5 (rs1799987) we investigate the influence of MIP-1α and CCR5, independently and combined, in susceptibility to clinically active TB in three populations, a Peruvian population (n = 1132), a !Xhosa population (n = 605) and a South African Coloured population (n = 221). The three populations include patients with clinically diagnosed pulmonary TB, as well as other, less prevalent forms of extrapulmonary TB. Methods and results: Copy number of CCL3L1 was measured using the paralogue ratio test and exhibited ranges between 0–6 copies per diploid genome (pdg) in Peru, between 0–12 pdg in !Xhosa samples and between 0–10 pdg in South African Coloured samples. The CCR5 promoter polymorphism was observed to differ significantly in allele frequency between populations (*A; Peru f = 0.67, !Xhosa f = 0.38, Coloured f = 0.48). Conclusions: The case–control association studies performed however find, surprisingly, no evidence for an influence of variation in genes coding for MIP-1α or CCR5 individually or together in susceptibility to clinically active TB in these populations

Candidate gene prioritization by network analysis of differential expression using machine learning approaches

<p>Abstract</p> <p>Background</p> <p>Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals.</p> <p>To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network.</p> <p>Results</p> <p>We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (<it>Simple Expression Ranking</it>). Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the <it>Heat Kernel Diffusion Ranking </it>leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%.</p> <p>Conclusion</p> <p>In this study we could identify promising candidate genes using network based machine learning approaches even if no knowledge is available about the disease or phenotype.</p

Mortality and causes of death among violent offenders and victims-a Swedish population based longitudinal study

<p>Abstract</p> <p>Background</p> <p>Most previous studies on mortality in violent offenders or victims are based on prison or hospital samples, while this study analyzed overall and cause specific mortality among violent offenders, victims, and individuals who were both offenders and victims in a general sample of 48,834 18-20 year-old men conscripted for military service in 1969/70 in Sweden.</p> <p>Methods</p> <p>Each person completed two non-anonymous questionnaires concerning family, psychological, and behavioral factors. The cohort was followed for 35 years through official registers regarding violent offenses, victimization, and mortality. The impact of violence, victimization, early risk factors and hospitalization for psychiatric diagnosis or alcohol and drug misuse during follow up on mortality was investigated using Cox proportional hazard regression analyses.</p> <p>Results</p> <p>Repeat violent offenses were associated with an eleven fold higher hazard of dying from a substance-related cause and nearly fourfold higher hazard of dying from suicide. These figures remained significantly elevated also in multivariate analyses, with a 3.03 and 2.39 hazard ratio (HR), respectively. Participants with experience of violence and inpatient care for substance abuse or psychiatric disorder had about a two to threefold higher risk of dying compared to participants with no substance use or psychiatric disorder.</p> <p>Conclusions</p> <p>Violent offending and being victimized are associated with excess mortality and a risk of dying from an alcohol or drug-related cause or suicide. Consequently, prevention of violent behavior might have an effect on overall mortality and suicide rates. Prevention of alcohol and drug use is also warranted.</p

Harmonin-b, an actin-binding scaffold protein, is involved in the adaptation of mechanoelectrical transduction by sensory hair cells

We assessed the involvement of harmonin-b, a submembranous protein containing PDZ domains, in the mechanoelectrical transduction machinery of inner ear hair cells. Harmonin-b is located in the region of the upper insertion point of the tip link that joins adjacent stereocilia from different rows and that is believed to gate transducer channel(s) located in the region of the tip link's lower insertion point. In Ush1cdfcr-2J/dfcr-2J mutant mice defective for harmonin-b, step deflections of the hair bundle evoked transduction currents with altered speed and extent of adaptation. In utricular hair cells, hair bundle morphology and maximal transduction currents were similar to those observed in wild-type mice, but adaptation was faster and more complete. Cochlear outer hair cells displayed reduced maximal transduction currents, which may be the consequence of moderate structural anomalies of their hair bundles. Their adaptation was slower and displayed a variable extent. The latter was positively correlated with the magnitude of the maximal transduction current, but the cells that showed the largest currents could be either hyperadaptive or hypoadaptive. To interpret our observations, we used a theoretical description of mechanoelectrical transduction based on the gating spring theory and a motor model of adaptation. Simulations could account for the characteristics of transduction currents in wild-type and mutant hair cells, both vestibular and cochlear. They led us to conclude that harmonin-b operates as an intracellular link that limits adaptation and engages adaptation motors, a dual role consistent with the scaffolding property of the protein and its binding to both actin filaments and the tip link component cadherin-23

Post hoc pattern matching: assigning significance to statistically defined expression patterns in single channel microarray data

<p>Abstract</p> <p>Background</p> <p>Researchers using RNA expression microarrays in experimental designs with more than two treatment groups often identify statistically significant genes with ANOVA approaches. However, the ANOVA test does not discriminate which of the multiple treatment groups differ from one another. Thus, <it>post hoc </it>tests, such as linear contrasts, template correlations, and pairwise comparisons are used. Linear contrasts and template correlations work extremely well, especially when the researcher has <it>a priori </it>information pointing to a particular pattern/template among the different treatment groups. Further, all pairwise comparisons can be used to identify particular, treatment group-dependent patterns of gene expression. However, these approaches are biased by the researcher's assumptions, and some treatment-based patterns may fail to be detected using these approaches. Finally, different patterns may have different probabilities of occurring by chance, importantly influencing researchers' conclusions about a pattern and its constituent genes.</p> <p>Results</p> <p>We developed a four step, <it>post hoc </it>pattern matching (PPM) algorithm to automate single channel gene expression pattern identification/significance. First, 1-Way Analysis of Variance (ANOVA), coupled with <it>post hoc </it>'all pairwise' comparisons are calculated for all genes. Second, for each ANOVA-significant gene, all pairwise contrast results are encoded to create unique pattern ID numbers. The # genes found in each pattern in the data is identified as that pattern's 'actual' frequency. Third, using Monte Carlo simulations, those patterns' frequencies are estimated in random data ('random' gene pattern frequency). Fourth, a Z-score for overrepresentation of the pattern is calculated ('actual' against 'random' gene pattern frequencies). We wrote a Visual Basic program (StatiGen) that automates PPM procedure, constructs an Excel workbook with standardized graphs of overrepresented patterns, and lists of the genes comprising each pattern. The visual basic code, installation files for StatiGen, and sample data are available as supplementary material.</p> <p>Conclusion</p> <p>The PPM procedure is designed to augment current microarray analysis procedures by allowing researchers to incorporate all of the information from post hoc tests to establish unique, overarching gene expression patterns in which there is no overlap in gene membership. In our hands, PPM works well for studies using from three to six treatment groups in which the researcher is interested in treatment-related patterns of gene expression. Hardware/software limitations and extreme number of theoretical expression patterns limit utility for larger numbers of treatment groups. Applied to a published microarray experiment, the StatiGen program successfully flagged patterns that had been manually assigned in prior work, and further identified other gene expression patterns that may be of interest. Thus, over a moderate range of treatment groups, PPM appears to work well. It allows researchers to assign statistical probabilities to patterns of gene expression that fit <it>a priori </it>expectations/hypotheses, it preserves the data's ability to show the researcher interesting, yet unanticipated gene expression patterns, and assigns the majority of ANOVA-significant genes to non-overlapping patterns.</p

Susceptibility of Pancreatic Beta Cells to Fatty Acids Is Regulated by LXR/PPARα-Dependent Stearoyl-Coenzyme A Desaturase

Chronically elevated levels of fatty acids-FA can cause beta cell death in vitro. Beta cells vary in their individual susceptibility to FA-toxicity. Rat beta cells were previously shown to better resist FA-toxicity in conditions that increased triglyceride formation or mitochondrial and peroxisomal FA-oxidation, possibly reducing cytoplasmic levels of toxic FA-moieties. We now show that stearoyl-CoA desaturase-SCD is involved in this cytoprotective mechanism through its ability to transfer saturated FA into monounsaturated FA that are incorporated in lipids. In purified beta cells, SCD expression was induced by LXR- and PPARα-agonists, which were found to protect rat, mouse and human beta cells against palmitate toxicity. When their SCD was inhibited or silenced, the agonist-induced protection was also suppressed. A correlation between beta cell-SCD expression and susceptibility to palmitate was also found in beta cell preparations isolated from different rodent models. In mice with LXR-deletion (LXRβ-/- and LXRαβ-/-), beta cells presented a reduced SCD-expression as well as an increased susceptibility to palmitate-toxicity, which could not be counteracted by LXR or PPARα agonists. In Zucker fatty rats and in rats treated with the LXR-agonist TO1317, beta cells show an increased SCD-expression and lower palmitate-toxicity. In the normal rat beta cell population, the subpopulation with lower metabolic responsiveness to glucose exhibits a lower SCD1 expression and a higher susceptibility to palmitate toxicity. These data demonstrate that the beta cell susceptibility to saturated fatty acids can be reduced by stearoyl-coA desaturase, which upon stimulation by LXR and PPARα agonists favors their desaturation and subsequent incorporation in neutral lipids

Repaired tetralogy of Fallot: the roles of cardiovascular magnetic resonance in evaluating pathophysiology and for pulmonary valve replacement decision support

Surgical management of tetralogy of Fallot (TOF) results in anatomic and functional abnormalities in the majority of patients. Although right ventricular volume load due to severe pulmonary regurgitation can be tolerated for many years, there is now evidence that the compensatory mechanisms of the right ventricular myocardium ultimately fail and that if the volume load is not eliminated or reduced by pulmonary valve replacement the dysfunction might be irreversible. Cardiovascular magnetic resonance (CMR) has evolved during the last 2 decades as the reference standard imaging modality to assess the anatomic and functional sequelae in patients with repaired TOF. This article reviews the pathophysiology of chronic right ventricular volume load after TOF repair and the risks and benefits of pulmonary valve replacement. The CMR techniques used to comprehensively evaluate the patient with repaired TOF are reviewed and the role of CMR in supporting clinical decisions regarding pulmonary valve replacement is discussed

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field