Characterization of novel StAR (steroidogenic acute regulatory protein) mutations causing non-classic lipoid adrenal hyperplasia

Context Steroidogenic acute regulatory protein (StAR) is crucial for transport of cholesterol to mitochondria where biosynthesis of steroids is initiated. Loss of StAR function causes lipoid congenital adrenal hyperplasia (LCAH). Objective StAR gene mutations causing partial loss of function manifest atypical and may be mistaken as familial glucocorticoid deficiency. Only a few mutations have been reported. Design To report clinical, biochemical, genetic, protein structure and functional data on two novel StAR mutations, and to compare them with published literature. Setting Collaboration between the University Children's Hospital Bern, Switzerland, and the CIBERER, Hospital Vall d'Hebron, Autonomous University, Barcelona, Spain. Patients Two subjects of a non-consanguineous Caucasian family were studied. The 46,XX phenotypic normal female was diagnosed with adrenal insufficiency at the age of 10 months, had normal pubertal development and still has no signs of hypergonodatropic hypogonadism at 32 years of age. Her 46,XY brother was born with normal male external genitalia and was diagnosed with adrenal insufficiency at 14 months. Puberty was normal and no signs of hypergonadotropic hypogonadism are present at 29 years of age. Results StAR gene analysis revealed two novel compound heterozygote mutations T44HfsX3 and G221S. T44HfsX3 is a loss-of-function StAR mutation. G221S retains partial activity (~30%) and is therefore responsible for a milder, non-classic phenotype. G221S is located in the cholesterol binding pocket and seems to alter binding/release of cholesterol. Conclusions StAR mutations located in the cholesterol binding pocket (V187M, R188C, R192C, G221D/S) seem to cause non-classic lipoid CAH. Accuracy of genotype-phenotype prediction by in vitro testing may vary with the assays employed.

Design and construction of a new Drosophila species, D.synthetica, by synthetic regulatory evolution

Here, I merge the principles of synthetic biology1,2 and regulatory evolution3-11 to create a new species12-15 with a minimal set of known elements. Using preexisting transgenes and recessive mutations of Drosophila melanogaster, a transgenic population arises with small eyes and a different venation pattern that fulfills the criteria of a new species according to Mayr's "Biological Species Concept"7,10. The genetic circuit entails the loss of a non-essential transcription factor and the introduction of cryptic enhancers. Subsequent activation of those enhancers causes hybrid lethality. The transition from "transgenic organisms" towards "synthetic species", such as Drosophila synthetica, constitutes a safety mechanism to avoid hybridization with wild type populations and preserve natural biodiversity16-18. Drosophila synthetica is the first transgenic organism that cannot hybridize with the original wild type population but remains fertile when crossed with other transgenic animals.

Leydig-cell tumour in children: variable clinical presentation, diagnostic features, follow-up and genetic analysis of four cases

BACKGROUND: Testicular tumours are relatively uncommon in infants and children, accounting for only 1-2% of all paediatric solid tumours. Of these approximately 1.5% are Leydig-cell tumours. Further, activating mutations of the luteinizing hormone receptor gene (LHR), as well as of the G protein genes, such as Gsalpha (gsp) and Gialpha (gip2) subunits, and cyclin-dependent kinase gene 4(CDK4) have been associated with the development of several endocrine neoplasms. AIMS/METHODS: In this report, the clinical variability of Leydig-cell tumours in four children is described. The LHR-, gsp-, gip2- and CDK4 genes were investigated to establish the possible molecular pathogenesis of the variable phenotype of the Leydig-cell tumours. RESULTS: No activating mutations in these genes were found in the four Leydig-cell tumours studied. Therefore, the absence of activating mutations in LHR, as well as in both the 'hot spot' regions for activating mutations within the G-alpha subunits and in the regulatory 'hot spot' on the CDK4 genes in these tumours indicates molecular heterogeneity among Leydig-cell tumours. CONCLUSION: Four children with a variable phenotype caused by Leydig-cell tumours are described. A molecular analysis of all the 'activating' genes and mutational regions known so far was performed, but no abnormalities were found. The lessons learnt from these clinically variable cases are: perform ultrasound early and most importantly, consider discrepancies between testicular swelling, tumour size and androgen production.

Mechanisms of intrinsic beating variability in cardiac cell cultures and model pacemaker networks

Heart rate variability (HRV) exhibits fluctuations characterized by a power law behavior of its power spectrum. The interpretation of this nonlinear HRV behavior, resulting from interactions between extracardiac regulatory mechanisms, could be clinically useful. However, the involvement of intrinsic variations of pacemaker rate in HRV has scarcely been investigated. We examined beating variability in spontaneously active incubating cultures of neonatal rat ventricular myocytes using microelectrode arrays. In networks of mathematical model pacemaker cells, we evaluated the variability induced by the stochastic gating of transmembrane currents and of calcium release channels and by the dynamic turnover of ion channels. In the cultures, spontaneous activity originated from a mobile focus. Both the beat-to-beat movement of the focus and beat rate variability exhibited a power law behavior. In the model networks, stochastic fluctuations in transmembrane currents and stochastic gating of calcium release channels did not reproduce the spatiotemporal patterns observed in vitro. In contrast, long-term correlations produced by the turnover of ion channels induced variability patterns with a power law behavior similar to those observed experimentally. Therefore, phenomena leading to long-term correlated variations in pacemaker cellular function may, in conjunction with extracardiac regulatory mechanisms, contribute to the nonlinear characteristics of HRV.

Mental health and quality of life after genetic testing for Huntington disease: a long-term effect study in Germany

Predictive genetic testing for Huntington disease (HD) might cause severe short-term psychological reactions in patients with poor mental health. Very few studies exist on the long-term effects of genetic HD testing. The aim of this study was to assess mental health and quality of life in persons who were tested for HD mutation, to compare mental health depending on the result of the genetic test (non-carriers, gene carriers, and patients with HD) and to identify predictors of mental health and quality of life via linear regression. The data were collected by self-report questionnaires. In total, 121 individuals participated in this study: 52 were non-carriers, 54 were gene carriers, and 15 were gene carriers suffering from HD. Non-carriers and gene carriers showed better mental health and quality of life than HD-patients but did not differ from each other. In non-carriers four variables predicted increased depression and low mental quality of life: low perceived social support, no intimate relationship, female sex and younger age. For gene carriers three predictors were found: low perceived social support, the expectation of an unfavorable genetic test result before the testing procedure and being childless. To prevent detrimental effects of HD testing on mental health and mental quality of life, specific attention should be paid to persons with limited social networks during genetic counseling. Assessment of expectations related to the test result and mental health prior to a genetic testing procedure may help to identify gene carriers at risk of poor coping after an unfavorable test result.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

DISSECTION OF STRESS RESPONSE NETWORKS REGULATING MULTIPLE STRESSES IN RICE

Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.

Integrative analysis of RUNX1 downstream pathways and target genes

BACKGROUND: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. RESULTS: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFbeta, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. CONCLUSION: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications.

The Eyes Have It: Regulatory and Structural Changes Both Underlie Cichlid Visual Pigment Diversity

A major goal of evolutionary biology is to unravel the molecular genetic mechanisms that underlie functional diversification and adaptation. We investigated how changes in gene regulation and coding sequence contribute to sensory diversification in two replicate radiations of cichlid fishes. In the clear waters of Lake Malawi, differential opsin expression generates diverse visual systems, with sensitivities extending from the ultraviolet to the red regions of the spectrum. These sensitivities fall into three distinct clusters and are correlated with foraging habits. In the turbid waters of Lake Victoria, visual sensitivity is constrained to longer wavelengths, and opsin expression is correlated with ambient light. In addition to regulatory changes, we found that the opsins coding for the shortest-and longest-wavelength visual pigments have elevated numbers of potentially functional substitutions. Thus, we present a model of sensory evolution in which both molecular genetic mechanisms work in concert. Changes in gene expression generate large shifts in visual pigment sensitivity across the collective opsin spectral range, but changes in coding sequence appear to fine-tune visual pigment sensitivity at the short-and long-wavelength ends of this range, where differential opsin expression can no longer extend visual pigment sensitivity.

Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

Nuclear and plastid markers reveal the persistence of genetic identity: A new perspective on the evolutionary history of Petunia exserta

Recently divergent species that can hybridize are ideal models for investigating the genetic exchanges that can occur while preserving the species boundaries. Petunia exserta is an endemic species from a very limited and specific area that grows exclusively in rocky shelters. These shaded spots are an inhospitable habitat for all other Petunia species, including the closely related and widely distributed species P. axillaris. Individuals with intermediate morphologic characteristics have been found near the rocky shelters and were believed to be putative hybrids between P. exserta and P. axillaris, suggesting a situation where Petunia exserta is losing its genetic identity. In the current study, we analyzed the plastid intergenic spacers trnS/trnG and trnH/psbA and six nuclear CAPS markers in a large sampling design of both species to understand the evolutionary process occurring in this biological system. Bayesian clustering methods, cpDNA haplotype networks, genetic diversity statistics, and coalescence-based analyses support a scenario where hybridization occurs while two genetic clusters corresponding to two species are maintained. Our results reinforce the importance of coupling differentially inherited markers with an extensive geographic sample to assess the evolutionary dynamics of recently diverged species that can hybridize. (C) 2013 Elsevier Inc. All rights reserved.

Clinical and genetic characteristics of long QT syndrome

Long QT syndrome (LQTS) is an arrhythmogenic ion channel disorder characterized by severely abnormal ventricular repolarization, which results in prolongation of the electrocardiographic QT interval. The condition is associated with sudden cardiac death due to malignant ventricular arrhythmias similar in form to the hallmark torsade de pointes. Eleven years after the identification of the principle cardiac channels involved in the condition, hundreds of mutations in, to date, 10 genes have been associated with the syndrome. Genetic investigations carried out up until the present have shown that, although the severe form of the disease is sporadic, there are a number of common polymorphisms in genes associated with the condition that may confer susceptibility to the development of torsade de pointes in some individuals, particularly when specific drugs are being administered. Moreover, some polymorphisms have been shown to have regulatory properties that either enhance or counteract a particular mutation's impact. Understanding of the molecular processes underlying the syndrome has enabled treatment to be optimized and has led to better survival among sufferers, thereby demonstrating a key correspondence between genotype, phenotype and therapy. Despite these developments, a quarter of patients do not have mutations in the genes identified to date. Consequently, LQTS continues to be an area of active research. This article contains a summary of the main clinical and genetic developments concerning the syndrome that have taken place during the last decade.

The Individualized Genetic Barrier Predicts Treatment Response in a Large Cohort of HIV-1 Infected Patients

The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational pathways, and we modeled phenotypic drug resistance as monotonically increasing along any escape pathway. Using this model, the individualized genetic barrier (IGB) to each drug is derived as the probability of the virus not acquiring additional mutations that confer resistance. Drug-specific IGBs were combined to obtain the IGB to an entire regimen, which quantifies the virus' genetic potential for developing drug resistance under combination therapy. The IGB was tested as a predictor of therapeutic outcome using between 2,185 and 2,631 treatment change episodes of subtype B infected patients from the Swiss HIV Cohort Study Database, a large observational cohort. Using logistic regression, significant univariate predictors included most of the 18 drugs and single-drug IGBs, the IGB to the entire regimen, the expert rules-based genotypic susceptibility score (GSS), several individual mutations, and the peak viral load before treatment change. In the multivariate analysis, the only genotype-derived variables that remained significantly associated with virological success were GSS and, with 10-fold stronger association, IGB to regimen. When predicting suppression of viral load below 400 cps/ml, IGB outperformed GSS and also improved GSS-containing predictors significantly, but the difference was not significant for suppression below 50 cps/ml. Thus, the IGB to regimen is a novel data-derived predictor of treatment outcome that has potential to improve the interpretation of genotypic drug resistance tests.

Reduced neutrophil count in people of African descent is due to a regulatory variant in the Duffy antigen receptor for chemokines gene.

Persistently low white blood cell count (WBC) and neutrophil count is a well-described phenomenon in persons of African ancestry, whose etiology remains unknown. We recently used admixture mapping to identify an approximately 1-megabase region on chromosome 1, where ancestry status (African or European) almost entirely accounted for the difference in WBC between African Americans and European Americans. To identify the specific genetic change responsible for this association, we analyzed genotype and phenotype data from 6,005 African Americans from the Jackson Heart Study (JHS), the Health, Aging and Body Composition (Health ABC) Study, and the Atherosclerosis Risk in Communities (ARIC) Study. We demonstrate that the causal variant must be at least 91% different in frequency between West Africans and European Americans. An excellent candidate is the Duffy Null polymorphism (SNP rs2814778 at chromosome 1q23.2), which is the only polymorphism in the region known to be so differentiated in frequency and is already known to protect against Plasmodium vivax malaria. We confirm that rs2814778 is predictive of WBC and neutrophil count in African Americans above beyond the previously described admixture association (P = 3.8 x 10(-5)), establishing a novel phenotype for this genetic variant.

Saturday Morning Television Advertisements Aired on English and Spanish Language Networks along the Texas-Mexico Border

Objectives: The aim of this content analysis study is to characterize the TV advertisements aired to an at-risk child population along the Texas-Mexico border. Methods: We characterized the early Saturday morning TV advertisements aired by three broadcast network categories (U.S. English language, U.S. Spanish language, and Mexican Spanish language) in Spring 2010. The number, type (food related vs. non-food related), target audience, and persuasion tactics used were recorded. Advertised foods, based on nutrition content, were categorized as meeting or not meeting current dietary guidelines. Results: Most commercials were non-food related (82.7%, 397 of 480). The majority of the prepared foods (e.g., cereals, snacks, and drinks) advertised did not meet the current U.S. Dietary Guidelines. Additionally, nutrition content information was not available for many of the foods advertised on the Mexican Spanish language broadcast network category. Conclusions: For U.S. children at risk for obesity along the Texas-Mexico border exposure to TV food advertisements may result in the continuation of sedentary behavior as well as an increased consumption of foods of poor nutritional quality. An international regulatory effort to monitor and enforce the reduction of child-oriented food advertising is needed. Editors' Note: This article was submitted in response to the first issue of the Journal of Applied Research on Children: Latino Children.