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Sample records for predicting qualitative phenotypes

  1. Qualitative Dynamical Modelling Can Formally Explain Mesoderm Specification and Predict Novel Developmental Phenotypes.

    PubMed

    Mbodj, Abibatou; Gustafson, E Hilary; Ciglar, Lucia; Junion, Guillaume; Gonzalez, Aitor; Girardot, Charles; Perrin, Laurent; Furlong, Eileen E M; Thieffry, Denis

    2016-09-01

    Given the complexity of developmental networks, it is often difficult to predict the effect of genetic perturbations, even within coding genes. Regulatory factors generally have pleiotropic effects, exhibit partially redundant roles, and regulate highly interconnected pathways with ample cross-talk. Here, we delineate a logical model encompassing 48 components and 82 regulatory interactions involved in mesoderm specification during Drosophila development, thereby providing a formal integration of all available genetic information from the literature. The four main tissues derived from mesoderm correspond to alternative stable states. We demonstrate that the model can predict known mutant phenotypes and use it to systematically predict the effects of over 300 new, often non-intuitive, loss- and gain-of-function mutations, and combinations thereof. We further validated several novel predictions experimentally, thereby demonstrating the robustness of model. Logical modelling can thus contribute to formally explain and predict regulatory outcomes underlying cell fate decisions. PMID:27599298

  2. High-Throughput Near-Infrared Reflectance Spectroscopy for Predicting Quantitative and Qualitative Composition Phenotypes of Individual Maize Kernels

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Near-infrared reflectance (NIR) spectroscopy can be used for fast and reliable prediction of organic compounds in complex biological samples. We used a recently developed NIR spectroscopy instrument to predict starch, protein, oil, and weight of individual maize (Zea mays) seeds. The starch, prote...

  3. Heliconia phenotypic diversity based on qualitative descriptors.

    PubMed

    Guimarães, W N R; Martins, L S S; Castro, C E F; Carvalho Filho, J L S; Loges, V

    2014-01-01

    The aim of this study was to characterize Heliconia genotypes phenotypically using 26 qualitative descriptors. The evaluations were conducted in five flowering stems per clump in three replicates of 22 Heliconia genotypes. Data were subjected to multivariate analysis, the Mahalanobis dissimilarity measure was estimated, and the dendrogram was generated using the nearest neighbor method. From the values generated by the dissimilarity matrix and the clusters formed among the Heliconia genotypes studied, the phenotypic characterizations that best differentiated the genotypes were: pseudostem and wax green tone (light or dark green), leaf-wax petiole, the petiole hair, cleft margin at the base of the petiole, midrib underside shade of green, wax midrib underside, color sheet (light or dark green), unequal lamina base, torn limb, inflorescence-wax, position of inflorescence, bract leaf in apex, twisting of the rachis, and type of bloom. These results will be applied in the preparation of a catalog for Heliconia descriptors, in the selection of different genotypes with most promising characteristics for crosses, and for the characterization of new genotypes to be introduced in germplasm collections. PMID:24782170

  4. Wine Expertise Predicts Taste Phenotype

    PubMed Central

    Hayes, John E; Pickering, Gary J

    2011-01-01

    Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance – with appropriate caveats about populations tested, outcomes measured and psychophysical methods used – an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli. PMID:22888174

  5. Empirically derived phenotypic subgroups – qualitative and quantitative trait analyses

    PubMed Central

    Wilcox, Marsha A; Wyszynski, Diego F; Panhuysen, Carolien I; Ma, Qianli; Yip, Agustin; Farrell, John; Farrer, Lindsay A

    2003-01-01

    Background The Framingham Heart Study has contributed a great deal to advances in medicine. Most of the phenotypes investigated have been univariate traits (quantitative or qualitative). The aims of this study are to derive multivariate traits by identifying homogeneous groups of people and assigning both qualitative and quantitative trait scores; to assess the heritability of the derived traits; and to conduct both qualitative and quantitative linkage analysis on one of the heritable traits. Methods Multiple correspondence analysis, a nonparametric analogue of principal components analysis, was used for data reduction. Two-stage clustering, using both k-means and agglomerative hierarchical clustering, was used to cluster individuals based upon axes (factor) scores obtained from the data reduction. Probability of cluster membership was calculated using binary logistic regression. Heritability was calculated using SOLAR, which was also used for the quantitative trait analysis. GENEHUNTER-PLUS was used for the qualitative trait analysis. Results We found four phenotypically distinct groups. Membership in the smallest group was heritable (38%, p < 1 × 10-6) and had characteristics consistent with atherogenic dyslipidemia. We found both qualitative and quantitative LOD scores above 3 on chromosomes 11 and 14 (11q13, 14q23, 14q31). There were two Kong & Cox LOD scores above 1.0 on chromosome 6 (6p21) and chromosome 11 (11q23). Conclusion This approach may be useful for the identification of genetic heterogeneity in complex phenotypes by clarifying the phenotype definition prior to linkage analysis. Some of our findings are in regions linked to elements of atherogenic dyslipidemia and related diagnoses, some may be novel, or may be false positives. PMID:14975083

  6. Behavioural phenotypes predict disease susceptibility and infectiousness.

    PubMed

    Araujo, Alessandra; Kirschman, Lucas; Warne, Robin W

    2016-08-01

    Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans. PMID:27555652

  7. Analysis and predictive modeling of asthma phenotypes.

    PubMed

    Brasier, Allan R; Ju, Hyunsu

    2014-01-01

    Molecular classification using robust biochemical measurements provides a level of diagnostic precision that is unattainable using indirect phenotypic measurements. Multidimensional measurements of proteins, genes, or metabolites (analytes) can identify subtle differences in the pathophysiology of patients with asthma in a way that is not otherwise possible using physiological or clinical assessments. We overview a method for relating biochemical analyte measurements to generate predictive models of discrete (categorical) clinical outcomes, a process referred to as "supervised classification." We consider problems inherent in wide (small n and large p) high-dimensional data, including the curse of dimensionality, collinearity and lack of information content. We suggest methods for reducing the data to the most informative features. We describe different approaches for phenotypic modeling, using logistic regression, classification and regression trees, random forest and nonparametric regression spline modeling. We provide guidance on post hoc model evaluation and methods to evaluate model performance using ROC curves and generalized additive models. The application of validated predictive models for outcome prediction will significantly impact the clinical management of asthma. PMID:24162915

  8. In silico phenotyping via co-training for improved phenotype prediction from genotype

    PubMed Central

    Witteveen, Menno J.; Anttila, Verneri; Terwindt, Gisela M.; van den Maagdenberg, Arn M.J.M.; Borgwardt, Karsten

    2015-01-01

    Motivation: Predicting disease phenotypes from genotypes is a key challenge in medical applications in the postgenomic era. Large training datasets of patients that have been both genotyped and phenotyped are the key requisite when aiming for high prediction accuracy. With current genotyping projects producing genetic data for hundreds of thousands of patients, large-scale phenotyping has become the bottleneck in disease phenotype prediction. Results: Here we present an approach for imputing missing disease phenotypes given the genotype of a patient. Our approach is based on co-training, which predicts the phenotype of unlabeled patients based on a second class of information, e.g. clinical health record information. Augmenting training datasets by this type of in silico phenotyping can lead to significant improvements in prediction accuracy. We demonstrate this on a dataset of patients with two diagnostic types of migraine, termed migraine with aura and migraine without aura, from the International Headache Genetics Consortium. Conclusions: Imputing missing disease phenotypes for patients via co-training leads to larger training datasets and improved prediction accuracy in phenotype prediction. Availability and implementation: The code can be obtained at: http://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/co-training.html Contact: karsten.borgwardt@bsse.ethz.ch or menno.witteveen@bsse.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26072497

  9. Prediction of microbial phenotypes based on comparative genomics

    PubMed Central

    2015-01-01

    The accessibility of almost complete genome sequences of uncultivable microbial species from metagenomes necessitates computational methods predicting microbial phenotypes solely based on genomic data. Here we investigate how comparative genomics can be utilized for the prediction of microbial phenotypes. The PICA framework facilitates application and comparison of different machine learning techniques for phenotypic trait prediction. We have improved and extended PICA's support vector machine plug-in and suggest its applicability to large-scale genome databases and incomplete genome sequences. We have demonstrated the stability of the predictive power for phenotypic traits, not perturbed by the rapid growth of genome databases. A new software tool facilitates the in-depth analysis of phenotype models, which associate expected and unexpected protein functions with particular traits. Most of the traits can be reliably predicted in only 60-70% complete genomes. We have established a new phenotypic model that predicts intracellular microorganisms. Thereby we could demonstrate that also independently evolved phenotypic traits, characterized by genome reduction, can be reliably predicted based on comparative genomics. Our results suggest that the extended PICA framework can be used to automatically annotate phenotypes in near-complete microbial genome sequences, as generated in large numbers in current metagenomics studies. PMID:26451672

  10. Developing predictive assays: the phenotypic screening "rule of 3".

    PubMed

    Vincent, Fabien; Loria, Paula; Pregel, Marko; Stanton, Robert; Kitching, Linda; Nocka, Karl; Doyonnas, Regis; Steppan, Claire; Gilbert, Adam; Schroeter, Thomas; Peakman, Marie-Claire

    2015-06-24

    Phenotypic drug discovery approaches can positively affect the translation of preclinical findings to patients. However, not all phenotypic assays are created equal. A critical question then follows: What are the characteristics of the optimal assays? We analyze this question and propose three specific criteria related to the disease relevance of the assay-system, stimulus, and end point-to help design the most predictive phenotypic assays. PMID:26109101

  11. On-time clinical phenotype prediction based on narrative reports

    PubMed Central

    Bejan, Cosmin A.; Vanderwende, Lucy; Evans, Heather L.; Wurfel, Mark M.; Yetisgen-Yildiz, Meliha

    2013-01-01

    In this paper we describe a natural language processing system which is able to predict whether or not a patient exhibits a specific phenotype using the information extracted from the narrative reports associated with the patient. Furthermore, the phenotypic annotations from our report dataset were performed at the report level which allows us to perform the prediction of the clinical phenotype at any point in time during the patient hospitalization period. Our experiments indicate that an important factor in achieving better results for this problem is to determine how much information to extract from the patient reports in the time interval between the patient admission time and the current prediction time. PMID:24551325

  12. Multikernel linear mixed models for complex phenotype prediction.

    PubMed

    Weissbrod, Omer; Geiger, Dan; Rosset, Saharon

    2016-07-01

    Linear mixed models (LMMs) and their extensions have recently become the method of choice in phenotype prediction for complex traits. However, LMM use to date has typically been limited by assuming simple genetic architectures. Here, we present multikernel linear mixed model (MKLMM), a predictive modeling framework that extends the standard LMM using multiple-kernel machine learning approaches. MKLMM can model genetic interactions and is particularly suitable for modeling complex local interactions between nearby variants. We additionally present MKLMM-Adapt, which automatically infers interaction types across multiple genomic regions. In an analysis of eight case-control data sets from the Wellcome Trust Case Control Consortium and more than a hundred mouse phenotypes, MKLMM-Adapt consistently outperforms competing methods in phenotype prediction. MKLMM is as computationally efficient as standard LMMs and does not require storage of genotypes, thus achieving state-of-the-art predictive power without compromising computational feasibility or genomic privacy. PMID:27302636

  13. Cellular imaging: a key phenotypic screening strategy for predictive toxicology

    PubMed Central

    Xu, Jinghai J.

    2015-01-01

    Incorporating phenotypic screening as a key strategy enhances predictivity and translatability of drug discovery efforts. Cellular imaging serves as a “phenotypic anchor” to identify important toxicologic pathology that encompasses an array of underlying mechanisms, thus provides an effective means to reduce drug development failures due to insufficient safety. This mini-review highlights the latest advances in hepatotoxicity, cardiotoxicity, and genetic toxicity tests that utilized cellular imaging as a screening strategy, and recommends path forward for further improvement. PMID:26441648

  14. Inference on biological mechanisms using an integrated phenotype prediction model.

    PubMed

    Enomoto, Yumi; Ushijima, Masaru; Miyata, Satoshi; Matsuura, Masaaki; Ohtaki, Megu

    2008-03-01

    We propose a methodology for constructing an integrated phenotype prediction model that accounts for multiple pathways regulating a targeted phenotype. The method uses multiple prediction models, each expressing a particular pattern of gene-to-gene interrelationship, such as epistasis. We also propose a methodology using Gene Ontology annotations to infer a biological mechanism from the integrated phenotype prediction model. To construct the integrated models, we employed multiple logistic regression models using a two-step learning approach to examine a number of patterns of gene-to-gene interrelationships. We first selected individual prediction models with acceptable goodness of fit, and then combined the models. The resulting integrated model predicts phenotype as a logical sum of predicted results from the individual models. We used published microarray data on neuroblastoma from Ohira et al (2005) for illustration, constructing an integrated model to predict prognosis and infer the biological mechanisms controlling prognosis. Although the resulting integrated model comprised a small number of genes compared to a previously reported analysis of these data, the model demonstrated excellent performance, with an error rate of 0.12 in a validation analysis. Gene Ontology analysis suggested that prognosis of patients with neuroblastoma may be influenced by biological processes such as cell growth, G-protein signaling, phosphoinositide-mediated signaling, alcohol metabolism, glycolysis, neurophysiological processes, and catecholamine catabolism. PMID:18578362

  15. Predicting phenotype from genotype: normal pigmentation.

    PubMed

    Valenzuela, Robert K; Henderson, Miquia S; Walsh, Monica H; Garrison, Nanibaa' A; Kelch, Jessica T; Cohen-Barak, Orit; Erickson, Drew T; John Meaney, F; Bruce Walsh, J; Cheng, Keith C; Ito, Shosuke; Wakamatsu, Kazumasa; Frudakis, Tony; Thomas, Matthew; Brilliant, Murray H

    2010-03-01

    Genetic information in forensic studies is largely limited to CODIS data and the ability to match samples and assign them to an individual. However, there are circumstances, in which a given DNA sample does not match anyone in the CODIS database, and no other information about the donor is available. In this study, we determined 75 SNPs in 24 genes (previously implicated in human or animal pigmentation studies) for the analysis of single- and multi-locus associations with hair, skin, and eye color in 789 individuals of various ethnic backgrounds. Using multiple linear regression modeling, five SNPs in five genes were found to account for large proportions of pigmentation variation in hair, skin, and eyes in our across-population analyses. Thus, these models may be of predictive value to determine an individual's pigmentation type from a forensic sample, independent of ethnic origin. PMID:20158590

  16. Genotypic richness predicts phenotypic variation in an endangered clonal plant.

    PubMed

    Evans, Suzanna M; Sinclair, Elizabeth A; Poore, Alistair G B; Bain, Keryn F; Vergés, Adriana

    2016-01-01

    Declines in genetic diversity within a species can affect the stability and functioning of populations. The conservation of genetic diversity is thus a priority, especially for threatened or endangered species. The importance of genetic variation, however, is dependent on the degree to which it translates into phenotypic variation for traits that affect individual performance and ecological processes. This is especially important for predominantly clonal species, as no single clone is likely to maximise all aspects of performance. Here we show that intraspecific genotypic diversity as measured using microsatellites is a strong predictor of phenotypic variation in morphological traits and shoot productivity of the threatened, predominantly clonal seagrass Posidonia australis, on the east coast of Australia. Biomass and surface area variation was most strongly predicted by genotypic richness, while variation in leaf chemistry (phenolics and nitrogen) was unrelated to genotypic richness. Genotypic richness did not predict tissue loss to herbivores or epiphyte load, however we did find that increased herbivore damage was positively correlated with allelic richness. Although there was no clear relationship between higher primary productivity and genotypic richness, variation in shoot productivity within a meadow was significantly greater in more genotypically diverse meadows. The proportion of phenotypic variation explained by environmental conditions varied among different genotypes, and there was generally no variation in phenotypic traits among genotypes present in the same meadows. Our results show that genotypic richness as measured through the use of presumably neutral DNA markers does covary with phenotypic variation in functionally relevant traits such as leaf morphology and shoot productivity. The remarkably long lifespan of individual Posidonia plants suggests that plasticity within genotypes has played an important role in the longevity of the species

  17. Genotypic richness predicts phenotypic variation in an endangered clonal plant

    PubMed Central

    Sinclair, Elizabeth A.; Poore, Alistair G.B.; Bain, Keryn F.; Vergés, Adriana

    2016-01-01

    Declines in genetic diversity within a species can affect the stability and functioning of populations. The conservation of genetic diversity is thus a priority, especially for threatened or endangered species. The importance of genetic variation, however, is dependent on the degree to which it translates into phenotypic variation for traits that affect individual performance and ecological processes. This is especially important for predominantly clonal species, as no single clone is likely to maximise all aspects of performance. Here we show that intraspecific genotypic diversity as measured using microsatellites is a strong predictor of phenotypic variation in morphological traits and shoot productivity of the threatened, predominantly clonal seagrass Posidonia australis, on the east coast of Australia. Biomass and surface area variation was most strongly predicted by genotypic richness, while variation in leaf chemistry (phenolics and nitrogen) was unrelated to genotypic richness. Genotypic richness did not predict tissue loss to herbivores or epiphyte load, however we did find that increased herbivore damage was positively correlated with allelic richness. Although there was no clear relationship between higher primary productivity and genotypic richness, variation in shoot productivity within a meadow was significantly greater in more genotypically diverse meadows. The proportion of phenotypic variation explained by environmental conditions varied among different genotypes, and there was generally no variation in phenotypic traits among genotypes present in the same meadows. Our results show that genotypic richness as measured through the use of presumably neutral DNA markers does covary with phenotypic variation in functionally relevant traits such as leaf morphology and shoot productivity. The remarkably long lifespan of individual Posidonia plants suggests that plasticity within genotypes has played an important role in the longevity of the species

  18. Evaluation of Qualitative Methods for Phenotyping Brachymesophalangia – V from Radiographs of Children

    PubMed Central

    Williams, Kimberly D.; Nahhas, Ramzi W.; Cottom, Carol R.; Lawrence, Sharon; Subedi, Janardan; Jha, Bharat; Czerwinski, Stefan A.; Blangero, John; Williams-Blangero, Sarah; Towne, Bradford

    2012-01-01

    Objective Brachymesophalangia – V (BMP-V), the general term for a short and broad middle phalanx of the 5th digit, presents both alone and in a large number of complex brachydactylies and developmental disorders. Past anthropological and epidemiological studies of growth and development have examined the prevalence of BMP-V because small developmental disorders may signal more complex disruptions of skeletal growth and development. Historically, however, consensus on qualitative phenotype methodology has not been established. In large-scale, non-clinical studies such as the Fels Longitudinal Study and the Jiri Growth Study, quantitative assessment of the hand is not always the most efficient manner of screening for skeletal dysmorphologies. The current study evaluates qualitative phenotyping techniques for BMP-V used in past anthropological studies of growth and development in order to establish a useful and reliable screening method for large study samples. Methods A total of 1,360 radiographs from Jiri Growth Study participants aged 3 – 18 years were evaluated. BMP-V was assessed using three methods: 1) subjective evaluation of length and width of the bone; 2) comparison with skeletal age-matched radiographs; and 3) subjective evaluation of the length of the middle 4th and 5th phalanges. Results We found that the method that uses skeletal age-matched reference radiographs is the better tool for assessing BMP-V because it considers the shape, rather than solely the length and width of the bone, which can be difficult to judge accurately without measurement. This study highlights the complexity of phenotypic assessment of BMP-V and by extension other brachydactylies. PMID:22131202

  19. Design of Biomedical Robots for Phenotype Prediction Problems.

    PubMed

    deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Sonis, Stephen T

    2016-08-01

    Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem. PMID:27347715

  20. Migration Phenotype of Brain-Cancer Cells Predicts Patient Outcomes.

    PubMed

    Smith, Chris L; Kilic, Onur; Schiapparelli, Paula; Guerrero-Cazares, Hugo; Kim, Deok-Ho; Sedora-Roman, Neda I; Gupta, Saksham; O'Donnell, Thomas; Chaichana, Kaisorn L; Rodriguez, Fausto J; Abbadi, Sara; Park, JinSeok; Quiñones-Hinojosa, Alfredo; Levchenko, Andre

    2016-06-21

    Glioblastoma multiforme is a heterogeneous and infiltrative cancer with dismal prognosis. Studying the migratory behavior of tumor-derived cell populations can be informative, but it places a high premium on the precision of in vitro methods and the relevance of in vivo conditions. In particular, the analysis of 2D cell migration may not reflect invasion into 3D extracellular matrices in vivo. Here, we describe a method that allows time-resolved studies of primary cell migration with single-cell resolution on a fibrillar surface that closely mimics in vivo 3D migration. We used this platform to screen 14 patient-derived glioblastoma samples. We observed that the migratory phenotype of a subset of cells in response to platelet-derived growth factor was highly predictive of tumor location and recurrence in the clinic. Therefore, migratory phenotypic classifiers analyzed at the single-cell level in a patient-specific way can provide high diagnostic and prognostic value for invasive cancers. PMID:27292647

  1. A Whole-Cell Computational Model Predicts Phenotype from Genotype

    PubMed Central

    Karr, Jonathan R.; Sanghvi, Jayodita C.; Macklin, Derek N.; Gutschow, Miriam V.; Jacobs, Jared M.; Bolival, Benjamin; Assad-Garcia, Nacyra; Glass, John I.; Covert, Markus W.

    2012-01-01

    SUMMARY Understanding how complex phenotypes arise from individual molecules and their interactions is a primary challenge in biology that computational approaches are poised to tackle. We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions. An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and experimental measurements. Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data. The model provides insights into many previously unobserved cellular behaviors, including in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication rates. In addition, experimental analysis directed by model predictions identified previously undetected kinetic parameters and biological functions. We conclude that comprehensive whole-cell models can be used to facilitate biological discovery. PMID:22817898

  2. Predicting Development of the Metabolically Healthy Obese Phenotype

    PubMed Central

    Achilike, Immaculeta; Hazuda, Helen P.; Fowler, Sharon P.; Aung, KoKo; Lorenzo, Carlos

    2014-01-01

    Objective The metabolically healthy (MHO) and unhealthy obese (MUHO) differ in terms of cardiovascular risk. However, little is known about predicting the development of these phenotypes and the future stability of the MHO phenotype. Therefore, we examined these two issues in the San Antonio Heart Study. Design Longitudinal, population-based study of cardiometabolic risk factors among Mexican Americans and non-Hispanic whites in San Antonio. Subjects The study sample included 2,368 participants with neither MUHO nor diabetes at baseline. Median follow-up was 7.8 years. MHO was defined as obesity with ≤1 metabolic abnormality; MUHO, as obesity with ≥2 abnormalities. Results At baseline, 1,595 and 498 individuals were non-obese with ≤1 and ≥2 metabolic abnormalities, respectively; 275 were MHO. Among non-obese individuals, independent predictors of incident MHO (OR for 1-SD change [95% CI]) included body mass index (8.12 [5.66 – 11.7]), triglycerides (0.52 [0.39 – 0.68]), and HDL-C (1.41 [1.11 – 1.81]), whereas independent predictors of incident MUHO included BMI (5.97 [4.58 – 7.77]) and triglycerides (1.26 [1.05 – 1.51]). Among participants with ≤1 metabolic abnormality, obesity was associated with greater odds of developing multiple metabolic abnormalities (OR 2.26 [1.74 – 2.95]). Conclusions Triglycerides and HDL-C may be useful for predicting progression to MHO. MHO may not be a stable condition, because it confers an increased risk of developing multiple metabolic abnormalities. PMID:24984752

  3. Predicting when climate-driven phenotypic change affects population dynamics.

    PubMed

    McLean, Nina; Lawson, Callum R; Leech, Dave I; van de Pol, Martijn

    2016-06-01

    Species' responses to climate change are variable and diverse, yet our understanding of how different responses (e.g. physiological, behavioural, demographic) relate and how they affect the parameters most relevant for conservation (e.g. population persistence) is lacking. Despite this, studies that observe changes in one type of response typically assume that effects on population dynamics will occur, perhaps fallaciously. We use a hierarchical framework to explain and test when impacts of climate on traits (e.g. phenology) affect demographic rates (e.g. reproduction) and in turn population dynamics. Using this conceptual framework, we distinguish four mechanisms that can prevent lower-level responses from impacting population dynamics. Testable hypotheses were identified from the literature that suggest life-history and ecological characteristics which could predict when these mechanisms are likely to be important. A quantitative example on birds illustrates how, even with limited data and without fully-parameterized population models, new insights can be gained; differences among species in the impacts of climate-driven phenological changes on population growth were not explained by the number of broods or density dependence. Our approach helps to predict the types of species in which climate sensitivities of phenotypic traits have strong demographic and population consequences, which is crucial for conservation prioritization of data-deficient species. PMID:27062059

  4. Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations.

    PubMed

    Shah, Sonia; Bonder, Marc J; Marioni, Riccardo E; Zhu, Zhihong; McRae, Allan F; Zhernakova, Alexandra; Harris, Sarah E; Liewald, Dave; Henders, Anjali K; Mendelson, Michael M; Liu, Chunyu; Joehanes, Roby; Liang, Liming; Levy, Daniel; Martin, Nicholas G; Starr, John M; Wijmenga, Cisca; Wray, Naomi R; Yang, Jian; Montgomery, Grant W; Franke, Lude; Deary, Ian J; Visscher, Peter M

    2015-07-01

    We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association studies on BMI (n ∼ 350,000) and height (n ∼ 250,000) to date. We derived methylation predictors by estimating probe-trait effects in discovery samples and tested them in external samples. Methylation profiles associated with BMI in older individuals from the Lothian Birth Cohorts (LBCs, n = 1,366) explained 4.9% of the variation in BMI in Dutch adults from the LifeLines DEEP study (n = 750) but did not account for any BMI variation in adolescents from the Brisbane Systems Genetic Study (BSGS, n = 403). Methylation profiles based on the Dutch sample explained 4.9% and 3.6% of the variation in BMI in the LBCs and BSGS, respectively. Methylation profiles predicted BMI independently of genetic profiles in an additive manner: 7%, 8%, and 14% of variance of BMI in the LBCs were explained by the methylation predictor, the genetic predictor, and a model containing both, respectively. The corresponding percentages for LifeLines DEEP were 5%, 9%, and 13%, respectively, suggesting that the methylation profiles represent environmental effects. The differential effects of the BMI methylation profiles by age support previous observations of age modulation of genetic contributions. In contrast, methylation profiles accounted for almost no variation in height, consistent with a mainly genetic contribution to inter-individual variation. The BMI results suggest that combining genetic and epigenetic information might have greater utility for complex-trait prediction. PMID:26119815

  5. Predicting Phenotypes from Genetic Crosses: A Mathematical Concept to Help Struggling Biology Students

    ERIC Educational Resources Information Center

    Baurhoo, Neerusha; Darwish, Shireef

    2012-01-01

    Predicting phenotypic outcomes from genetic crosses is often very difficult for biology students, especially those with learning disabilities. With our mathematical concept, struggling students in inclusive biology classrooms are now better equipped to solve genetic problems and predict phenotypes, because of improved understanding of dominance…

  6. Predictive qualitative risk model of bovine rabies occurrence in Brazil.

    PubMed

    Braga, Guilherme Basseto; Grisi-Filho, José Henrique Hildebrand; Leite, Bruno Meireles; de Sena, Elaine Fátima; Dias, Ricardo Augusto

    2014-03-01

    Bovine rabies remains endemic in Brazil and despite control efforts, the disease still spreads insidiously. The main vector is the hematophagous bat, Desmodus rotundus. The present work aimed to create a predictive qualitative model of the occurrence of bovine rabies in each municipality in 25 of the 27 Brazilian States. The risk of rabies transmission from bats to bovine was estimated using decision-tree models of receptivity and vulnerability. Questionnaires, which covered a number of questions related to the surveillance of possible risk factors, such as bovine rabies outbreaks in the previous year, the presence of bat roosts, bat rabies positivity and environmental changes, were sent to the local veterinary units of each State. The bovine density and geomorphologic features were obtained from national databases and geographic information systems. Of the 433 municipalities presenting bovine rabies outbreaks in 2010, 178 (41.1%) were classified by the model as high risk, 212 (49.0%) were classified as moderate risk, 25 (5.8%) were classified as low risk, whereas the risk was undetermined in 18 municipalities (4.1%). An ROC curve was built to determine if the risk evaluated by the model could adequately discriminate between municipalities with and without rabies occurrence in future years. The risk estimator for the year 2011 was classified as moderately accurate. In the future, these models could allow the targeting of rabies control efforts, with the adoption of control measures directed to the higher risk locations and the optimization of the field veterinary staff deployment throughout the country. Additionally, efforts must be made to encourage continuous surveillance of risk factors. PMID:24433635

  7. Prediction of gene–phenotype associations in humans, mice, and plants using phenologs

    PubMed Central

    2013-01-01

    Background Phenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such “orthologous phenotypes,” or “phenologs,” are examples of deep homology, and may be used to predict additional candidate disease genes. Results In this work, we develop an unsupervised algorithm for ranking phenolog-based candidate disease genes through the integration of predictions from the k nearest neighbor phenologs, comparing classifiers and weighting functions by cross-validation. We also improve upon the original method by extending the theory to paralogous phenotypes. Our algorithm makes use of additional phenotype data — from chicken, zebrafish, and E. coli, as well as new datasets for C. elegans — establishing that several types of annotations may be treated as phenotypes. We demonstrate the use of our algorithm to predict novel candidate genes for human atrial fibrillation (such as HRH2, ATP4A, ATP4B, and HOPX) and epilepsy (e.g., PAX6 and NKX2-1). We suggest gene candidates for pharmacologically-induced seizures in mouse, solely based on orthologous phenotypes from E. coli. We also explore the prediction of plant gene–phenotype associations, as for the Arabidopsis response to vernalization phenotype. Conclusions We are able to rank gene predictions for a significant portion of the diseases in the Online Mendelian Inheritance in Man database. Additionally, our method suggests candidate genes for mammalian seizures based only on bacterial phenotypes and gene orthology. We demonstrate that phenotype information may come from diverse sources, including drug sensitivities, gene ontology biological processes, and in situ hybridization annotations. Finally, we offer testable candidates for a variety of human diseases, plant traits, and other classes of phenotypes across a wide array of species. PMID:23800157

  8. Inherited PTEN mutations and the prediction of phenotype.

    PubMed

    Leslie, Nicholas R; Longy, Michel

    2016-04-01

    PTEN has been heavily studied due to its role as a tumour suppressor and as a core inhibitory component of the phosphoinositide 3-kinase (PI3K) signalling network. It is a broadly expressed phosphatase which displays complexity and diversity in both its functions and regulation and accordingly, in the laboratory numerous classes of functionally distinct mutations have been generated. Inherited loss of function mutations in the PTEN gene were originally identified in sufferers of Cowden disease, but later shown to associate with more diverse human pathologies, mostly relating to cell and tissue overgrowth, leading to the use of the broader term, PTEN Hamartoma Tumour Syndrome. Recent phenotypic analysis of clinical cohorts of PTEN mutation carriers, combined with laboratory studies of the consequences of these mutations implies that stable catalytically inactive PTEN mutants may lead to the most severe phenotypes, and conversely, that mutants retaining partial function associate more frequently with a milder phenotype, with autism spectrum disorder often being diagnosed. Future work will be needed to confirm and to refine these genotype-phenotype relationships and convert this developing knowledge into improved patient management and potentially treatment with emerging drugs which target the PI3K pathway. PMID:26827793

  9. Interethnic variation of CYP2C19 alleles, 'predicted' phenotypes and 'measured' metabolic phenotypes across world populations.

    PubMed

    Fricke-Galindo, I; Céspedes-Garro, C; Rodrigues-Soares, F; Naranjo, M E G; Delgado, Á; de Andrés, F; López-López, M; Peñas-Lledó, E; LLerena, A

    2016-04-01

    The present study evaluates the worldwide frequency distribution of CYP2C19 alleles and CYP2C19 metabolic phenotypes ('predicted' from genotypes and 'measured' with a probe drug) among healthy volunteers from different ethnic groups and geographic regions, as well as the relationship between the 'predicted' and 'measured' CYP2C19 metabolic phenotypes. A total of 52 181 healthy volunteers were studied within 138 selected original research papers. CYP2C19*17 was 42- and 24-fold more frequent in Mediterranean-South Europeans and Middle Easterns than in East Asians (P<0.001, in both cases). Contrarily, CYP2C19*2 and CYP2C19*3 alleles were more frequent in East Asians (30.26% and 6.89%, respectively), and even a twofold higher frequency of these alleles was found in Native populations from Oceania (61.30% and 14.42%, respectively; P<0.001, in all cases), which may be a consequence of genetic drift process in the Pacific Islands. Regarding CYP2C19 metabolic phenotype, poor metabolizers (PMs) were more frequent among Asians than in Europeans, contrarily to the phenomenon reported for CYP2D6. A correlation has been found between the frequencies of CYP2C19 poor metabolism 'predicted' from CYP2C19 genotypes (gPMs) and the poor metabolic phenotype 'measured' with a probe drug (mPMs) when subjects are either classified by ethnicity (r=0.94, P<0.001) or geographic region (r=0.99, P=0.002). Nevertheless, further research is needed in African and Asian populations, which are under-represented, and additional CYP2C19 variants and the 'measured' phenotype should be studied. PMID:26503820

  10. Markov chain Monte Carlo linkage analysis of a complex qualitative phenotype.

    PubMed

    Hinrichs, A; Lin, J H; Reich, T; Bierut, L; Suarez, B K

    1999-01-01

    We tested a new computer program, LOKI, that implements a reversible jump Markov chain Monte Carlo (MCMC) technique for segregation and linkage analysis. Our objective was to determine whether this software, designed for use with continuously distributed phenotypes, has any efficacy when applied to the discrete disease states of the simulated data from the Mordor data from GAW Problem 1. Although we were able to identify the genomic location for two of the three quantitative trait loci by repeated application of the software, the MCMC sampler experienced significant mixing problems indicating that the method, as currently formulated in LOKI, was not suitable for the discrete phenotypes in this data set. PMID:10597502

  11. Hydrolysis of sucrose octa-acetate: qualitative differences in taster and demistaster avoidance phenotypes.

    PubMed

    Capeless, C G; Boughter, J D; Whitney, G

    1994-12-01

    Calcium hydroxide and sodium hydroxide were used to hydrolyse sucrose octa-acetate (SOA) as a means of evaluating the taster (Soaa) and demitaster (Soac) allelic phenotypes of the genetic locus Soa. The SWR/J (taster) inbred strain and the B6.SW Soaa (taster) congenic strain were demonstrated to cease avoiding upon nearly complete hydrolysis of 10(-5) M SOA with calcium hydroxide or sodium hydroxide and of 10(-4) M SOA with calcium hydroxide. The BALB/cByJ, C3HeB/FeJ and DBA/2J (demitaster) inbred strains were demonstrated to cease avoiding after only a partial hydrolysis of 10(-3) M SOA using calcium hydroxide. It is suggested that specificity for the number or placement of the acetates of SOA underlies the difference between the taster and demitaster phenotypes. PMID:7735839

  12. PREDICTING INTERMEDIATE PHENOTYPES IN ASTHMA USING BRONCHOALVEOLAR LAVAGE-DERIVED CYTOKINES

    PubMed Central

    Brasier, Allan R.; Victor, Sundar; Ju, Hyunsu; Busse, William W.; Curran-Everett, Douglas; Bleecker, Eugene; Castro, Mario; Chung, Kian Fan; Gaston, Benjamin; Israel, Elliot; Wenzel, Sally E.; Erzurum, Serpil C.; Jarjour, Nizar N.; Calhoun, William J.

    2011-01-01

    An important problem in realizing personalized medicine is the development of methods for identifying disease subtypes using quantitative proteomics. Recently we found that bronchoalveolar lavage (BAL) cytokine patterns contain information about dynamic lung responsiveness. In this study, we examined physiological data from 1048 subjects enrolled in the US Severe Asthma Research Program (SARP) to identify four largely separable, quantitative intermediate phenotypes. Upper extremes in the study population were identified for eosinophil- or neutrophil- predominant inflammation, bronchodilation in response to albuterol treatment, or methacholine sensitivity. We evaluated four different statistical (“machine”) learning methods to predict each intermediate phenotypes using BAL cytokine measurements on a 76 subject subset. Comparison of these models using area under the ROC curve and overall classification accuracy indicated that logistic regression and multivariate adaptive regression splines produced the most accurate methods to predict intermediate asthma phenotypes. These robust classification methods will aid future translational studies in asthma targeted at specific intermediate phenotypes. PMID:20718815

  13. Qualitative and Quantitative Protein Complex Prediction Through Proteome-Wide Simulations.

    PubMed

    Rizzetto, Simone; Priami, Corrado; Csikász-Nagy, Attila

    2015-10-01

    Despite recent progress in proteomics most protein complexes are still unknown. Identification of these complexes will help us understand cellular regulatory mechanisms and support development of new drugs. Therefore it is really important to establish detailed information about the composition and the abundance of protein complexes but existing algorithms can only give qualitative predictions. Herein, we propose a new approach based on stochastic simulations of protein complex formation that integrates multi-source data--such as protein abundances, domain-domain interactions and functional annotations--to predict alternative forms of protein complexes together with their abundances. This method, called SiComPre (Simulation based Complex Prediction), achieves better qualitative prediction of yeast and human protein complexes than existing methods and is the first to predict protein complex abundances. Furthermore, we show that SiComPre can be used to predict complexome changes upon drug treatment with the example of bortezomib. SiComPre is the first method to produce quantitative predictions on the abundance of molecular complexes while performing the best qualitative predictions. With new data on tissue specific protein complexes becoming available SiComPre will be able to predict qualitative and quantitative differences in the complexome in various tissue types and under various conditions. PMID:26492574

  14. PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources

    PubMed Central

    Kahanda, Indika; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa

    2015-01-01

    The human phenotype ontology (HPO) was recently developed as a standardized vocabulary for describing the phenotype abnormalities associated with human diseases. At present, only a small fraction of human protein coding genes have HPO annotations. But, researchers believe that a large portion of currently unannotated genes are related to disease phenotypes. Therefore, it is important to predict gene-HPO term associations using accurate computational methods. In this work we demonstrate the performance advantage of the structured SVM approach which was shown to be highly effective for Gene Ontology term prediction in comparison to several baseline methods. Furthermore, we highlight a collection of informative data sources suitable for the problem of predicting gene-HPO associations, including large scale literature mining data. PMID:26834980

  15. Metagenomic predictions: from microbiome to complex health and environmental phenotypes in humans and cattle.

    PubMed

    Ross, Elizabeth M; Moate, Peter J; Marett, Leah C; Cocks, Ben G; Hayes, Ben J

    2013-01-01

    Mammals have a large cohort of endo- and ecto- symbiotic microorganisms (the microbiome) that potentially influence host phenotypes. There have been numerous exploratory studies of these symbiotic organisms in humans and other animals, often with the aim of relating the microbiome to a complex phenotype such as body mass index (BMI) or disease state. Here, we describe an efficient methodology for predicting complex traits from quantitative microbiome profiles. The method was demonstrated by predicting inflammatory bowel disease (IBD) status and BMI from human microbiome data, and enteric greenhouse gas production from dairy cattle rumen microbiome profiles. The method uses unassembled massively parallel sequencing (MPS) data to form metagenomic relationship matrices (analogous to genomic relationship matrices used in genomic predictions) to predict IBD, BMI and methane production phenotypes with useful accuracies (r = 0.423, 0.422 and 0.466 respectively). Our results show that microbiome profiles derived from MPS can be used to predict complex phenotypes of the host. Although the number of biological replicates used here limits the accuracy that can be achieved, preliminary results suggest this approach may surpass current prediction accuracies that are based on the host genome. This is especially likely for traits that are largely influenced by the gut microbiota, for example digestive tract disorders or metabolic functions such as enteric methane production in cattle. PMID:24023808

  16. Metagenomic Predictions: From Microbiome to Complex Health and Environmental Phenotypes in Humans and Cattle

    PubMed Central

    Ross, Elizabeth M.; Moate, Peter J.; Marett, Leah C.; Cocks, Ben G.; Hayes, Ben J.

    2013-01-01

    Mammals have a large cohort of endo- and ecto- symbiotic microorganisms (the microbiome) that potentially influence host phenotypes. There have been numerous exploratory studies of these symbiotic organisms in humans and other animals, often with the aim of relating the microbiome to a complex phenotype such as body mass index (BMI) or disease state. Here, we describe an efficient methodology for predicting complex traits from quantitative microbiome profiles. The method was demonstrated by predicting inflammatory bowel disease (IBD) status and BMI from human microbiome data, and enteric greenhouse gas production from dairy cattle rumen microbiome profiles. The method uses unassembled massively parallel sequencing (MPS) data to form metagenomic relationship matrices (analogous to genomic relationship matrices used in genomic predictions) to predict IBD, BMI and methane production phenotypes with useful accuracies (r = 0.423, 0.422 and 0.466 respectively). Our results show that microbiome profiles derived from MPS can be used to predict complex phenotypes of the host. Although the number of biological replicates used here limits the accuracy that can be achieved, preliminary results suggest this approach may surpass current prediction accuracies that are based on the host genome. This is especially likely for traits that are largely influenced by the gut microbiota, for example digestive tract disorders or metabolic functions such as enteric methane production in cattle. PMID:24023808

  17. Narcissism predicts impulsive buying: phenotypic and genetic evidence.

    PubMed

    Cai, Huajian; Shi, Yuanyuan; Fang, Xiang; Luo, Yu L L

    2015-01-01

    Impulsive buying makes billions of dollars for retail businesses every year, particularly in an era of thriving e-commerce. Narcissism, characterized by impulsivity and materialism, may serve as a potential antecedent to impulsive buying. To test this hypothesis, two studies examined the relationship between narcissism and impulsive buying. In Study 1, we surveyed an online sample and found that while adaptive narcissism was not correlated with impulsive buying, maladaptive narcissism was significantly predictive of the impulsive buying tendency. By investigating 304 twin pairs, Study 2 showed that global narcissism and its two components, adaptive and maladaptive narcissism, as well as the impulsive buying tendency were heritable. The study found, moreover, that the connections between global narcissism and impulsive buying, and between maladaptive narcissism and impulsive buying were genetically based. These findings not only establish a link between narcissism and impulsive buying but also help to identify the origins of the link. The present studies deepen our understanding of narcissism, impulsive buying, and their interrelationship. PMID:26217251

  18. Narcissism predicts impulsive buying: phenotypic and genetic evidence

    PubMed Central

    Cai, Huajian; Shi, Yuanyuan; Fang, Xiang; Luo, Yu L. L.

    2015-01-01

    Impulsive buying makes billions of dollars for retail businesses every year, particularly in an era of thriving e-commerce. Narcissism, characterized by impulsivity and materialism, may serve as a potential antecedent to impulsive buying. To test this hypothesis, two studies examined the relationship between narcissism and impulsive buying. In Study 1, we surveyed an online sample and found that while adaptive narcissism was not correlated with impulsive buying, maladaptive narcissism was significantly predictive of the impulsive buying tendency. By investigating 304 twin pairs, Study 2 showed that global narcissism and its two components, adaptive and maladaptive narcissism, as well as the impulsive buying tendency were heritable. The study found, moreover, that the connections between global narcissism and impulsive buying, and between maladaptive narcissism and impulsive buying were genetically based. These findings not only establish a link between narcissism and impulsive buying but also help to identify the origins of the link. The present studies deepen our understanding of narcissism, impulsive buying, and their interrelationship. PMID:26217251

  19. The influence of disease categories on gene candidate predictions from model organism phenotypes

    PubMed Central

    2014-01-01

    Background The molecular etiology is still to be identified for about half of the currently described Mendelian diseases in humans, thereby hindering efforts to find treatments or preventive measures. Advances, such as new sequencing technologies, have led to increasing amounts of data becoming available with which to address the problem of identifying disease genes. Therefore, automated methods are needed that reliably predict disease gene candidates based on available data. We have recently developed Exomiser as a tool for identifying causative variants from exome analysis results by filtering and prioritising using a number of criteria including the phenotype similarity between the disease and mouse mutants involving the gene candidates. Initial investigations revealed a variation in performance for different medical categories of disease, due in part to a varying contribution of the phenotype scoring component. Results In this study, we further analyse the performance of our cross-species phenotype matching algorithm, and examine in more detail the reasons why disease gene filtering based on phenotype data works better for certain disease categories than others. We found that in addition to misleading phenotype alignments between species, some disease categories are still more amenable to automated predictions than others, and that this often ties in with community perceptions on how well the organism works as model. Conclusions In conclusion, our automated disease gene candidate predictions are highly dependent on the organism used for the predictions and the disease category being studied. Future work on computational disease gene prediction using phenotype data would benefit from methods that take into account the disease category and the source of model organism data. PMID:25093073

  20. Prediction of trabecular bone qualitative properties using scanning quantitative ultrasound

    NASA Astrophysics Data System (ADS)

    Qin, Yi-Xian; Lin, Wei; Mittra, Erik; Xia, Yi; Cheng, Jiqi; Judex, Stefan; Rubin, Clint; Müller, Ralph

    2013-11-01

    Microgravity induced bone loss represents a critical health problem in astronauts, particularly occurred in weight-supporting skeleton, which leads to osteopenia and increase of fracture risk. Lack of suitable evaluation modality makes it difficult for monitoring skeletal status in long term space mission and increases potential risk of complication. Such disuse osteopenia and osteoporosis compromise trabecular bone density, and architectural and mechanical properties. While X-ray based imaging would not be practical in space, quantitative ultrasound may provide advantages to characterize bone density and strength through wave propagation in complex trabecular structure. This study used a scanning confocal acoustic diagnostic and navigation system (SCAN) to evaluate trabecular bone quality in 60 cubic trabecular samples harvested from adult sheep. Ultrasound image based SCAN measurements in structural and strength properties were validated by μCT and compressive mechanical testing. This result indicated a moderately strong negative correlations observed between broadband ultrasonic attenuation (BUA) and μCT-determined bone volume fraction (BV/TV, R2=0.53). Strong correlations were observed between ultrasound velocity (UV) and bone's mechanical strength and structural parameters, i.e., bulk Young's modulus (R2=0.67) and BV/TV (R2=0.85). The predictions for bone density and mechanical strength were significantly improved by using a linear combination of both BUA and UV, yielding R2=0.92 for BV/TV and R2=0.71 for bulk Young's modulus. These results imply that quantitative ultrasound can characterize trabecular structural and mechanical properties through measurements of particular ultrasound parameters, and potentially provide an excellent estimation for bone's structural integrity.

  1. Prediction of trabecular bone qualitative properties using scanning quantitative ultrasound

    PubMed Central

    Qin, Yi-Xian; Lin, Wei; Mittra, Erik; Xia, Yi; Cheng, Jiqi; Judex, Stefan; Rubin, Clint; Müller, Ralph

    2012-01-01

    Microgravity induced bone loss represents a critical health problem in astronauts, particularly occurred in weight-supporting skeleton, which leads to osteopenia and increase of fracture risk. Lack of suitable evaluation modality makes it difficult for monitoring skeletal status in long term space mission and increases potential risk of complication. Such disuse osteopenia and osteoporosis compromise trabecular bone density, and architectural and mechanical properties. While X-ray based imaging would not be practical in space, quantitative ultrasound may provide advantages to characterize bone density and strength through wave propagation in complex trabecular structure. This study used a scanning confocal acoustic diagnostic and navigation system (SCAN) to evaluate trabecular bone quality in 60 cubic trabecular samples harvested from adult sheep. Ultrasound image based SCAN measurements in structural and strength properties were validated by μCT and compressive mechanical testing. This result indicated a moderately strong negative correlations observed between broadband ultrasonic attenuation (BUA) and μCT-determined bone volume fraction (BV/TV, R2=0.53). Strong correlations were observed between ultrasound velocity (UV) and bone’s mechanical strength and structural parameters, i.e., bulk Young’s modulus (R2=0.67) and BV/TV (R2=0.85). The predictions for bone density and mechanical strength were significantly improved by using a linear combination of both BUA and UV, yielding R2=0.92 for BV/TV and R2=0.71 for bulk Young’s modulus. These results imply that quantitative ultrasound can characterize trabecular structural and mechanical properties through measurements of particular ultrasound parameters, and potentially provide an excellent estimation for bone’s structural integrity. PMID:23976803

  2. Prediction of trabecular bone qualitative properties using scanning quantitative ultrasound.

    PubMed

    Qin, Yi-Xian; Lin, Wei; Mittra, Erik; Xia, Yi; Cheng, Jiqi; Judex, Stefan; Rubin, Clint; Müller, Ralph

    2013-11-01

    Microgravity induced bone loss represents a critical health problem in astronauts, particularly occurred in weight-supporting skeleton, which leads to osteopenia and increase of fracture risk. Lack of suitable evaluation modality makes it difficult for monitoring skeletal status in long term space mission and increases potential risk of complication. Such disuse osteopenia and osteoporosis compromise trabecular bone density, and architectural and mechanical properties. While X-ray based imaging would not be practical in space, quantitative ultrasound may provide advantages to characterize bone density and strength through wave propagation in complex trabecular structure. This study used a scanning confocal acoustic diagnostic and navigation system (SCAN) to evaluate trabecular bone quality in 60 cubic trabecular samples harvested from adult sheep. Ultrasound image based SCAN measurements in structural and strength properties were validated by μCT and compressive mechanical testing. This result indicated a moderately strong negative correlations observed between broadband ultrasonic attenuation (BUA) and μCT-determined bone volume fraction (BV/TV, R(2)=0.53). Strong correlations were observed between ultrasound velocity (UV) and bone's mechanical strength and structural parameters, i.e., bulk Young's modulus (R(2)=0.67) and BV/TV (R(2)=0.85). The predictions for bone density and mechanical strength were significantly improved by using a linear combination of both BUA and UV, yielding R(2)=0.92 for BV/TV and R(2)=0.71 for bulk Young's modulus. These results imply that quantitative ultrasound can characterize trabecular structural and mechanical properties through measurements of particular ultrasound parameters, and potentially provide an excellent estimation for bone's structural integrity. PMID:23976803

  3. Building predictive models for mechanism-of-action classification from phenotypic assay data sets.

    PubMed

    Berg, Ellen L; Yang, Jian; Polokoff, Mark A

    2013-12-01

    Compound mechanism-of-action information can be critical for drug development decisions but is often challenging for phenotypic drug discovery programs. One concern is that compounds selected by phenotypic screening will have a previously known but undesirable target mechanism. Here we describe a useful method for assigning mechanism class to compounds and bioactive agents using an 84-feature signature from a panel of primary human cell systems (BioMAP systems). For this approach, a reference data set of well-characterized compounds was used to develop predictive models for 28 mechanism classes using support vector machines. These mechanism classes encompass safety and efficacy-related mechanisms, include both target-specific and pathway-based classes, and cover the most common mechanisms identified in phenotypic screens, such as inhibitors of mitochondrial and microtubule function, histone deacetylase, and cAMP elevators. Here we describe the performance and the application of these predictive models in a decision scheme for triaging phenotypic screening hits using a previously published data set of 309 environmental chemicals tested as part of the Environmental Protection Agency's ToxCast program. By providing quantified membership in specific mechanism classes, this approach is suitable for identification of off-target toxicity mechanisms as well as enabling target deconvolution of phenotypic drug discovery hits. PMID:24088371

  4. Computational models for prediction of yeast strain potential for winemaking from phenotypic profiles.

    PubMed

    Mendes, Inês; Franco-Duarte, Ricardo; Umek, Lan; Fonseca, Elza; Drumonde-Neves, João; Dequin, Sylvie; Zupan, Blaz; Schuller, Dorit

    2013-01-01

    Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40 °C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 µg/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection

  5. SuSPect: enhanced prediction of single amino acid variant (SAV) phenotype using network features.

    PubMed

    Yates, Christopher M; Filippis, Ioannis; Kelley, Lawrence A; Sternberg, Michael J E

    2014-07-15

    Whole-genome and exome sequencing studies reveal many genetic variants between individuals, some of which are linked to disease. Many of these variants lead to single amino acid variants (SAVs), and accurate prediction of their phenotypic impact is important. Incorporating sequence conservation and network-level features, we have developed a method, SuSPect (Disease-Susceptibility-based SAV Phenotype Prediction), for predicting how likely SAVs are to be associated with disease. SuSPect performs significantly better than other available batch methods on the VariBench benchmarking dataset, with a balanced accuracy of 82%. SuSPect is available at www.sbg.bio.ic.ac.uk/suspect. The Web site has been implemented in Perl and SQLite and is compatible with modern browsers. An SQLite database of possible missense variants in the human proteome is available to download at www.sbg.bio.ic.ac.uk/suspect/download.html. PMID:24810707

  6. Forensic DNA Phenotyping: Predicting human appearance from crime scene material for investigative purposes.

    PubMed

    Kayser, Manfred

    2015-09-01

    Forensic DNA Phenotyping refers to the prediction of appearance traits of unknown sample donors, or unknown deceased (missing) persons, directly from biological materials found at the scene. "Biological witness" outcomes of Forensic DNA Phenotyping can provide investigative leads to trace unknown persons, who are unidentifiable with current comparative DNA profiling. This intelligence application of DNA marks a substantially different forensic use of genetic material rather than that of current DNA profiling presented in the courtroom. Currently, group-specific pigmentation traits are already predictable from DNA with reasonably high accuracies, while several other externally visible characteristics are under genetic investigation. Until individual-specific appearance becomes accurately predictable from DNA, conventional DNA profiling needs to be performed subsequent to appearance DNA prediction. Notably, and where Forensic DNA Phenotyping shows great promise, this is on a (much) smaller group of potential suspects, who match the appearance characteristics DNA-predicted from the crime scene stain or from the deceased person's remains. Provided sufficient funding being made available, future research to better understand the genetic basis of human appearance will expectedly lead to a substantially more detailed description of an unknown person's appearance from DNA, delivering increased value for police investigations in criminal and missing person cases involving unknowns. PMID:25716572

  7. Using complete genome comparisons to identify sequences whose presence accurately predicts clinically important phenotypes.

    PubMed

    Hall, Barry G; Cardenas, Heliodoro; Barlow, Miriam

    2013-01-01

    In clinical settings it is often important to know not just the identity of a microorganism, but also the danger posed by that particular strain. For instance, Escherichia coli can range from being a harmless commensal to being a very dangerous enterohemorrhagic (EHEC) strain. Determining pathogenic phenotypes can be both time consuming and expensive. Here we propose a simple, rapid, and inexpensive method of predicting pathogenic phenotypes on the basis of the presence or absence of short homologous DNA segments in an isolate. Our method compares completely sequenced genomes without the necessity of genome alignments in order to identify the presence or absence of the segments to produce an automatic alignment of the binary string that describes each genome. Analysis of the segment alignment allows identification of those segments whose presence strongly predicts a phenotype. Clinical application of the method requires nothing more that PCR amplification of each of the set of predictive segments. Here we apply the method to identifying EHEC strains of E. coli and to distinguishing E. coli from Shigella. We show in silico that with as few as 8 predictive sequences, if even three of those predictive sequences are amplified the probability of being EHEC or Shigella is >0.99. The method is thus very robust to the occasional amplification failure for spurious reasons. Experimentally, we apply the method to screening a set of 98 isolates to distinguishing E. coli from Shigella, and EHEC from non-EHEC E. coli strains and show that all isolates are correctly identified. PMID:23935901

  8. Phenotypic novelty in experimental hybrids is predicted by the genetic distance between species of cichlid fish

    PubMed Central

    2009-01-01

    Background Transgressive segregation describes the occurrence of novel phenotypes in hybrids with extreme trait values not observed in either parental species. A previously experimentally untested prediction is that the amount of transgression increases with the genetic distance between hybridizing species. This follows from QTL studies suggesting that transgression is most commonly due to complementary gene action or epistasis, which become more frequent at larger genetic distances. This is because the number of QTLs fixed for alleles with opposing signs in different species should increase with time since speciation provided that speciation is not driven by disruptive selection. We measured the amount of transgression occurring in hybrids of cichlid fish bred from species pairs with gradually increasing genetic distances and varying phenotypic similarity. Transgression in multi-trait shape phenotypes was quantified using landmark-based geometric morphometric methods. Results We found that genetic distance explained 52% and 78% of the variation in transgression frequency in F1 and F2 hybrids, respectively. Confirming theoretical predictions, transgression when measured in F2 hybrids, increased linearly with genetic distance between hybridizing species. Phenotypic similarity of species on the other hand was not related to the amount of transgression. Conclusion The commonness and ease with which novel phenotypes are produced in cichlid hybrids between unrelated species has important implications for the interaction of hybridization with adaptation and speciation. Hybridization may generate new genotypes with adaptive potential that did not reside as standing genetic variation in either parental population, potentially enhancing a population's responsiveness to selection. Our results make it conceivable that hybridization contributed to the rapid rates of phenotypic evolution in the large and rapid adaptive radiations of haplochromine cichlids. PMID:19961584

  9. Clinical validity: Combinatorial pharmacogenomics predicts antidepressant responses and healthcare utilizations better than single gene phenotypes.

    PubMed

    Altar, C A; Carhart, J M; Allen, J D; Hall-Flavin, D K; Dechairo, B M; Winner, J G

    2015-10-01

    In four previous studies, a combinatorial multigene pharmacogenomic test (GeneSight) predicted those patients whose antidepressant treatment for major depressive disorder resulted in poorer efficacy and increased health-care resource utilizations. Here, we extended the analysis of clinical validity to the combined data from these studies. We also compared the outcome predictions of the combinatorial use of allelic variations in genes for four cytochrome P450 (CYP) enzymes (CYP2D6, CYP2C19, CYP2C9 and CYP1A2), the serotonin transporter (SLC6A4) and serotonin 2A receptor (HTR2A) with the outcome predictions for the very same subjects using traditional, single-gene analysis. Depression scores were measured at baseline and 8-10 weeks later for the 119 fully blinded subjects who received treatment as usual (TAU) with antidepressant standard of care, without the benefit of pharmacogenomic medication guidance. For another 96 TAU subjects, health-care utilizations were recorded in a 1-year, retrospective chart review. All subjects were genotyped after the clinical study period, and phenotype subgroups were created among those who had been prescribed a GeneSight panel medication that is a substrate for either CYP enzyme or serotonin effector protein. On the basis of medications prescribed for each subject at baseline, the combinatorial pharmacogenomic (CPGx™) GeneSight method categorized each subject into either a green ('use as directed'), yellow ('use with caution') or red category ('use with increased caution and with more frequent monitoring') phenotype, whereas the single-gene method categorized the same subjects with the traditional phenotype (for example, poor, intermediate, extensive or ultrarapid CYP metabolizer). The GeneSight combinatorial categorization approach discriminated and predicted poorer outcomes for red category patients prescribed medications metabolized by CYP2D6, CYP2C19 and CYP1A2 (P=0.0034, P=0.04 and P=0.03, respectively), whereas the single

  10. On the role of mid-infrared predicted phenotypes in fertility and health dairy breeding programs.

    PubMed

    Bastin, C; Théron, L; Lainé, A; Gengler, N

    2016-05-01

    Fertility and health traits are of prime importance in dairy breeding programs. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10), thereby hampering genetic improvement in disease resistance and fertility. Hence, indicators are useful in the prediction of genetic merit for fertility and health traits as long as they are easier to measure than direct fitness traits, heritable, and genetically correlated. Considering that changes in (fine) milk composition over a lactation reflect the physiological status of the cow, mid-infrared (MIR) analysis of milk opens the door to a wide range of potential indicator traits of fertility and health. Previous studies investigated the phenotypic and genetic relationships between fertility and MIR-predicted phenotypes, most being related to negative postpartum energy balance and body fat mobilization (e.g., fat:protein ratio, urea, fatty acids profile). Results showed that a combination of various fatty acid traits (e.g., C18:1 cis-9 and C10:0) could be used to improve fertility. Furthermore, occurrence of (sub)clinical ketosis has been related to milk-based phenotypes such as fat:protein ratio, fatty acids, and ketone bodies. Hence, MIR-predicted acetone and β-hydroxybutyrate contents in milk could be useful for breeding cows less susceptible to ketosis. Although studies investigating the genetic association among mastitis and MIR-predicted phenotypes are scarce, a wide range of traits, potentially predicted by MIR spectrometry, are worthy of consideration. These include traits related to the disease response of the cow (e.g., lactoferrin), reduced secretory activity (e.g., casein), and the alteration of the blood-milk barrier (e.g., minerals). Moreover, direct MIR prediction of fertility and health traits should be further considered. To conclude, MIR-predicted phenotypes have a role to play in the improvement of dairy cow fertility and health. However, further studies are warranted to

  11. The contribution of dominance to phenotype prediction in a pine breeding and simulated population

    PubMed Central

    de Almeida Filho, J E; Guimarães, J F R; e Silva, F F; de Resende, M D V; Muñoz, P; Kirst, M; Resende, M F R

    2016-01-01

    Pedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive–dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait. PMID:27118156

  12. The contribution of dominance to phenotype prediction in a pine breeding and simulated population.

    PubMed

    de Almeida Filho, J E; Guimarães, J F R; E Silva, F F; de Resende, M D V; Muñoz, P; Kirst, M; Resende, M F R

    2016-07-01

    Pedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive-dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait. PMID:27118156

  13. A phenotype of early infancy predicts reactivity of the amygdala in male adults.

    PubMed

    Schwartz, C E; Kunwar, P S; Greve, D N; Kagan, J; Snidman, N C; Bloch, R B

    2012-10-01

    One of the central questions that has occupied those disciplines concerned with human development is the nature of continuities and discontinuities from birth to maturity. The amygdala has a central role in the processing of novelty and emotion in the brain. Although there is considerable variability among individuals in the reactivity of the amygdala to novel and emotional stimuli, the origin of these individual differences is not well understood. Four-month old infants called high reactive (HR) demonstrate a distinctive pattern of vigorous motor activity and crying to specific unfamiliar visual, auditory and olfactory stimuli in the laboratory. Low-reactive infants show the complementary pattern. Here, we demonstrate that the HR infant phenotype predicts greater amygdalar reactivity to novel faces almost two decades later in adults. A prediction of individual differences in brain function at maturity can be made on the basis of a single behavioral assessment made in the laboratory at 4 months of age. This is the earliest known human behavioral phenotype that predicts individual differences in patterns of neural activity at maturity. These temperamental differences rooted in infancy may be relevant to understanding individual differences in vulnerability and resilience to clinical psychiatric disorder. Males who were HR infants showed particularly high levels of reactivity to novel faces in the amygdala that distinguished them as adults from all other sex/temperament subgroups, suggesting that their amygdala is particularly prone to engagement by unfamiliar faces. These findings underline the importance of taking gender into account when studying the developmental neurobiology of human temperament and anxiety disorders. The genetic study of behavioral and biologic intermediate phenotypes (or 'endophenotypes') indexing anxiety-proneness offers an important alternative to examining phenotypes based on clinically defined disorder. As the HR phenotype is characterized

  14. The more the merrier? How a few SNPs predict pigmentation phenotypes in the Northern German population.

    PubMed

    Caliebe, Amke; Harder, Melanie; Schuett, Rebecca; Krawczak, Michael; Nebel, Almut; von Wurmb-Schwark, Nicole

    2016-05-01

    Human pigmentation traits are of great interest to many research areas, from ancient DNA analysis to forensic science. We developed a gene-based predictive model for pigmentation phenotypes in a realistic target population for forensic case work from Northern Germany and compared our model with those brought forth by previous studies of genetically more heterogeneous populations. In doing so, we aimed at answering the following research questions: (1) do existing models allow good prediction of high-quality phenotypes in a genetically similar albeit more homogeneous population? (2) Would a model specifically set up for the more homogeneous population perform notably better than existing models? (3) Can the number of markers included in existing models be reduced without compromising their predictive capability in the more homogenous population? We investigated the association between eye, hair and skin colour and 12 candidate single-nucleotide polymorphisms (SNPs) from six genes. Our study comprised two samples of 300 and 100 individuals from Northern Germany. SNP rs12913832 in HERC2 was found to be strongly associated with blue eye colour (odds ratio=40.0, P<1.2 × 10(-4)) and to yield moderate predictive power (AUC: 77%; sensitivity: 90%, specificity: 63%, both at a 0.5 threshold for blue eye colour probability). SNP associations with hair and skin colour were weaker and genotypes less predictive. A comparison with two recently published sets of markers to predict eye and hair colour revealed that the consideration of additional SNPs with weak-to-moderate effect increased the predictive power for eye colour, but not for hair colour. PMID:26286644

  15. Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture.

    PubMed

    Goddard, M E; Kemper, K E; MacLeod, I M; Chamberlain, A J; Hayes, B J

    2016-07-27

    Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement. PMID:27440663

  16. Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

    PubMed Central

    Goddard, M. E.; Kemper, K. E.; MacLeod, I. M.; Chamberlain, A. J.; Hayes, B. J.

    2016-01-01

    Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement. PMID:27440663

  17. Integrative approaches for predicting protein function and prioritizing genes for complex phenotypes using protein interaction networks

    PubMed Central

    Ma, Xiaotu; Chen, Ting

    2014-01-01

    With the rapid development of biotechnologies, many types of biological data including molecular networks are now available. However, to obtain a more complete understanding of a biological system, the integration of molecular networks with other data, such as molecular sequences, protein domains and gene expression profiles, is needed. A key to the use of networks in biological studies is the definition of similarity among proteins over the networks. Here, we review applications of similarity measures over networks with a special focus on the following four problems: (i) predicting protein functions, (ii) prioritizing genes related to a phenotype given a set of seed genes that have been shown to be related to the phenotype, (iii) prioritizing genes related to a phenotype by integrating gene expression profiles and networks and (iv) identification of false positives and false negatives from RNAi experiments. Diffusion kernels are demonstrated to give superior performance in all these tasks, leading to the suggestion that diffusion kernels should be the primary choice for a network similarity metric over other similarity measures such as direct neighbors and shortest path distance. PMID:23788799

  18. Phenotypic Variance Predicts Symbiont Population Densities in Corals: A Modeling Approach

    PubMed Central

    van Woesik, Robert; Shiroma, Kazuyo; Koksal, Semen

    2010-01-01

    Background We test whether the phenotypic variance of symbionts (Symbiodinium) in corals is closely related with the capacity of corals to acclimatize to increasing seawater temperatures. Moreover, we assess whether more specialist symbionts will increase within coral hosts under ocean warming. The present study is only applicable to those corals that naturally have the capacity to support more than one type of Symbiodinium within the lifetime of a colony; for example, Montastraea annularis and Montastraea faveolata. Methodology/Principal Findings The population dynamics of competing Symbiodinium symbiont populations were projected through time in coral hosts using a novel, discrete time optimal–resource model. Models were run for two Atlantic Ocean localities. Four symbiont populations, with different environmental optima and phenotypic variances, were modeled to grow, divide, and compete in the corals under seasonal fluctuations in solar insolation and seawater temperature. Elevated seawater temperatures were input into the model 1.5°C above the seasonal summer average, and the symbiont population response was observed for each location. The models showed dynamic fluctuations in Symbiodinium populations densities within corals. Population density predictions for Lee Stocking Island, the Bahamas, where temperatures were relatively homogenous throughout the year, showed a dominance of both type 2, with high phenotypic variance, and type 1, a high-temperature and high-insolation specialist. Whereas the densities of Symbiodinium types 3 and 4, a high-temperature, low-insolation specialist, and a high-temperature, low-insolation generalist, remained consistently low. Predictions for Key Largo, Florida, where environmental conditions were more seasonally variable, showed the coexistence of generalists (types 2 and 4) and low densities of specialists (types 1 and 3). When elevated temperatures were input into the model, population densities in corals at Lee Stocking

  19. Predictive oncology: multidisciplinary, multi-scale in-silico modeling linking phenotype, morphology and growth

    PubMed Central

    Sanga, Sandeep; Frieboes, Hermann B.; Zheng, Xiaoming; Gatenby, Robert; Bearer, Elaine L.; Cristini, Vittorio

    2007-01-01

    Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically review advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we propose and discuss a multi-scale, i.e., from the molecular to the gross tumor scale, mathematical and computational “first-principle” approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We demonstrate that this methodology, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of

  20. Bicluster Sampled Coherence Metric (BSCM) provides an accurate environmental context for phenotype predictions

    PubMed Central

    2015-01-01

    Background Biclustering is a popular method for identifying under which experimental conditions biological signatures are co-expressed. However, the general biclustering problem is NP-hard, offering room to focus algorithms on specific biological tasks. We hypothesize that conditional co-regulation of genes is a key factor in determining cell phenotype and that accurately segregating conditions in biclusters will improve such predictions. Thus, we developed a bicluster sampled coherence metric (BSCM) for determining which conditions and signals should be included in a bicluster. Results Our BSCM calculates condition and cluster size specific p-values, and we incorporated these into the popular integrated biclustering algorithm cMonkey. We demonstrate that incorporation of our new algorithm significantly improves bicluster co-regulation scores (p-value = 0.009) and GO annotation scores (p-value = 0.004). Additionally, we used a bicluster based signal to predict whether a given experimental condition will result in yeast peroxisome induction. Using the new algorithm, the classifier accuracy improves from 41.9% to 76.1% correct. Conclusions We demonstrate that the proposed BSCM helps determine which signals ought to be co-clustered, resulting in more accurately assigned bicluster membership. Furthermore, we show that BSCM can be extended to more accurately detect under which experimental conditions the genes are co-clustered. Features derived from this more accurate analysis of conditional regulation results in a dramatic improvement in the ability to predict a cellular phenotype in yeast. The latest cMonkey is available for download at https://github.com/baliga-lab/cmonkey2. The experimental data and source code featured in this paper is available http://AitchisonLab.com/BSCM. BSCM has been incorporated in the official cMonkey release. PMID:25881257

  1. Phenotypic and biomarker evaluation of zebrafish larvae as an alternative model to predict mammalian hepatotoxicity.

    PubMed

    Verstraelen, Sandra; Peers, Bernard; Maho, Walid; Hollanders, Karen; Remy, Sylvie; Berckmans, Pascale; Covaci, Adrian; Witters, Hilda

    2016-09-01

    Zebrafish phenotypic assays have shown promise to assess human hepatotoxicity, though scoring of liver morphology remains subjective and difficult to standardize. Liver toxicity in zebrafish larvae at 5 days was assessed using gene expression as the biomarker approach, complementary to phenotypic analysis and analytical data on compound uptake. This approach aimed to contribute to improved hepatotoxicity prediction, with the goal of identifying biomarker(s) as a step towards the development of transgenic models for prioritization. Morphological effects of hepatotoxic compounds (acetaminophen, amiodarone, coumarin, methapyrilene and myclobutanil) and saccharin as the negative control were assessed after exposure in zebrafish larvae. The hepatotoxic compounds induced the expected zebrafish liver degeneration or changes in size, whereas saccharin did not have any phenotypic adverse effect. Analytical methods based on liquid chromatography-mass spectrometry were optimized to measure stability of selected compounds in exposure medium and internal concentration in larvae. All compounds were stable, except amiodarone for which precipitation was observed. There was a wide variation between the levels of compound in the zebrafish larvae with a higher uptake of amiodarone, methapyrilene and myclobutanil. Detection of hepatocyte markers (CP, CYP3A65, GC and TF) was accomplished by in situ hybridization of larvae to coumarin and myclobutanil and confirmed by real-time reverse transcription-quantitative polymerase chain reaction. Experiments showed decreased expression of all markers. Next, other liver-specific biomarkers (i.e. FABP10a and NR1H4) and apoptosis (i.e. CASP-3 A and TP53) or cytochrome P450-related (CYP2K19) and oxidoreductase activity-related (ZGC163022) genes, were screened. Links between basic mechanisms of liver injury and results of biomarker responses are described. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26946349

  2. It’s the machine that matters: Predicting gene function and phenotype from protein networks

    PubMed Central

    Wang, Peggy I.; Marcotte, Edward M.

    2010-01-01

    Increasing knowledge about the organization of proteins into complexes, systems, and pathways has led to a flowering of theoretical approaches for exploiting this knowledge in order to better learn the functions of proteins and their roles underlying phenotypic traits and diseases. Much of this body of theory has been developed and tested in model organisms, relying on their relative simplicity and genetic and biochemical tractability to accelerate the research. In this review, we discuss several of the major approaches for computationally integrating proteomics and genomics observations into integrated protein networks, then applying guilt-by-association in these networks in order to identify genes underlying traits. Recent trends in this field include a rising appreciation of the modular network organization of proteins underlying traits or mutational phenotypes, and how to exploit such protein modularity using computational approaches related to the internet search algorithm PageRank. Many protein network-based predictions have recently been experimentally confirmed in yeast, worms, plants, and mice, and several successful approaches in model organisms have been directly translated to analyze human disease, with notable recent applications to glioma and breast cancer prognosis. PMID:20637909

  3. Predicting a clinical/biochemical phenotype for PKU/MHP patients with PAH gene mutations.

    PubMed

    Kasnauskiene, J; Cimbalistiene, L; Kucinskas, V

    2008-10-01

    Phenylketonuria (PKU) and mild hyperphenylalaninemia (MHP) are allelic disorders caused by mutations in the gene encoding phenylalanine hydroxylase (PAH). In this study, a total of 218 independent PAH chromosomes (109 unrelated patients with PKU residing in Lithuania) were investigated. All 13 exons of the PAH gene of all PKU probands were scanned for DNA alterations by denaturing gradient gel electrophoresis (DGGE). In the cases of a specific DGGE pattern recognised, mutations were identified by direct fluorescent automated sequencing or by restriction enzyme digestion analysis of a relevant exons. 25 different PAH gene mutations were identified in Lithuania. We estimated a connection between individual PAH locus mutations and biochemical and metabolic phenotypes in patients in whom the mutant allele acts on its own, i.e., in functionally hemizygous patients and using the assigned value (AV) method to determine the severity of both common and rare mutant alleles, as well as to check a model to predict the combined phenotypic effect of two mutant PAH alleles. PMID:19062537

  4. Users' experiences of an emergency department patient admission predictive tool: A qualitative evaluation.

    PubMed

    Jessup, Melanie; Crilly, Julia; Boyle, Justin; Wallis, Marianne; Lind, James; Green, David; Fitzgerald, Gerard

    2016-09-01

    Emergency department overcrowding is an increasing issue impacting patients, staff and quality of care, resulting in poor patient and system outcomes. In order to facilitate better management of emergency department resources, a patient admission predictive tool was developed and implemented. Evaluation of the tool's accuracy and efficacy was complemented with a qualitative component that explicated the experiences of users and its impact upon their management strategies, and is the focus of this article. Semi-structured interviews were conducted with 15 pertinent users, including bed managers, after-hours managers, specialty department heads, nurse unit managers and hospital executives. Analysis realised dynamics of accuracy, facilitating communication and enabling group decision-making Users generally welcomed the enhanced potential to predict and plan following the incorporation of the patient admission predictive tool into their daily and weekly decision-making processes. They offered astute feedback with regard to their responses when faced with issues of capacity and communication. Participants reported an growing confidence in making informed decisions in a cultural context that is continually moving from reactive to proactive. This information will inform further patient admission predictive tool development specifically and implementation processes generally. PMID:25916833

  5. Assisted reproductive outcomes in women with different polycystic ovary syndrome phenotypes: the predictive value of anti-Müllerian hormone.

    PubMed

    Ramezanali, Fariba; Ashrafi, Mahnaz; Hemat, Mandana; Arabipoor, Arezoo; Jalali, Samaneh; Moini, Ashraf

    2016-05-01

    This cross-sectional study aimed to evaluate IVF/intracytoplasmic sperm injection (ICSI) outcomes in different polycystic ovary syndrome (PCOS) phenotypes (A, B, C and D) compared with a control group and the predictive values of serum anti-Müllerian hormone (AMH) in PCOS phenotypes for main outcomes. This study evaluated 386 PCOS women and 350 patients with male factor infertility. Women with phenotypes A and C had significantly higher concentrations of AMH than those with phenotype B (P < 0.001). Clinical pregnancy rate (CPR) in the phenotype D group (53.3%) was higher than other groups (32.5%, 26.4% and 36.8%, respectively, in phenotypes A, B and C), but not to a significant level. Multivariable regression analysis, after adjusting for women's age and body mass index, revealed that PCOS phenotypes A and B were associated with a decreased CPR compared with the control group (odds ratio [OR]: 0.46, confidence interval [CI]: 0.26-0.8, P = 0.007 and OR: 0.34, CI: 0.18-0.62, P = 0.001, respectively). It seems a combination of hyperandrogenism and chronic anovulation is associated with a negative impact on the CPR in these patients. These results demonstrated that AMH concentration is related to PCO morphology but not predictive for CPR and live birth rate. PMID:26968928

  6. Genotyping of 28 blood group alleles in blood donors from Mali: Prediction of rare phenotypes.

    PubMed

    Ba, Alhassane; Bagayoko, Seydou; Chiaroni, Jacques; Baiily, Pascal; Silvy, Monique

    2016-04-01

    We determined the frequencies of clinically relevant blood group alleles in 300 blood donors from Mali. Multiplex test based on xMAP technology was used to investigate six blood group systems (RH, KEL, MNS, FY, JK, DO, HPA) and complementary analysis were conducted for MNS and RH systems. Polymorphisms that affect the specificity of molecular tests leading to discrepant genotype results are discussed. Antigen expressions were predicted showing that 50% of donors expressed at least one traditional low prevalence antigen, and 11.6% lacked the ability to express at least one high prevalence antigen compatible with Dob-, HPA1a-, S-s-U-, Jsb-, RH:-31 and/or RH:-34 phenotypes. PMID:26616029

  7. Estrogen Metabolism and Exposure in a Genotypic-Phenotypic Model for Breast Cancer Risk Prediction

    PubMed Central

    Crooke, Philip S.; Justenhoven, Christina; Brauch, Hiltrud; Dawling, Sheila; Roodi, Nady; Higginbotham, Kathryn S. P.; Plummer, W. Dale; Schuyler, Peggy A.; Sanders, Melinda E; Page, David L.; Smith, Jeffrey R.; Dupont, William D.; Parl, Fritz F.

    2012-01-01

    Background Current models of breast cancer risk prediction do not directly reflect mammary estrogen metabolism or genetic variability in exposure to carcinogenic estrogen metabolites. Methods We developed a model that simulates the kinetic effect of genetic variants of the enzymes CYP1A1, CYP1B1, and COMT on the production of the main carcinogenic estrogen metabolite, 4-hydroxyestradiol (4-OHE2), expressed as area under the curve metric (4-OHE2-AUC). The model also incorporates phenotypic factors (age, body mass index, hormone replacement therapy, oral contraceptives, family history), which plausibly influence estrogen metabolism and the production of 4-OHE2. We applied the model to two independent, population-based breast cancer case-control groups, the German GENICA study (967 cases, 971 controls) and the Nashville Breast Cohort (NBC; 465 cases, 885 controls). Results In the GENICA study, premenopausal women at the 90th percentile of 4-OHE2-AUC among control subjects had a risk of breast cancer that was 2.30 times that of women at the 10th control 4-OHE2-AUC percentile (95% CI 1.7 – 3.2, P = 2.9 × 10−7). This relative risk was 1.89 (95% CI 1.5 – 2.4, P = 2.2 × 10−8) in postmenopausal women. In the NBC, this relative risk in postmenopausal women was 1.81 (95% CI 1.3 – 2.6, P = 7.6 × 10−4), which increased to 1.83 (95% CI 1.4 – 2.3, P = 9.5 × 10−7) when a history of proliferative breast disease was included in the model. Conclusions The model combines genotypic and phenotypic factors involved in carcinogenic estrogen metabolite production and cumulative estrogen exposure to predict breast cancer risk. Impact The estrogen carcinogenesis-based model has the potential to provide personalized risk estimates. PMID:21610218

  8. Microbial Forensics: Predicting Phenotypic Characteristics and Environmental Conditions from Large-Scale Gene Expression Profiles

    PubMed Central

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-01-01

    A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications. PMID:25774498

  9. Predicting the Effect of Surface Texture on the Qualitative Form of Prehension

    PubMed Central

    Flatters, Ian John; Otten, Loanne; Witvliet, Anna; Henson, Brian; Holt, Raymond John; Culmer, Pete; Bingham, Geoffrey Parker; Wilkie, Richard McGilchrist; Mon-Williams, Mark

    2012-01-01

    Reach-to-grasp movements change quantitatively in a lawful (i.e. predictable) manner with changes in object properties. We explored whether altering object texture would produce qualitative changes in the form of the precontact movement patterns. Twelve participants reached to lift objects from a tabletop. Nine objects were produced, each with one of three grip surface textures (high-friction, medium-friction and low-friction) and one of three widths (50 mm, 70 mm and 90 mm). Each object was placed at three distances (100 mm, 300 mm and 500 mm), representing a total of 27 trial conditions. We observed two distinct movement patterns across all trials—participants either: (i) brought their arm to a stop, secured the object and lifted it from the tabletop; or (ii) grasped the object ‘on-the-fly’, so it was secured in the hand while the arm was moving. A majority of grasps were on-the-fly when the texture was high-friction and none when the object was low-friction, with medium-friction producing an intermediate proportion. Previous research has shown that the probability of on-the-fly behaviour is a function of grasp surface accuracy constraints. A finger friction rig was used to calculate the coefficients of friction for the objects and these calculations showed that the area available for a stable grasp (the ‘functional grasp surface size’) increased with surface friction coefficient. Thus, knowledge of functional grasp surface size is required to predict the probability of observing a given qualitative form of grasping in human prehensile behaviour. PMID:22403706

  10. Genotype-phenotype correlations in 5-fluorouracil metabolism: a candidate DPYD haplotype to improve toxicity prediction.

    PubMed

    Gentile, G; Botticelli, A; Lionetto, L; Mazzuca, F; Simmaco, M; Marchetti, P; Borro, M

    2016-08-01

    5-Fluorouracil is among the most widely used anticancer drug, but a fraction of treated patients develop severe toxicity, with potentially lethal injuries. The predictive power of the available pretreatment assays, used to identify patients at risk of severe toxicity, needs improvements. This study aimed to correlate a phenotypic marker of 5-fluorouracil metabolism (the individual degradation rate of 5-fluorouracil-5-FUDR) with 15 functional polymorphisms in the dihydropyrimidine dehydrogenase gene (DPYD). Single SNP (single-nucleotide polymorphism) analysis revealed that the SNPs rs1801160, rs1801265, rs2297595 and rs3918290 (splice site variant IVS14+1G>A) were significantly associated with a decreased value of 5-FUDR, and the rs3918290 causing the larger decrease. Multi-SNP analysis showed that a three-SNP haplotype (Hap7) involving rs1801160, rs1801265 and rs2297595 causes a marked decrease in 5-FUDR, comparable to that caused by the splice site variant rs3918290, which is the main pharmacogenetic marker associated with severe fluorouracil toxicity. The similar effect played by Hap7 and by the splice site variant rs3918290 upon individual 5-FUDR suggests that Hap7 could also represent a similar determinant of fluorouracil toxicity. Haplotype assessment could improve the predictive value of DPYD genetic markers aimed at the pre-emptive identification of patients at risk of severe 5-fluorouracil toxicity.The Pharmacogenomics Journal advance online publication, 28 July 2015; doi:10.1038/tpj.2015.56. PMID:26216193

  11. Epithelial–mesenchymal transition-associated secretory phenotype predicts survival in lung cancer patients

    PubMed Central

    Reka, Ajaya Kumar; Chen, Guoan; Keshamouni, Venkateshwar G.

    2014-01-01

    In cancer cells, the process of epithelial–mesenchymal transition (EMT) confers migratory and invasive capacity, resistance to apoptosis, drug resistance, evasion of host immune surveillance and tumor stem cell traits. Cells undergoing EMT may represent tumor cells with metastatic potential. Characterizing the EMT secretome may identify biomarkers to monitor EMT in tumor progression and provide a prognostic signature to predict patient survival. Utilizing a transforming growth factor-β-induced cell culture model of EMT, we quantitatively profiled differentially secreted proteins, by GeLC-tandem mass spectrometry. Integrating with the corresponding transcriptome, we derived an EMT-associated secretory phenotype (EASP) comprising of proteins that were differentially upregulated both at protein and mRNA levels. Four independent primary tumor-derived gene expression data sets of lung cancers were used for survival analysis by the random survival forests (RSF) method. Analysis of 97-gene EASP expression in human lung adenocarcinoma tumors revealed strong positive correlations with lymph node metastasis, advanced tumor stage and histological grade. RSF analysis built on a training set (n = 442), including age, sex and stage as variables, stratified three independent lung cancer data sets into low-, medium- and high-risk groups with significant differences in overall survival. We further refined EASP to a 20 gene signature (rEASP) based on variable importance scores from RSF analysis. Similar to EASP, rEASP predicted survival of both adenocarcinoma and squamous carcinoma patients. More importantly, it predicted survival in the early-stage cancers. These results demonstrate that integrative analysis of the critical biological process of EMT provides mechanism-based and clinically relevant biomarkers with significant prognostic value. PMID:24510113

  12. Accuracy of genomic prediction using deregressed breeding values estimated from purebred and crossbred offspring phenotypes in pigs.

    PubMed

    Hidalgo, A M; Bastiaansen, J W M; Lopes, M S; Veroneze, R; Groenen, M A M; de Koning, D-J

    2015-07-01

    Genomic selection is applied to dairy cattle breeding to improve the genetic progress of purebred (PB) animals, whereas in pigs and poultry the target is a crossbred (CB) animal for which a different strategy appears to be needed. The source of information used to estimate the breeding values, i.e., using phenotypes of CB or PB animals, may affect the accuracy of prediction. The objective of our study was to assess the direct genomic value (DGV) accuracy of CB and PB pigs using different sources of phenotypic information. Data used were from 3 populations: 2,078 Dutch Landrace-based, 2,301 Large White-based, and 497 crossbreds from an F1 cross between the 2 lines. Two female reproduction traits were analyzed: gestation length (GLE) and total number of piglets born (TNB). Phenotypes used in the analyses originated from offspring of genotyped individuals. Phenotypes collected on CB and PB animals were analyzed as separate traits using a single-trait model. Breeding values were estimated separately for each trait in a pedigree BLUP analysis and subsequently deregressed. Deregressed EBV for each trait originating from different sources (CB or PB offspring) were used to study the accuracy of genomic prediction. Accuracy of prediction was computed as the correlation between DGV and the DEBV of the validation population. Accuracy of prediction within PB populations ranged from 0.43 to 0.62 across GLE and TNB. Accuracies to predict genetic merit of CB animals with one PB population in the training set ranged from 0.12 to 0.28, with the exception of using the CB offspring phenotype of the Dutch Landrace that resulted in an accuracy estimate around 0 for both traits. Accuracies to predict genetic merit of CB animals with both parental PB populations in the training set ranged from 0.17 to 0.30. We conclude that prediction within population and trait had good predictive ability regardless of the trait being the PB or CB performance, whereas using PB population(s) to predict

  13. Comparing the predictive abilities of phenotypic and marker-assisted selection methods in a biparental lettuce population

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Breeding and selection for the traits with polygenic inheritance is a challenging task that can be done by phenotypic selection, by marker-assisted selection or by genome wide selection. We tested predictive ability of four selection models in a biparental population genotyped with 95 SNP markers an...

  14. Phenotype Prediction of Pathogenic Nonsynonymous Single Nucleotide Polymorphisms in WFS1

    PubMed Central

    Qian, Xuli; Qin, Luyang; Xing, Guangqian; Cao, Xin

    2015-01-01

    Wolfram syndrome (WS) is a rare, progressive, neurodegenerative disorder that has an autosomal recessive pattern of inheritance. The gene for WS, wolfram syndrome 1 gene (WFS1), is located on human chromosome 4p16.1 and encodes a transmembrane protein. To date, approximately 230 mutations in WFS1 have been confirmed, in which nonsynonymous single nucleotide polymorphisms (nsSNPs) are the most common forms of genetic variation. Nonetheless, there is poor knowledge on the relationship between SNP genotype and phenotype in other nsSNPs of the WFS1 gene. Here, we analysed 395 nsSNPs associated with the WFS1 gene using different computational methods and identified 20 nsSNPs to be potentially pathogenic. Furthermore, to identify the amino acid distributions and significances of pathogenic nsSNPs in the protein of WFS1, its transmembrane domain was constructed by the TMHMM server, which suggested that mutations outside of the TMhelix could have more effects on protein function. The predicted pathogenic mutations for the nsSNPs of the WFS1 gene provide an excellent guide for screening pathogenic mutations. PMID:26435059

  15. Predicting complex phenotype-genotype interactions to enable yeast engineering: Saccharomyces cerevisiae as a model organism and a cell factory.

    PubMed

    Dikicioglu, Duygu; Pir, Pınar; Oliver, Stephen G

    2013-09-01

    There is an increasing use of systems biology approaches in both "red" and "white" biotechnology in order to enable medical, medicinal, and industrial applications. The intricate links between genotype and phenotype may be explained through the use of the tools developed in systems biology, synthetic biology, and evolutionary engineering. Biomedical and biotechnological research are among the fields that could benefit most from the elucidation of this complex relationship. Researchers have studied fitness extensively to explain the phenotypic impacts of genetic variations. This elaborate network of dependencies and relationships so revealed are further complicated by the influence of environmental effects that present major challenges to our achieving an understanding of the cellular mechanisms leading to healthy or diseased phenotypes or optimized production yields. An improved comprehension of complex genotype-phenotype interactions and their accurate prediction should enable us to more effectively engineer yeast as a cell factory and to use it as a living model of human or pathogen cells in intelligent screens for new drugs. This review presents different methods and approaches undertaken toward improving our understanding and prediction of the growth phenotype of the yeast Saccharomyces cerevisiae as both a model and a production organism. PMID:24031036

  16. Characteristics of Plant Essential Genes Allow for within- and between-Species Prediction of Lethal Mutant Phenotypes[OPEN

    PubMed Central

    Lloyd, John P.; Seddon, Alexander E.; Moghe, Gaurav D.; Simenc, Matthew C.; Shiu, Shin-Han

    2015-01-01

    Essential genes represent critical cellular components whose disruption results in lethality. Characteristics shared among essential genes have been uncovered in fungal and metazoan model systems. However, features associated with plant essential genes are largely unknown and the full set of essential genes remains to be discovered in any plant species. Here, we show that essential genes in Arabidopsis thaliana have distinct features useful for constructing within- and cross-species prediction models. Essential genes in A. thaliana are often single copy or derived from older duplications, highly and broadly expressed, slow evolving, and highly connected within molecular networks compared with genes with nonlethal mutant phenotypes. These gene features allowed the application of machine learning methods that predicted known lethal genes as well as an additional 1970 likely essential genes without documented phenotypes. Prediction models from A. thaliana could also be applied to predict Oryza sativa and Saccharomyces cerevisiae essential genes. Importantly, successful predictions drew upon many features, while any single feature was not sufficient. Our findings show that essential genes can be distinguished from genes with nonlethal phenotypes using features that are similar across kingdoms and indicate the possibility for translational application of our approach to species without extensive functional genomic and phenomic resources. PMID:26286535

  17. NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

    PubMed Central

    Padmanabhan, Kanchana; Shpanskaya, Yekaterina; Banfield, Jill; Scott, Kathleen; Mihelcic, James R.; Samatova, Nagiza F.

    2012-01-01

    Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to

  18. Working-memory endophenotype and dyslexia-associated genetic variant predict dyslexia phenotype.

    PubMed

    Männel, Claudia; Meyer, Lars; Wilcke, Arndt; Boltze, Johannes; Kirsten, Holger; Friederici, Angela D

    2015-10-01

    Developmental dyslexia, a severe impairment of literacy acquisition, is known to have a neurological basis and a strong genetic background. However, effects of individual genetic variations on dyslexia-associated deficits are only moderate and call for the assessment of the genotype's impact on mediating neuro-endophenotypes by the imaging genetics approach. Using voxel-based morphometry (VBM) in German participants with and without dyslexia, we investigated gray matter changes and their association with impaired phonological processing, such as reduced verbal working memory. These endophenotypical alterations were, together with dyslexia-associated genetic variations, examined on their suitability as potential predictors of dyslexia. We identified two gray matter clusters in the left posterior temporal cortex related to verbal working memory capacity. Regional cluster differences correlated with genetic risk variants in TNFRSF1B. High-genetic-risk participants exhibit a structural predominance of auditory-association areas relative to auditory-sensory areas, which may partly compensate for deficient early auditory-sensory processing stages of verbal working memory. The reverse regional predominance observed in low-genetic-risk participants may in turn reflect reliance on these early auditory-sensory processing stages. Logistic regression analysis further supported that regional gray matter differences and genetic risk interact in the prediction of individuals' diagnostic status: With increasing genetic risk, the working-memory related structural predominance of auditory-association areas relative to auditory-sensory areas classifies participants with dyslexia versus control participants. Focusing on phonological deficits in dyslexia, our findings suggest endophenotypical changes in the left posterior temporal cortex could comprise novel pathomechanisms for verbal working memory-related processes translating TNFRSF1B genotype into the dyslexia phenotype. PMID

  19. Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

    PubMed Central

    Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

    2015-01-01

    The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

  20. MR-determined metabolic phenotype of breast cancer in prediction of lymphatic spread, grade, and hormone status.

    PubMed

    Bathen, Tone F; Jensen, Line R; Sitter, Beathe; Fjösne, Hans E; Halgunset, Jostein; Axelson, David E; Gribbestad, Ingrid S; Lundgren, Steinar

    2007-08-01

    The purpose of the study was to evaluate the use of metabolic phenotype, described by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS), as a tool for prediction of histological grade, hormone status, and axillary lymphatic spread in breast cancer patients. Biopsies from breast cancer (n = 91) and adjacent non-involved tissue (n = 48) were excised from patients (n = 77) during surgery. HR MAS MR spectra of intact samples were acquired. Multivariate models relating spectral data to histological grade, lymphatic spread, and hormone status were designed. The multivariate methods applied were variable reduction by principal component analysis (PCA) or partial least-squares regression-uninformative variable elimination (PLS-UVE), and modelling by PLS, probabilistic neural network (PNN), or cascade correlation neural network. In the end, model verification by prediction of blind samples (n = 12) was performed. Validation of PNN training resulted in sensitivity and specificity ranging from 83 to 100% for all predictions. Verification of models by blind sample testing showed that hormone status was well predicted by both PNN and PLS (11 of 12 correct), lymphatic spread was best predicted by PLS (8 of 12), whereas PLS-UVE PNN was the best approach for predicting grade (9 of 12 correct). MR-determined metabolic phenotype may have a future role as a supplement for clinical decision-making-concerning adjuvant treatment and the adaptation to more individualised treatment protocols. PMID:17061040

  1. The Broad Autism Phenotype Predicts Relationship Outcomes in Newly Formed College Roommates

    ERIC Educational Resources Information Center

    Faso, Daniel J.; Corretti, Conrad A.; Ackerman, Robert A.; Sasson, Noah J.

    2016-01-01

    Although previous studies have reported that the broad autism phenotype is associated with reduced relationship quality within established relationships, understanding how this association emerges requires assessment prior to relationship development. In the present longitudinal study, college roommates with minimal familiarity prior to…

  2. IRF-1 responsiveness to IFN-γ predicts different cancer immune phenotypes

    PubMed Central

    Murtas, D; Maric, D; De Giorgi, V; Reinboth, J; Worschech, A; Fetsch, P; Filie, A; Ascierto, M L; Bedognetti, D; Liu, Q; Uccellini, L; Chouchane, L; Wang, E; Marincola, F M; Tomei, S

    2013-01-01

    Background: Several lines of evidence suggest a dichotomy between immune active and quiescent cancers, with the former associated with a good prognostic phenotype and better responsiveness to immunotherapy. Central to such dichotomy is the master regulator of the acute inflammatory process interferon regulatory factor (IRF)-1. However, it remains unknown whether the responsiveness of IRF-1 to cytokines is able to differentiate cancer immune phenotypes. Methods: IRF-1 activation was measured in 15 melanoma cell lines at basal level and after treatment with IFN-γ, TNF-α and a combination of both. Microarray analysis was used to compare transcriptional patterns between cell lines characterised by high or low IRF-1 activation. Results: We observed a strong positive correlation between IRF-1 activation at basal level and after IFN-γ and TNF-α treatment. Microarray demonstrated that three cell lines with low and three with high IRF-1 inducible translocation scores differed in the expression of 597 transcripts. Functional interpretation analysis showed mTOR and Wnt/β-cathenin as the top downregulated pathways in the cell lines with low inducible IRF-1 activation, suggesting that a low IRF-1 inducibility recapitulates a cancer phenotype already described in literature characterised by poor prognosis. Conclusion: Our findings support the central role of IRF-1 in influencing different tumour phenotypes. PMID:23807161

  3. Whole-Genome Sequencing Analysis Accurately Predicts Antimicrobial Resistance Phenotypes in Campylobacter spp.

    PubMed

    Zhao, S; Tyson, G H; Chen, Y; Li, C; Mukherjee, S; Young, S; Lam, C; Folster, J P; Whichard, J M; McDermott, P F

    2016-01-01

    The objectives of this study were to identify antimicrobial resistance genotypes for Campylobacter and to evaluate the correlation between resistance phenotypes and genotypes using in vitro antimicrobial susceptibility testing and whole-genome sequencing (WGS). A total of 114 Campylobacter species isolates (82 C. coli and 32 C. jejuni) obtained from 2000 to 2013 from humans, retail meats, and cecal samples from food production animals in the United States as part of the National Antimicrobial Resistance Monitoring System were selected for study. Resistance phenotypes were determined using broth microdilution of nine antimicrobials. Genomic DNA was sequenced using the Illumina MiSeq platform, and resistance genotypes were identified using assembled WGS sequences through blastx analysis. Eighteen resistance genes, including tet(O), blaOXA-61, catA, lnu(C), aph(2″)-Ib, aph(2″)-Ic, aph(2')-If, aph(2″)-Ig, aph(2″)-Ih, aac(6')-Ie-aph(2″)-Ia, aac(6')-Ie-aph(2″)-If, aac(6')-Im, aadE, sat4, ant(6'), aad9, aph(3')-Ic, and aph(3')-IIIa, and mutations in two housekeeping genes (gyrA and 23S rRNA) were identified. There was a high degree of correlation between phenotypic resistance to a given drug and the presence of one or more corresponding resistance genes. Phenotypic and genotypic correlation was 100% for tetracycline, ciprofloxacin/nalidixic acid, and erythromycin, and correlations ranged from 95.4% to 98.7% for gentamicin, azithromycin, clindamycin, and telithromycin. All isolates were susceptible to florfenicol, and no genes associated with florfenicol resistance were detected. There was a strong correlation (99.2%) between resistance genotypes and phenotypes, suggesting that WGS is a reliable indicator of resistance to the nine antimicrobial agents assayed in this study. WGS has the potential to be a powerful tool for antimicrobial resistance surveillance programs. PMID:26519386

  4. Predictability of Phenotype in Relation to Common β-Lactam Resistance Mechanisms in Escherichia coli and Klebsiella pneumoniae.

    PubMed

    Agyekum, Alex; Fajardo-Lubián, Alicia; Ai, Xiaoman; Ginn, Andrew N; Zong, Zhiyong; Guo, Xuejun; Turnidge, John; Partridge, Sally R; Iredell, Jonathan R

    2016-05-01

    The minimal concentration of antibiotic required to inhibit the growth of different isolates of a given species with no acquired resistance mechanisms has a normal distribution. We have previously shown that the presence or absence of transmissible antibiotic resistance genes has excellent predictive power for phenotype. In this study, we analyzed the distribution of six β-lactam antibiotic susceptibility phenotypes associated with commonly acquired resistance genes in Enterobacteriaceae in Sydney, Australia. Escherichia coli (n = 200) and Klebsiella pneumoniae (n = 178) clinical isolates, with relevant transmissible resistance genes (blaTEM, n = 33; plasmid AmpC, n = 69; extended-spectrum β-lactamase [ESBL], n = 116; and carbapenemase, n = 100), were characterized. A group of 60 isolates with no phenotypic resistance to any antibiotics tested and carrying none of the important β-lactamase genes served as comparators. The MICs for all drug-bacterium combinations had a normal distribution, varying only in the presence of additional genes relevant to the phenotype or, for ertapenem resistance in K. pneumoniae, with a loss or change in the outer membrane porin protein OmpK36. We demonstrated mutations in ompK36 or absence of OmpK36 in all isolates in which reduced susceptibility to ertapenem (MIC, >1 mg/liter) was evident. Ertapenem nonsusceptibility in K. pneumoniae was most common in the context of an OmpK36 variant with an ESBL or AmpC gene. Surveillance strategies to define appropriate antimicrobial therapies should include genotype-phenotype relationships for all major transmissible resistance genes and the characterization of mutations in relevant porins in organisms, like K. pneumoniae. PMID:26912748

  5. The broad autism phenotype predicts relationship outcomes in newly formed college roommates.

    PubMed

    Faso, Daniel J; Corretti, Conrad A; Ackerman, Robert A; Sasson, Noah J

    2016-05-01

    Although previous studies have reported that the broad autism phenotype is associated with reduced relationship quality within established relationships, understanding how this association emerges requires assessment prior to relationship development. In the present longitudinal study, college roommates with minimal familiarity prior to cohabitation (N = 162) completed the broad autism phenotype questionnaire and intermittently reported on their relationship quality and interpersonal behaviors toward their roommate over their first 10 weeks of living together. Actor-Partner Interdependence Models demonstrated that roommates mismatched on aloofness (one high and one low) had lower relationship satisfaction than those matched on it, with the interpersonal behavior of warmth mediating this association. Because relationship satisfaction remained high when both roommates were aloof, satisfaction does not appear predicated upon the presence of aloofness generally but rather reflects a product of dissimilarity in aloof profiles between roommates. In contrast, although participants reported less relationship satisfaction and commitment with roommates higher on pragmatic language abnormalities, mismatches on this broad autism phenotype trait, and on rigid personality, were less consequential. In sum, these findings suggest that complementary profiles of social motivation may facilitate relationship quality during the early course of relationship development. PMID:26014840

  6. Genomic prediction using phenotypes from pedigreed lines with no marker data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Until now genomic prediction in plant breeding has only used information from individuals that have been genotyped. In practice, information from non-genotyped relatives of genotyped individuals can be used to improve the genomic prediction accuracy. Single-step genomic prediction integrates all the...

  7. A Computational Protein Phenotype Prediction Approach to Analyze the Deleterious Mutations of Human MED12 Gene.

    PubMed

    Banaganapalli, Babajan; Mohammed, Kaleemuddin; Khan, Imran Ali; Al-Aama, Jumana Y; Elango, Ramu; Shaik, Noor Ahmad

    2016-09-01

    Genetic mutations in MED12, a subunit of Mediator complex are seen in a broad spectrum of human diseases. However, the underlying basis of how these pathogenic mutations elicit protein phenotype changes in terms of 3D structure, stability and protein binding sites remains unknown. Therefore, we aimed to investigate the structural and functional impacts of MED12 mutations, using computational methods as an alternate to traditional in vivo and in vitro approaches. The MED12 gene mutations details and their corresponding clinical associations were collected from different databases and by text-mining. Initially, diverse computational approaches were applied to categorize the different classes of mutations based on their deleterious impact to MED12. Then, protein structures for wild and mutant types built by integrative modeling were analyzed for structural divergence, solvent accessibility, stability, and functional interaction deformities. Finally, this study was able to identify that genetic mutations mapped to exon-2 region, highly conserved LCEWAV and Catenin domains induce biochemically severe amino acid changes which alters the protein phenotype as well as the stability of MED12-CYCC interactions. To better understand the deleterious nature of FS-IDs and Indels, this study asserts the utility of computational screening based on their propensity towards non-sense mediated decay. Current study findings may help to narrow down the number of MED12 mutations to be screened for mediator complex dysfunction associated genetic diseases. This study supports computational methods as a primary filter to verify the plausible impact of pathogenic mutations based on the perspective of evolution, expression and phenotype of proteins. J. Cell. Biochem. 117: 2023-2035, 2016. © 2016 Wiley Periodicals, Inc. PMID:26813965

  8. GALNT2 suppresses malignant phenotypes through IGF-1 receptor and predicts favorable prognosis in neuroblastoma

    PubMed Central

    Jeng, Yung-Ming; Lu, Meng-Yao; Yang, Yung-Li; Jou, Shiann-Tarng; Lin, Dong-Tsamn; Chang, Hsiu-Hao; Lin, Kai-Hsin; Hsu, Wen-Ming; Huang, Min-Chuan

    2014-01-01

    Aberrant expression of the simple mucin-type carbohydrate antigens such as Tn antigen is associated with malignant transformation and cancer progression. N-acetylgalactosaminyltransferase 2 (GALNT2), one of the enzymes that mediate the initial step of mucin-type O-glycosylation, is responsible for forming Tn antigen. GALNT2 is expressed differentially in nervous tissues during mouse embryogenesis; however, the role of GALNT2 in neuroblastoma (NB) remains unclear. Here we showed that increased GALNT2 expression evaluated using immunohistochemistry in NB tumor tissues correlated well with the histological grade of differentiation as well as younger age at diagnosis, early clinical stage, primary tumor originated from the extra-adrenal site, favorable INPC histology, and MYCN non-amplification. Multivariate analysis showed that GALNT2 expression is an independent prognostic factor for better survival for NB patients. GALNT2 overexpression suppressed IGF-1-induced cell growth, migration, and invasion of NB cells, whereas GALNT2 knockdown enhanced these NB phenotypes. Mechanistic investigations demonstrated that GALNT2 overexpression modified O-glycans on IGF-1R, which suppressed IGF-1-triggered IGF-1R dimerization and subsequent downstream signaling events. Conversely, these properties were reversed by GALNT2 knockdown in NB cells. Our findings suggest that GALNT2 regulates malignant phenotypes of NB cells through the IGF-1R signaling pathway, suggesting a critical role for GALNT2 in the pathogenesis of NB. PMID:25362349

  9. GALNT2 suppresses malignant phenotypes through IGF-1 receptor and predicts favorable prognosis in neuroblastoma.

    PubMed

    Ho, Wan-Ling; Chou, Chih-Hsing; Jeng, Yung-Ming; Lu, Meng-Yao; Yang, Yung-Li; Jou, Shiann-Tarng; Lin, Dong-Tsamn; Chang, Hsiu-Hao; Lin, Kai-Hsin; Hsu, Wen-Ming; Huang, Min-Chuan

    2014-12-15

    Aberrant expression of the simple mucin-type carbohydrate antigens such as Tn antigen is associated with malignant transformation and cancer progression. N-acetylgalactosaminyltransferase 2 (GALNT2), one of the enzymes that mediate the initial step of mucin-type O-glycosylation, is responsible for forming Tn antigen. GALNT2 is expressed differentially in nervous tissues during mouse embryogenesis; however, the role of GALNT2 in neuroblastoma (NB) remains unclear. Here we showed that increased GALNT2 expression evaluated using immunohistochemistry in NB tumor tissues correlated well with the histological grade of differentiation as well as younger age at diagnosis, early clinical stage, primary tumor originated from the extra-adrenal site, favorable INPC histology, and MYCN non-amplification. Multivariate analysis showed that GALNT2 expression is an independent prognostic factor for better survival for NB patients. GALNT2 overexpression suppressed IGF-1-induced cell growth, migration, and invasion of NB cells, whereas GALNT2 knockdown enhanced these NB phenotypes. Mechanistic investigations demonstrated that GALNT2 overexpression modified O-glycans on IGF-1R, which suppressed IGF-1-triggered IGF-1R dimerization and subsequent downstream signaling events. Conversely, these properties were reversed by GALNT2 knockdown in NB cells. Our findings suggest that GALNT2 regulates malignant phenotypes of NB cells through the IGF-1R signaling pathway, suggesting a critical role for GALNT2 in the pathogenesis of NB. PMID:25362349

  10. A Pharmacometabonomic Approach To Predicting Metabolic Phenotypes and Pharmacokinetic Parameters of Atorvastatin in Healthy Volunteers.

    PubMed

    Huang, Qing; Aa, Jiye; Jia, Huning; Xin, Xiaoqing; Tao, Chunlei; Liu, Linsheng; Zou, Bingjie; Song, Qinxin; Shi, Jian; Cao, Bei; Yong, Yonghong; Wang, Guangji; Zhou, Guohua

    2015-09-01

    Genetic polymorphism and environment each influence individual variability in drug metabolism and disposition. It is preferable to predict such variability, which may affect drug efficacy and toxicity, before drug administration. We examined individual differences in the pharmacokinetics of atorvastatin by applying gas chromatography-mass spectrometry-based metabolic profiling to predose plasma samples from 48 healthy volunteers. We determined the level of atorvastatin in plasma using liquid chromatography-tandem mass spectrometry. With the endogenous molecules, which showed a good correlation with pharmacokinetic parameters, a refined partial least-squares model was calculated based on predose data from a training set of 36 individuals and exhibited good predictive capability for the other 12 individuals in the prediction set. In addition, the model was successfully used to predictively classify individual pharmacokinetic responses into subgroups. Metabolites such as tryptophan, alanine, arachidonic acid, 2-hydroxybutyric acid, cholesterol, and isoleucine were indicated as candidate markers for predicting by showing better predictive capability for explaining individual differences than a conventional physiological index. These results suggest that a pharmacometabonomic approach offers the potential to predict individual differences in pharmacokinetics and therefore to facilitate individualized drug therapy. PMID:26216528

  11. Machine learning-based prediction of drug–drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties

    PubMed Central

    Cheng, Feixiong; Zhao, Zhongming

    2014-01-01

    Objective Drug–drug interactions (DDIs) are an important consideration in both drug development and clinical application, especially for co-administered medications. While it is necessary to identify all possible DDIs during clinical trials, DDIs are frequently reported after the drugs are approved for clinical use, and they are a common cause of adverse drug reactions (ADR) and increasing healthcare costs. Computational prediction may assist in identifying potential DDIs during clinical trials. Methods Here we propose a heterogeneous network-assisted inference (HNAI) framework to assist with the prediction of DDIs. First, we constructed a comprehensive DDI network that contained 6946 unique DDI pairs connecting 721 approved drugs based on DrugBank data. Next, we calculated drug–drug pair similarities using four features: phenotypic similarity based on a comprehensive drug–ADR network, therapeutic similarity based on the drug Anatomical Therapeutic Chemical classification system, chemical structural similarity from SMILES data, and genomic similarity based on a large drug–target interaction network built using the DrugBank and Therapeutic Target Database. Finally, we applied five predictive models in the HNAI framework: naive Bayes, decision tree, k-nearest neighbor, logistic regression, and support vector machine, respectively. Results The area under the receiver operating characteristic curve of the HNAI models is 0.67 as evaluated using fivefold cross-validation. Using antipsychotic drugs as an example, several HNAI-predicted DDIs that involve weight gain and cytochrome P450 inhibition were supported by literature resources. Conclusions Through machine learning-based integration of drug phenotypic, therapeutic, structural, and genomic similarities, we demonstrated that HNAI is promising for uncovering DDIs in drug development and postmarketing surveillance. PMID:24644270

  12. ISG15 predicts poor prognosis and promotes cancer stem cell phenotype in nasopharyngeal carcinoma

    PubMed Central

    Han, Ping; Wang, Hong-Bo; Liang, Fa-Ya; Feng, Guo-Kai; Zhou, Ai-Jun; Cai, Mu-Yan; Zhong, Qian; Zeng, Mu-Sheng; Huang, Xiao-Ming

    2016-01-01

    Interferon-stimulated gene 15 (ISG15), the first identified ubiquitin-like protein, is known for its anti-viral capacity. However, its role in tumorigenesis remains controversial. Here, using RNA-seq profiling analysis, we identified ISG15 as a differentially expressed gene in nasopharyngeal carcinoma (NPC) and validated its overexpression in NPC samples and cells. High ISG15 levels in NPC tissues were correlated with more frequent local recurrence and shorter overall survival and disease-free survival. ISG15 overexpression promoted a cancer stem cell phenotype in NPC cells, including increased colony and tumorsphere formation abilities, pluripotency-associated genes expression, and in vivo tumorigenicity. By contrast, knockdown of ISG15 attenuated stemness characteristics in NPC cells. Furthermore, overexpression of ISG15 increased NPC cell resistance to radiation and cisplatin (DDP) treatment. Our study demonstrates a protumor role of ISG15, and suggests that ISG15 is a prognostic predictor and a potential therapeutic target for NPC. PMID:26919245

  13. Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge

    PubMed Central

    Tarca, Adi L.; Lauria, Mario; Unger, Michael; Bilal, Erhan; Boue, Stephanie; Kumar Dey, Kushal; Hoeng, Julia; Koeppl, Heinz; Martin, Florian; Meyer, Pablo; Nandy, Preetam; Norel, Raquel; Peitsch, Manuel; Rice, Jeremy J.; Romero, Roberto; Stolovitzky, Gustavo; Talikka, Marja; Xiang, Yang; Zechner, Christoph

    2013-01-01

    Motivation: After more than a decade since microarrays were used to predict phenotype of biological samples, real-life applications for disease screening and identification of patients who would best benefit from treatment are still emerging. The interest of the scientific community in identifying best approaches to develop such prediction models was reaffirmed in a competition style international collaboration called IMPROVER Diagnostic Signature Challenge whose results we describe herein. Results: Fifty-four teams used public data to develop prediction models in four disease areas including multiple sclerosis, lung cancer, psoriasis and chronic obstructive pulmonary disease, and made predictions on blinded new data that we generated. Teams were scored using three metrics that captured various aspects of the quality of predictions, and best performers were awarded. This article presents the challenge results and introduces to the community the approaches of the best overall three performers, as well as an R package that implements the approach of the best overall team. The analyses of model performance data submitted in the challenge as well as additional simulations that we have performed revealed that (i) the quality of predictions depends more on the disease endpoint than on the particular approaches used in the challenge; (ii) the most important modeling factor (e.g. data preprocessing, feature selection and classifier type) is problem dependent; and (iii) for optimal results datasets and methods have to be carefully matched. Biomedical factors such as the disease severity and confidence in diagnostic were found to be associated with the misclassification rates across the different teams. Availability: The lung cancer dataset is available from Gene Expression Omnibus (accession, GSE43580). The maPredictDSC R package implementing the approach of the best overall team is available at www.bioconductor.org or http://bioinformaticsprb.med.wayne.edu/. Contact

  14. Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses.

    PubMed

    Neher, Richard A; Bedford, Trevor; Daniels, Rodney S; Russell, Colin A; Shraiman, Boris I

    2016-03-22

    Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny. PMID:26951657

  15. Does individual variation in metabolic phenotype predict fish behaviour and performance?

    PubMed

    Metcalfe, N B; Van Leeuwen, T E; Killen, S S

    2016-01-01

    There is increasing interest in documenting and explaining the existence of marked intraspecific variation in metabolic rate in animals, with fishes providing some of the best-studied examples. After accounting for variation due to other factors, there can typically be a two to three-fold variation among individual fishes for both standard and maximum metabolic rate (SMR and MMR). This variation is reasonably consistent over time (provided that conditions remain stable), and its underlying causes may be influenced by both genes and developmental conditions. In this paper, current knowledge of the extent and causes of individual variation in SMR, MMR and aerobic scope (AS), collectively its metabolic phenotype, is reviewed and potential links among metabolism, behaviour and performance are described. Intraspecific variation in metabolism has been found to be related to other traits: fishes with a relatively high SMR tend to be more dominant and grow faster in high food environments, but may lose their advantage and are more prone to risk-taking when conditions deteriorate. In contrast to the wide body of research examining links between SMR and behavioural traits, very little work has been directed towards understanding the ecological consequences of individual variation in MMR and AS. Although AS can differ among populations of the same species in response to performance demands, virtually nothing is known about the effects of AS on individual behaviours such as those associated with foraging or predator avoidance. Further, while factors such as food availability, temperature, hypoxia and the fish's social environment are known to alter resting and MMRs in fishes, there is a paucity of studies examining how these effects vary among individuals, and how this variation relates to behaviour. Given the observed links between metabolism and measures of performance, understanding the metabolic responses of individuals to changing environments will be a key area for

  16. Prediction and Analysis of Canonical EF Hand Loop and Qualitative Estimation of Ca2+ Binding Affinity

    PubMed Central

    Mazumder, Mohit; Padhan, Narendra; Bhattacharya, Alok; Gourinath, Samudrala

    2014-01-01

    The diversity of functions carried out by EF hand-containing calcium-binding proteins is due to various interactions made by these proteins as well as the range of affinity levels for Ca2+ displayed by them. However, accurate methods are not available for prediction of binding affinities. Here, amino acid patterns of canonical EF hand sequences obtained from available crystal structures were used to develop a classifier that distinguishes Ca2+-binding loops and non Ca2+-binding regions with 100% accuracy. To investigate further, we performed a proteome-wide prediction for E. histolytica, and classified known EF-hand proteins. We compared our results with published methods on the E. histolytica proteome scan, and demonstrated our method to be more specific and accurate for predicting potential canonical Ca2+-binding loops. Furthermore, we annotated canonical EF-hand motifs and classified them based on their Ca2+-binding affinities using support vector machines. Using a novel method generated from position-specific scoring metrics and then tested against three different experimentally derived EF-hand-motif datasets, predictions of Ca2+-binding affinities were between 87 and 90% accurate. Our results show that the tool described here is capable of predicting Ca2+-binding affinity constants of EF-hand proteins. The web server is freely available at http://202.41.10.46/calb/index.html. PMID:24760183

  17. Conserved synteny at the protein family level reveals genes underlying Shewanella species cold tolerance and predicts their novel phenotypes

    SciTech Connect

    Karpinets, Tatiana V.; Obraztsova, Anna; Wang, Yanbing; Schmoyer, Denise D.; Kora, Guruprasad; Park, Byung H.; Serres, Margrethe H.; Romine, Margaret F.; Land, Miriam L.; Kothe, Terence B.; Fredrickson, Jim K.; Nealson, Kenneth H.; Uberbacher, Edward

    2010-03-01

    Bacteria of the genus Shewanella can thrive in different environments and demonstrate significant variability in their metabolic and ecophysiological capabilities including cold and salt tolerance. Genomic characteristics underlying this variability across species are largely unknown. In this study we address the problem by a comparison of the physiological, metabolic and genomic characteristics of 19 sequenced Shewanella species. We have employed two novel approaches based on association of a phenotypic trait with the number of the trait-specific protein families (Pfam domains) and on the conservation of synteny (order in the genome) of the trait-related genes. Our first approach is top-down and involves experimental evaluation and quantification of the species’ cold tolerance followed by identification of the correlated Pfam domains and genes with a conserved synteny. The second, a bottom-up approach, predicts novel phenotypes of the species by calculating profiles of each Pfam domain among their genomes and following pair-wise correlation of the profiles and their network clustering. Using the first approach we find a link between cold and salt tolerance of the species and the presence in the genome of a Na+/H+ antiporter gene cluster. Other cold tolerance related genes includes peptidases, chemotaxis sensory transducer proteins, a cysteine exporter, and helicases. Using the bottom-up approach we found several novel phenotypes in the newly sequenced Shewanella species, including degradation of aromatic compounds by an aerobic hybrid pathway in S. woodyi, degradation of ethanolamine by S. benthica, and propanediol degradation by S. putrefaciens CN32 and S. sp. W3-18-1.

  18. Type and level of RMRP functional impairment predicts phenotype in the cartilage hair hypoplasia-anauxetic dysplasia spectrum.

    PubMed

    Thiel, Christian T; Mortier, Geert; Kaitila, Ilkka; Reis, André; Rauch, Anita

    2007-09-01

    Mutations in the RMRP gene lead to a wide spectrum of autosomal recessive skeletal dysplasias, ranging from the milder phenotypes metaphyseal dysplasia without hypotrichosis and cartilage hair hypoplasia (CHH) to the severe anauxetic dysplasia (AD). This clinical spectrum includes different degrees of short stature, hair hypoplasia, defective erythrogenesis, and immunodeficiency. The RMRP gene encodes the untranslated RNA component of the mitochondrial RNA-processing ribonuclease, RNase MRP. We recently demonstrated that mutations may affect both messenger RNA (mRNA) and ribosomal RNA (rRNA) cleavage and thus cell-cycle regulation and protein synthesis. To investigate the genotype-phenotype correlation, we analyzed the position and the functional effect of 13 mutations in patients with variable features of the CHH-AD spectrum. Those at the end of the spectrum include a novel patient with anauxetic dysplasia who was compound heterozygous for the null mutation g.254_263delCTCAGCGCGG and the mutation g.195C-->T, which was previously described in patients with milder phenotypes. Mapping of nucleotide conservation to the two-dimensional structure of the RMRP gene revealed that disease-causing mutations either affect evolutionarily conserved nucleotides or are likely to alter secondary structure through mispairing in stem regions. In vitro testing of RNase MRP multiprotein-specific mRNA and rRNA cleavage of different mutations revealed a strong correlation between the decrease in rRNA cleavage in ribosomal assembly and the degree of bone dysplasia, whereas reduced mRNA cleavage, and thus cell-cycle impairment, predicts the presence of hair hypoplasia, immunodeficiency, and hematological abnormalities and thus increased cancer risk. PMID:17701897

  19. Phenotypes of the ovarian follicular basal lamina predict developmental competence of oocytes

    PubMed Central

    Irving-Rodgers, Helen F.; Morris, Stephanie; Collett, Rachael A.; Peura, Teija T.; Davy, Margaret; Thompson, Jeremy G.; Mason, Helen D.; Rodgers, Raymond J.

    2009-01-01

    BACKGROUND The ovarian follicular basal lamina underlies the epithelial membrana granulosa and maintains the avascular intra-follicular compartment. Additional layers of basal lamina occur in a number of pathologies, including pili annulati and diabetes. We previously found additional layers of follicular basal lamina in a significant percentage of healthy bovine follicles. We wished to determine if this phenomenon existed in humans, and if it was related to oocyte function in the bovine. METHODS AND RESULTS We examined follicles from human ovaries (n = 18) by electron microscopy and found that many follicles had additional layers of basal lamina. Oocytes (n = 222) from bovine follicles with normal or unusual basal laminas were isolated and their ability to undergo in vitro maturation, fertilization and culture to blastocyst was compared. Healthy bovine follicles with a single layer of basal lamina had oocytes with significantly (P < 0.01) greater developmental competence than healthy follicles with additional layers of follicular basal lamina (65% versus 28%). CONCLUSIONS These findings provide direct evidence that the phenotype of the follicular basal lamina is related to oocyte competence. PMID:19095662

  20. Lineage-specific STAT5 target gene activation in hematopoietic progenitor cells predicts the FLT3(+)-mediated leukemic phenotype.

    PubMed

    Müller, T A; Grundler, R; Istvanffy, R; Rudelius, M; Hennighausen, L; Illert, A L; Duyster, J

    2016-08-01

    Mutations that activate FMS-like tyrosine kinase 3 (FLT3) are frequent occurrences in acute myeloid leukemia. Two distinct types of mutations have been described: internal duplication of the juxtamembranous domain (ITD) and point mutations of the tyrosine kinase domain (TKD). Although both mutations lead to constitutive FLT3 signaling, only FLT3-ITD strongly activates signal transducer and activator of transcription 5 (STAT5). In a murine transplantation model, FLT3-ITD induces a myeloproliferative neoplasm, whereas FLT3-TKD leads to a lymphoid malignancy with significantly longer latency. Here we report that the presence of STAT5 is critical for the development of a myeloproliferative disease by FLT3-ITD in mice. Deletion of Stat5 in FLT3-ITD-induced leukemogenesis leads not only to a significantly longer survival (82 vs 27 days) of the diseased mice, but also to an immunophenotype switch with expansion of the lymphoid cell compartment. Interestingly, we were able to show differential STAT5 activation in FLT3-ITD(+) myeloid and lymphoid murine progenitors. STAT5 target genes such as Oncostatin M were highly expressed in FLT3-ITD(+) myeloid but not in FLT3-ITD(+) lymphoid progenitor cells. Strikingly, FLT3-TKD expression in combination with Oncostatin M is sufficient to reverse the phenotype to a myeloproliferative disease in FLT3-TKD mice. Thus, lineage-specific STAT5 activation in hematopoietic progenitor cells predicts the FLT3(+)-mediated leukemic phenotype in mice. PMID:27046463

  1. A testosterone-related structural brain phenotype predicts aggressive behavior from childhood to adulthood.

    PubMed

    Nguyen, Tuong-Vi; McCracken, James T; Albaugh, Matthew D; Botteron, Kelly N; Hudziak, James J; Ducharme, Simon

    2016-01-01

    Structural covariance, the examination of anatomic correlations between brain regions, has emerged recently as a valid and useful measure of developmental brain changes. Yet the exact biological processes leading to changes in covariance, and the relation between such covariance and behavior, remain largely unexplored. The steroid hormone testosterone represents a compelling mechanism through which this structural covariance may be developmentally regulated in humans. Although steroid hormone receptors can be found throughout the central nervous system, the amygdala represents a key target for testosterone-specific effects, given its high density of androgen receptors. In addition, testosterone has been found to impact cortical thickness (CTh) across the whole brain, suggesting that it may also regulate the structural relationship, or covariance, between the amygdala and CTh. Here, we examined testosterone-related covariance between amygdala volumes and whole-brain CTh, as well as its relationship to aggression levels, in a longitudinal sample of children, adolescents, and young adults 6-22 years old. We found: (1) testosterone-specific modulation of the covariance between the amygdala and medial prefrontal cortex (mPFC); (2) a significant relationship between amygdala-mPFC covariance and levels of aggression; and (3) mediation effects of amygdala-mPFC covariance on the relationship between testosterone and aggression. These effects were independent of sex, age, pubertal stage, estradiol levels and anxious-depressed symptoms. These findings are consistent with prior evidence that testosterone targets the neural circuits regulating affect and impulse regulation, and show, for the first time in humans, how androgen-dependent organizational effects may regulate a very specific, aggression-related structural brain phenotype from childhood to young adulthood. PMID:26431805

  2. Phenotypic side effects prediction by optimizing correlation with chemical and target profiles of drugs.

    PubMed

    Kanji, Rakesh; Sharma, Abhinav; Bagler, Ganesh

    2015-11-01

    Despite technological progresses and improved understanding of biological systems, discovery of novel drugs is an inefficient, arduous and expensive process. Research and development cost of drugs is unreasonably high, largely attributed to the high attrition rate of candidate drugs due to adverse drug reactions. Computational methods for accurate prediction of drug side effects, rooted in empirical data of drugs, have the potential to enhance the efficacy of the drug discovery process. Identification of features critical for specifying side effects would facilitate efficient computational procedures for their prediction. We devised a generalized ordinary canonical correlation model for prediction of drug side effects based on their chemical properties as well as their target profiles. While the former is based on 2D and 3D chemical features, the latter enumerates a systems-level property of drugs. We find that the model incorporating chemical features outperforms that incorporating target profiles. Furthermore we identified the 2D and 3D chemical properties that yield best results, thereby implying their relevance in specifying adverse drug reactions. PMID:26252576

  3. Broad Autism Phenotype in Typically Developing Children Predicts Performance on an Eye-Tracking Measure of Joint Attention

    PubMed Central

    Serlin, Gayle C.; Siller, Michael

    2015-01-01

    We examined visual attention allocation during a set of social videos that are intended to elicit the coordination of attention with another person, compared to a control condition. Deficits in joint attention are a characteristic of young children with autism spectrum disorder (ASD). Participants included a diverse sample of 50 typically developing school-aged children between 3 and 9 years of age (M = 6:3, SD = 1:8). Results demonstrated that gaze allocation differed significantly between the experimental and control condition. Further, individual differences in gaze allocation were significantly predicted by a parent-report measure evaluating features of the broad autism phenotype. This study contributes to a research program that aims to develop and validate an endophenotype measure of ASD. PMID:22847297

  4. When Are Qualitative Testing Results Sufficient To Predict a Reduction in Illnesses in a Microbiological Food Safety Risk Assessment?

    PubMed

    Ebel, Eric D; Williams, Michael S

    2015-08-01

    Process models that include the myriad pathways that pathogen-contaminated food may traverse before consumption and the dose-response function to relate exposure to likelihood of illness may represent a "gold standard" for quantitative microbial risk assessment. Nevertheless, simplifications that rely on measuring the change in contamination occurrence of a raw food at the end of production may provide reasonable approximations of the effects measured by a process model. In this study, we parameterized three process models representing different product-pathogen pairs (i.e., chicken-Salmonella, chicken-Campylobacter, and beef-E. coli O157:H7) to compare with predictions based on qualitative testing of the raw product before consideration of mixing, partitioning, growth, attenuation, or dose-response processes. The results reveal that reductions in prevalence generated from qualitative testing of raw finished product usually underestimate the reduction in likelihood of illness for a population of consumers. Qualitative microbial testing results depend on the test's limit of detection. The negative bias is greater for limits of detection that are closer to the center of the contamination distribution and becomes less as the limit of detection is moved further into the right tail of the distribution. Nevertheless, a positive bias can result when the limit of detection refers to very high contamination levels. Changes in these high levels translate to larger consumed doses for which the slope of the dose-response function is smaller compared with the larger slope associated with smaller doses. Consequently, in these cases, a proportional reduction in prevalence of contamination results in a less than proportional reduction in probability of illness. The magnitudes of the biases are generally less for nonscalar (versus scalar) adjustments to the distribution. PMID:26219357

  5. Predicting Ancestral Segmentation Phenotypes from Drosophila to Anopheles Using In Silico Evolution.

    PubMed

    Rothschild, Jeremy B; Tsimiklis, Panagiotis; Siggia, Eric D; François, Paul

    2016-05-01

    Molecular evolution is an established technique for inferring gene homology but regulatory DNA turns over so rapidly that inference of ancestral networks is often impossible. In silico evolution is used to compute the most parsimonious path in regulatory space for anterior-posterior patterning linking two Dipterian species. The expression pattern of gap genes has evolved between Drosophila (fly) and Anopheles (mosquito), yet one of their targets, eve, has remained invariant. Our model predicts that stripe 5 in fly disappears and a new posterior stripe is created in mosquito, thus eve stripe modules 3+7 and 4+6 in fly are homologous to 3+6 and 4+5 in mosquito. We can place Clogmia on this evolutionary pathway and it shares the mosquito homologies. To account for the evolution of the other pair-rule genes in the posterior we have to assume that the ancestral Dipterian utilized a dynamic method to phase those genes in relation to eve. PMID:27227405

  6. Predicting Ancestral Segmentation Phenotypes from Drosophila to Anopheles Using In Silico Evolution

    PubMed Central

    Rothschild, Jeremy B.; Tsimiklis, Panagiotis; Siggia, Eric D.; François, Paul

    2016-01-01

    Molecular evolution is an established technique for inferring gene homology but regulatory DNA turns over so rapidly that inference of ancestral networks is often impossible. In silico evolution is used to compute the most parsimonious path in regulatory space for anterior-posterior patterning linking two Dipterian species. The expression pattern of gap genes has evolved between Drosophila (fly) and Anopheles (mosquito), yet one of their targets, eve, has remained invariant. Our model predicts that stripe 5 in fly disappears and a new posterior stripe is created in mosquito, thus eve stripe modules 3+7 and 4+6 in fly are homologous to 3+6 and 4+5 in mosquito. We can place Clogmia on this evolutionary pathway and it shares the mosquito homologies. To account for the evolution of the other pair-rule genes in the posterior we have to assume that the ancestral Dipterian utilized a dynamic method to phase those genes in relation to eve. PMID:27227405

  7. Attention deficits predict phenotypic outcomes in syndrome-specific and domain-specific ways.

    PubMed

    Cornish, K; Steele, A; Monteiro, C Rondinelli Cobra; Karmiloff-Smith, A; Scerif, G

    2012-01-01

    Attentional difficulties, both at home and in the classroom, are reported across a number of neurodevelopmental disorders. However, exactly how attention influences early socio-cognitive learning remains unclear. We addressed this question both concurrently and longitudinally in a cross-syndrome design, with respect to the communicative domain of vocabulary and to the cognitive domain of early literacy, and then extended the analysis to social behavior. Participants were young children (aged 4-9 years at Time 1) with either Williams syndrome (WS, N = 26) or Down syndrome (DS, N = 26) and typically developing controls (N = 103). Children with WS displayed significantly greater attentional deficits (as indexed by teacher report of behavior typical of attention deficit hyperactivity disorder (ADHD) than children with DS, but both groups had greater attentional problems than the controls. Despite their attention differences, children with DS and those with WS were equivalent in their cognitive abilities of reading single words, both at Time 1 and 12 months later, at Time 2, although they differed in their early communicative abilities in terms of vocabulary. Greater ADHD-like behaviors predicted poorer subsequent literacy for children with DS, but not for children with WS, pointing to syndrome-specific attentional constraints on specific aspects of early development. Overall, our findings highlight the need to investigate more precisely whether and, if so, how, syndrome-specific profiles of behavioral difficulties constrain learning and socio-cognitive outcomes across different domains. PMID:22798954

  8. Molecular value predictions: associations with beef quality, carcass, production, behavior, and efficiency phenotypes in Brahman cattle.

    PubMed

    Greenwood, P L; Cafe, L M; McIntyre, B L; Geesink, G H; Thompson, J M; Polkinghorne, R; Pethick, D W; Robinson, D L

    2013-12-01

    Data from 2 previously published experiments, New South Wales (NSW; n = 161) and Western Australia (WA; n = 135), were used to test molecular value predictions (MVP), generated from commercially available gene markers, on economically important traits of Bos indicus (Brahman) cattle. Favorable tenderness MVP scores were associated with reduced shear force values of strip loin (LM) steaks aged 7 d from Achilles-hung carcasses (P ≤ 0.06), as well as steaks aged 1 (P ≤ 0.08) or 7 d (P ≤ 0.07) from carcasses hung from the pelvis (tenderstretch). Favorable tenderness MVP scores were also associated with improved consumer tenderness ratings for strip loin steaks aged 7 d and either Achilles hung (P ≤ 0.006) or tenderstretched (P ≤ 0.07). Similar results were observed in NSW for rump (top butt; gluteus medius) steaks, with favorable tenderness MVP scores associated with more tender (P = 0.006) and acceptable (P = 0.008) beef. Favorable marbling MVP scores were associated with improved (P ≤ 0.021) marbling scores and intramuscular fat (IMF) content in the NSW experiment, despite low variation in marbling in the Brahman cattle. For the WA experiment, however, there were no (P ≥ 0.71) relationships between marbling MVP and marbling scores or IMF content. Although residual (net) feed intake (RFI) was not associated (P = 0.63) with the RFI (feed efficiency) MVP, the RFI MVP was adversely associated with LM tenderness and acceptability of 7-d-aged Achilles-hung carcasses in NSW (P ≤ 0.031) and WA (P ≤ 0.037). Some other relationships and trends were noted between the MVP and the other traits, but few reached statistical significance, and none were evident in both experiments. Results from this study provide evidence to support the use of the tenderness MVP. The value of the marbling MVP, which was associated with marbling in only 1 herd, warrants further evaluation; however, there appears to be no evidence to support use of the RFI MVP in Brahman cattle. PMID

  9. Analysis of the Reasons for Non-Uptake of Predictive Testing for Huntington's Disease in Spain: A Qualitative Study.

    PubMed

    Rivera-Navarro, Jesús; Cubo, Esther; Mariscal, Natividad

    2015-12-01

    Children of persons affected by Huntington's disease (HD) have a 50% chance of inheriting the disease. Genetic testing in Spain is offered to individuals (presymptomatic test) or mothers of fetuses (prenatal) who run the risk of suffering from HD. The objective of this study is to analyze the factors that influence the decisions of adult children of persons affected with HD regarding predictive testing. A qualitative research methodology was used involving 4 focus groups (FGs) made up of adult children of persons with HD in different cities in Spain. The results of the study showed that over half of the focus group participants were inclined to decline genetic testing. The main explanatory determinants for taking or not taking the predictive test are: Maturity of the individual at risk, which was directly related to age; Ability to cope with a positive test result; Experience of living with HD sufferers; Information about testing and psychological support; Attitude of the family; Social visibility of genetic testing; Personality and temperament of each subject at risk of HD. These results imply that these factors should be analyzed in more detail in quantitative studies in order to help the Spanish Department of Health understand why some children of parents with HD decline genetic testing, so that they may and apply these data when creating specific policy regarding this issue. PMID:25921556

  10. The common occurrence of epistasis in the determination of human pigmentation and its impact on DNA-based pigmentation phenotype prediction.

    PubMed

    Pośpiech, Ewelina; Wojas-Pelc, Anna; Walsh, Susan; Liu, Fan; Maeda, Hitoshi; Ishikawa, Takaki; Skowron, Małgorzata; Kayser, Manfred; Branicki, Wojciech

    2014-07-01

    The role of epistatic effects in the determination of complex traits is often underlined but its significance in the prediction of pigmentation phenotypes has not been evaluated so far. The prediction of pigmentation from genetic data can be useful in forensic science to describe the physical appearance of an unknown offender, victim, or missing person who cannot be identified via conventional DNA profiling. Available forensic DNA prediction systems enable the reliable prediction of several eye and hair colour categories. However, there is still space for improvement. Here we verified the association of 38 candidate DNA polymorphisms from 13 genes and explored the extent to which interactions between them may be involved in human pigmentation and their impact on forensic DNA prediction in particular. The model-building set included 718 Polish samples and the model-verification set included 307 independent Polish samples and additional 72 samples from Japan. In total, 29 significant SNP-SNP interactions were found with 5 of them showing an effect on phenotype prediction. For predicting green eye colour, interactions between HERC2 rs12913832 and OCA2 rs1800407 as well as TYRP1 rs1408799 raised the prediction accuracy expressed by AUC from 0.667 to 0.697 and increased the prediction sensitivity by >3%. Interaction between MC1R 'R' variants and VDR rs731236 increased the sensitivity for light skin by >1% and by almost 3% for dark skin colour prediction. Interactions between VDR rs1544410 and TYR rs1042602 as well as between MC1R 'R' variants and HERC2 rs12913832 provided an increase in red/non-red hair prediction accuracy from an AUC of 0.902-0.930. Our results thus underline epistasis as a common phenomenon in human pigmentation genetics and demonstrate that considering SNP-SNP interactions in forensic DNA phenotyping has little impact on eye, hair and skin colour prediction. PMID:24681889

  11. Phenotyping of UGT1A1 Activity Using Raltegravir Predicts Pharmacokinetics and Toxicity of Irinotecan in FOLFIRI

    PubMed Central

    Lee, Lawrence Soon-U; Seng, Kok-Yong; Wang, Ling-Zhi; Yong, Wei-Peng; Hee, Kim-Hor; Soh, Thomas I.; Wong, Andrea; Cheong, Pei F.; Soong, Richie; Sapari, Nur S.; Soo, Ross; Fan, Lu; Lee, Soo-Chin; Goh, Boon C.

    2016-01-01

    Background Irinotecan toxicity correlates with UGT1A1 activity. We explored whether phenotyping UGT1A1 using a probe approach works better than current genotyping methods. Methods Twenty-four Asian cancer patients received irinotecan as part of the FOLFIRI regimen. Subjects took raltegravir 400 mg orally and intravenous midazolam 1 mg. Pharmacokinetic analyses were performed using WinNonLin and NONMEM. Genomic DNA was isolated and screened for the known genetic variants in UGT1A1 and CYP3A4/5. Results SN-38G/SN-38 AUC ratio correlated well with Raltegravir glucuronide/ Raltegravir AUC ratio (r = 0.784 p<0.01). Midazolam clearance correlated well with irinotecan clearance (r = 0.563 p<0.01). SN-38 AUC correlated well with Log10Nadir Absolute Neutrophil Count (ANC) (r = -0.397 p<0.05). Significant correlation was found between nadir ANC and formation rate constant of raltegravir glucuronide (r = 0.598, P<0.005), but not UGT1A1 genotype. Conclusion Raltegravir glucuronide formation is a good predictor of nadir ANC, and can predict neutropenia in East Asian patients. Prospective studies with dose adjustments should be done to develop raltegravir as a probe to optimize irinotecan therapy. Trial Registration Clinicaltrials.gov NCT00808184 PMID:26808671

  12. Expanding the clinical spectrum of the 'HDAC8-phenotype' - implications for molecular diagnostics, counseling and risk prediction.

    PubMed

    Parenti, I; Gervasini, C; Pozojevic, J; Wendt, K S; Watrin, E; Azzollini, J; Braunholz, D; Buiting, K; Cereda, A; Engels, H; Garavelli, L; Glazar, R; Graffmann, B; Larizza, L; Lüdecke, H J; Mariani, M; Masciadri, M; Pié, J; Ramos, F J; Russo, S; Selicorni, A; Stefanova, M; Strom, T M; Werner, R; Wierzba, J; Zampino, G; Gillessen-Kaesbach, G; Wieczorek, D; Kaiser, F J

    2016-05-01

    Cornelia de Lange syndrome (CdLS) is a clinically heterogeneous disorder characterized by typical facial dysmorphism, cognitive impairment and multiple congenital anomalies. Approximately 75% of patients carry a variant in one of the five cohesin-related genes NIPBL, SMC1A, SMC3, RAD21 and HDAC8. Herein we report on the clinical and molecular characterization of 11 patients carrying 10 distinct variants in HDAC8. Given the high number of variants identified so far, we advise sequencing of HDAC8 as an indispensable part of the routine molecular diagnostic for patients with CdLS or CdLS-overlapping features. The phenotype of our patients is very broad, whereas males tend to be more severely affected than females, who instead often present with less canonical CdLS features. The extensive clinical variability observed in the heterozygous females might be at least partially associated with a completely skewed X-inactivation, observed in seven out of eight female patients. Our cohort also includes two affected siblings whose unaffected mother was found to be mosaic for the causative mutation inherited to both affected children. This further supports the urgent need for an integration of highly sensitive sequencing technology to allow an appropriate molecular diagnostic, genetic counseling and risk prediction. PMID:26671848

  13. Kernel-based variance component estimation and whole-genome prediction of pre-corrected phenotypes and progeny tests for dairy cow health traits

    PubMed Central

    Morota, Gota; Boddhireddy, Prashanth; Vukasinovic, Natascha; Gianola, Daniel; DeNise, Sue

    2014-01-01

    Prediction of complex trait phenotypes in the presence of unknown gene action is an ongoing challenge in animals, plants, and humans. Development of flexible predictive models that perform well irrespective of genetic and environmental architectures is desirable. Methods that can address non-additive variation in a non-explicit manner are gaining attention for this purpose and, in particular, semi-parametric kernel-based methods have been applied to diverse datasets, mostly providing encouraging results. On the other hand, the gains obtained from these methods have been smaller when smoothed values such as estimated breeding value (EBV) have been used as response variables. However, less emphasis has been placed on the choice of phenotypes to be used in kernel-based whole-genome prediction. This study aimed to evaluate differences between semi-parametric and parametric approaches using two types of response variables and molecular markers as inputs. Pre-corrected phenotypes (PCP) and EBV obtained for dairy cow health traits were used for this comparison. We observed that non-additive genetic variances were major contributors to total genetic variances in PCP, whereas additivity was the largest contributor to variability of EBV, as expected. Within the kernels evaluated, non-parametric methods yielded slightly better predictive performance across traits relative to their additive counterparts regardless of the type of response variable used. This reinforces the view that non-parametric kernels aiming to capture non-linear relationships between a panel of SNPs and phenotypes are appealing for complex trait prediction. However, like past studies, the gain in predictive correlation was not large for either PCP or EBV. We conclude that capturing non-additive genetic variation, especially epistatic variation, in a cross-validation framework remains a significant challenge even when it is important, as seems to be the case for health traits in dairy cows. PMID:24715901

  14. IDEPI: Rapid Prediction of HIV-1 Antibody Epitopes and Other Phenotypic Features from Sequence Data Using a Flexible Machine Learning Platform

    PubMed Central

    Hepler, N. Lance; Scheffler, Konrad; Weaver, Steven; Murrell, Ben; Richman, Douglas D.; Burton, Dennis R.; Poignard, Pascal; Smith, Davey M.; Kosakovsky Pond, Sergei L.

    2014-01-01

    Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals — a cure and a vaccine – remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes) for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab), determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license), documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi. PMID:25254639

  15. Changes throughout lactation in phenotypic and genetic correlations between methane emissions and milk fatty acid contents predicted from milk mid-infrared spectra.

    PubMed

    Vanrobays, M-L; Bastin, C; Vandenplas, J; Hammami, H; Soyeurt, H; Vanlierde, A; Dehareng, F; Froidmont, E; Gengler, N

    2016-09-01

    The aim of this study was to estimate phenotypic and genetic correlations between methane production (Mp) and milk fatty acid contents of first-parity Walloon Holstein cows throughout lactation. Calibration equations predicting daily Mp (g/d) and milk fatty acid contents (g/100 dL of milk) were applied on milk mid-infrared spectra related to Walloon milk recording. A total of 241,236 predictions of Mp and milk fatty acids were used. These data were collected between 5 and 305 d in milk in 33,555 first-parity Holstein cows from 626 herds. Pedigree data included 109,975 animals. Bivariate (i.e., Mp and a fatty acid trait) random regression test-day models were developed to estimate phenotypic and genetic parameters of Mp and milk fatty acids. Individual short-chain fatty acids (SCFA) and groups of saturated fatty acids, SCFA, and medium-chain fatty acids showed positive phenotypic and genetic correlations with Mp (from 0.10 to 0.16 and from 0.23 to 0.30 for phenotypic and genetic correlations, respectively), whereas individual long-chain fatty acids (LCFA), and groups of LCFA, monounsaturated fatty acids, and unsaturated fatty acids showed null to positive phenotypic and genetic correlations with Mp (from -0.03 to 0.13 and from -0.02 to 0.32 for phenotypic and genetic correlations, respectively). However, these correlations changed throughout lactation. First, de novo individual and group fatty acids (i.e., C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, SCFA group) showed low phenotypic or genetic correlations (or both) in early lactation and higher at the end of lactation. In contrast, phenotypic and genetic correlations between Mp and C16:0, which could be de novo synthetized or derived from blood lipids, were more stable during lactation. This fatty acid is the most abundant fatty acid of the saturated fatty acid and medium-chain fatty acid groups of which correlations with Mp showed the same pattern across lactation. Phenotypic and genetic correlations between Mp and C17

  16. Refinement of the prediction of N-acetyltransferase 2 (NAT2) phenotypes with respect to enzyme activity and urinary bladder cancer risk.

    PubMed

    Selinski, Silvia; Blaszkewicz, Meinolf; Ickstadt, Katja; Hengstler, Jan G; Golka, Klaus

    2013-12-01

    Polymorphisms of N-acetyltransferase 2 (NAT2) are well known to modify urinary bladder cancer risk as well as efficacy and toxicity of pharmaceuticals via reduction in the enzyme's acetylation capacity. Nevertheless, the discussion about optimal NAT2 phenotype prediction, particularly differentiation between different degrees of slow acetylation, is still controversial. Therefore, we investigated the impact of single nucleotide polymorphisms and their haplotypes on slow acetylation in vivo and on bladder cancer risk. For this purpose, we used a study cohort of 1,712 bladder cancer cases and 2,020 controls genotyped for NAT2 by RFLP-PCR and for the tagSNP rs1495741 by TaqMan(®) assay. A subgroup of 344 individuals was phenotyped by the caffeine test in vivo. We identified an 'ultra-slow' acetylator phenotype based on combined *6A/*6A, *6A/*7B and *7B/*7B genotypes containing the homozygous minor alleles of C282T (rs1041983, *6A, *7B) and G590A (rs1799930, *6A). 'Ultra-slow' acetylators have significantly about 32 and 46 % lower activities of caffeine metabolism compared with other slow acetylators and with the *5B/*5B genotypes, respectively (P < 0.01, both). The 'ultra-slow' genotype showed an association with bladder cancer risk in the univariate analysis (OR = 1.31, P = 0.012) and a trend adjusted for age, gender and smoking habits (OR = 1.22, P = 0.082). In contrast, slow acetylators in general were not associated with bladder cancer risk, neither in the univariate (OR = 1.02, P = 0.78) nor in the adjusted (OR = 0.98, P = 0.77) analysis. In conclusion, this study suggests that NAT2 phenotype prediction should be refined by consideration of an 'ultra-slow' acetylation genotype. PMID:24221535

  17. Phenotype, Body Composition, and Prediction Equations (Indian Fatty Liver Index) for Non-Alcoholic Fatty Liver Disease in Non-Diabetic Asian Indians: A Case-Control Study

    PubMed Central

    Bhatt, Surya Prakash; Misra, Anoop; Nigam, Priyanka; Guleria, Randeep; Pasha, M. A. Qadar

    2015-01-01

    Objective In this study, we have attempted comparison of detailed body composition phenotype of Asian Indians with non-alcoholic fatty liver disease (NAFLD) vs. those without, in a case controlled manner. We also aim to analyse prediction equations for NAFLD for non-diabetic Asian Indians, and compare performance of these with published prediction equations researched from other populations. Methods In this case-control study, 162 cases and 173 age-and sex-matched controls were recruited. Clinical, anthropometric, metabolic, and body composition profiles, and liver ultrasound were done. Fasting insulin levels, value of homeostasis model assessment of insulin resistance (HOMA-IR), and serum high sensitive C-reactive protein (hs-CRP) levels were evaluated. Multivariate logistic and linear regression analyses were used to arrive at prediction equations for fatty liver [Indian fatty liver index (IFLI)]. Results As compared to those without fatty liver, those with fatty liver exhibited the following; Excess dorsocervical fat (‘Buffalo hump’), skin tags, xanthelasma, ‘double chin’, arcus; excess total, abdominal and subcutaneous adiposity, and high blood pressure, blood glucose, measures of insulin resistance (fasting insulin and HOMA-IR values), lipids and hs-CRP levels. Two prediction equations were developed; Clinical [Indian Fatty Liver Index-Clinical; IFLI-C]: 1(double chin) +15.5 (systolic blood pressure) +13.8 (buffalo hump); and IFLI-Clinical and Biochemical (CB): serum triglycerides+12 (insulin)+1(systolic blood pressure) +18 (buffalo hump). On ROC Curve analysis, IFLI performed better than all published prediction equations, except one. Conclusion Non-diabetic Asian Indians with NAFLD researched by us were overweight/obese, had excess abdominal and subcutaneous fat, multiple other phenotypic markers, had higher insulin resistance, glycemia, dyslipidemia and subclinical inflammation than those without. Prediction score developed by us for NAFLD; IFLI

  18. Evaluation of the Genotypic Prediction of HIV-1 Coreceptor Use versus a Phenotypic Assay and Correlation with the Virological Response to Maraviroc: the ANRS GenoTropism Study▿

    PubMed Central

    Recordon-Pinson, Patricia; Soulié, Cathia; Flandre, Philippe; Descamps, Diane; Lazrek, Mouna; Charpentier, Charlotte; Montes, Brigitte; Trabaud, Mary-Anne; Cottalorda, Jacqueline; Schneider, Véronique; Morand-Joubert, Laurence; Tamalet, Catherine; Desbois, Delphine; Macé, Muriel; Ferré, Virginie; Vabret, Astrid; Ruffault, Annick; Pallier, Coralie; Raymond, Stéphanie; Izopet, Jacques; Reynes, Jacques; Marcelin, Anne-Geneviève; Masquelier, Bernard

    2010-01-01

    Genotypic algorithms for prediction of HIV-1 coreceptor usage need to be evaluated in a clinical setting. We aimed at studying (i) the correlation of genotypic prediction of coreceptor use in comparison with a phenotypic assay and (ii) the relationship between genotypic prediction of coreceptor use at baseline and the virological response (VR) to a therapy including maraviroc (MVC). Antiretroviral-experienced patients were included in the MVC Expanded Access Program if they had an R5 screening result with Trofile (Monogram Biosciences). V3 loop sequences were determined at screening, and coreceptor use was predicted using 13 genotypic algorithms or combinations of algorithms. Genotypic predictions were compared to Trofile; dual or mixed (D/M) variants were considered as X4 variants. Both genotypic and phenotypic results were obtained for 189 patients at screening, with 54 isolates scored as X4 or D/M and 135 scored as R5 with Trofile. The highest sensitivity (59.3%) for detection of X4 was obtained with the Geno2pheno algorithm, with a false-positive rate set up at 10% (Geno2pheno10). In the 112 patients receiving MVC, a plasma viral RNA load of <50 copies/ml was obtained in 68% of cases at month 6. In multivariate analysis, the prediction of the X4 genotype at baseline with the Geno2pheno10 algorithm including baseline viral load and CD4 nadir was independently associated with a worse VR at months 1 and 3. The baseline weighted genotypic sensitivity score was associated with VR at month 6. There were strong arguments in favor of using genotypic coreceptor use assays for determining which patients would respond to CCR5 antagonist. PMID:20530226

  19. Overexpression Of Hepatocyte Nuclear Factor-1beta Predicting Poor Prognosis Is Associated With Biliary Phenotype In Patients With Hepatocellular Carcinoma

    PubMed Central

    Yu, Dan-Dan; Jing, Ying-Ying; Guo, Shi-Wei; Ye, Fei; Lu, Wen; Li, Quan; Dong, Yu-Long; Gao, Lu; Yang, Yu-Ting; Yang, Yang; Wu, Meng-Chao; Wei, Li-Xin

    2015-01-01

    Hepatocyte nuclear factor-1beta (HNF-1B) is involved in the hepatobiliary specification of hepatoblasts to cholangiocytes during liver development, and is strongly expressed throughout adult biliary epithelium. The aim of this study was to examine the expression of HNF-1B in different pathologic subtypes of primary liver cancer, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (ICC), and the relationship between HNF-1B expression, clinicopathological features and prognosis. We retrospectively investigated 2 cohorts of patients, including 183 HCCs and 69 ICCs. The expression of HNF-1B was examined by immunohistochemistry. We found that HNF-1B expression was associated with pathological subtype of primary tumor, and HNF-1B expression in HCC tissue may be associated with the change of phenotype on recurrence. The HNF-1B expression was positively correlated with biliary/HPC (hepatic progenitor cell) markers expression. Further, multivariable analysis showed that HNF-1B expression was an independent prognostic factor for both overall survival and disease-free survival of HCC patients. However, no correlation between HNF-1B expression and survival was found in ICC patients. In summary, HCC with high HNF-1B expression displayed biliary phenotype and tended to show poorer prognosis. HNF-1B-positive malignant cells could be bipotential cells and give rise to both hepatocytic and cholangiocytic lineages during tumorigenesis. PMID:26311117

  20. Investigation of NS3 Protease Resistance-Associated Variants and Phenotypes for the Prediction of Treatment Response to HCV Triple Therapy

    PubMed Central

    Susser, Simone; Vermehren, Johannes; Peiffer, Kai-Henrik; Filmann, Natalie; Bon, Dimitra; Kuntzen, Thomas; Mauss, Stefan; Grammatikos, Georgios; Perner, Dany; Berkowski, Caterina; Herrmann, Eva; Zeuzem, Stefan; Bartenschlager, Ralf; Sarrazin, Christoph

    2016-01-01

    Triple therapy of chronic hepatitis C virus (HCV) infection with boceprevir (BOC) or telaprevir (TVR) leads to virologic failure in many patients which is often associated with the selection of resistance-associated variants (RAVs). These resistance profiles are of importance for the selection of potential rescue treatment options. In this study, we sequenced baseline NS3 RAVs population-based and investigated the sensitivity of NS3 phenotypes in an HCV replicon assay together with clinical factors for a prediction of treatment response in a cohort of 165 German and Swiss patients treated with a BOC or TVR-based triple therapy. Overall, the prevalence of baseline RAVs was low, although the frequency of RAVs was higher in patients with virologic failure compared to those who achieved a sustained virologic response (SVR) (7% versus 1%, P = 0.06). The occurrence of RAVs was associated with a resistant NS3 quasispecies phenotype (P<0.001), but the sensitivity of phenotypes was not associated with treatment outcome (P = 0.2). The majority of single viral and host predictors of SVR was only weakly associated with treatment response. In multivariate analyses, low AST levels, female sex and an IFNL4 CC genotype were independently associated with SVR. However, a combined analysis of negative predictors revealed a significantly lower overall number of negative predictors in patients with SVR in comparison to individuals with virologic failure (P<0.0001) and the presence of 2 or less negative predictors was indicative for SVR. These results demonstrate that most single baseline viral and host parameters have a weak influence on the response to triple therapy, whereas the overall number of negative predictors has a high predictive value for SVR. PMID:27281344

  1. Leukemia-induced phenotypic and functional defects in natural killer cells predict failure to achieve remission in acute myeloid leukemia.

    PubMed

    Stringaris, Kate; Sekine, Takuya; Khoder, Ahmad; Alsuliman, Abdullah; Razzaghi, Bonnie; Sargeant, Ruhena; Pavlu, Jiri; Brisley, Gill; de Lavallade, Hugues; Sarvaria, Anushruthi; Marin, David; Mielke, Stephan; Apperley, Jane F; Shpall, Elizabeth J; Barrett, A John; Rezvani, Katayoun

    2014-05-01

    The majority of patients with acute myeloid leukemia will relapse, and older patients often fail to achieve remission with induction chemotherapy. We explored the possibility that leukemic suppression of innate immunity might contribute to treatment failure. Natural killer cell phenotype and function was measured in 32 consecutive acute myeloid leukemia patients at presentation, including 12 achieving complete remission. Compared to 15 healthy age-matched controls, natural killer cells from acute myeloid leukemia patients were abnormal at presentation, with downregulation of the activating receptor NKp46 (P=0.007) and upregulation of the inhibitory receptor NKG2A (P=0.04). Natural killer cells from acute myeloid leukemia patients had impaired effector function against autologous blasts and K562 targets, with significantly reduced CD107a degranulation, TNF-α and IFN-γ production. Failure to achieve remission was associated with NKG2A overexpression and reduced TNF-α production. These phenotypic and functional abnormalities were partially restored in the 12 patients achieving remission. In vitro co-incubation of acute myeloid leukemia blasts with natural killer cells from healthy donors induced significant impairment in natural killer cell TNF-α and IFN-γ production (P=0.02 and P=0.01, respectively) against K562 targets and a trend to reduced CD107a degranulation (P=0.07). Under transwell conditions, the inhibitory effect of AML blasts on NK cytotoxicity and effector function was still present, and this inhibitory effect was primarily mediated by IL-10. These results suggest that acute myeloid leukemia blasts induce long-lasting changes in natural killer cells, impairing their effector function and reducing the competence of the innate immune system, favoring leukemia survival. PMID:24488563

  2. Leukemia-induced phenotypic and functional defects in natural killer cells predict failure to achieve remission in acute myeloid leukemia

    PubMed Central

    Stringaris, Kate; Sekine, Takuya; Khoder, Ahmad; Alsuliman, Abdullah; Razzaghi, Bonnie; Sargeant, Ruhena; Pavlu, Jiri; Brisley, Gill; de Lavallade, Hugues; Sarvaria, Anushruthi; Marin, David; Mielke, Stephan; Apperley, Jane F.; Shpall, Elizabeth J.; Barrett, A. John; Rezvani, Katayoun

    2014-01-01

    The majority of patients with acute myeloid leukemia will relapse, and older patients often fail to achieve remission with induction chemotherapy. We explored the possibility that leukemic suppression of innate immunity might contribute to treatment failure. Natural killer cell phenotype and function was measured in 32 consecutive acute myeloid leukemia patients at presentation, including 12 achieving complete remission. Compared to 15 healthy age-matched controls, natural killer cells from acute myeloid leukemia patients were abnormal at presentation, with downregulation of the activating receptor NKp46 (P=0.007) and upregulation of the inhibitory receptor NKG2A (P=0.04). Natural killer cells from acute myeloid leukemia patients had impaired effector function against autologous blasts and K562 targets, with significantly reduced CD107a degranulation, TNF-α and IFN-γ production. Failure to achieve remission was associated with NKG2A overexpression and reduced TNF-α production. These phenotypic and functional abnormalities were partially restored in the 12 patients achieving remission. In vitro co-incubation of acute myeloid leukemia blasts with natural killer cells from healthy donors induced significant impairment in natural killer cell TNF-α and IFN-γ production (P=0.02 and P=0.01, respectively) against K562 targets and a trend to reduced CD107a degranulation (P=0.07). Under transwell conditions, the inhibitory effect of AML blasts on NK cytotoxicity and effector function was still present, and this inhibitory effect was primarily mediated by IL-10. These results suggest that acute myeloid leukemia blasts induce long-lasting changes in natural killer cells, impairing their effector function and reducing the competence of the innate immune system, favoring leukemia survival. PMID:24488563

  3. LCN2 Promoter Methylation Status as Novel Predictive Marker for Microvessel Density and Aggressive Tumor Phenotype in Breast Cancer Patients.

    PubMed

    Meka, Phanni bhushann; Jarjapu, Sarika; Nanchari, Santhoshi Rani; Vishwakarma, Sandeep Kumar; Edathara, Prajitha Mohandas; Gorre, Manjula; Cingeetham, Anuradha; Vuree, Sugunakar; Annamaneni, Sandhya; Dunna, Nageswara Rao; Mukta, Srinivasulu; B, Triveni; Satti, Vishnupriya

    2015-01-01

    LCN2 (Lipocalin 2) is a 25 KD secreted acute phase protein, reported to be a novel regulator of angiogenesis in breast cancer. Up regulation of LCN2 had been observed in multiple cancers including breast cancer, pancreatic cancer and ovarian cancer. However, the role of LCN2 promoter methylation in the formation of microvessels is poorly understood. The aim of this study was to analyze the association of LCN 2 promoter methylation with microvessel formation and tumor cell proliferation in breast cancer patients. The LCN2 promoter methylation status was studied in 64 breast cancer tumors by methylation specific PCR (MSP). Evaluation of microvessel density (MVD) and Ki67 cell proliferation index was achieved by immunohistochemical staining using CD34 and MIB-1 antibodies, respectively. LCN2 promoter unmethylation status was observed in 43 (67.2%) of breast cancer patients whereas LCN2 methylation status was seen in 21 (32.8%). Further, LCN2 promoter unmethylation status was associated with aggressive tumor phenotype and elevated mean MVD in breast cancer patients. PMID:26163623

  4. Disease Phenotype, Activity and Clinical Course Prediction Based on C-Reactive Protein Levels at Diagnosis in Patients with Crohn’s Disease: Results from the CONNECT Study

    PubMed Central

    Kwon, Jee Hye; Im, Jong Pil; Ye, Byong Duk; Cheon, Jae Hee; Jang, Hyun Joo; Lee, Kang Moon; Kim, You Sun; Kim, Sang Wook; Kim, Young Ho; Song, Geun Am; Han, Dong Soo; Kim, Won Ho; Kim, Joo Sung

    2016-01-01

    Background/Aims C-reactive protein (CRP) is an easily measured index of disease activity, but its ability to predict clinical course is controversial. We therefore designed a study to determine whether the CRP level at Crohn’s disease (CD) diagnosis is a valuable indicator of the disease phenotype, activity, and clinical course. Methods We retrospectively analyzed 705 CD patients from 32 institutions. The patients were classified into two groups according to CRP level. The patients’ demographic and clinical characteristics and their use of immunosuppressive or biological agents were recorded. Disease location and behavior, hospitalization, and surgery were analyzed. Results A high CRP was associated with younger age, steroid use, colonic or ileocolonic location, high CD activity index, and active inflammation at colonoscopy (p<0.001). As the disease progressed, patients with high CRP were more likely to exhibit strictures (p=0.027). There were significant differences in the use of 5-aminosalicylic acid, antibiotics, corticosteroids, azathioprine, and infliximab (p<0.001, p<0.001, p<0.001, p<0.001, and p=0.023, respectively). Hospitalization was also more frequent in patients with high CRP. Conclusions The CRP level at diagnosis is useful for evaluating the phenotype, activity, and clinical course of CD. Closer follow-up strategies, with early aggressive treatment, could be considered for patients with high CRP. PMID:27021506

  5. Genetically predicted body mass index and Alzheimer's disease-related phenotypes in three large samples: Mendelian randomization analyses.

    PubMed

    Mukherjee, Shubhabrata; Walter, Stefan; Kauwe, John S K; Saykin, Andrew J; Bennett, David A; Larson, Eric B; Crane, Paul K; Glymour, M Maria

    2015-12-01

    Observational research shows that higher body mass index (BMI) increases Alzheimer's disease (AD) risk, but it is unclear whether this association is causal. We applied genetic variants that predict BMI in Mendelian randomization analyses, an approach that is not biased by reverse causation or confounding, to evaluate whether higher BMI increases AD risk. We evaluated individual-level data from the AD Genetics Consortium (ADGC: 10,079 AD cases and 9613 controls), the Health and Retirement Study (HRS: 8403 participants with algorithm-predicted dementia status), and published associations from the Genetic and Environmental Risk for AD consortium (GERAD1: 3177 AD cases and 7277 controls). No evidence from individual single-nucleotide polymorphisms or polygenic scores indicated BMI increased AD risk. Mendelian randomization effect estimates per BMI point (95% confidence intervals) were as follows: ADGC, odds ratio (OR) = 0.95 (0.90-1.01); HRS, OR = 1.00 (0.75-1.32); GERAD1, OR = 0.96 (0.87-1.07). One subscore (cellular processes not otherwise specified) unexpectedly predicted lower AD risk. PMID:26079416

  6. Novel combinations of phenotypic biomarkers predict development of epilepsy in the lithium-pilocarpine model of temporal lobe epilepsy in rats.

    PubMed

    Bröer, Sonja; Löscher, Wolfgang

    2015-12-01

    The discovery and validation of biomarkers in neurological and neurodegenerative diseases is an important challenge for early diagnosis of disease and for the development of therapeutics. Epilepsy is often a consequence of brain insults such as traumatic brain injury or stroke, but as yet no biomarker exists to predict the development of epilepsy in patients at risk. Given the complexity of epilepsy, it is unlikely that a single biomarker is sufficient for this purpose, but a combinatorial approach may be needed to overcome the challenge of individual variability and disease heterogeneity. The goal of the present prospective study in the lithium-pilocarpine model of epilepsy in rats was to determine the discriminative utility of combinations of phenotypic biomarkers by examining their ability to predict epilepsy. For this purpose, we used a recent model refinement that allows comparing rats that will or will not develop spontaneous recurrent seizures (SRS) after pilocarpine-induced status epilepticus (SE). Potential biomarkers included in our study were seizure threshold and seizure severity in response to timed i.v. infusion of pentylenetetrazole (PTZ) and behavioral alterations determined by a battery of tests during the three weeks following SE. Three months after SE, video/EEG monitoring was used to determine which rats had developed SRS. To determine whether a biomarker or combination of biomarkers performed better than chance at predicting epilepsy after SE, derived data underwent receiver operating characteristic (ROC) curve analyses. When comparing rats with and without SRS and sham controls, the best intergroup discrimination was obtained by combining all measurements, resulting in a ROC area under curve (AUC) of 0.9592 (P<0.01), indicating an almost perfect discrimination or accuracy to predict development of SRS. These data indicate that a combinatorial biomarker approach may overcome the challenge of individual variability in the prediction of epilepsy

  7. Patients’ Opinions about Knowing Their Risk for Depression and What to Do about It. The PredictD-Qualitative Study

    PubMed Central

    Bellón, Juan Á.; Moreno-Peral, Patricia; Moreno-Küstner, Berta; Motrico, Emma; Aiarzagüena, José M.; Fernández, Anna; Fernández-Alonso, Carmen; Montón-Franco, Carmen; Rodríguez-Bayón, Antonina; Ballesta-Rodríguez, María Isabel; Rüntel-Geidel, Ariadne; Payo-Gordón, Janire; Serrano-Blanco, Antoni; Oliván-Blázquez, Bárbara; Araujo, Luz; Muñoz-García, María del Mar; King, Michael; Nazareth, Irwin; Amezcua, Manuel

    2014-01-01

    Background The predictD study developed and validated a risk algorithm for predicting the onset of major depression in primary care. We aimed to explore the opinion of patients about knowing their risk for depression and the values and criteria upon which these opinions are based. Methods A maximum variation sample of patients was taken, stratified by city, age, gender, immigrant status, socio-economic status and lifetime depression. The study participants were 52 patients belonging to 13 urban health centres in seven different cities around Spain. Seven Focus Groups (FGs) were given held with primary care patients, one for each of the seven participating cities. Results The results showed that patients generally welcomed knowing their risk for depression. Furthermore, in light of available evidence several patients proposed potential changes in their lifestyles to prevent depression. Patients generally preferred to ask their General Practitioners (GPs) for advice, though mental health specialists were also mentioned. They suggested that GPs undertake interventions tailored to each patient, from a “patient-centred” approach, with certain communication skills, and giving advice to help patients cope with the knowledge that they are at risk of becoming depressed. Conclusions Patients are pleased to be informed about their risk for depression. We detected certain beliefs, attitudes, values, expectations and behaviour among the patients that were potentially useful for future primary prevention programmes on depression. PMID:24646951

  8. Phenylalanine hydroxylase deficiency in south Italy: Genotype-phenotype correlations, identification of a novel mutant PAH allele and prediction of BH4 responsiveness.

    PubMed

    Trunzo, Roberta; Santacroce, Rosa; D'Andrea, Giovanna; Longo, Vittoria; De Girolamo, Giuseppe; Dimatteo, Claudia; Leccese, Angelica; Bafunno, Valeria; Lillo, Vincenza; Papadia, Francesco; Margaglione, Maurizio

    2015-10-23

    We investigated the mutation spectrum of the phenylalanine hydroxylase gene (PAH) in a cohort of patients from 33 Italian PKU families. Mutational screening of the known coding region, including conventional intron splice sites, was performed by direct sequencing of the patients' genomic DNA. Thirty-three different disease causing mutations were identified in our patient group, including 19 missense, 6 splicing, 3 nonsense, 5 deletions, with a detection rate of 100%. The most prevalent mutation was the IVS10-11G>A, accounting for 12.1% of PKU alleles studied. Other frequent mutations were: p.R261Q (9.1%), p.P281L (7.6%), and p.R408W (6.1%). We also identified one novel missense mutation, p.H290Q. A spectrum of 31 different genotypes was observed and a genotype based predictions of BH4-responsiveness were assessed. Among all genotypes, 13 were predicted to be BH4-responsive represented by thirteen PKU families. In addition, genotype-phenotype correlations were performed. This study reveals the importance of a full genotyping of PKU patients and the prediction of BH4-responsiveness, not only because of the definitive diagnosis and prediction of the optimal diet, but also to point out those patients that could benefit from new therapeutic approach. They may potentially benefit from BH4 therapy which, combined with a less strict diet, or eventually in special cases as monotherapy, may contribute to reduce nutritional deficiencies and minimize neurological and psychological dysfunctions. PMID:26210745

  9. An assessment of computer model techniques to predict quantitative and qualitative measures of speech perception in university classrooms for varying room sizes and noise levels

    NASA Astrophysics Data System (ADS)

    Kim, Hyeong-Seok

    The objective of this dissertation was to assess the use of computer modeling techniques to predict quantitative and qualitative measures of speech perception in classrooms under realistic conditions of background noise and reverberation. Secondary objectives included (1) finding relationships among acoustical measurements made in actual classrooms and in the computer models of the actual rooms as a prediction tool of 15 acoustic parameters at the design stage of projects and (2) finding relationships among speech perception scores and 15 acoustic parameters to determine the best predictors of speech perception in actual classroom conditions. Fifteen types of acoustical measurements were made in three actual classrooms with reverberation times of 0.5, 1.3, and 5.1 seconds. Speech perception tests using a Modified Rhyme Test list were also given to 22 subject in each room with five noise conditions of signal-to-noise ratios of 31, 24, 15, 0, -10. Computer models of the rooms were constructed using a commercially available computer model software program. The 15 acoustical measurements were made at 6 or 9 locations in the model rooms. Impulse responses obtained in the computer models of the rooms were convolved with the anechoically recorded speech tests used in the full size rooms to produce a compact disk with the MRT lists with the acoustical response of the computer model rooms. Speech perception tests using this as source material were given to the subjects over loudspeaker in an acoustic test booth. The results of the study showed correlations (R2) of between acoustical measures made in the full size classrooms and the computer models of the classrooms of 0.92 to 0.99 with standard errors of 0.033 to 7.311. Comparisons between speech perception scores tested in the rooms and acoustical measurements made in the rooms and in the computer models of the classrooms showed that the measures have similar prediction accuracy with other studies in the literatures. The

  10. Concordance of HIV Type 1 Tropism Phenotype to Predictions Using Web-Based Analysis of V3 Sequences: Composite Algorithms May Be Needed to Properly Assess Viral Tropism

    PubMed Central

    Cabral, Gabriela Bastos; Ferreira, João Leandro de Paula; Coelho, Luana Portes Osório; Fonsi, Mylva; Estevam, Denise Lotufo; Cavalcanti, Jaqueline Souza

    2012-01-01

    Abstract Genotypic prediction of HIV-1 tropism has been considered a practical surrogate for phenotypic tests and recently an European Consensus has set up recommendations for its use in clinical practice. Twenty-five antiretroviral-experienced patients, all heavily treated cases with a median of 16 years of antiretroviral therapy, had viral tropism determined by the Trofile assay and predicted by HIV-1 sequencing of partial env, followed by interpretation using web-based tools. Trofile determined 17/24 (71%) as X4 tropic or dual/mixed viruses, with one nonreportable result. The use of European consensus recommendations for single sequences (geno2pheno false-positive rates 20% cutoff) would lead to 4/24 (16.7%) misclassifications, whereas a composite algorithm misclassified 1/24 (4%). The use of the geno2pheno clinical option using CD4 T cell counts at collection was useful in resolving some discrepancies. Applying the European recommendations followed by additional web-based tools for cases around the recommended cutoff would resolve most misclassifications. PMID:21919801

  11. Concordance of HIV type 1 tropism phenotype to predictions using web-based analysis of V3 sequences: composite algorithms may be needed to properly assess viral tropism.

    PubMed

    Cabral, Gabriela Bastos; Ferreira, João Leandro de Paula; Coelho, Luana Portes Osório; Fonsi, Mylva; Estevam, Denise Lotufo; Cavalcanti, Jaqueline Souza; Brígido, Luis Fernando de Macedo

    2012-07-01

    Genotypic prediction of HIV-1 tropism has been considered a practical surrogate for phenotypic tests and recently an European Consensus has set up recommendations for its use in clinical practice. Twenty-five antiretroviral-experienced patients, all heavily treated cases with a median of 16 years of antiretroviral therapy, had viral tropism determined by the Trofile assay and predicted by HIV-1 sequencing of partial env, followed by interpretation using web-based tools. Trofile determined 17/24 (71%) as X4 tropic or dual/mixed viruses, with one nonreportable result. The use of European consensus recommendations for single sequences (geno2pheno false-positive rates 20% cutoff) would lead to 4/24 (16.7%) misclassifications, whereas a composite algorithm misclassified 1/24 (4%). The use of the geno2pheno clinical option using CD4 T cell counts at collection was useful in resolving some discrepancies. Applying the European recommendations followed by additional web-based tools for cases around the recommended cutoff would resolve most misclassifications. PMID:21919801

  12. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    PubMed

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  13. Prediction of Long-Term Benefits of Inhaled Steroids by Phenotypic Markers in Moderate-to-Severe COPD: A Randomized Controlled Trial

    PubMed Central

    Snoeck-Stroband, Jiska B.; Lapperre, Therese S.; Sterk, Peter J.; Hiemstra, Pieter S.; Thiadens, Henk A.; Boezen, H. Marike; ten Hacken, Nick H. T.; Kerstjens, Huib A. M.; Postma, Dirkje S.; Timens, Wim; Sont, Jacob K.

    2015-01-01

    Background The decline in lung function can be reduced by long-term inhaled corticosteroid (ICS) treatment in subsets of patients with chronic obstructive pulmonary disease (COPD). We aimed to identify which clinical, physiological and non-invasive inflammatory characteristics predict the benefits of ICS on lung function decline in COPD. Methods Analysis was performed in 50 steroid-naive compliant patients with moderate to severe COPD (postbronchodilator forced expiratory volume in one second (FEV1), 30–80% of predicted, compatible with GOLD stages II-III), age 45–75 years, >10 packyears smoking and without asthma. Patients were treated with fluticasone propionate (500 μg bid) or placebo for 2.5 years. Postbronchodilator FEV1, dyspnea and health status were measured every 3 months; lung volumes, airway hyperresponsiveness (PC20), and induced sputum at 0, 6 and 30 months. A linear mixed effect model was used for analysis of this hypothesis generating study. Results Significant predictors of attenuated FEV1-decline by fluticasone treatment compared to placebo were: fewer packyears smoking, preserved diffusion capacity, limited hyperinflation and lower inflammatory cell counts in induced sputum (p<0.04). Conclusions Long-term benefits of ICS on lung function decline in patients with moderate-to-severe COPD are most pronounced in patients with fewer packyears, and less severe emphysema and inflammation. These data generate novel hypotheses on phenotype-driven therapy in COPD. Trial Registration ClinicalTrials.gov NCT00158847 PMID:26659582

  14. Predominant expression of truncated EpCAM is associated with a more aggressive phenotype and predicts poor overall survival in colorectal cancer.

    PubMed

    Seeber, Andreas; Untergasser, Gerold; Spizzo, Gilbert; Terracciano, Luigi; Lugli, Alessandro; Kasal, Armin; Kocher, Florian; Steiner, Normann; Mazzoleni, Guido; Gastl, Guenther; Fong, Dominic

    2016-08-01

    Regulated intramembrane proteolysis (RIP) has been shown to be an important mechanism for oncogenic activation of EpCAM through nuclear translocation of the intracellular domain EpICD. Recently, we identified two different membranous EpCAM variants namely EpCAM(MF) (full-length) and EpCAM(MT) (truncated) to be expressed in the majority of human epithelial tumors. The aim of our study was to evaluate the potential role of these two protein variants as additional prognostic biomarkers in colorectal cancer. In most studies only one antibody targeting the extracellular domain of EpCAM (EpEX) has been used, whereas in the present study additionally an antibody which detects the intracellular domain (EpICD) was applied to discriminate between different EpCAM variants. Using immunohistochemistry, we analyzed the expression of EpCAM(MF) and EpCAM(MT) variants in 640 patients with colorectal cancer and determined their correlations with other prognostic factors and clinical outcome. A statistically significant association was observed for EpCAM(MT) with advanced tumor stage (p < 0.001), histological grade (p = 0.01), vascular (p < 0.001) and marginal (p = 0.002) invasion. Survival analysis demonstrated reduced overall survival (p < 0.004) in patients with tumors expressing the EpCAM(MT) phenotype when compared to patients with tumors expressing the EpCAM(MF) variant. In conclusion, this study for the first time indicates that expression of EpCAM(MT) is associated with a more aggressive phenotype and predicts poor survival in patients with colorectal cancer. PMID:26996277

  15. Immunostimulatory early phenotype of tumor-associated macrophages does not predict tumor growth outcome in an HLA-DR mouse model of prostate cancer.

    PubMed

    Riabov, Vladimir; Kim, David; Chhina, Surmeet; Alexander, Richard B; Klyushnenkova, Elena N

    2015-07-01

    Tumor-associated macrophages (TAM) were shown to support the progression of many solid tumors. However, anti-tumor properties of TAM were also reported in several types of cancer. Here, we investigated the phenotype and functions of TAM in two transgenic mouse models of prostate cancer that display striking differences in tumor growth outcome. Mice expressing prostate-specific antigen (PSA) as a self-antigen specifically in prostate (PSAtg mice) rejected PSA-expressing transgenic adenocarcinoma of mouse prostate (TRAMP) tumors. However, the introduction of HLA-DRB1*1501 (DR2b) transgene presenting PSA-derived peptides in a MHC class II-restricted manner exacerbated the growth of TRAMP-PSA tumors in DR2bxPSA F 1 mice. Despite the difference in tumor growth outcome, tumors in both strains were equally and intensively infiltrated by macrophages on the first week after tumor challenge. TAM exhibited mixed M1/M2 polarization and simultaneously produced pro-inflammatory (TNFα, IL1β) and anti-inflammatory (IL10) cytokines. TAM from both mouse strains demonstrated antigen-presenting potential and pronounced immunostimulatory activity. Moreover, they equally induced apoptosis of tumor cells. In vivo depletion of macrophages in DR2bxPSA F 1 but not PSAtg mice aggravated tumor growth suggesting that macrophages more strongly contribute to anti-tumor immunity when specific presentation of PSA to CD4+ T cells is possible. In summary, we conclude that in the early stages of tumor progression, the phenotype and functional properties of TAM did not predict tumor growth outcome in two transgenic prostate cancer models. Furthermore, we demonstrated that during the initial stage of prostate cancer development, TAM have the potential to activate T cell immunity and mediate anti-tumor effects. PMID:25893810

  16. Mode-coupling theory of self-diffusion in diblock copolymers I. General derivation and qualitative predictions

    SciTech Connect

    Guenza, M.; Tang, H.; Schweizer, K.S.

    1998-01-01

    A microscopic theory of self-diffusion in diblock copolymer melts and solutions has been developed based on polymeric mode-coupling methods formulated at the level of the time and space correlated interchain excluded volume and chi-parameter forces. Equilibrium structural correlations are determined via microscopic liquid state integral equation or coarse-grained field theoretic methods. The specific dynamical consequences of self-assembly are predicted to depend rather sensitively on temperature, degree of polymerization, copolymer composition and concentration, and local block friction coefficients. The dominant physical effect for entangled diblocks is the retardation of the relaxation time of the interchain excluded volume forces due to the thermodynamically-driven segregation of blocks into microdomains, resulting in suppression of translational motion. Analytic analysis in the long chain limit allows the derivation of new scaling laws relating the self-diffusion constant and chain degree of polymerization and solution concentration. Potential limitations for real copolymer materials associated with the structurally and dynamically isotropic description adopted by the theory are discussed. {copyright} {ital 1998 American Institute of Physics.}

  17. The prognostic blood biomarker proadrenomedullin for outcome prediction in patients with chronic obstructive pulmonary disease (COPD): a qualitative clinical review.

    PubMed

    Schuetz, Philipp; Marlowe, Robert J; Mueller, Beat

    2015-03-01

    Plasma proadrenomedullin (ProADM) is a blood biomarker that may aid in multidimensional risk assessment of patients with chronic obstructive pulmonary disease (COPD). Co-secreted 1:1 with adrenomedullin (ADM), ProADM is a less biologically active, more chemically stable surrogate for this pluripotent regulatory peptide, which due to biological and ex vivo physical characteristics is difficult to reliably directly quantify. Upregulated by hypoxia, inflammatory cytokines, bacterial products, and shear stress and expressed widely in pulmonary cells and ubiquitously throughout the body, ADM exerts or mediates vasodilatory, natriuretic, diuretic, antioxidative, anti-inflammatory, antimicrobial, and metabolic effects. Observational data from four separate studies totaling 1366 patients suggest that as a single factor, ProADM is a significant independent, and accurate, long-term all-cause mortality predictor in COPD. This body of work also suggests that combined with different groups of demographic/clinical variables, ProADM provides significant incremental long-term mortality prediction power relative to the groups of variables alone. Additionally, the literature contains indications that ProADM may be a global cardiopulmonary stress marker, potentially supplying prognostic information when cardiopulmonary exercise testing results such as 6-min walk distance are unavailable due to time or other resource constraints or to a patient's advanced disease. Prospective, randomized, controlled interventional studies are needed to demonstrate whether ProADM use in risk-based guidance of site-of-care, monitoring, and treatment decisions improves clinical, quality-of-life, or pharmacoeconomic outcomes in patients with COPD. PMID:25252756

  18. High plasma chemerin is associated with renal dysfunction and predictive for cardiovascular events - Insights from phenotype and genotype characterization.

    PubMed

    Leiherer, Andreas; Muendlein, Axel; Kinz, Elena; Vonbank, Alexander; Rein, Philipp; Fraunberger, Peter; Malin, Cornelia; Saely, Christoph H; Drexel, Heinz

    2016-02-01

    The novel adipokine chemerin, encoded by the RARRES2 gene, has been suggested to be linked to insulin resistance and to the metabolic syndrome (MetS). However, no well-defined cardiovascular profile has been reported and the association with coronary artery disease (CAD) is a matter of debate. Because there is a relation between renal dysfunction and CAD, we analyzed plasma chemerin levels and the estimated glomerular filtration rate (eGFR) in 495 patients undergoing coronary angiography for the evaluation of established or suspected stable CAD. Chemerin levels were higher in patients with Type 2 diabetes mellitus (T2DM, n=111) and the metabolic syndrome (MetS, n=147) than in subjects without T2DM (191.5±72.9 vs. 169.7±64.7ng/ml, p=0.001) or the MetS (201.2±71.0 vs. 163,1ng/ml, p<0.001), but did not differ significantly between patients with significant CAD (n=247) and those without significant CAD (177.1±67.0 vs. 171.7±67.2ng/ml, p=0.193). Analysis of covariance using age, sex, and BMI as covariates showed that chemerin was significantly and independently associated with eGFR (F=49.6, p<0.001). After an 8-year follow-up period, patients with high chemerin levels were more often affected by cardiovascular events (HR=1.72 [95% CI 1.19-2.47], p=0.004), even after appropriate adjustment for age, gender, BMI, as well as eGFR (adjusted HR 1.51 [95% CI 1.03-2.23], p=0.037). Given the cardiometabolic role of chemerin, we also applied a Cardio-Metabo Chip analysis and revealed a genome-wide significant association with SNPs (rs55709438, rs2444030, and rs3098423) located at chromosomal region 15q15-23, which were associated with metabolic traits and eGFR. This study for the first time demonstrates that high chemerin concentrations are significantly associated with renal impairment and predictive of cardiovascular events and that 15q15-23 might have an impact on chemerin levels beyond common genetic variations in RARRES2. PMID:26304698

  19. Phenotypic switching in bacteria

    NASA Astrophysics Data System (ADS)

    Merrin, Jack

    Living matter is a non-equilibrium system in which many components work in parallel to perpetuate themselves through a fluctuating environment. Physiological states or functionalities revealed by a particular environment are called phenotypes. Transitions between phenotypes may occur either spontaneously or via interaction with the environment. Even in the same environment, genetically identical bacteria can exhibit different phenotypes of a continuous or discrete nature. In this thesis, we pursued three lines of investigation into discrete phenotypic heterogeneity in bacterial populations: the quantitative characterization of the so-called bacterial persistence, a theoretical model of phenotypic switching based on those measurements, and the design of artificial genetic networks which implement this model. Persistence is the phenotype of a subpopulation of bacteria with a reduced sensitivity to antibiotics. We developed a microfluidic apparatus, which allowed us to monitor the growth rates of individual cells while applying repeated cycles of antibiotic treatments. We were able to identify distinct phenotypes (normal and persistent) and characterize the stochastic transitions between them. We also found that phenotypic heterogeneity was present prior to any environmental cue such as antibiotic exposure. Motivated by the experiments with persisters, we formulated a theoretical model describing the dynamic behavior of several discrete phenotypes in a periodically varying environment. This theoretical framework allowed us to quantitatively predict the fitness of dynamic populations and to compare survival strategies according to environmental time-symmetries. These calculations suggested that persistence is a strategy used by bacterial populations to adapt to fluctuating environments. Knowledge of the phenotypic transition rates for persistence may provide statistical information about the typical environments of bacteria. We also describe a design of artificial

  20. Predictive value of CpG island methylator phenotype for tumor recurrence in hepatitis B virus-associated hepatocellular carcinoma following liver transplantation

    PubMed Central

    2010-01-01

    Background CpG island methylator phenotype (CIMP), in which multiple genes concordantly methylated, has been demonstrated to be associated with progression, recurrence, as well as overall survival in some types of cancer. Methods We examined the promoter methylation status of seven genes including P16, CDH1, GSTP1, DAPK, XAF1, SOCS1 and SYK in 65 cases of HCC treated with LT by methylation-specific PCR. CIMP+ was defined as having three or more genes that are concordantly methylated. The relationship between CIMP status and clinicopathological parameters, as well as tumor recurrence was further analyzed. Results CIMP+ was more frequent in HCC with AFP > 400 ng/ml than those with AFP ≤ 400 ng/ml (P = 0.017). In addition, patients with CIMP+ were prone to have multiple tumor numbers than those with CIMP- (P = 0.007). Patients with CIMP+ tumors had significantly worse recurrence-free survival (RFS) than patients with CIMP-tumors by Kaplan-Meier estimates (P = 0.004). Multivariate analysis also revealed that CIMP status might be a novel independent prognostic factor of RFS for HCC patients treated with LT (HR: 3.581; 95% CI: 1.473-8.710, P = 0.005). Conclusion Our results suggested that CIMP could serve as a new prognostic biomarker to predict the risk of tumor recurrence in HCC after transplantation. PMID:20678188

  1. Features of CD44+/CD24-low phenotypic cell distribution in relation to predictive markers and molecular subtypes of invasive ductal carcinoma of the breast.

    PubMed

    Gudadze, M; Kankava, Q; Mariamidze, A; Burkadze, G

    2014-03-01

    Breast cancer is the most widespread pathology among women. Despite the current progresses in research and treatment of metastatic breast cancer, mortality caused by this disease is still high, because above mentioned therapy is limited due to existence of cells resistant to therapy . Cancer stem cells are the only cells with ability of unlimited proliferative activity and cancerous potential, thus, they participate in the growth, progression and dissemination of cancer. Cancer stem cells are resistant to various forms of therapy, including chemotherapy and radiotherapy . Results of examination showed that 50% of all cases are positive on so called markers of stem cells, thus 45% of cases are negative. CD44+/CD24-low cases (cases that reveal stem cell-phenotype) in the group of invasive ductal carcinoma of Luminal A molecular subtype are almost as many as CD44+/CD24+ and CD44-/CD24+ phenotype cancers. In this group non-stem phenotype cases are 65%, so 5 times more than stem cell phenotype cancers. 1324 postoperative breast materials studied through 2008-2012 at the laboratory of "Pathgeo-Union of Pathologists" LTD and Academician N. Kipshidze Central University Clinic were used as test materials and specimens from 393 patients with invasive ductal carcinoma were selected. CD44/CD24 markers' expression in phenotypically different cancers and clinic-pathologic parameters as well as various biological features was conducted by the Pearson's correlation analysis and using X2 test. Statistical analysis of obtained numeral data was held using SPSS V.19.0 program. Confidence interval of 95% was considered statistically significant. Stem cell phenotype positive cases are with the highest percentage represented in Luminal B and basal-like molecular subgroup that to our minds is associated with their aggressive behavior and resistance to chemotherapy. Relatively good prognosis and response to chemotherapy of Luminal A molecular subtype cancers are to be stipulated by lower

  2. Qualitative Evaluation.

    ERIC Educational Resources Information Center

    Stone, James C., Ed.; James, Raymond A., Ed.

    1981-01-01

    "Qualitative evaluation" is the theme of this issue of the California Journal of Teacher Education. Ralph Tyler states that evaluation is essentially descriptive, and using numbers does not solve basic problems. Martha Elin Vernazza examines the issue of objectivity in history and its implications for evaluation. She posits that the decisive…

  3. Trajectory constraints in qualitative simulation

    SciTech Connect

    Brajnik, G.; Clancy, D.J.

    1996-12-31

    We present a method for specifying temporal constraints on trajectories of dynamical systems and enforcing them during qualitative simulation. This capability can be used to focus a simulation, simulate non-autonomous and piecewise-continuous systems, reason about boundary condition problems and incorporate observations into the simulation. The method has been implemented in TeQSIM, a qualitative simulator that combines the expressive power of qualitative differential equations with temporal logic. It interleaves temporal logic model checking with the simulation to constrain and refine the resulting predicted behaviors and to inject discontinuous changes into the simulation.

  4. Logistic regression models to predict solvent accessible residues using sequence- and homology-based qualitative and quantitative descriptors applied to a domain-complete X-ray structure learning set

    PubMed Central

    Nepal, Reecha; Spencer, Joanna; Bhogal, Guneet; Nedunuri, Amulya; Poelman, Thomas; Kamath, Thejas; Chung, Edwin; Kantardjieff, Katherine; Gottlieb, Andrea; Lustig, Brooke

    2015-01-01

    A working example of relative solvent accessibility (RSA) prediction for proteins is presented. Novel logistic regression models with various qualitative descriptors that include amino acid type and quantitative descriptors that include 20- and six-term sequence entropy have been built and validated. A domain-complete learning set of over 1300 proteins is used to fit initial models with various sequence homology descriptors as well as query residue qualitative descriptors. Homology descriptors are derived from BLASTp sequence alignments, whereas the RSA values are determined directly from the crystal structure. The logistic regression models are fitted using dichotomous responses indicating buried or accessible solvent, with binary classifications obtained from the RSA values. The fitted models determine binary predictions of residue solvent accessibility with accuracies comparable to other less computationally intensive methods using the standard RSA threshold criteria 20 and 25% as solvent accessible. When an additional non-homology descriptor describing Lobanov–Galzitskaya residue disorder propensity is included, incremental improvements in accuracy are achieved with 25% threshold accuracies of 76.12 and 74.79% for the Manesh-215 and CASP(8+9) test sets, respectively. Moreover, the described software and the accompanying learning and validation sets allow students and researchers to explore the utility of RSA prediction with simple, physically intuitive models in any number of related applications. PMID:26664348

  5. The Caffeine Cytochrome P450 1A2 Metabolic Phenotype Does Not Predict the Metabolism of Heterocyclic Aromatic Amines in Humans

    PubMed Central

    Turesky, Robert J.; White, Kami K.; Wilkens, Lynne R.; Marchand, Loïc Le

    2015-01-01

    2-Amino-1-methylimidazo[4,5-b]pyridine (PhIP) and 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) are carcinogenic heterocyclic aromatic amines (HAAs) formed in well-done cooked meats. Chemicals that induce cytochrome P450 (P450) 1A2, a major enzyme involved in the bioactivation of HAAs, also form in cooked meat. Therefore, well-done cooked meat may pose an increase in cancer risk because it contains both inducers of P450 1A2 and procarcinogenic HAAs. We examined the influence of components in meat to modulate P450 1A2 activity and the metabolism of PhIP and MeIQx in volunteers during a 4 week feeding study of well-done cooked beef. The mean P450 1A2 activity, assessed by caffeine metabolic phenotyping, ranged from 6.3 to 7.1 before the feeding study commenced and from 9.6 to 10.4 during the meat feeding period: the difference in means was significant (P < 0.001). Unaltered PhIP, MeIQx, and their P450 1A2 metabolites, N2-(β-1-glucosiduronyl-2-(hydroxyamino)-1-methyl-6-phenylimidazo[4,5-b]pyridine (HON-PhIP-N2-Gl); N3-(β-1-glucosiduronyl-2-(hydroxyamino)-1-methyl-6-phenylimidazo[4,5-b]pyridine (HON-PhIP-N3-Gl); 2-amino-3-methylimidazo-[4,5-f]quinoxaline-8-carboxylic acid (IQx-8-COOH); and 2-amino-8-(hydroxymethyl)-3-methylimidazo[4,5-f]quinoxaline (8-CH2OH-IQx) were measured in urine during days 2, 14, and 28 days of the meat diet. Significant correlations were observed on these days between the levels of the unaltered HAAs and their oxidized metabolites, when expressed as percent of dose ingested or as metabolic ratios. However, there was no statistically significant correlation between the caffeine P450 1A2 phenotype and any urinary HAA biomarker. Although the P450 1A2 activity varied by greater than 20-fold among the subjects, there was a large intra-individual variation of the P450 1A2 phenotype and inconsistent responses to inducers of P450 1A2. The coefficient of variation of the P450 1A2 phenotype within-individual ranged between 1 to 112% (median=40

  6. Epigenetics in heart failure phenotypes.

    PubMed

    Berezin, Alexander

    2016-12-01

    Chronic heart failure (HF) is a leading clinical and public problem posing a higher risk of morbidity and mortality in different populations. HF appears to be in both phenotypic forms: HF with reduced left ventricular ejection fraction (HFrEF) and HF with preserved left ventricular ejection fraction (HFpEF). Although both HF phenotypes can be distinguished through clinical features, co-morbidity status, prediction score, and treatment, the clinical outcomes in patients with HFrEF and HFpEF are similar. In this context, investigation of various molecular and cellular mechanisms leading to the development and progression of both HF phenotypes is very important. There is emerging evidence that epigenetic regulation may have a clue in the pathogenesis of HF. This review represents current available evidence regarding the implication of epigenetic modifications in the development of different HF phenotypes and perspectives of epigenetic-based therapies of HF. PMID:27335803

  7. Bitter taste phenotype and body weight predict children’s selection of sweet and savory foods at a palatable test-meal☆

    PubMed Central

    Keller, Kathleen L.; Olsen, Annemarie; Cravener, Terri L.; Bloom, Rachel; Chung, Wendy K.; Deng, Liyong; Lanzano, Patricia; Meyermann, Karol

    2014-01-01

    Previous studies show that children who are sensitive to the bitter taste of 6-n-propylthiouracil (PROP) report more frequent intake of sweets and less frequent intake of meats (savory fats) relative to children who are PROP insensitive. Laboratory studies are needed to confirm these findings. In this study, seventy-nine 4- to 6-year-olds from diverse ethnicities attended four laboratory sessions, the last of which included a palatable buffet consisting of savory-fats (e.g. pizza), sweet-fats (e.g. cookies, cakes), and sweets (e.g. juices, candies). PROP phenotype was classified by two methods: 1) a common screening procedure to divide children into tasters and nontasters, and 2) a three-concentration method used to approximate PROP thresholds. Height and weight were measured and saliva was collected for genotyping TAS2R38, a bitter taste receptor related to the PROP phenotype. Data were analyzed by General Linear Model ANOVA with intake from savory fats, sweet-fats, and sweets as dependent variables and PROP status as the independent variable. BMI z-score, sex, age, and ethnicity were included as covariates. Adjusted energy intake from the food group “sweets” at the test-meal was greater for tasters than for nontasters. PROP status did not influence children’s adjusted intake of savory-fats, but BMI z-score did. The TAS2R38 genotype did not impact intake at the test-meal. At a palatable buffet, PROP taster children preferentially consumed more sweets than nontaster children, while heavier children consumed more savory fats. These findings may have implications for understanding differences in susceptibility to hyperphagia. PMID:24607656

  8. Phenotypic deconstruction of gene circuitry

    NASA Astrophysics Data System (ADS)

    Lomnitz, Jason G.; Savageau, Michael A.

    2013-06-01

    It remains a challenge to obtain a global perspective on the behavioral repertoire of complex nonlinear gene circuits. In this paper, we describe a method for deconstructing complex systems into nonlinear sub-systems, based on mathematically defined phenotypes, which are then represented within a system design space that allows the repertoire of qualitatively distinct phenotypes of the complex system to be identified, enumerated, and analyzed. This method efficiently characterizes large regions of system design space and quickly generates alternative hypotheses for experimental testing. We describe the motivation and strategy in general terms, illustrate its use with a detailed example involving a two-gene circuit with a rich repertoire of dynamic behavior, and discuss experimental means of navigating the system design space.

  9. Impage Analysis for Mapping Immeasurable Phenotypes in Maize

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A majority of phenotypic variance in maize has qualitative aspects that are immeasurable by rulers or scalars. Image analysis may improve the phenotypic quantification by increasing the objectivity and granularity of quantification, which in turn may result in an increase in the rate at which the ge...

  10. Perceptions of risk and predictive testing held by the first-degree relatives of patients with rheumatoid arthritis in England, Austria and Germany: a qualitative study

    PubMed Central

    Stack, Rebecca J; Stoffer, Michaela; Englbrecht, Mathias; Mosor, Erika; Falahee, Marie; Simons, Gwenda; Smolen, Josef; Schett, Georg; Buckley, Chris D; Kumar, Kanta; Hansson, Mats; Hueber, Axel; Stamm, Tanja; Raza, Karim

    2016-01-01

    Objectives The family members of patients with rheumatoid arthritis (RA) are at increased risk of developing RA and are potential candidates for predictive testing. This study explored the perceptions of first-degree relatives of people with RA about being at risk of RA and engaging in predictive testing. Methods 34 first-degree relatives (siblings and offspring) of patients with RA from the UK, Germany and Austria participated in semistructured interviews about their perceptions of RA risk and the prospect of predictive testing. Interviews were audio-recorded, transcribed verbatim and analysed using thematic analysis. Results First-degree relatives were aware of their susceptibility to RA, but were unsure of the extent of their risk. When considering their future risk, some relatives were concerned about the potential impact that RA would have on their lives. Relatives were concerned that knowing their actual risk would increase their anxiety and would affect decisions about their future. Also, relatives were concerned about the levels of uncertainty associated with predictive testing. Those in favour of knowing their future risk felt that they would need additional support to understand the risk information and cope with the emotional impact of this information. Conclusions Identifying individuals at risk of RA may allow targeted interventions to reduce the risk and consequence of future disease; however, relatives have concerns about predictive testing and risk information. The development of strategies to quantify and communicate risk needs to take these views into account and incorporate approaches to mitigate concerns and minimise the psychological impact of risk information. PMID:27357193

  11. Publishing Qualitative Research.

    ERIC Educational Resources Information Center

    Smith, Mary Lee

    1987-01-01

    Article defines qualitative research and describes the form that an article based on qualitative research might take. Encourages readers to submit articles based on qualitative research to the American Educational Research Journal. (RB)

  12. Relaxed selection is a precursor to the evolution of phenotypic plasticity

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Phenotypic plasticity represents one of the most important ways that organisms adaptively respond to environmental variation. Alternate phenotypes produced through phenotypic plasiticity generally arise through conditional gene expression, which is predicted to result in relaxed selective constrain...

  13. Genetic heterogeneity in Cornelia de Lange syndrome (CdLS) and CdLS-like phenotypes with observed and predicted levels of mosaicism

    PubMed Central

    Ansari, Morad; Poke, Gemma; Ferry, Quentin; Williamson, Kathleen; Aldridge, Roland; Meynert, Alison M; Bengani, Hemant; Chan, Cheng Yee; Kayserili, Hülya; Avci, Şahin; Hennekam, Raoul C M; Lampe, Anne K; Redeker, Egbert; Homfray, Tessa; Ross, Alison; Falkenberg Smeland, Marie; Mansour, Sahar; Parker, Michael J; Cook, Jacqueline A; Splitt, Miranda; Fisher, Richard B; Fryer, Alan; Magee, Alex C; Wilkie, Andrew; Barnicoat, Angela; Brady, Angela F; Cooper, Nicola S; Mercer, Catherine; Deshpande, Charu; Bennett, Christopher P; Pilz, Daniela T; Ruddy, Deborah; Cilliers, Deirdre; Johnson, Diana S; Josifova, Dragana; Rosser, Elisabeth; Thompson, Elizabeth M; Wakeling, Emma; Kinning, Esther; Stewart, Fiona; Flinter, Frances; Girisha, Katta M; Cox, Helen; Firth, Helen V; Kingston, Helen; Wee, Jamie S; Hurst, Jane A; Clayton-Smith, Jill; Tolmie, John; Vogt, Julie; Tatton–Brown, Katrina; Chandler, Kate; Prescott, Katrina; Wilson, Louise; Behnam, Mahdiyeh; McEntagart, Meriel; Davidson, Rosemarie; Lynch, Sally-Ann; Sisodiya, Sanjay; Mehta, Sarju G; McKee, Shane A; Mohammed, Shehla; Holden, Simon; Park, Soo-Mi; Holder, Susan E; Harrison, Victoria; McConnell, Vivienne; Lam, Wayne K; Green, Andrew J; Donnai, Dian; Bitner-Glindzicz, Maria; Donnelly, Deirdre E; Nellåker, Christoffer; Taylor, Martin S; FitzPatrick, David R

    2014-01-01

    Background Cornelia de Lange syndrome (CdLS) is a multisystem disorder with distinctive facial appearance, intellectual disability and growth failure as prominent features. Most individuals with typical CdLS have de novo heterozygous loss-of-function mutations in NIPBL with mosaic individuals representing a significant proportion. Mutations in other cohesin components, SMC1A, SMC3, HDAC8 and RAD21 cause less typical CdLS. Methods We screened 163 affected individuals for coding region mutations in the known genes, 90 for genomic rearrangements, 19 for deep intronic variants in NIPBL and 5 had whole-exome sequencing. Results Pathogenic mutations [including mosaic changes] were identified in: NIPBL 46 [3] (28.2%); SMC1A 5 [1] (3.1%); SMC3 5 [1] (3.1%); HDAC8 6 [0] (3.6%) and RAD21 1 [0] (0.6%). One individual had a de novo 1.3 Mb deletion of 1p36.3. Another had a 520 kb duplication of 12q13.13 encompassing ESPL1, encoding separase, an enzyme that cleaves the cohesin ring. Three de novo mutations were identified in ANKRD11 demonstrating a phenotypic overlap with KBG syndrome. To estimate the number of undetected mosaic cases we used recursive partitioning to identify discriminating features in the NIPBL-positive subgroup. Filtering of the mutation-negative group on these features classified at least 18% as ‘NIPBL-like’. A computer composition of the average face of this NIPBL-like subgroup was also more typical in appearance than that of all others in the mutation-negative group supporting the existence of undetected mosaic cases. Conclusions Future diagnostic testing in ‘mutation-negative’ CdLS thus merits deeper sequencing of multiple DNA samples derived from different tissues. PMID:25125236

  14. Proteomics of the Radioresistant Phenotype in Head-and-Neck Cancer: Gp96 as a Novel Prediction Marker and Sensitizing Target for Radiotherapy

    SciTech Connect

    Lin, Ting-Yang; Chang, Joseph Tung-Chieh; Wang, Hung-Ming

    2010-09-01

    Purpose: Radiotherapy is an integral part of the treatment modality for head-neck cancer (HNC), but in some cases the disease is radioresistant. We designed this study to identify molecules that may be involved in this resistance. Methods and Materials: Two radioresistant sublines were established by fractionated irradiation of the HNC cell lines, to determine differentially proteins between parental and radioresistant cells. Proteomic analysis and reverse-transcription polymerase chain reaction were used to identify and confirm the differential proteins. The siRNA knockdown experiments were applied to examine cellular functions of a radioresistant gene, with investigation of the alterations in colonogenic survival, cell cycle status, and reactive oxygen species levels. Xenografted mouse tumors were studied to validate the results. Results: IN all, 64 proteins were identified as being potentially associated with radioresistance, which are involved in several cellular pathways, including regulation of stimulus response, cell apoptosis, and glycolysis. Six genes were confirmed to be differentially expressed in both radioresistant sublines, with Gp96, Grp78, HSP60, Rab40B, and GDF-15 upregulated, and annexin V downregulated. Gp96 was further investigated for its functions in response to radiation. Gp96-siRNA transfectants displayed a radiation-induced growth delay, reduction in colonogenic survival, increased cellular reactive oxygen species levels, and increased proportion of the cells in the G2/M phase. Xenograft mice administered Gp96-siRNA showed significantly enhanced growth suppression in comparison with radiation treatment alone (p = 0.009). Conclusions: We identified 64 proteins and verified 6 genes that are potentially involved in the radioresistant phenotype. We further demonstrated that Gp96 knockdown enhances radiosensitivity both in cells and in vivo, which may lead to a better prognosis of HNC treatment.

  15. Qualitative Genetics - Examples from Soybean and Other Crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Qualitative genetics, also known as Mendelian genetics or transmission genetics, refers to those genetic traits that have a distinct appearance (phenotype) and are controlled by one or several genes. Examples of qualitative genetics include response to abiotic and biotic stresses, and anatomical, m...

  16. Qualitative genetics - examples from soybean and other crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Qualitative genetics, also known as Mendelian genetics or transmission genetics, refers to those genetic traits that have a distinct appearance (phenotype) and are controlled by one or few genes. Examples of qualitative genetics include response to abiotic and biotic stresses, and anatomical, morpho...

  17. Skin metabolism of aminophenols: Human keratinocytes as a suitable in vitro model to qualitatively predict the dermal transformation of 4-amino-2-hydroxytoluene in vivo

    SciTech Connect

    Goebel, C. Hewitt, N.J.; Kunze, G.; Wenker, M.; Hein, D.W.; Beck, H.; Skare, J.

    2009-02-15

    4-Amino-2-hydroxytolune (AHT) is an aromatic amine ingredient in oxidative hair colouring products. As skin contact occurs during hair dyeing, characterisation of dermal metabolism is important for the safety assessment of this chemical class. We have compared the metabolism of AHT in the human keratinocyte cell line HaCaT with that observed ex-vivo in human skin and in vivo (topical application versus oral (p.o.) and intravenous (i.v.) route). Three major metabolites of AHT were excreted, i.e. N-acetyl-AHT, AHT-sulfate and AHT-glucuronide. When 12.5 mg/kg AHT was applied topically, the relative amounts of each metabolite were altered such that N-acetyl-AHT product was the major metabolite (66% of the dose in comparison with 37% and 32% of the same applied dose after i.v. and p.o. administration, respectively). N-acetylated products were the only metabolites detected in HaCaT cells and ex-vivo whole human skin discs for AHT and p-aminophenol (PAP), an aromatic amine known to undergo N-acetylation in vivo. Since N-acetyltransferase 1 (NAT1) is the responsible enzyme, kinetics of AHT was further compared to the standard NAT1 substrate p-aminobenzoic acid (PABA) in the HaCaT model revealing similar values for K{sub m} and V{sub max}. In conclusion NAT1 dependent dermal N-acetylation of AHT represents a 'first-pass' metabolism effect in the skin prior to entering the systemic circulation. Since the HaCaT cell model represents a suitable in vitro assay for addressing the qualitative contribution of the skin to the metabolism of topically-applied aromatic amines it may contribute to a reduction in animal testing.

  18. Melanoma-specific MHC-II expression represents a tumour-autonomous phenotype and predicts response to anti-PD-1/PD-L1 therapy

    PubMed Central

    Johnson, Douglas B.; Estrada, Monica V.; Salgado, Roberto; Sanchez, Violeta; Doxie, Deon B.; Opalenik, Susan R.; Vilgelm, Anna E.; Feld, Emily; Johnson, Adam S.; Greenplate, Allison R.; Sanders, Melinda E.; Lovly, Christine M.; Frederick, Dennie T.; Kelley, Mark C.; Richmond, Ann; Irish, Jonathan M.; Shyr, Yu; Sullivan, Ryan J.; Puzanov, Igor; Sosman, Jeffrey A.; Balko, Justin M.

    2016-01-01

    Anti-PD-1 therapy yields objective clinical responses in 30–40% of advanced melanoma patients. Since most patients do not respond, predictive biomarkers to guide treatment selection are needed. We hypothesize that MHC-I/II expression is required for tumour antigen presentation and may predict anti-PD-1 therapy response. In this study, across 60 melanoma cell lines, we find bimodal expression patterns of MHC-II, while MHC-I expression was ubiquitous. A unique subset of melanomas are capable of expressing MHC-II under basal or IFNγ-stimulated conditions. Using pathway analysis, we show that MHC-II(+) cell lines demonstrate signatures of ‘PD-1 signalling', ‘allograft rejection' and ‘T-cell receptor signalling', among others. In two independent cohorts of anti-PD-1-treated melanoma patients, MHC-II positivity on tumour cells is associated with therapeutic response, progression-free and overall survival, as well as CD4+ and CD8+ tumour infiltrate. MHC-II+ tumours can be identified by melanoma-specific immunohistochemistry using commercially available antibodies for HLA-DR to improve anti-PD-1 patient selection. PMID:26822383

  19. Association genetics of oleoresin flow in loblolly pine: discovering genes and predicting phenotype for improved resistance to bark beetles and bioenergy potential.

    PubMed

    Westbrook, Jared W; Resende, Marcio F R; Munoz, Patricio; Walker, Alejandro R; Wegrzyn, Jill L; Nelson, C Dana; Neale, David B; Kirst, Matias; Huber, Dudley A; Gezan, Salvador A; Peter, Gary F; Davis, John M

    2013-07-01

    Rapidly enhancing oleoresin production in conifer stems through genomic selection and genetic engineering may increase resistance to bark beetles and terpenoid yield for liquid biofuels. We integrated association genetic and genomic prediction analyses of oleoresin flow (g 24 h(-1)) using 4854 single nucleotide polymorphisms (SNPs) in expressed genes within a pedigreed population of loblolly pine (Pinus taeda) that was clonally replicated at three sites in the southeastern United States. Additive genetic variation in oleoresin flow (h(2) ≈ 0.12-0.30) was strongly correlated between years in which precipitation varied (r(a) ≈ 0.95), while the genetic correlation between sites declined from 0.8 to 0.37 with increasing differences in soil and climate among sites. A total of 231 SNPs were significantly associated with oleoresin flow, of which 81% were specific to individual sites. SNPs in sequences similar to ethylene signaling proteins, ABC transporters, and diterpenoid hydroxylases were associated with oleoresin flow across sites. Despite this complex genetic architecture, we developed a genomic prediction model to accelerate breeding for enhanced oleoresin flow that is robust to environmental variation. Results imply that breeding could increase oleoresin flow 1.5- to 2.4-fold in one generation. PMID:23534834

  20. Evolution of phenotypic plasticity in colonizing species.

    PubMed

    Lande, Russell

    2015-05-01

    I elaborate an hypothesis to explain inconsistent empirical findings comparing phenotypic plasticity in colonizing populations or species with plasticity from their native or ancestral range. Quantitative genetic theory on the evolution of plasticity reveals that colonization of a novel environment can cause a transient increase in plasticity: a rapid initial increase in plasticity accelerates evolution of a new optimal phenotype, followed by slow genetic assimilation of the new phenotype and reduction of plasticity. An association of colonization with increased plasticity depends on the difference in the optimal phenotype between ancestral and colonized environments, the difference in mean, variance and predictability of the environment, the cost of plasticity, and the time elapsed since colonization. The relative importance of these parameters depends on whether a phenotypic character develops by one-shot plasticity to a constant adult phenotype or by labile plasticity involving continuous and reversible development throughout adult life. PMID:25558898

  1. System monitoring and diagnosis with qualitative models

    NASA Technical Reports Server (NTRS)

    Kuipers, Benjamin

    1991-01-01

    A substantial foundation of tools for model-based reasoning with incomplete knowledge was developed: QSIM (a qualitative simulation program) and its extensions for qualitative simulation; Q2, Q3 and their successors for quantitative reasoning on a qualitative framework; and the CC (component-connection) and QPC (Qualitative Process Theory) model compilers for building QSIM QDE (qualitative differential equation) models starting from different ontological assumptions. Other model-compilers for QDE's, e.g., using bond graphs or compartmental models, have been developed elsewhere. These model-building tools will support automatic construction of qualitative models from physical specifications, and further research into selection of appropriate modeling viewpoints. For monitoring and diagnosis, plausible hypotheses are unified against observations to strengthen or refute the predicted behaviors. In MIMIC (Model Integration via Mesh Interpolation Coefficients), multiple hypothesized models of the system are tracked in parallel in order to reduce the 'missing model' problem. Each model begins as a qualitative model, and is unified with a priori quantitative knowledge and with the stream of incoming observational data. When the model/data unification yields a contradiction, the model is refuted. When there is no contradiction, the predictions of the model are progressively strengthened, for use in procedure planning and differential diagnosis. Only under a qualitative level of description can a finite set of models guarantee the complete coverage necessary for this performance. The results of this research are presented in several publications. Abstracts of these published papers are presented along with abtracts of papers representing work that was synergistic with the NASA grant but funded otherwise. These 28 papers include but are not limited to: 'Combined qualitative and numerical simulation with Q3'; 'Comparative analysis and qualitative integral representations

  2. Social-Cognition and the Broad Autism Phenotype: Identifying Genetically Meaningful Phenotypes

    ERIC Educational Resources Information Center

    Losh, Molly; Piven, Joseph

    2007-01-01

    Background: Strong evidence from twin and family studies suggests that the genetic liability to autism may be expressed through personality and language characteristics qualitatively similar, but more subtly expressed than those defining the full syndrome. This study examined behavioral features of this "broad autism phenotype" (BAP) in relation…

  3. Circulating immune cell phenotype can predict the outcome of lenalidomide plus low-dose dexamethasone treatment in patients with refractory/relapsed multiple myeloma.

    PubMed

    Lee, Sung-Eun; Lim, Ji-Young; Ryu, Da-Bin; Kim, Tae Woo; Yoon, Jae-Ho; Cho, Byung-Sik; Eom, Ki-Seong; Kim, Yoo-Jin; Kim, Hee-Je; Lee, Seok; Cho, Seok-Goo; Kim, Dong-Wook; Lee, Jong-Wook; Min, Woo-Sung; Kim, Myungshin; Min, Chang-Ki

    2016-08-01

    Although the antimyeloma effect of lenalidomide is associated with activation of the immune system, the exact in vivo immunomodulatory mechanisms of lenalidomide combined with low-dose dexamethasone (Len-dex) in refractory/relapsed multiple myeloma (RRMM) patients remain unclear. In this study, we analyzed the association between immune cell populations and clinical outcomes in patients receiving Len-dex for the treatment of RRMM. Peripheral blood samples from 90 RRMM patients were taken on day 1 of cycles 1 (baseline), 2, 3, and 4 of Len-dex therapy. Peripheral blood CD3(+), CD4(+), and CD8(+) cell frequencies were significantly decreased by 3 cycles of therapy, whereas NK cell frequency was significantly increased after the 3rd cycle. For the myeloid-derived suppressor cell (MDSC) subset, the frequency of granulocytic MDSCs transiently increased after the 1st cycle, whereas there was an increase in monocytic MDSC (M-MDSC) frequency after the 1st and 3rd cycles. Among 81 evaluable patients, failure to achieve a response of VGPR or greater was associated with a decrease in CD8(+) cell frequency and increase in M-MDSC frequency after 3 cycles of Len-dex treatment. A high proportion of natural killer T (NKT)-like cells (CD3(+)/CD56(+)) prior to Len-dex treatment might predict a longer time to progression. In addition, patients with a smaller decrease in the frequency of both CD3(+) cells and CD8(+) cells by 3 cycles exhibited a longer time to the next treatment. These results demonstrated that early changes in immune cell subsets are useful immunologic indicators of the efficacy of Len-dex treatment in RRMM. PMID:27342591

  4. Loss of Secreted Frizzled-Related Protein 4 Correlates with an Aggressive Phenotype and Predicts Poor Outcome in Ovarian Cancer Patients

    PubMed Central

    Nixdorf, Sheri; Ford, Caroline E.; Olivier, Jake; Caduff, Rosmarie; Scurry, James P.; Guertler, Rea; Hornung, Daniela; Mueller, Renato; Fink, Daniel A.; Hacker, Neville F.; Heinzelmann-Schwarz, Viola A.

    2012-01-01

    Background Activation of the Wnt signaling pathway is implicated in aberrant cellular proliferation in various cancers. In 40% of endometrioid ovarian cancers, constitutive activation of the pathway is due to oncogenic mutations in β-catenin or other inactivating mutations in key negative regulators. Secreted frizzled-related protein 4 (SFRP4) has been proposed to have inhibitory activity through binding and sequestering Wnt ligands. Methodology/Principal Findings We performed RT-qPCR and Western-blotting in primary cultures and ovarian cell lines for SFRP4 and its key downstream regulators activated β-catenin, β-catenin and GSK3β. SFRP4 was then examined by immunohistochemistry in a cohort of 721 patients and due to its proposed secretory function, in plasma, presenting the first ELISA for SFRP4. SFRP4 was most highly expressed in tubal epithelium and decreased with malignant transformation, both on RNA and on protein level, where it was even more profound in the membrane fraction (p<0.0001). SFRP4 was expressed on the protein level in all histotypes of ovarian cancer but was decreased from borderline tumors to cancers and with loss of cellular differentiation. Loss of membrane expression was an independent predictor of poor survival in ovarian cancer patients (p = 0.02 unadjusted; p = 0.089 adjusted), which increased the risk of a patient to die from this disease by the factor 1.8. Conclusions/Significance Our results support a role for SFRP4 as a tumor suppressor gene in ovarian cancers via inhibition of the Wnt signaling pathway. This has not only predictive implications but could also facilitate a therapeutic role using epigenetic targets. PMID:22363760

  5. Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Crop Injury Profile as a Function of Cropping Practices, and the Abiotic and Biotic Environment. I. Conceptual Bases

    PubMed Central

    Aubertot, Jean-Noël; Robin, Marie-Hélène

    2013-01-01

    The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop. PMID:24019908

  6. Vascular phenotype identification and anti-angiogenic treatment recommendation: A pseudo-multiscale mathematical model of angiogenesis.

    PubMed

    Hutchinson, L G; Gaffney, E A; Maini, P K; Wagg, J; Phipps, A; Byrne, H M

    2016-06-01

    The development of anti-angiogenic drugs for cancer therapy has yielded some promising candidates, but novel approaches for interventions to angiogenesis have led to disappointing results. In addition, there is a shortage of biomarkers that are predictive of response to anti-angiogenic treatments. Consequently, the complex biochemical and physiological basis for tumour angiogenesis remains incompletely understood. We have adopted a mathematical approach to address these issues, formulating a spatially averaged multiscale model that couples the dynamics of VEGF, Ang1, Ang2 and PDGF, with those of mature and immature endothelial cells and pericyte cells. The model reproduces qualitative experimental results regarding pericyte coverage of vessels after treatment by anti-Ang2, anti-VEGF and combination anti-VEGF/anti-Ang2 antibodies. We used the steady state behaviours of the model to characterise angiogenic and non-angiogenic vascular phenotypes, and used mechanistic perturbations representing hypothetical anti-angiogenic treatments to generate testable hypotheses regarding transitions to non-angiogenic phenotypes that depend on the pre-treatment vascular phenotype. Additionally, we predicted a synergistic effect between anti-VEGF and anti-Ang2 treatments when applied to an immature pre-treatment vascular phenotype, but not when applied to a normalised angiogenic pre-treatment phenotype. Based on these findings, we conclude that changes in vascular phenotype are predicted to be useful as an experimental biomarker of response to treatment. Further, our analysis illustrates the potential value of non-spatial mathematical models for generating tractable predictions regarding the action of anti-angiogenic therapies. PMID:26987523

  7. Qualitative Student Models.

    ERIC Educational Resources Information Center

    Clancey, William J.

    The concept of a qualitative model is used as the focus of this review of qualitative student models in order to compare alternative computational models and to contrast domain requirements. The report is divided into eight sections: (1) Origins and Goals (adaptive instruction, qualitative models of processes, components of an artificial…

  8. Effectively Communicating Qualitative Research

    ERIC Educational Resources Information Center

    Ponterotto, Joseph G.; Grieger, Ingrid

    2007-01-01

    This article is a guide for counseling researchers wishing to communicate the methods and results of their qualitative research to varied audiences. The authors posit that the first step in effectively communicating qualitative research is the development of strong qualitative research skills. To this end, the authors review a process model for…

  9. Requiem for Qualitative Analysis.

    ERIC Educational Resources Information Center

    Journal of Chemical Education, 1983

    1983-01-01

    Five papers presented at the Seventh Biennial Conference on Chemical Education (Stillwater, Oklahoma 1982) focused on qualitative analysis curricula and instruction. Topics included benefits of qualitative analysis, use of iodo/bromo-complexes in qualitative analysis schemes, lecture demonstrations, and brief descriptions of three courses. (JN)

  10. Quantifying and predicting Drosophila larvae crawling phenotypes

    PubMed Central

    Günther, Maximilian N.; Nettesheim, Guilherme; Shubeita, George T.

    2016-01-01

    The fruit fly Drosophila melanogaster is a widely used model for cell biology, development, disease, and neuroscience. The fly’s power as a genetic model for disease and neuroscience can be augmented by a quantitative description of its behavior. Here we show that we can accurately account for the complex and unique crawling patterns exhibited by individual Drosophila larvae using a small set of four parameters obtained from the trajectories of a few crawling larvae. The values of these parameters change for larvae from different genetic mutants, as we demonstrate for fly models of Alzheimer’s disease and the Fragile X syndrome, allowing applications such as genetic or drug screens. Using the quantitative model of larval crawling developed here we use the mutant-specific parameters to robustly simulate larval crawling, which allows estimating the feasibility of laborious experimental assays and aids in their design. PMID:27323901

  11. Quantifying and predicting Drosophila larvae crawling phenotypes.

    PubMed

    Günther, Maximilian N; Nettesheim, Guilherme; Shubeita, George T

    2016-01-01

    The fruit fly Drosophila melanogaster is a widely used model for cell biology, development, disease, and neuroscience. The fly's power as a genetic model for disease and neuroscience can be augmented by a quantitative description of its behavior. Here we show that we can accurately account for the complex and unique crawling patterns exhibited by individual Drosophila larvae using a small set of four parameters obtained from the trajectories of a few crawling larvae. The values of these parameters change for larvae from different genetic mutants, as we demonstrate for fly models of Alzheimer's disease and the Fragile X syndrome, allowing applications such as genetic or drug screens. Using the quantitative model of larval crawling developed here we use the mutant-specific parameters to robustly simulate larval crawling, which allows estimating the feasibility of laborious experimental assays and aids in their design. PMID:27323901

  12. Adaptive evolution of molecular phenotypes

    NASA Astrophysics Data System (ADS)

    Held, Torsten; Nourmohammad, Armita; Lässig, Michael

    2014-09-01

    Molecular phenotypes link genomic information with organismic functions, fitness, and evolution. Quantitative traits are complex phenotypes that depend on multiple genomic loci. In this paper, we study the adaptive evolution of a quantitative trait under time-dependent selection, which arises from environmental changes or through fitness interactions with other co-evolving phenotypes. We analyze a model of trait evolution under mutations and genetic drift in a single-peak fitness seascape. The fitness peak performs a constrained random walk in the trait amplitude, which determines the time-dependent trait optimum in a given population. We derive analytical expressions for the distribution of the time-dependent trait divergence between populations and of the trait diversity within populations. Based on this solution, we develop a method to infer adaptive evolution of quantitative traits. Specifically, we show that the ratio of the average trait divergence and the diversity is a universal function of evolutionary time, which predicts the stabilizing strength and the driving rate of the fitness seascape. From an information-theoretic point of view, this function measures the macro-evolutionary entropy in a population ensemble, which determines the predictability of the evolutionary process. Our solution also quantifies two key characteristics of adapting populations: the cumulative fitness flux, which measures the total amount of adaptation, and the adaptive load, which is the fitness cost due to a population's lag behind the fitness peak.

  13. Fisher’s Geometrical Model Emerges as a Property of Complex Integrated Phenotypic Networks

    PubMed Central

    Martin, Guillaume

    2014-01-01

    Models relating phenotype space to fitness (phenotype–fitness landscapes) have seen important developments recently. They can roughly be divided into mechanistic models (e.g., metabolic networks) and more heuristic models like Fisher’s geometrical model. Each has its own drawbacks, but both yield testable predictions on how the context (genomic background or environment) affects the distribution of mutation effects on fitness and thus adaptation. Both have received some empirical validation. This article aims at bridging the gap between these approaches. A derivation of the Fisher model “from first principles” is proposed, where the basic assumptions emerge from a more general model, inspired by mechanistic networks. I start from a general phenotypic network relating unspecified phenotypic traits and fitness. A limited set of qualitative assumptions is then imposed, mostly corresponding to known features of phenotypic networks: a large set of traits is pleiotropically affected by mutations and determines a much smaller set of traits under optimizing selection. Otherwise, the model remains fairly general regarding the phenotypic processes involved or the distribution of mutation effects affecting the network. A statistical treatment and a local approximation close to a fitness optimum yield a landscape that is effectively the isotropic Fisher model or its extension with a single dominant phenotypic direction. The fit of the resulting alternative distributions is illustrated in an empirical data set. These results bear implications on the validity of Fisher’s model’s assumptions and on which features of mutation fitness effects may vary (or not) across genomic or environmental contexts. PMID:24583582

  14. Joint association analysis of bivariate quantitative and qualitative traits.

    PubMed

    Yuan, Mengdie; Diao, Guoqing

    2011-01-01

    Univariate genome-wide association analysis of quantitative and qualitative traits has been investigated extensively in the literature. In the presence of correlated phenotypes, it is more intuitive to analyze all phenotypes simultaneously. We describe an efficient likelihood-based approach for the joint association analysis of quantitative and qualitative traits in unrelated individuals. We assume a probit model for the qualitative trait, under which an unobserved latent variable and a prespecified threshold determine the value of the qualitative trait. To jointly model the quantitative and qualitative traits, we assume that the quantitative trait and the latent variable follow a bivariate normal distribution. The latent variable is allowed to be correlated with the quantitative phenotype. Simultaneous modeling of the quantitative and qualitative traits allows us to make more precise inference on the pleiotropic genetic effects. We derive likelihood ratio tests for the testing of genetic effects. An application to the Genetic Analysis Workshop 17 data is provided. The new method yields reasonable power and meaningful results for the joint association analysis of the quantitative trait Q1 and the qualitative trait disease status at SNPs with not too small MAF. PMID:22373162

  15. Qualitative assessment of vaginal microflora during use of tampons of various compositions.

    PubMed

    Onderdonk, A B; Zamarchi, G R; Rodriguez, M L; Hirsch, M L; Muñoz, A; Kass, E H

    1987-12-01

    The effect of vaginal tampons on the microbial flora during menstruation has recently been studied by several investigators. However, little information regarding the qualitative effects attributable to particular tampon fibers is available. The purpose of the present study was to compare the effects of polyacrylate rayon tampons and cotton-viscose rayon blend tampons on the qualitative bacterial counts obtained from tampons and concomitant vaginal swabs and to determine whether either of these tampon types alters the qualitative makeup of the vaginal microflora when compared with the microflora in the same women using all-cotton tampons or external catamenial pads. Tampon and swab samples were obtained as described previously (A. B. Onderdonk, G. R. Zamarchi, M. L. Rodriguez, M. L. Hirsch, A. Muñoz, and E. H. Kass, Appl. Environ. Microbiol. 53:2774-2778). The genus and species of the six dominant bacterial species in each sample were identified, if possible. A statistical evaluation of the qualitative makeup of the microflora revealed that the same numerically dominant phenotypes were present regardless of sample type, sample time, or catamenial product. Predictable changes in total numbers among the dominant species were also noted when the data were evaluated by day of menstrual cycle. The correlation between the total numbers of each dominant species present was evaluated by day of cycle, and the findings are discussed. PMID:3435143

  16. Significance of Lewis phenotyping using saliva and gastric tissue: comparison with the Lewis phenotype inferred from Lewis and secretor genotypes.

    PubMed

    Hong, Yun Ji; Hwang, Sang Mee; Kim, Taek Soo; Song, Eun Young; Park, Kyoung Un; Song, Junghan; Han, Kyou-Sup

    2014-01-01

    Lewis phenotypes using various types of specimen were compared with the Lewis phenotype predicted from Lewis and Secretor genotypes. This is the first logical step in explaining the association between the Lewis expression and Helicobacter pylori. We performed a study of the followings on 209 patients who underwent routine gastroscopy: erythrocyte and saliva Lewis phenotyping, gastric Lewis phenotyping by the tissue array, and the Lewis and Secretor genes genotyping. The results of phenotyping were as follows [Le(a-b-), Le(a+b-), Le(a-b+), and Le(a+b+), respectively, in order]: erythrocyte (12.4%, 25.8%, 61.2%, and 0.5%); saliva (2.4%, 27.3%, 70.3%, and 0.0%); gastric mucosa (8.1%, 6.7%, 45.5%, and 39.7%). The frequency of Le, le (59/508) , le (59/1067) , and le (59) alleles was 74.6%, 21.3%, 3.1%, and 1.0%, respectively, among 418 alleles. The saliva Lewis phenotype was completely consistent with the Lewis phenotype inferred from Lewis and Secretor genotypes, but that of gastric mucosa could not be predicted from genotypes. Lewis phenotyping using erythrocytes is only adequate for transfusion needs. Saliva testing for the Lewis phenotype is a more reliable method for determining the peripheral Lewis phenotype of an individual and the gastric Lewis phenotype must be used for the study on the association between Helicobacter pylori and the Lewis phenotype. PMID:24783214

  17. Novel phenotypes of prediabetes?

    PubMed

    Häring, Hans-Ulrich

    2016-09-01

    This article describes phenotypes observed in a prediabetic population (i.e. a population with increased risk for type 2 diabetes) from data collected at the University hospital of Tübingen. We discuss the impact of genetic variation on insulin secretion, in particular the effect on compensatory hypersecretion, and the incretin-resistant phenotype of carriers of the gene variant TCF7L2 is described. Imaging studies used to characterise subphenotypes of fat distribution, metabolically healthy obesity and metabolically unhealthy obesity are described. Also discussed are ectopic fat stores in liver and pancreas that determine the phenotype of metabolically healthy and unhealthy fatty liver and the recently recognised phenotype of fatty pancreas. The metabolic impact of perivascular adipose tissue and pancreatic fat is discussed. The role of hepatokines, particularly that of fetuin-A, in the crosstalk between these organs is described. Finally, the role of brain insulin resistance in the development of the different prediabetes phenotypes is discussed. PMID:27344314

  18. Evolution of molecular phenotypes under stabilizing selection

    NASA Astrophysics Data System (ADS)

    Nourmohammad, Armita; Schiffels, Stephan; Lässig, Michael

    2013-01-01

    Molecular phenotypes are important links between genomic information and organismic functions, fitness, and evolution. Complex phenotypes, which are also called quantitative traits, often depend on multiple genomic loci. Their evolution builds on genome evolution in a complicated way, which involves selection, genetic drift, mutations and recombination. Here we develop a coarse-grained evolutionary statistics for phenotypes, which decouples from details of the underlying genotypes. We derive approximate evolution equations for the distribution of phenotype values within and across populations. This dynamics covers evolutionary processes at high and low recombination rates, that is, it applies to sexual and asexual populations. In a fitness landscape with a single optimal phenotype value, the phenotypic diversity within populations and the divergence between populations reach evolutionary equilibria, which describe stabilizing selection. We compute the equilibrium distributions of both quantities analytically and we show that the ratio of mean divergence and diversity depends on the strength of selection in a universal way: it is largely independent of the phenotype’s genomic encoding and of the recombination rate. This establishes a new method for the inference of selection on molecular phenotypes beyond the genome level. We discuss the implications of our findings for the predictability of evolutionary processes.

  19. Teaching Qualitative Research

    ERIC Educational Resources Information Center

    Delyser, Dydia

    2008-01-01

    Explicitly qualitative research has never before been so popular in human geography, and this article hopes to encourage more graduate students and faculty members to undertake the teaching of qualitative geography. The article describes one such course for graduate students, highlighting its challenges and rewards, and focusing on exercises…

  20. Qualitative Studies: Historiographical Antecedents.

    ERIC Educational Resources Information Center

    Mills, Rilla Dean

    This paper provides an overview of qualitative studies' antecedents among historiographers and of the positivist tide which nearly engulfed them. Humans live by interpretations. The task of social science--the basic task of qualitative studies--is to study these interpretations so that we can better understand the meanings which people use to…

  1. Visualizing Qualitative Information

    ERIC Educational Resources Information Center

    Slone, Debra J.

    2009-01-01

    The abundance of qualitative data in today's society and the need to easily scrutinize, digest, and share this information calls for effective visualization and analysis tools. Yet, no existing qualitative tools have the analytic power, visual effectiveness, and universality of familiar quantitative instruments like bar charts, scatter-plots, and…

  2. Statistical models for trisomic phenotypes

    SciTech Connect

    Lamb, N.E.; Sherman, S.L.; Feingold, E.

    1996-01-01

    Certain genetic disorders are rare in the general population but more common in individuals with specific trisomies, which suggests that the genes involved in the etiology of these disorders may be located on the trisomic chromosome. As with all aneuploid syndromes, however, a considerable degree of variation exists within each phenotype so that any given trait is present only among a subset of the trisomic population. We have previously presented a simple gene-dosage model to explain this phenotypic variation and developed a strategy to map genes for such traits. The mapping strategy does not depend on the simple model but works in theory under any model that predicts that affected individuals have an increased likelihood of disomic homozygosity at the trait locus. This paper explores the robustness of our mapping method by investigating what kinds of models give an expected increase in disomic homozygosity. We describe a number of basic statistical models for trisomic phenotypes. Some of these are logical extensions of standard models for disomic phenotypes, and some are more specific to trisomy. Where possible, we discuss genetic mechanisms applicable to each model. We investigate which models and which parameter values give an expected increase in disomic homozygosity in individuals with the trait. Finally, we determine the sample sizes required to identify the increased disomic homozygosity under each model. Most of the models we explore yield detectable increases in disomic homozygosity for some reasonable range of parameter values, usually corresponding to smaller trait frequencies. It therefore appears that our mapping method should be effective for a wide variety of moderately infrequent traits, even though the exact mode of inheritance is unlikely to be known. 21 refs., 8 figs., 1 tab.

  3. Sampling in Qualitative Research

    PubMed Central

    LUBORSKY, MARK R.; RUBINSTEIN, ROBERT L.

    2011-01-01

    In gerontology the most recognized and elaborate discourse about sampling is generally thought to be in quantitative research associated with survey research and medical research. But sampling has long been a central concern in the social and humanistic inquiry, albeit in a different guise suited to the different goals. There is a need for more explicit discussion of qualitative sampling issues. This article will outline the guiding principles and rationales, features, and practices of sampling in qualitative research. It then describes common questions about sampling in qualitative research. In conclusion it proposes the concept of qualitative clarity as a set of principles (analogous to statistical power) to guide assessments of qualitative sampling in a particular study or proposal. PMID:22058580

  4. Phenotypes of childhood asthma: are they real?

    PubMed

    Spycher, B D; Silverman, M; Kuehni, C E

    2010-08-01

    It has been suggested that there are several distinct phenotypes of childhood asthma or childhood wheezing. Here, we review the research relating to these phenotypes, with a focus on the methods used to define and validate them. Childhood wheezing disorders manifest themselves in a range of observable (phenotypic) features such as lung function, bronchial responsiveness, atopy and a highly variable time course (prognosis). The underlying causes are not sufficiently understood to define disease entities based on aetiology. Nevertheless, there is a need for a classification that would (i) facilitate research into aetiology and pathophysiology, (ii) allow targeted treatment and preventive measures and (iii) improve the prediction of long-term outcome. Classical attempts to define phenotypes have been one-dimensional, relying on few or single features such as triggers (exclusive viral wheeze vs. multiple trigger wheeze) or time course (early transient wheeze, persistent and late onset wheeze). These definitions are simple but essentially subjective. Recently, a multi-dimensional approach has been adopted. This approach is based on a wide range of features and relies on multivariate methods such as cluster or latent class analysis. Phenotypes identified in this manner are more complex but arguably more objective. Although phenotypes have an undisputed standing in current research on childhood asthma and wheezing, there is confusion about the meaning of the term 'phenotype' causing much circular debate. If phenotypes are meant to represent 'real' underlying disease entities rather than superficial features, there is a need for validation and harmonization of definitions. The multi-dimensional approach allows validation by replication across different populations and may contribute to a more reliable classification of childhood wheezing disorders and to improved precision of research relying on phenotype recognition, particularly in genetics. Ultimately, the underlying

  5. First insights into the genotype–phenotype map of phenotypic stability in rye

    PubMed Central

    Wang, Yu; Mette, Michael Florian; Miedaner, Thomas; Wilde, Peer; Reif, Jochen C.; Zhao, Yusheng

    2015-01-01

    Improving phenotypic stability of crops is pivotal for coping with the detrimental impacts of climate change. The goal of this study was to gain first insights into the genetic architecture of phenotypic stability in cereals. To this end, we determined grain yield, thousand kernel weight, test weight, falling number, and both protein and soluble pentosan content for two large bi-parental rye populations connected through one common parent and grown in multi-environmental field trials involving more than 15 000 yield plots. Based on these extensive phenotypic data, we calculated parameters for static and dynamic phenotypic stability of the different traits and applied linkage mapping using whole-genome molecular marker profiles. While we observed an absence of large-effect quantitative trait loci (QTLs) underlying yield stability, large and stable QTLs were found for phenotypic stability of test weight, soluble pentosan content, and falling number. Applying genome-wide selection, which in contrast to marker-assisted selection also takes into account loci with small-effect sizes, considerably increased the accuracy of prediction of phenotypic stability for all traits by exploiting both genetic relatedness and linkage between single-nucleotide polymorphisms and QTLs. We conclude that breeding for crop phenotypic stability can be improved in related populations using genomic selection approaches established upon extensive phenotypic data. PMID:25873667

  6. Macrophage phenotypes in atherosclerosis.

    PubMed

    Colin, Sophie; Chinetti-Gbaguidi, Giulia; Staels, Bart

    2014-11-01

    Initiation and progression of atherosclerosis depend on local inflammation and accumulation of lipids in the vascular wall. Although many cells are involved in the development and progression of atherosclerosis, macrophages are fundamental contributors. For nearly a decade, the phenotypic heterogeneity and plasticity of macrophages has been studied. In atherosclerotic lesions, macrophages are submitted to a large variety of micro-environmental signals, such as oxidized lipids and cytokines, which influence the phenotypic polarization and activation of macrophages resulting in a dynamic plasticity. The macrophage phenotype spectrum is characterized, at the extremes, by the classical M1 macrophages induced by T-helper 1 (Th-1) cytokines and by the alternative M2 macrophages induced by Th-2 cytokines. M2 macrophages can be further classified into M2a, M2b, M2c, and M2d subtypes. More recently, additional plaque-specific macrophage phenotypes have been identified, termed as Mox, Mhem, and M4. Understanding the mechanisms and functional consequences of the phenotypic heterogeneity of macrophages will contribute to determine their potential role in lesion development and plaque stability. Furthermore, research on macrophage plasticity could lead to novel therapeutic approaches to counteract cardiovascular diseases such as atherosclerosis. The present review summarizes our current knowledge on macrophage subsets in atherosclerotic plaques and mechanism behind the modulation of the macrophage phenotype. PMID:25319333

  7. Comparison of predicted susceptibility between genotype and virtual phenotype HIV drug resistance interpretation systems among treatment-naive HIV-infected patients in Asia: TASER-M cohort analysis

    PubMed Central

    2012-01-01

    Background Accurate interpretation of HIV drug resistance (HIVDR) testing is challenging, yet important for patient care. We compared genotyping interpretation, based on the Stanford University HIV Drug Resistance Database (Stanford HIVdb), and virtual phenotyping, based on the Janssen Diagnostics BVBA’s vircoTYPE™ HIV-1, and investigated their level of agreement in antiretroviral (ARV) naive patients in Asia, where non-B subtypes predominate. Methods Sequences from 1301 ARV-naive patients enrolled in the TREAT Asia Studies to Evaluate Resistance – Monitoring Study (TASER-M) were analysed by both interpreting systems. Interpretations from both Stanford HIVdb and vircoTYPE™ HIV-1 were initially grouped into 2 levels: susceptible and non-susceptible. Discrepancy was defined as a discordant result between the susceptible and non-susceptible interpretations from the two systems for the same ARV. Further analysis was performed when interpretations from both systems were categorised into 3 levels: susceptible, intermediate and resistant; whereby discrepancies could be categorised as major discrepancies and minor discrepancies. Major discrepancy was defined as having a susceptible result from one system and resistant from the other. Minor discrepancy corresponded to having an intermediate interpretation in one system, with a susceptible or resistant result in the other. The level of agreement was analysed using the prevalence adjusted bias adjusted kappa (PABAK). Results Overall, the agreement was high, with each ARV being in “almost perfect agreement”, using Landis and Koch’s categorisation. Highest discordance was observed for efavirenz (75/1301, 5.8%), all arising from susceptible Stanford HIVdb versus non-susceptible vircoTYPE™ HIV-1 predictions. Protease Inhibitors had highest level of concordance with PABAKs all above 0.99, followed by Nucleoside Reverse Transcriptase Inhibitors with PABAKs above 0.97 and non-NRTIs with the lowest PABAK of 0.88. The

  8. Human Gut-Commensalic Lactobacillus ruminis ATCC 25644 Displays Sortase-Assembled Surface Piliation: Phenotypic Characterization of Its Fimbrial Operon through In Silico Predictive Analysis and Recombinant Expression in Lactococcus lactis

    PubMed Central

    Yu, Xia; Lyytinen, Outi; Kant, Ravi; Åvall-Jääskeläinen, Silja; von Ossowski, Ingemar; Palva, Airi

    2015-01-01

    Sortase-dependent surface pili (or fimbriae) in Gram-positive bacteria are well documented as a key virulence factor for certain harmful opportunistic pathogens. However, it is only recently known that these multi-subunit protein appendages are also belonging to the “friendly” commensals and now, with this new perspective, they have come to be categorized as a niche-adaptation factor as well. In this regard, it was shown earlier that sortase-assembled piliation is a native fixture of two human intestinal commensalics (i.e., Lactobacillus rhamnosus and Bifidobacterium bifidum), and correspondingly where the pili involved have a significant role in cellular adhesion and immunomodulation processes. We now reveal that intestinal indigenous (or autochthonous) Lactobacillus ruminis is another surface-piliated commensal lactobacillar species. Heeding to in silico expectations, the predicted loci for the LrpCBA-called pili are organized tandemly in the L. ruminis genome as a canonical fimbrial operon, which then encodes for three pilin-proteins and a single C-type sortase enzyme. Through electron microscopic means, we showed that these pilus formations are a surface assemblage of tip, basal, and backbone pilin subunits (respectively named LrpC, LrpB, and LrpA) in L. ruminis, and also when expressed recombinantly in Lactococcus lactis. As well, by using the recombinant-piliated lactococci, we could define certain ecologically relevant phenotypic traits, such as the ability to adhere to extracellular matrix proteins and gut epithelial cells, but also to effectuate an induced dampening on Toll-like receptor 2 signaling and interleukin-8 responsiveness in immune-related cells. Within the context of the intestinal microcosm, by wielding such niche-advantageous cell-surface properties the LrpCBA pilus would undoubtedly have a requisite functional role in the colonization dynamics of L. ruminis indigeneity. Our study provides only the second description of a native

  9. Effects of dietary enrichment with a marine oil-based n-3 LCPUFA supplement in sows with predicted birth weight phenotypes on growth performance and carcass quality of offspring.

    PubMed

    Smit, M N; Spencer, J D; Patterson, J L; Dyck, M K; Dixon, W T; Foxcroft, G R

    2015-05-01

    Effects of a marine oil-based n-3 LCPUFA supplement (mLCPUFA) fed from weaning until the end of the next lactation to sows with a predicted low litter birth weight (LBW) phenotype on growth performance and carcass quality of litters born to these sows were studied, based on the hypothesis that LBW litters would benefit most from mLCPUFA supplementation. Sows were allocated to be fed either standard corn/soybean meal-based gestation and lactation diets (CON), or the same diets enriched with 0.5% of the mLCPUFA supplement at the expense of corn. The growth performance from birth until slaughter of the litters with the lowest average birth weight in each treatment (n=24 per treatment) is reported in this paper. At weaning, each litter was split between two nursery pens with three to six pigs per pen. At the end of the 5-week nursery period, two barrows and two gilts from each litter that had individual birth weights closest to their litter average birth weight, were moved to experimental grow-finish pens (barn A), where they were housed as two pigs per pen, sorted by sex within litter. Remaining pigs in each litter were moved to another grow-finish barn (barn B) and kept in mixed-sex pens of up to 10 littermates. After 8 weeks, one of the two pigs in each pen in barn A was relocated to the pens holding their respective littermates in barn B. The remaining barrows and gilts were individually housed in the pens in barn A until slaughter. Maternal mLCPUFA supplementation increased docosahexaenoic acid (DHA) concentration in the brain, liver and Semitendinosus muscle of stillborn pigs (P<0.01), did not affect eicosapentaenoic acid and DHA concentrations in sow serum at the end of lactation, and did not affect average daily gain, average daily feed intake or feed utilization efficiency of the offspring. BW was higher (P<0.01) in the second half of the grow-finish phase in pigs from mLCPUFA sows compared with controls in barn A, where space and competition for feed was

  10. Phenotypic plasticity in two marine snails: constraints superseding life history.

    PubMed

    Hollander, J; Collyer, M L; Adams, D C; Johannesson, K

    2006-11-01

    In organisms encountering predictable environments, fixed development is expected, whereas in organisms that cannot predict their future environment, phenotypic plasticity would be optimal to increase local adaptation. To test this prediction we experimentally compared phenotypic plasticity in two rocky-shore snail species; Littorina saxatilis releasing miniature snails on the shore, and Littorina littorea releasing drifting larvae settling on various shores, expecting L. littorea to show more phenotypic plasticity than L. saxatilis. We compared magnitude and direction of vectors of phenotypic difference in juvenile shell traits after 3 months exposure to different stimuli simulating sheltered and crab-rich shores, or wave-exposed and crab-free shores. Both species showed similar direction and magnitude of vectors of phenotypic difference with minor differences only between ecotypes of the nondispersing species, indicating that plasticity is an evolving trait in L. saxatilis. The lack of a strong plastic response in L. littorea might be explained by limits rather than costs to plasticity. PMID:17040383

  11. Histomorphological Phenotyping of the Adult Mouse Brain.

    PubMed

    Mikhaleva, Anna; Kannan, Meghna; Wagner, Christel; Yalcin, Binnaz

    2016-01-01

    This article describes a series of standard operating procedures for morphological phenotyping of the mouse brain using basic histology. Many histological studies of the mouse brain use qualitative approaches based on what the human eye can detect. Consequently, some phenotypic information may be missed. Here we describe a quantitative approach for the assessment of brain morphology that is simple and robust. A total of 78 measurements are made throughout the brain at specific and well-defined regions, including the cortex, the hippocampus, and the cerebellum. Experimental design and timeline considerations, including strain background effects, the importance of sectioning quality, measurement variability, and efforts to correct human errors are discussed. © 2016 by John Wiley & Sons, Inc. PMID:27584555

  12. Phenotypic plasticity with instantaneous but delayed switches.

    PubMed

    Utz, Margarete; Jeschke, Jonathan M; Loeschcke, Volker; Gabriel, Wilfried

    2014-01-01

    Phenotypic plasticity is a widespread phenomenon, allowing organisms to better adapt to changing environments. Most empirical and theoretical studies are restricted to irreversible plasticity where the expression of a specific phenotype is mostly determined during development. However, reversible plasticity is not uncommon; here, organisms are able to switch back and forth between phenotypes. We present two optimization models for the fitness of (i) non-plastic, (ii) irreversibly plastic, and (iii) reversibly plastic genotypes in a fluctuating environment. In one model, the fitness values of an organism during different life phases act together multiplicatively (so as to consider traits that are related to survival). The other model additionally considers additive effects (corresponding to traits related to fecundity). Both models yield qualitatively similar results. If the only costs of reversible plasticity are due to temporal maladaptation while switching between phenotypes, reversibility is virtually always advantageous over irreversibility, especially for slow environmental fluctuations. If reversibility implies an overall decreased fitness, then irreversibility is advantageous if the environment fluctuates quickly or if stress events last relatively short. Our results are supported by observations from different types of organisms and have implications for many basic and applied research questions, e.g., on invasive alien species. PMID:24041594

  13. HCG blood test - qualitative

    MedlinePlus

    ... qualitative Images Blood test References Lee P, Pincus MR, McPherson RA. Diagnosis and management of cancer using serologic tumor markers. In: McPherson RA, Pincus MR, eds. Henry's Clinical Diagnosis and Management by Laboratory ...

  14. Computers and Qualitative Research.

    ERIC Educational Resources Information Center

    Willis, Jerry; Jost, Muktha

    1999-01-01

    Discusses the use of computers in qualitative research, including sources of information; collaboration; electronic discussion groups; Web sites; Internet search engines; electronic sources of data; data collection; communicating research results; desktop publishing; hypermedia and multimedia documents; electronic publishing; holistic and…

  15. Monozygotic twins with trisomy 18: a report of discordant phenotype.

    PubMed Central

    Schlessel, J S; Brown, W T; Lysikiewicz, A; Schiff, R; Zaslav, A L

    1990-01-01

    The predicted incidence of liveborn monozygotic trisomy 18 twins is one per million births. The first case of liveborn monozygotic trisomy 18 twins was reported in 1989 and we report a second case in which striking phenotypic discordance existed. The probability of monozygotic trisomy 18 twinning and the mechanisms for phenotypic discordance in trisomic twins is discussed. Images PMID:2246775

  16. Qualitative simulation for process modeling and control

    NASA Technical Reports Server (NTRS)

    Dalle Molle, D. T.; Edgar, T. F.

    1989-01-01

    A qualitative model is developed for a first-order system with a proportional-integral controller without precise knowledge of the process or controller parameters. Simulation of the qualitative model yields all of the solutions to the system equations. In developing the qualitative model, a necessary condition for the occurrence of oscillatory behavior is identified. Initializations that cannot exhibit oscillatory behavior produce a finite set of behaviors. When the phase-space behavior of the oscillatory behavior is properly constrained, these initializations produce an infinite but comprehensible set of asymptotically stable behaviors. While the predictions include all possible behaviors of the real system, a class of spurious behaviors has been identified. When limited numerical information is included in the model, the number of predictions is significantly reduced.

  17. Multidimensional Clinical Phenotyping of an Adult Cystic Fibrosis Patient Population

    PubMed Central

    Conrad, Douglas J.; Bailey, Barbara A.

    2015-01-01

    Background Cystic Fibrosis (CF) is a multi-systemic disease resulting from mutations in the Cystic Fibrosis Transmembrane Regulator (CFTR) gene and has major manifestations in the sino-pulmonary, and gastro-intestinal tracts. Clinical phenotypes were generated using 26 common clinical variables to generate classes that overlapped quantiles of lung function and were based on multiple aspects of CF systemic disease. Methods The variables included age, gender, CFTR mutations, FEV1% predicted, FVC% predicted, height, weight, Brasfield chest xray score, pancreatic sufficiency status and clinical microbiology results. Complete datasets were compiled on 211 subjects. Phenotypes were identified using a proximity matrix generated by the unsupervised Random Forests algorithm and subsequent clustering by the Partitioning around Medoids (PAM) algorithm. The final phenotypic classes were then characterized and compared to a similar dataset obtained three years earlier. Findings Clinical phenotypes were identified using a clustering strategy that generated four and five phenotypes. Each strategy identified 1) a low lung health scores phenotype, 2) a younger, well-nourished, male-dominated class, 3) various high lung health score phenotypes that varied in terms of age, gender and nutritional status. This multidimensional clinical phenotyping strategy identified classes with expected microbiology results and low risk clinical phenotypes with pancreatic sufficiency. Interpretation This study demonstrated regional adult CF clinical phenotypes using non-parametric, continuous, ordinal and categorical data with a minimal amount of subjective data to identify clinically relevant phenotypes. These studies identified the relative stability of the phenotypes, demonstrated specific phenotypes consistent with published findings and identified others needing further study. PMID:25822311

  18. Prioritizing sequence polymorphisms for potential association with phenotype

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The millions of SNP, insertions and deletions revealed by next generation sequencing (NGS), are certain to include polymorphisms responsible for phenotypic variation. Distinguishing causal from benign variants may allow genomic predictions that are robust across populations. While variants underly...

  19. Causal Phenotype Discovery via Deep Networks

    PubMed Central

    Kale, David C.; Che, Zhengping; Bahadori, Mohammad Taha; Li, Wenzhe; Liu, Yan; Wetzel, Randall

    2015-01-01

    The rapid growth of digital health databases has attracted many researchers interested in using modern computational methods to discover and model patterns of health and illness in a research program known as computational phenotyping. Much of the work in this area has focused on traditional statistical learning paradigms, such as classification, prediction, clustering, pattern mining. In this paper, we propose a related but different paradigm called causal phenotype discovery, which aims to discover latent representations of illness that are causally predictive. We illustrate this idea with a two-stage framework that combines the latent representation learning power of deep neural networks with state-of-the-art tools from causal inference. We apply this framework to two large ICU time series data sets and show that it can learn features that are predictively useful, that capture complex physiologic patterns associated with critical illnesses, and that are potentially more clinically meaningful than manually designed features. PMID:26958203

  20. Phenotypic plasticity in bacterial plasmids.

    PubMed Central

    Turner, Paul E

    2004-01-01

    Plasmid pB15 was previously shown to evolve increased horizontal (infectious) transfer at the expense of reduced vertical (intergenerational) transfer and vice versa, a key trade-off assumed in theories of parasite virulence. Whereas the models predict that susceptible host abundance should determine which mode of transfer is selectively favored, host density failed to mediate the trade-off in pB15. One possibility is that the plasmid's transfer deviates from the assumption that horizontal spread (conjugation) occurs in direct proportion to cell density. I tested this hypothesis using Escherichia coli/pB15 associations in laboratory serial culture. Contrary to most models of plasmid transfer kinetics, my data show that pB15 invades static (nonshaking) bacterial cultures only at intermediate densities. The results can be explained by phenotypic plasticity in traits governing plasmid transfer. As cells become more numerous, the plasmid's conjugative transfer unexpectedly declines, while the trade-off between transmission routes causes vertical transfer to increase. Thus, at intermediate densities the plasmid's horizontal transfer can offset selection against plasmid-bearing cells, but at high densities pB15 conjugates so poorly that it cannot invade. I discuss adaptive vs. nonadaptive causes for the phenotypic plasticity, as well as potential mechanisms that may lead to complex transfer dynamics of plasmids in liquid environments. PMID:15166133

  1. Genetic resources for phenotyping

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Phenotyping of structured populations, along with molecular genotyping, will be essential for marker development in peanut. This research is essential for making the peanut genome sequence and genomic tools useful to breeders because it makes the connection between genes, gene markers, genetic maps...

  2. Down Syndrome: Cognitive Phenotype

    ERIC Educational Resources Information Center

    Silverman, Wayne

    2007-01-01

    Down syndrome is the most prevalent cause of intellectual impairment associated with a genetic anomaly, in this case, trisomy of chromosome 21. It affects both physical and cognitive development and produces a characteristic phenotype, although affected individuals vary considerably with respect to severity of specific impairments. Studies…

  3. Plant phenotypic plasticity in a changing climate.

    PubMed

    Nicotra, A B; Atkin, O K; Bonser, S P; Davidson, A M; Finnegan, E J; Mathesius, U; Poot, P; Purugganan, M D; Richards, C L; Valladares, F; van Kleunen, M

    2010-12-01

    Climate change is altering the availability of resources and the conditions that are crucial to plant performance. One way plants will respond to these changes is through environmentally induced shifts in phenotype (phenotypic plasticity). Understanding plastic responses is crucial for predicting and managing the effects of climate change on native species as well as crop plants. Here, we provide a toolbox with definitions of key theoretical elements and a synthesis of the current understanding of the molecular and genetic mechanisms underlying plasticity relevant to climate change. By bringing ecological, evolutionary, physiological and molecular perspectives together, we hope to provide clear directives for future research and stimulate cross-disciplinary dialogue on the relevance of phenotypic plasticity under climate change. PMID:20970368

  4. Evolving phenotypic networks in silico.

    PubMed

    François, Paul

    2014-11-01

    Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. PMID:24956562

  5. Rapid discrimination of the phenotypic variants of von Willebrand disease.

    PubMed

    Roberts, Jonathan C; Morateck, Patti A; Christopherson, Pamela A; Yan, Ke; Hoffmann, Raymond G; Gill, Joan Cox; Montgomery, Robert R

    2016-05-19

    Approximately 20% to 25% of patients with von Willebrand disease (VWD) have a qualitative defect of the von Willebrand factor (VWF) protein activities. Variant VWD typically is classified as type 1C, 2A, 2B, 2M, or 2N depending on the VWF activity defect. Traditionally, diagnosis has relied on multiple clinical laboratory assays to assign VWD phenotype. We developed an enzyme-linked immunosorbent assay (ELISA) to measure the various activities of VWF on a single plate and evaluated 160 patient samples enrolled in the Zimmerman Program for the Molecular and Clinical Biology of von Willebrand Disease with type 2 VWD. Using linear discriminate analysis (LDA), this assay was able to identify type 1C, 2A, 2B, 2M, or 2N VWD with an overall accuracy of 92.5% in the patient study cohort. LDA jackknife analysis, a statistical resampling technique, identified variant VWD with an overall accuracy of 88.1%, which predicts the assay's performance in the general population. In addition, this assay demonstrated correlation with traditional clinical laboratory VWF assays. The VWF multiplex activity assay may be useful as a same-day screening assay when considering the diagnosis of variant VWD in an individual patient. PMID:26917779

  6. Simulation of avascular tumor growth by agent-based game model involving phenotype-phenotype interactions.

    PubMed

    Chen, Yong; Wang, Hengtong; Zhang, Jiangang; Chen, Ke; Li, Yumin

    2015-01-01

    All tumors, both benign and metastatic, undergo an avascular growth stage with nutrients supplied by the surrounding tissue. This avascular growth process is much easier to carry out in more qualitative and quantitative experiments starting from tumor spheroids in vitro with reliable reproducibility. Essentially, this tumor progression would be described as a sequence of phenotypes. Using agent-based simulation in a two-dimensional spatial lattice, we constructed a composite growth model in which the phenotypic behavior of tumor cells depends on not only the local nutrient concentration and cell count but also the game among cells. Our simulation results demonstrated that in silico tumors are qualitatively similar to those observed in tumor spheroid experiments. We also found that the payoffs in the game between two living cell phenotypes can influence the growth velocity and surface roughness of tumors at the same time. Finally, this current model is flexible and can be easily extended to discuss other situations, such as environmental heterogeneity and mutation. PMID:26648395

  7. Simulation of avascular tumor growth by agent-based game model involving phenotype-phenotype interactions

    PubMed Central

    Chen, Yong; Wang, Hengtong; Zhang, Jiangang; Chen, Ke; Li, Yumin

    2015-01-01

    All tumors, both benign and metastatic, undergo an avascular growth stage with nutrients supplied by the surrounding tissue. This avascular growth process is much easier to carry out in more qualitative and quantitative experiments starting from tumor spheroids in vitro with reliable reproducibility. Essentially, this tumor progression would be described as a sequence of phenotypes. Using agent-based simulation in a two-dimensional spatial lattice, we constructed a composite growth model in which the phenotypic behavior of tumor cells depends on not only the local nutrient concentration and cell count but also the game among cells. Our simulation results demonstrated that in silico tumors are qualitatively similar to those observed in tumor spheroid experiments. We also found that the payoffs in the game between two living cell phenotypes can influence the growth velocity and surface roughness of tumors at the same time. Finally, this current model is flexible and can be easily extended to discuss other situations, such as environmental heterogeneity and mutation. PMID:26648395

  8. Qualitative Assertions as Prescriptive Statements

    ERIC Educational Resources Information Center

    Nolen, Amanda; Talbert, Tony

    2011-01-01

    The primary question regarding prescriptive appropriateness is a difficult one to answer for the qualitative researcher. While there are certainly qualitative researchers who have offered prescriptive protocols to better define and describe the terrain of qualitative research design and there are qualitative researchers who offer research…

  9. Reasoning about energy in qualitative simulation

    NASA Technical Reports Server (NTRS)

    Fouche, Pierre; Kuipers, Benjamin J.

    1992-01-01

    While possible behaviors of a mechanism that are consistent with an incomplete state of knowledge can be predicted through qualitative modeling and simulation, spurious behaviors corresponding to no solution of any ordinary differential equation consistent with the model may be generated. The present method for energy-related reasoning eliminates an important source of spurious behaviors, as demonstrated by its application to a nonlinear, proportional-integral controlled. It is shown that such qualitative properties of such a system as stability and zero-offset control are captured by the simulation.

  10. Demystifying Interdisciplinary Qualitative Research

    ERIC Educational Resources Information Center

    Greckhamer, Thomas; Koro-Ljungberg, Mirka; Cilesiz, Sebnem; Hayes, Sharon

    2008-01-01

    This article seeks to demystify, through deconstruction, the concept of "interdisciplinarity" in the context of qualitative research to contribute to a new praxis of knowledge production through reflection on the possibilities and impossibilities of interdisciplinarity. A review and discussion of disciplinarity and interdisciplinarity leads the…

  11. [Qualitative case study].

    PubMed

    Debout, Christophe

    2016-06-01

    The qualitative case study is a research method which enables a complex phenomenon to be explored through the identification of different factors interacting with each other. The case observed is a real situation. In the field of nursing science, it may be a clinical decision-making process. The study thereby enables the patient or health professional experience to be conceptualised. PMID:27338694

  12. Disciplining Qualitative Research

    ERIC Educational Resources Information Center

    Denzin, Norman K.; Lincoln, Yvonna S.; Giardina, Michael D.

    2006-01-01

    Qualitative research exists in a time of global uncertainty. Around the world, governments are attempting to regulate scientific inquiry by defining what counts as "good" science. These regulatory activities raise fundamental, philosophical epistemological, political and pedagogical issues for scholarship and freedom of speech in the academy. This…

  13. Entropy Is Simple, Qualitatively.

    ERIC Educational Resources Information Center

    Lambert, Frank L.

    2002-01-01

    Suggests that qualitatively, entropy is simple. Entropy increase from a macro viewpoint is a measure of the dispersal of energy from localized to spread out at a temperature T. Fundamentally based on statistical and quantum mechanics, this approach is superior to the non-fundamental "disorder" as a descriptor of entropy change. (MM)

  14. The Qualitative Similarity Hypothesis

    ERIC Educational Resources Information Center

    Paul, Peter V.; Lee, Chongmin

    2010-01-01

    Evidence is presented for the qualitative similarity hypothesis (QSH) with respect to children and adolescents who are d/Deaf or hard of hearing. The primary focus is on the development of English language and literacy skills, and some information is provided on the acquisition of English as a second language. The QSH is briefly discussed within…

  15. Bookstart: A Qualitative Evaluation.

    ERIC Educational Resources Information Center

    Moore, Maggie; Wade, Barrie

    2003-01-01

    A qualitative study of Bookstart, which gave free children's books and support to British inner-city families, collected data from librarians, health visitors, and nursery school staff. Bookstart increased positive attitudes toward and interest in books. Health visitors' support was crucial in helping parents use the books to support children's…

  16. Strategy revealing phenotypic differences among synthetic oscillator designs.

    PubMed

    Lomnitz, Jason G; Savageau, Michael A

    2014-09-19

    Considerable progress has been made in identifying and characterizing the component parts of genetic oscillators, which play central roles in all organisms. Nonlinear interaction among components is sufficiently complex that mathematical models are required to elucidate their elusive integrated behavior. Although natural and synthetic oscillators exhibit common architectures, there are numerous differences that are poorly understood. Utilizing synthetic biology to uncover basic principles of simpler circuits is a way to advance understanding of natural circadian clocks and rhythms. Following this strategy, we address the following questions: What are the implications of different architectures and molecular modes of transcriptional control for the phenotypic repertoire of genetic oscillators? Are there designs that are more realizable or robust? We compare synthetic oscillators involving one of three architectures and various combinations of the two modes of transcriptional control using a methodology that provides three innovations: a rigorous definition of phenotype, a procedure for deconstructing complex systems into qualitatively distinct phenotypes, and a graphical representation for illuminating the relationship between genotype, environment, and the qualitatively distinct phenotypes of a system. These methods provide a global perspective on the behavioral repertoire, facilitate comparisons of alternatives, and assist the rational design of synthetic gene circuitry. In particular, the results of their application here reveal distinctive phenotypes for several designs that have been studied experimentally as well as a best design among the alternatives that has yet to be constructed and tested. PMID:25019938

  17. Adaptive phenotypic plasticity in the Midas cichlid fish pharyngeal jaw and its relevance in adaptive radiation

    PubMed Central

    2011-01-01

    Background Phenotypic evolution and its role in the diversification of organisms is a central topic in evolutionary biology. A neglected factor during the modern evolutionary synthesis, adaptive phenotypic plasticity, more recently attracted the attention of many evolutionary biologists and is now recognized as an important ingredient in both population persistence and diversification. The traits and directions in which an ancestral source population displays phenotypic plasticity might partly determine the trajectories in morphospace, which are accessible for an adaptive radiation, starting from the colonization of a novel environment. In the case of repeated colonizations of similar environments from the same source population this "flexible stem" hypothesis predicts similar phenotypes to arise in repeated subsequent radiations. The Midas Cichlid (Amphilophus spp.) in Nicaragua has radiated in parallel in several crater-lakes seeded by populations originating from the Nicaraguan Great Lakes. Here, we tested phenotypic plasticity in the pharyngeal jaw of Midas Cichlids. The pharyngeal jaw apparatus of cichlids, a second set of jaws functionally decoupled from the oral ones, is known to mediate ecological specialization and often differs strongly between sister-species. Results We performed a common garden experiment raising three groups of Midas cichlids on food differing in hardness and calcium content. Analyzing the lower pharyngeal jaw-bones we find significant differences between diet groups qualitatively resembling the differences found between specialized species. Observed differences in pharyngeal jaw expression between groups were attributable to the diet's mechanical resistance, whereas surplus calcium in the diet was not found to be of importance. Conclusions The pharyngeal jaw apparatus of Midas Cichlids can be expressed plastically if stimulated mechanically during feeding. Since this trait is commonly differentiated - among other traits - between

  18. Phenotype accessibility and noise in random threshold gene regulatory networks.

    PubMed

    Pinho, Ricardo; Garcia, Victor; Feldman, Marcus W

    2014-01-01

    Evolution requires phenotypic variation in a population of organisms for selection to function. Gene regulatory processes involved in organismal development affect the phenotypic diversity of organisms. Since only a fraction of all possible phenotypes are predicted to be accessed by the end of development, organisms may evolve strategies to use environmental cues and noise-like fluctuations to produce additional phenotypic diversity, and hence to enhance the speed of adaptation. We used a generic model of organismal development --gene regulatory networks-- to investigate how different levels of noise on gene expression states (i.e. phenotypes) may affect access to new, unique phenotypes, thereby affecting phenotypic diversity. We studied additional strategies that organisms might adopt to attain larger phenotypic diversity: either by augmenting their genome or the number of gene expression states. This was done for different types of gene regulatory networks that allow for distinct levels of regulatory influence on gene expression or are more likely to give rise to stable phenotypes. We found that if gene expression is binary, increasing noise levels generally decreases phenotype accessibility for all network types studied. If more gene expression states are considered, noise can moderately enhance the speed of discovery if three or four gene expression states are allowed, and if there are enough distinct regulatory networks in the population. These results were independent of the network types analyzed, and were robust to different implementations of noise. Hence, for noise to increase the number of accessible phenotypes in gene regulatory networks, very specific conditions need to be satisfied. If the number of distinct regulatory networks involved in organismal development is large enough, and the acquisition of more genes or fine tuning of their expression states proves costly to the organism, noise can be useful in allowing access to more unique phenotypes

  19. Phenotype Accessibility and Noise in Random Threshold Gene Regulatory Networks

    PubMed Central

    Feldman, Marcus W.

    2015-01-01

    Evolution requires phenotypic variation in a population of organisms for selection to function. Gene regulatory processes involved in organismal development affect the phenotypic diversity of organisms. Since only a fraction of all possible phenotypes are predicted to be accessed by the end of development, organisms may evolve strategies to use environmental cues and noise-like fluctuations to produce additional phenotypic diversity, and hence to enhance the speed of adaptation. We used a generic model of organismal development --gene regulatory networks-- to investigate how different levels of noise on gene expression states (i.e. phenotypes) may affect access to new, unique phenotypes, thereby affecting phenotypic diversity. We studied additional strategies that organisms might adopt to attain larger phenotypic diversity: either by augmenting their genome or the number of gene expression states. This was done for different types of gene regulatory networks that allow for distinct levels of regulatory influence on gene expression or are more likely to give rise to stable phenotypes. We found that if gene expression is binary, increasing noise levels generally decreases phenotype accessibility for all network types studied. If more gene expression states are considered, noise can moderately enhance the speed of discovery if three or four gene expression states are allowed, and if there are enough distinct regulatory networks in the population. These results were independent of the network types analyzed, and were robust to different implementations of noise. Hence, for noise to increase the number of accessible phenotypes in gene regulatory networks, very specific conditions need to be satisfied. If the number of distinct regulatory networks involved in organismal development is large enough, and the acquisition of more genes or fine tuning of their expression states proves costly to the organism, noise can be useful in allowing access to more unique phenotypes

  20. Bioimaging for quantitative phenotype analysis.

    PubMed

    Chen, Weiyang; Xia, Xian; Huang, Yi; Chen, Xingwei; Han, Jing-Dong J

    2016-06-01

    With the development of bio-imaging techniques, an increasing number of studies apply these techniques to generate a myriad of image data. Its applications range from quantification of cellular, tissue, organismal and behavioral phenotypes of model organisms, to human facial phenotypes. The bio-imaging approaches to automatically detect, quantify, and profile phenotypic changes related to specific biological questions open new doors to studying phenotype-genotype associations and to precisely evaluating molecular changes associated with quantitative phenotypes. Here, we review major applications of bioimage-based quantitative phenotype analysis. Specifically, we describe the biological questions and experimental needs addressable by these analyses, computational techniques and tools that are available in these contexts, and the new perspectives on phenotype-genotype association uncovered by such analyses. PMID:26850283

  1. Qualitative Research: Comments and Controversies.

    ERIC Educational Resources Information Center

    Schutz, Robert W.

    1989-01-01

    This article comments upon the use of qualitative research in physical education, exercise, and sport science. Topics include unresolved methodological problems, data analysis, and the scope of qualitative research. (IAH)

  2. Methylator phenotype in colorectal cancer: A prognostic factor or not?

    PubMed

    Gallois, C; Laurent-Puig, P; Taieb, J

    2016-03-01

    Colorectal cancer (CRC) is due to different types of genetic alterations that are translated into different phenotypes. Among them, CpG island methylator phenotype (CIMP+) is the most recently involved in carcinogenesis of some CRC. The malignant transformation in this case is mainly due to the transcriptional inactivation of tumor suppressor genes. CIMP+ are reported to be more frequently found in the elderly and in women. The tumors are more frequently located in the proximal part of the colon, BRAF mutated and are associated with microsatellite instability (MSI) phenotype. All sporadic MSI CRC belong to the methylator phenotype, however some non MSI CRC may also harbor a methylator phenotype. The prognostic value of CIMP is not well known. Most studies show a worse prognosis in CIMP+ CRC, and adjuvant treatments seem to be more efficient. We review here the current knowledge on prognostic and predictive values in CIMP+ CRC. PMID:26702883

  3. Phenotypes of prediabetes and stratification of cardiometabolic risk.

    PubMed

    Stefan, Norbert; Fritsche, Andreas; Schick, Fritz; Häring, Hans-Ulrich

    2016-09-01

    Prediabetes is associated with increased risks of type 2 diabetes, cardiovascular disease, dementia, and cancer, and its prevalence is increasing worldwide. Lifestyle and pharmacological interventions in people with prediabetes can prevent the development of diabetes and possibly cardiovascular disease. However, prediabetes is a highly heterogeneous metabolic state, both with respect to its pathogenesis and prediction of disease. Improved understanding of these features and precise phenotyping of prediabetes could help to improve stratification of disease risk. In this Personal View, we focus on the extreme metabolic phenotypes of metabolically healthy obesity and metabolically unhealthy normal weight, insulin secretion failure, insulin resistance, visceral obesity, and non-alcoholic fatty liver disease. We present new analyses aimed at improving characterisation of phenotypes in lean, overweight, and obese people with prediabetes. We discuss evidence from lifestyle intervention studies to explore whether these phenotypes can also be used for individualised prediction and prevention of cardiometabolic diseases. PMID:27185609

  4. Belief propagation in genotype-phenotype networks.

    PubMed

    Moharil, Janhavi; May, Paul; Gaile, Daniel P; Blair, Rachael Hageman

    2016-03-01

    Graphical models have proven to be a valuable tool for connecting genotypes and phenotypes. Structural learning of phenotype-genotype networks has received considerable attention in the post-genome era. In recent years, a dozen different methods have emerged for network inference, which leverage natural variation that arises in certain genetic populations. The structure of the network itself can be used to form hypotheses based on the inferred direct and indirect network relationships, but represents a premature endpoint to the graphical analyses. In this work, we extend this endpoint. We examine the unexplored problem of perturbing a given network structure, and quantifying the system-wide effects on the network in a node-wise manner. The perturbation is achieved through the setting of values of phenotype node(s), which may reflect an inhibition or activation, and propagating this information through the entire network. We leverage belief propagation methods in Conditional Gaussian Bayesian Networks (CG-BNs), in order to absorb and propagate phenotypic evidence through the network. We show that the modeling assumptions adopted for genotype-phenotype networks represent an important sub-class of CG-BNs, which possess properties that ensure exact inference in the propagation scheme. The system-wide effects of the perturbation are quantified in a node-wise manner through the comparison of perturbed and unperturbed marginal distributions using a symmetric Kullback-Leibler divergence. Applications to kidney and skin cancer expression quantitative trait loci (eQTL) data from different mus musculus populations are presented. System-wide effects in the network were predicted and visualized across a spectrum of evidence. Sub-pathways and regions of the network responded in concert, suggesting co-regulation and coordination throughout the network in response to phenotypic changes. We demonstrate how these predicted system-wide effects can be examined in connection with

  5. Learning about Ecological Systems by Constructing Qualitative Models with DynaLearn

    ERIC Educational Resources Information Center

    Leiba, Moshe; Zuzovsky, Ruth; Mioduser, David; Benayahu, Yehuda; Nachmias, Rafi

    2012-01-01

    A qualitative model of a system is an abstraction that captures ordinal knowledge and predicts the set of qualitatively possible behaviours of the system, given a qualitative description of its structure and initial state. This paper examines an innovative approach to science education using an interactive learning environment that supports…

  6. Evolutionary adaptation of phenotypic plasticity in a synthetic microbial system

    NASA Astrophysics Data System (ADS)

    Tans, Sander

    2010-03-01

    While phenotypic plasticity -the capability to respond to the environment- is vital to organisms, tests of its adaptation have remained indecisive because constraints and selection in variable environments are unknown and entangled. We show that one can determine the phenotype-fitness landscape that specifies selection on plasticity, by uncoupling the environmental cue and stress in a genetically engineered microbial system. Evolutionary trajectories revealed genetic constraints in a regulatory protein, which imposed cross-environment trade-offs that favored specialization. However, depending on the synchronicity and amplitude of the applied cue and stress variations, adaptation could break constraints, resolve trade-offs, and evolve optimal phenotypes that exhibit qualitatively altered (inverse) responses to the cue. Our results provide a first step to explain the adaptive origins of complex behavior in heterogeneous environments.

  7. A Qualitative Model of the Differentiation Network in Chondrocyte Maturation: A Holistic View of Chondrocyte Hypertrophy.

    PubMed

    Kerkhofs, Johan; Leijten, Jeroen; Bolander, Johanna; Luyten, Frank P; Post, Janine N; Geris, Liesbet

    2016-01-01

    Differentiation of chondrocytes towards hypertrophy is a natural process whose control is essential in endochondral bone formation. It is additionally thought to play a role in several pathophysiological processes, with osteoarthritis being a prominent example. We perform a dynamic analysis of a qualitative mathematical model of the regulatory network that directs this phenotypic switch to investigate the influence of the individual factors holistically. To estimate the stability of a SOX9 positive state (associated with resting/proliferation chondrocytes) versus a RUNX2 positive one (associated with hypertrophy) we employ two measures. The robustness of the state in canalisation (size of the attractor basin) is assessed by a Monte Carlo analysis and the sensitivity to perturbations is assessed by a perturbational analysis of the attractor. Through qualitative predictions, these measures allow for an in silico screening of the effect of the modelled factors on chondrocyte maintenance and hypertrophy. We show how discrepancies between experimental data and the model's results can be resolved by evaluating the dynamic plausibility of alternative network topologies. The findings are further supported by a literature study of proposed therapeutic targets in the case of osteoarthritis. PMID:27579819

  8. A Comprehensive Evaluation of Disease Phenotype Networks for Gene Prioritization

    PubMed Central

    Li, Jianhua; Lin, Xiaoyan; Teng, Yueyang; Qi, Shouliang; Xiao, Dayu; Zhang, Jianying; Kang, Yan

    2016-01-01

    Identification of disease-causing genes is a fundamental challenge for human health studies. The phenotypic similarity among diseases may reflect the interactions at the molecular level, and phenotype comparison can be used to predict disease candidate genes. Online Mendelian Inheritance in Man (OMIM) is a database of human genetic diseases and related genes that has become an authoritative source of disease phenotypes. However, disease phenotypes have been described by free text; thus, standardization of phenotypic descriptions is needed before diseases can be compared. Several disease phenotype networks have been established in OMIM using different standardization methods. Two of these networks are important for phenotypic similarity analysis: the first and most commonly used network (mimMiner) is standardized by medical subject heading, and the other network (resnikHPO) is the first to be standardized by human phenotype ontology. This paper comprehensively evaluates for the first time the accuracy of these two networks in gene prioritization based on protein–protein interactions using large-scale, leave-one-out cross-validation experiments. The results show that both networks can effectively prioritize disease-causing genes, and the approach that relates two diseases using a logistic function improves prioritization performance. Tanimoto, one of four methods for normalizing resnikHPO, generates a symmetric network and it performs similarly to mimMiner. Furthermore, an integration of these two networks outperforms either network alone in gene prioritization, indicating that these two disease networks are complementary. PMID:27415759

  9. Effects of dietary enrichment with a marine oil-based n-3 LCPUFA supplement in sows with predicted birth weight phenotypes on birth litter quality and growth performance to weaning.

    PubMed

    Smit, M N; Spencer, J D; Patterson, J L; Dyck, M K; Dixon, W T; Foxcroft, G R

    2015-03-01

    The effects of a marine oil-based n-3 long-chain polyunsaturated fatty acid (mLCPUFA) supplement fed to the sow from weaning, through the rebreeding period, during gestation and until end of lactation on litter characteristics from birth until weaning were studied in sows with known litter birth weight phenotypes. It was hypothesized that low birth weight (LBW) litters would benefit more from mLCPUFA supplementation than high birth weight litters. A total of 163 sows (mean parity=4.9 ± 0.9) were rebred after weaning. Sows were pair-matched by parity and litter average birth weight of the previous three litters. Within pairs, sows were allocated to be fed either standard corn/soyabean meal-based gestation and lactation diets (CON), or the same diets enriched with 0.5% of the mLCPUFA supplement at the expense of corn. Each litter between 9 and 16 total pigs born was classified as LBW or medium/high average birth weight (MHBW) litter and there was a significant correlation (P<0.001) between litter average birth weight of the current and previous litters within sows (r=0.49). Sow serum was harvested at day 113 of gestation for determination of immunoglobulin G (IgG) concentrations. The number of pigs born total and alive were lower (P=0.01) in mLCPUFA than CON sows, whereas the number of stillborn and mummified pigs were similar between treatments. Number of stillborns (trend) and mummies (P<0.01) were higher in LBW than MHBW litters. Tissue weights and brain : tissue weight ratios were similar between treatments, but LBW litters had decreased tissue weights and increased brain : tissue weight ratios compared with MHBW litters. Placental weight was lower (P=0.01) in LBW than MHBW litters, but was not different between treatments. Average and total litter weight at day 1 was similar between treatments. mLCPUFA increased weaning weight (P=0.08) and average daily gain (P<0.05) in MHBW litters, but not in LBW litters. Pre-weaning mortality was similar between treatments

  10. EHR Big Data Deep Phenotyping

    PubMed Central

    Lenert, L.; Lopez-Campos, G.

    2014-01-01

    Summary Objectives Given the quickening speed of discovery of variant disease drivers from combined patient genotype and phenotype data, the objective is to provide methodology using big data technology to support the definition of deep phenotypes in medical records. Methods As the vast stores of genomic information increase with next generation sequencing, the importance of deep phenotyping increases. The growth of genomic data and adoption of Electronic Health Records (EHR) in medicine provides a unique opportunity to integrate phenotype and genotype data into medical records. The method by which collections of clinical findings and other health related data are leveraged to form meaningful phenotypes is an active area of research. Longitudinal data stored in EHRs provide a wealth of information that can be used to construct phenotypes of patients. We focus on a practical problem around data integration for deep phenotype identification within EHR data. The use of big data approaches are described that enable scalable markup of EHR events that can be used for semantic and temporal similarity analysis to support the identification of phenotype and genotype relationships. Conclusions Stead and colleagues’ 2005 concept of using light standards to increase the productivity of software systems by riding on the wave of hardware/processing power is described as a harbinger for designing future healthcare systems. The big data solution, using flexible markup, provides a route to improved utilization of processing power for organizing patient records in genotype and phenotype research. PMID:25123744

  11. Pseudomonas Aeruginosa Resistance Phenotypes and Phenotypic Highlighting Methods

    PubMed Central

    BĂLĂŞOIU, MARIA; BĂLĂŞOIU, A.T.; MĂNESCU, RODICA; AVRAMESCU, CARMEN; IONETE, OANA

    2014-01-01

    Pseudomonas aeruginosa genus bacteria are well known for their increased drug resistance (phenotypic ang genotypic resistance). The most important resistance mechanisms are: enzyme production, reduction of pore expression, reduction of the external membrane proteins expression, efflux systems, topoisomerase mutations. These mechanisms often accumulate and lead to multidrug ressitance strains emergence. The most frequent acquired resistance mechanisms are betalactamase-type enzyme production (ESBLs, AmpC, carbapenemases), which determine variable phenotypes of betalactamines resistance, phenotypes which are associated with aminoglycosides and quinolones resistance. The nonenzymatic drug resistance mechanisms are caused by efflux systems, pore reduction and penicillin-binding proteins (PBP) modification, which are often associated to other resistance mechanisms. Phenotypic methods used for testing these mechanisms are based on highlighting these phenotypes using Kirby Bauer antibiogram, clinical breakpoints, and “cut off” values recommended by EUCAST 2013 standard, version 3.1. PMID:25729587

  12. Injury profile SIMulator, a Qualitative aggregative modelling framework to predict injury profile as a function of cropping practices, and abiotic and biotic environment. II. Proof of concept: design of IPSIM-wheat-eyespot.

    PubMed

    Robin, Marie-Hélène; Colbach, Nathalie; Lucas, Philippe; Montfort, Françoise; Cholez, Célia; Debaeke, Philippe; Aubertot, Jean-Noël

    2013-01-01

    IPSIM (Injury Profile SIMulator) is a generic modelling framework presented in a companion paper. It aims at predicting a crop injury profile as a function of cropping practices and abiotic and biotic environment. IPSIM's modelling approach consists of designing a model with an aggregative hierarchical tree of attributes. In order to provide a proof of concept, a model, named IPSIM-Wheat-Eyespot, has been developed with the software DEXi according to the conceptual framework of IPSIM to represent final incidence of eyespot on wheat. This paper briefly presents the pathosystem, the method used to develop IPSIM-Wheat-Eyespot using IPSIM's modelling framework, simulation examples, an evaluation of the predictive quality of the model with a large dataset (526 observed site-years) and a discussion on the benefits and limitations of the approach. IPSIM-Wheat-Eyespot proved to successfully represent the annual variability of the disease, as well as the effects of cropping practices (Efficiency = 0.51, Root Mean Square Error of Prediction = 24%; bias = 5.0%). IPSIM-Wheat-Eyespot does not aim to precisely predict the incidence of eyespot on wheat. It rather aims to rank cropping systems with regard to the risk of eyespot on wheat in a given production situation through ex ante evaluations. IPSIM-Wheat-Eyespot can also help perform diagnoses of commercial fields. Its structure is simple and permits to combine available knowledge in the scientific literature (data, models) and expertise. IPSIM-Wheat-Eyespot is now available to help design cropping systems with a low risk of eyespot on wheat in a wide range of production situations, and can help perform diagnoses of commercial fields. In addition, it provides a proof of concept with regard to the modelling approach of IPSIM. IPSIM-Wheat-Eyespot will be a sub-model of IPSIM-Wheat, a model that will predict injury profile on wheat as a function of cropping practices and the production situation. PMID:24146783

  13. The qualitative similarity hypothesis.

    PubMed

    Paul, Peter V; Lee, Chongmin

    2010-01-01

    Evidence is presented for the qualitative similarity hypothesis (QSH) with respect to children and adolescents who are d/Deaf or hard of hearing. The primary focus is on the development of English language and literacy skills, and some information is provided on the acquisition of English as a second language. The QSH is briefly discussed within the purview of two groups of cognitive models: those that emphasize the cognitive development of individuals and those that pertain to disciplinary or knowledge structures. It is argued that the QSH has scientific merit with implications for classroom instruction. Future research should examine the validity of the QSH in other disciplines such as mathematics and science and should include perspectives from social as well as cognitive models. PMID:20415280

  14. Common Perspectives in Qualitative Research.

    PubMed

    Flannery, Marie

    2016-07-01

    The primary purpose of this column is to focus on several common core concepts that are foundational to qualitative research. Discussion of these concepts is at an introductory level and is designed to raise awareness and understanding of several conceptual foundations that undergird qualitative research. Because of the variety of qualitative approaches, not all concepts are relevant to every design and tradition. However, foundational aspects were selected for highlighting. PMID:27314194

  15. Emerging molecular phenotypes of asthma.

    PubMed

    Ray, Anuradha; Oriss, Timothy B; Wenzel, Sally E

    2015-01-15

    Although asthma has long been considered a heterogeneous disease, attempts to define subgroups of asthma have been limited. In recent years, both clinical and statistical approaches have been utilized to better merge clinical characteristics, biology, and genetics. These combined characteristics have been used to define phenotypes of asthma, the observable characteristics of a patient determined by the interaction of genes and environment. Identification of consistent clinical phenotypes has now been reported across studies. Now the addition of various 'omics and identification of specific molecular pathways have moved the concept of clinical phenotypes toward the concept of molecular phenotypes. The importance of these molecular phenotypes is being confirmed through the integration of molecularly targeted biological therapies. Thus the global term asthma is poised to become obsolete, being replaced by terms that more specifically identify the pathology associated with the disease. PMID:25326577

  16. Plant Phenotype Characterization System

    SciTech Connect

    Daniel W McDonald; Ronald B Michaels

    2005-09-09

    This report is the final scientific report for the DOE Inventions and Innovations Project: Plant Phenotype Characterization System, DE-FG36-04GO14334. The period of performance was September 30, 2004 through July 15, 2005. The project objective is to demonstrate the viability of a new scientific instrument concept for the study of plant root systems. The root systems of plants are thought to be important in plant yield and thus important to DOE goals in renewable energy sources. The scientific study and understanding of plant root systems is hampered by the difficulty in observing root activity and the inadequacy of existing root study instrumentation options. We have demonstrated a high throughput, non-invasive, high resolution technique for visualizing plant root systems in-situ. Our approach is based upon low-energy x-ray radiography and the use of containers and substrates (artificial soil) which are virtually transparent to x-rays. The system allows us to germinate and grow plant specimens in our containers and substrates and to generate x-ray images of the developing root system over time. The same plant can be imaged at different times in its development. The system can be used for root studies in plant physiology, plant morphology, plant breeding, plant functional genomics and plant genotype screening.

  17. Citrullinemia: phenotypic variations.

    PubMed

    Whelan, D T; Brusso, T; Spate, M

    1976-06-01

    An 18-month-old female infant was found to have citrullinemia on routine plasma screening by the Scriver Method at 5 days of age. At 10 days of age, plasma citrulline concentration was 0.704mumol/ml (normal, 0.010 to 0.030mumol/ml) and has remained 60 to 80 times higher than normal. Urine citrulline concentration was markedly elevated. Hyperammonemia occurred at 1 month of age. The serum ammonia concentration was 473mug/100 ml (normal, 50 to 250 mug/100 ml) and rose to 770mug/100 ml at 4 months of age. Dietary protein was restricted to 1.6 gm/kg/day. Without further change in protein intake, the serum ammonia concentration decreased to 280mug/100 ml and, since then, it has returned to normal. The addition of three synthetic L-amino acids was required for a short time during dietary therapy. At 10 months of age, the infant was given a normal diet. At 18 months of age, her physical and mental development is normal. Activity of argininosuccinic acid synthetase measured in skin fibroblasts was 0.0037mumol of radioactive carbon dioxide per milligram of protein per hour. To demonstrate heterozygosity, fasting plasma citrulline concentrations were measured in five members of the family. Comparison of findings in this patient with those reported in the literature suggests phenotypical variation of the disease, probably due to genetic heterogeneity. PMID:934749

  18. Qualitative and temporal reasoning in engine behavior analysis

    NASA Technical Reports Server (NTRS)

    Dietz, W. E.; Stamps, M. E.; Ali, M.

    1987-01-01

    Numerical simulation models, engine experts, and experimental data are used to generate qualitative and temporal representations of abnormal engine behavior. Engine parameters monitored during operation are used to generate qualitative and temporal representations of actual engine behavior. Similarities between the representations of failure scenarios and the actual engine behavior are used to diagnose fault conditions which have already occurred, or are about to occur; to increase the surveillance by the monitoring system of relevant engine parameters; and to predict likely future engine behavior.

  19. Qualitative Reasoning for Additional Die Casting Applications

    SciTech Connect

    R. Allen Miller; Dehua Cui; Yuming Ma

    2003-05-28

    If manufacturing incompatibility of a product can be evaluated at the early product design stage, the designers can modify their design to reduce the effect of potential manufacturing problems. This will result in fewer manufacturing problems, less redsign, less expensive tooling, lower cost, better quality, and shorter development time. For a given design, geometric reasoning can predict qualitatively the behaviors of a physical manufacturing process by representing and reasoning with incomplete knowledge of the physical phenomena. It integrates a design with manufacturing processes to help designers simultaneously consider design goals and manufacturing constraints during the early design stage. The geometric reasoning approach can encourage design engineers to qualitatively evaluate the compatibility of their design with manufacturing limitations and requirements.

  20. Monotonicity is a key feature of genotype-phenotype maps

    PubMed Central

    Gjuvsland, Arne B.; Wang, Yunpeng; Plahte, Erik; Omholt, Stig W.

    2013-01-01

    It was recently shown that monotone gene action, i.e., order-preservation between allele content and corresponding genotypic values in the mapping from genotypes to phenotypes, is a prerequisite for achieving a predictable parent-offspring relationship across the whole allele frequency spectrum. Here we test the consequential prediction that the design principles underlying gene regulatory networks are likely to generate highly monotone genotype-phenotype maps. To this end we present two measures of the monotonicity of a genotype-phenotype map, one based on allele substitution effects, and the other based on isotonic regression. We apply these measures to genotype-phenotype maps emerging from simulations of 1881 different 3-gene regulatory networks. We confirm that in general, genotype-phenotype maps are indeed highly monotonic across network types. However, regulatory motifs involving incoherent feedforward or positive feedback, as well as pleiotropy in the mapping between genotypes and gene regulatory parameters, are clearly predisposed for generating non-monotonicity. We present analytical results confirming these deep connections between molecular regulatory architecture and monotonicity properties of the genotype-phenotype map. These connections seem to be beyond reach by the classical distinction between additive and non-additive gene action. PMID:24223579

  1. An early thymic precursor phenotype predicts outcome exclusively in HOXA-overexpressing adult T-cell acute lymphoblastic leukemia: a Group for Research in Adult Acute Lymphoblastic Leukemia study

    PubMed Central

    Bond, Jonathan; Marchand, Tony; Touzart, Aurore; Cieslak, Agata; Trinquand, Amélie; Sutton, Laurent; Radford-Weiss, Isabelle; Lhermitte, Ludovic; Spicuglia, Salvatore; Dombret, Hervé; Macintyre, Elizabeth; Ifrah, Norbert; Hamel, Jean-François; Asnafi, Vahid

    2016-01-01

    Gene expression studies have consistently identified a HOXA-overexpressing cluster of T-cell acute lymphoblastic leukemias, but it is unclear whether these constitute a homogeneous clinical entity, and the biological consequences of HOXA overexpression have not been systematically examined. We characterized the biology and outcome of 55 HOXA-positive cases among 209 patients with adult T-cell acute lymphoblastic leukemia uniformly treated during the Group for Research on Adult Acute Lymphoblastic Leukemia (GRAALL)-2003 and -2005 studies. HOXA-positive patients had markedly higher rates of an early thymic precursor-like immunophenotype (40.8% versus 14.5%, P=0.0004), chemoresistance (59.3% versus 40.8%, P=0.026) and positivity for minimal residual disease (48.5% versus 23.5%, P=0.01) than the HOXA-negative group. These differences were due to particularly high frequencies of chemoresistant early thymic precursor-like acute lymphoblastic leukemia in HOXA-positive cases harboring fusion oncoproteins that transactivate HOXA. Strikingly, the presence of an early thymic precursor-like immunophenotype was associated with marked outcome differences within the HOXA-positive group (5-year overall survival 31.2% in HOXA-positive early thymic precursor versus 66.7% in HOXA-positive non-early thymic precursor, P=0.03), but not in HOXA-negative cases (5-year overall survival 74.2% in HOXA-negative early thymic precursor versus 57.2% in HOXA-negative non-early thymic precursor, P=0.44). Multivariate analysis further revealed that HOXA positivity independently affected event-free survival (P=0.053) and relapse risk (P=0.039) of chemoresistant T-cell acute lymphoblastic leukemia. These results show that the underlying mechanism of HOXA deregulation dictates the clinico-biological phenotype, and that the negative prognosis of early thymic precursor acute lymphoblastic leukemia is exclusive to HOXA-positive patients, suggesting that early treatment intensification is currently

  2. Disease insights through cross-species phenotype comparisons.

    PubMed

    Haendel, Melissa A; Vasilevsky, Nicole; Brush, Matthew; Hochheiser, Harry S; Jacobsen, Julius; Oellrich, Anika; Mungall, Christopher J; Washington, Nicole; Köhler, Sebastian; Lewis, Suzanna E; Robinson, Peter N; Smedley, Damian

    2015-10-01

    New sequencing technologies have ushered in a new era for diagnosis and discovery of new causative mutations for rare diseases. However, the sheer numbers of candidate variants that require interpretation in an exome or genomic analysis are still a challenging prospect. A powerful approach is the comparison of the patient's set of phenotypes (phenotypic profile) to known phenotypic profiles caused by mutations in orthologous genes associated with these variants. The most abundant source of relevant data for this task is available through the efforts of the Mouse Genome Informatics group and the International Mouse Phenotyping Consortium. In this review, we highlight the challenges in comparing human clinical phenotypes with mouse phenotypes and some of the solutions that have been developed by members of the Monarch Initiative. These tools allow the identification of mouse models for known disease-gene associations that may otherwise have been overlooked as well as candidate genes may be prioritized for novel associations. The culmination of these efforts is the Exomiser software package that allows clinical researchers to analyse patient exomes in the context of variant frequency and predicted pathogenicity as well the phenotypic similarity of the patient to any given candidate orthologous gene. PMID:26092691

  3. Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Injury Profile as a Function of Cropping Practices, and Abiotic and Biotic Environment. II. Proof of Concept: Design of IPSIM-Wheat-Eyespot

    PubMed Central

    Robin, Marie-Hélène; Colbach, Nathalie; Lucas, Philippe; Montfort, Françoise; Cholez, Célia; Debaeke, Philippe; Aubertot, Jean-Noël

    2013-01-01

    IPSIM (Injury Profile SIMulator) is a generic modelling framework presented in a companion paper. It aims at predicting a crop injury profile as a function of cropping practices and abiotic and biotic environment. IPSIM's modelling approach consists of designing a model with an aggregative hierarchical tree of attributes. In order to provide a proof of concept, a model, named IPSIM-Wheat-Eyespot, has been developed with the software DEXi according to the conceptual framework of IPSIM to represent final incidence of eyespot on wheat. This paper briefly presents the pathosystem, the method used to develop IPSIM-Wheat-Eyespot using IPSIM's modelling framework, simulation examples, an evaluation of the predictive quality of the model with a large dataset (526 observed site-years) and a discussion on the benefits and limitations of the approach. IPSIM-Wheat-Eyespot proved to successfully represent the annual variability of the disease, as well as the effects of cropping practices (Efficiency = 0.51, Root Mean Square Error of Prediction = 24%; bias = 5.0%). IPSIM-Wheat-Eyespot does not aim to precisely predict the incidence of eyespot on wheat. It rather aims to rank cropping systems with regard to the risk of eyespot on wheat in a given production situation through ex ante evaluations. IPSIM-Wheat-Eyespot can also help perform diagnoses of commercial fields. Its structure is simple and permits to combine available knowledge in the scientific literature (data, models) and expertise. IPSIM-Wheat-Eyespot is now available to help design cropping systems with a low risk of eyespot on wheat in a wide range of production situations, and can help perform diagnoses of commercial fields. In addition, it provides a proof of concept with regard to the modelling approach of IPSIM. IPSIM-Wheat-Eyespot will be a sub-model of IPSIM-Wheat, a model that will predict injury profile on wheat as a function of cropping practices and the production situation. PMID:24146783

  4. Qualitative interviewing as measurement.

    PubMed

    Paley, John

    2010-04-01

    The attribution of beliefs and other propositional attitudes is best understood as a form of measurement, however counter-intuitive this may seem. Measurement theory does not require that the thing measured should be a magnitude, or that the calibration of the measuring instrument should be numerical. It only requires a homomorphism between the represented domain and the representing domain. On this basis, maps measure parts of the world, usually geographical locations, and 'belief' statements measure other parts of the world, namely people's aptitudes. Having outlined an argument for this view, I deal with an obvious objection to it: that self-attribution of belief cannot be an exercise in measurement, because we are all aware, from introspection, that our beliefs have an intrinsically semantic form. Subsequently, I turn to the philosophical and methodological ramifications of the measurement theoretic view. I argue, first, that it undermines at least one version of constructivism and, second, that it provides an effective alternative to the residually Cartesian philosophy that underpins much qualitative research. Like other anti-Cartesian strategies, belief-attribution-as-measurement implies that the objective world is far more knowable than the subjective one, and that reality is ontologically prior to meaning. I regard this result as both plausible and welcome. PMID:20415963

  5. Quantitative and qualitative analysis of metabolic response at interim positron emission tomography scan combined with International Prognostic Index is highly predictive of outcome in diffuse large B-cell lymphoma.

    PubMed

    Nols, Nathalie; Mounier, Nicolas; Bouazza, Salima; Lhommel, Renaud; Costantini, Sabrina; Vander Borght, Thierry; Vekemans, Marie-Christiane; Sonet, Anne; Bosly, André; Michaux, Lucienne; André, Marc; Van Den Neste, Eric

    2014-04-01

    The prognostic value of interim (18)fluorodeoxyglucose positron emission tomography (i-PET) was investigated in 73 patients (median age 60 years) with diffuse large B-cell lymphoma (DLBCL). i-PET was analyzed using the Deauville score (DS) and change in maximum standardized uptake value (ΔSUV(max)). Patients with a DS of 1-3 demonstrated a significantly (p < 0.0001) better outcome (median follow-up 2.4 years) than patients with a score of 4 or 5 in terms of event-free survival (EFS) (79% vs. 36%), progression-free survival (PFS) (84% vs. 47%) and overall survival (OS) (91% vs. 51%). EFS (73% vs. 42%), PFS (78% vs. 50%) and OS (88% vs. 56%) were also significantly (p = 0.023) different between patients with ΔSUV(max) > 66% or ≤ 66%. Patients (n = 33) combining a favorable age-adjusted International Prognostic Index (IPI) (0 or 1) and a negative i-PET either by DS or ΔSUV(max) criteria showed a particularly good outcome (EFS: 85%, PFS: 88%, OS: 94%). Overall, i-PET was highly and independently predictive of any outcome, and its negative predictive value was improved by combination with IPI. PMID:23927393

  6. Using Numbers in Qualitative Research

    ERIC Educational Resources Information Center

    Maxwell, Joseph A.

    2010-01-01

    The use of numerical/quantitative data in qualitative research studies and reports has been controversial. Prominent qualitative researchers such as Howard Becker and Martyn Hammersley have supported the inclusion of what Becker called "quasi-statistics": simple counts of things to make statements such as "some," "usually," and "most" more…

  7. Qualitative Science in Experimental Time

    ERIC Educational Resources Information Center

    Eisenhart, Margaret

    2006-01-01

    This article addresses the "state of qualitative inquiry" in the sense of how that inquiry is being positioned in the current construction of a US national policy agenda for "scientifically based" education research. In the author's view, qualitative inquiry is being drowned out in the national agenda despite its ability to provide the kinds of…

  8. Phenotypic mapping and clinical ideology

    SciTech Connect

    Lurie, I.W.; Opitz, J.M.

    1995-07-17

    Scientists have been trying to determine whether the main clinical findings in the 4p deletion syndrome are due to a deletion of one small critical segment, or whether deletions of some particular segments of 4p are responsible for different phenotypic manifestations. This is the basic issue for the whole group of autosomal deletion syndromes, as well as for our understanding of mechanisms of the origin of the abnormal phenotype. All circumstances need to be taken into consideration when trying to apply molecular methods for the mapping of phenotypic findings in the 4p deletion or in any other autosomal deletion syndrome. 8 refs.

  9. Qualitative and quantitative descriptions of glenohumeral motion.

    PubMed

    Hill, A M; Bull, A M J; Wallace, A L; Johnson, G R

    2008-02-01

    Joint modelling plays an important role in qualitative and quantitative descriptions of both normal and abnormal joints, as well as predicting outcomes of alterations to joints in orthopaedic practice and research. Contemporary efforts in modelling have focussed upon the major articulations of the lower limb. Well-constrained arthrokinematics can form the basis of manageable kinetic and dynamic mathematical predictions. In order to contain computation of shoulder complex modelling, glenohumeral joint representations in both limited and complete shoulder girdle models have undergone a generic simplification. As such, glenohumeral joint models are often based upon kinematic descriptions of inadequate degrees of freedom (DOF) for clinical purposes and applications. Qualitative descriptions of glenohumeral motion range from the parody of a hinge joint to the complex realism of a spatial joint. In developing a model, a clear idea of intention is required in order to achieve a required application. Clinical applicability of a model requires both descriptive and predictive output potentials, and as such, a high level of validation is required. Without sufficient appreciation of the clinical intention of the arthrokinematic foundation to a model, error is all too easily introduced. Mathematical description of joint motion serves to quantify all relevant clinical parameters. Commonly, both the Euler angle and helical (screw) axis methods have been applied to the glenohumeral joint, although concordance between these methods and classical anatomical appreciation of joint motion is limited, resulting in miscommunication between clinician and engineer. Compounding these inconsistencies in motion quantification is gimbal lock and sequence dependency. PMID:17509885

  10. Physiological phenotyping of pediatric chronic obstructive airway diseases.

    PubMed

    Nyilas, Sylvia; Singer, Florian; Kumar, Nitin; Yammine, Sophie; Meier-Girard, Delphine; Koerner-Rettberg, Cordula; Casaulta, Carmen; Frey, Urs; Latzin, Philipp

    2016-07-01

    Inert tracer gas washout (IGW) measurements detect increased ventilation inhomogeneity (VI) in chronic lung diseases. Their suitability for different diseases, such as cystic fibrosis (CF) and primary ciliary dyskinesia (PCD), has already been shown. However, it is still unclear if physiological phenotypes based on different IGW variables can be defined independently of underlying disease. Eighty school-age children, 20 with CF, 20 with PCD, 20 former preterm children, and 20 healthy children, performed nitrogen multiple-breath washout, double-tracer gas (DTG) single-breath washout, and spirometry. Our primary outcome was the definition of physiological phenotypes based on IGW variables. We applied principal component analysis, hierarchical Ward's clustering, and enrichment analysis to compare clinical characteristics between the clusters. IGW variables used for clustering were lung clearance index (LCI) and convection-dependent [conductive ventilation heterogeneity index (Scond)] and diffusion-convection-dependent variables [acinar ventilation heterogeneity index (Sacin) and carbon dioxide and DTG phase III slopes]. Three main phenotypes were identified. Phenotype I (n = 38) showed normal values in all IGW outcome variables. Phenotype II (n = 21) was characterized by pronounced global and convection-dependent VI while diffusion-dependent VI was normal. Phenotype III (n = 21) was characterized by increased global and diffusion- and convection-dependent VI. Enrichment analysis revealed an overrepresentation of healthy children and former preterm children in phenotype I and of CF and PCD in phenotypes II and III. Patients in phenotype III showed the highest proportion and frequency of exacerbations and hospitalization in the year prior to the measurement. IGW techniques allow identification of clinically meaningful, disease-independent physiological clusters. Their predictive value of future disease outcomes remains to be determined. PMID:27231309