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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 Central

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

    2016-01-01

    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

    USDA-ARS?s Scientific Manuscript database

    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

    2014-04-17

    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.

  4. The evolution of social interactions changes predictions about interacting phenotypes.

    PubMed

    Kazancıoğlu, Erem; Klug, Hope; Alonzo, Suzanne H

    2012-07-01

    In many traits involved in social interactions, such as courtship and aggression, the phenotype is an outcome of interactions between individuals. Such traits whose expression in an individual is partly determined by the phenotype of its social partner are called "interacting phenotypes." Quantitative genetic models suggested that interacting phenotypes can evolve much faster than nonsocial traits. Current models, however, consider the interaction between phenotypes of social partners as a fixed phenotypic response rule, represented by an interaction coefficient (ψ). Here, we extend existing theoretical models and incorporate the interaction coefficient as a trait that can evolve. We find that the evolution of the interaction coefficient can change qualitatively the predictions about the rate and direction of evolution of interacting phenotypes. We argue that it is crucial to determine whether and how the phenotypic response of an individual to its social partner can evolve to make accurate predictions about the evolution of traits involved in social interactions. © 2012 The Author(s).

  5. 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

  6. Wine Expertise Predicts Taste Phenotype.

    PubMed

    Hayes, John E; Pickering, Gary J

    2012-03-01

    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.

  7. 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

  8. Mining phenotypes for gene function prediction

    PubMed Central

    Groth, Philip; Weiss, Bertram; Pohlenz, Hans-Dieter; Leser, Ulf

    2008-01-01

    Background Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In the past years, many technologies to systematically generate phenotypes in a high-throughput manner, such as RNA interference or gene knock-out, have been developed and used to decipher functions for genes. However, there have been relatively few efforts to make use of phenotype data beyond the single genotype-phenotype relationships. Results We present results on a study where we use a large set of phenotype data – in textual form – to predict gene annotation. To this end, we use text clustering to group genes based on their phenotype descriptions. We show that these clusters correlate well with several indicators for biological coherence in gene groups, such as functional annotations from the Gene Ontology (GO) and protein-protein interactions. We exploit these clusters for predicting gene function by carrying over annotations from well-annotated genes to other, less-characterized genes in the same cluster. For a subset of groups selected by applying objective criteria, we can predict GO-term annotations from the biological process sub-ontology with up to 72.6% precision and 16.7% recall, as evaluated by cross-validation. We manually verified some of these clusters and found them to exhibit high biological coherence, e.g. a group containing all available antennal Drosophila odorant receptors despite inconsistent GO-annotations. Conclusion The intrinsic nature of phenotypes to visibly reflect genetic activity underlines their usefulness in inferring new gene functions. Thus, systematically analyzing these data on a large scale offers many possibilities for inferring functional annotation of genes. We show that text clustering can play an important role in this process. PMID:18315868

  9. Male phenotype predicts insemination success in guppies.

    PubMed Central

    Pilastro, Andrea; Evans, Jonathan P; Sartorelli, Silvia; Bisazza, Angelo

    2002-01-01

    Theory predicts that mate choice can lead to an increase in female fecundity if the secondary sexual traits used by females to assess male quality covary with the number of sperm transferred during copulation. Where females mate multiply, such a relationship between male attractiveness and ejaculate size may, additionally (or alternatively), serve to augment the effect of indirect selection by biasing paternity in favour of preferred males. In either case, a positive correlation between male attractiveness and the size of ejaculates delivered at copulation is predicted. To date, some of the most convincing (indirect) evidence for this prediction comes from the guppy, a species of fish exhibiting a resource-free mating system in which attractive males tend to have larger sperm reserves. We show that, during solicited copulations, male guppies with preferred phenotypes actually transfer more sperm to females than their less-ornamented counterparts, irrespective of the size of their initial sperm stores. Our results also reveal that, during coercive copulations, the relationship between ejaculate size and the male's phenotype breaks down. This latter result, in conjunction with our finding that mating speed--a factor under the female's control-is a significant predictor of ejaculate size, leads us to speculate that females may exert at least partial control over the number of sperm inseminated during cooperative matings. PMID:12079654

  10. Transcriptome transfer produces a predictable cellular phenotype

    PubMed Central

    Sul, Jai-Yoon; Wu, Chia-wen K.; Zeng, Fanyi; Jochems, Jeanine; Lee, Miler T.; Kim, Tae Kyung; Peritz, Tiina; Buckley, Peter; Cappelleri, David J.; Maronski, Margaret; Kim, Minsun; Kumar, Vijay; Meaney, David; Kim, Junhyong; Eberwine, James

    2009-01-01

    Cellular phenotype is the conglomerate of multiple cellular processes involving gene and protein expression that result in the elaboration of a cell's particular morphology and function. It has been thought that differentiated postmitotic cells have their genomes hard wired, with little ability for phenotypic plasticity. Here we show that transfer of the transcriptome from differentiated rat astrocytes into a nondividing differentiated rat neuron resulted in the conversion of the neuron into a functional astrocyte-like cell in a time-dependent manner. This single-cell study permits high resolution of molecular and functional components that underlie phenotype identity. The RNA population from astrocytes contains RNAs in the appropriate relative abundances that give rise to regulatory RNAs and translated proteins that enable astrocyte identity. When transferred into the postmitotic neuron, the astrocyte RNA population converts 44% of the neuronal host cells into the destination astrocyte-like phenotype. In support of this observation, quantitative measures of cellular morphology, single-cell PCR, single-cell microarray, and single-cell functional analyses have been performed. The host-cell phenotypic changes develop over many weeks and are persistent. We call this process of RNA-induced phenotype changes, transcriptome-induced phenotype remodeling. PMID:19380745

  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. Whole genome prediction and heritability of childhood asthma phenotypes

    PubMed Central

    Clemmer, George L.; Croteau‐Chonka, Damien C.; Castaldi, Peter J.; Cho, Michael H.; Sordillo, Joanne E.; Lasky‐Su, Jessica A.; Raby, Benjamin A.; Tantisira, Kelan G.; Weiss, Scott T.

    2016-01-01

    Abstract Introduction While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma‐related phenotypes. Methods We applied several WGP methods to a well‐phenotyped cohort of 832 children with mild‐to‐moderate asthma from CAMP. We assessed narrow‐sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre‐ and post‐bronchodilator forced expiratory volume in 1 sec (FEV1), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort. Results We found that longitudinal lung function phenotypes demonstrated significant narrow‐sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4–8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts. Conclusions Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP‐prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma‐related heritable traits. PMID:27980782

  13. A Novel Knowledge-Driven Systems Biology Approach for Phenotype Prediction upon Genetic Intervention

    PubMed Central

    Chang, Rui; Shoemaker, Robert; Wang, Wei

    2011-01-01

    Deciphering the biological networks underlying complex phenotypic traits, e.g., human disease is undoubtedly crucial to understand the underlying molecular mechanisms and to develop effective therapeutics. Due to the network complexity and the relatively small number of available experiments, data-driven modeling is a great challenge for deducing the functions of genes/ proteins in the network and in phenotype formation. We propose a novel knowledge-driven systems biology method that utilizes qualitative knowledge to construct a Dynamic Bayesian network (DBN) to represent the biological network underlying a specific phenotype. Edges in this network depict physical interactions between genes and/or proteins. A qualitative knowledge model first translates typical molecular interactions into constraints when resolving the DBN structure and parameters. Therefore, the uncertainty of the network is restricted to a subset of models which are consistent with the qualitative knowledge. All models satisfying the constraints are considered as candidates for the underlying network. These consistent models are used to perform quantitative inference. By in silico inference, we can predict phenotypic traits upon genetic interventions and perturbing in the network. We applied our method to analyze the puzzling mechanism of breast cancer cell proliferation network and we accurately predicted cancer cell growth rate upon manipulating (anti)cancerous marker genes/proteins. PMID:21282866

  14. Integrating phenotype and gene expression data for predicting gene function.

    PubMed

    Malone, Brandon M; Perkins, Andy D; Bridges, Susan M

    2009-10-08

    This paper presents a framework for integrating disparate data sets to predict gene function. The algorithm constructs a graph, called an integrated similarity graph, by computing similarities based upon both gene expression and textual phenotype data. This integrated graph is then used to make predictions about whether individual genes should be assigned a particular annotation from the Gene Ontology. A combined graph was generated from publicly-available gene expression data and phenotypic information from Saccharomyces cerevisiae. This graph was used to assign annotations to genes, as were graphs constructed from gene expression data and textual phenotype information alone. While the F-measure appeared similar for all three methods, annotations based upon the integrated similarity graph exhibited a better overall precision than gene expression or phenotype information alone can generate. The integrated approach was also able to assign almost as many annotations as the gene expression method alone, and generated significantly more total and correct assignments than the phenotype information could provide. These results suggest that augmenting standard gene expression data sets with publicly-available textual phenotype data can help generate more precise functional annotation predictions while mitigating the weaknesses of a standard textual phenotype approach.

  15. Multikernel linear mixed models for complex phenotype prediction

    PubMed Central

    Weissbrod, Omer; Geiger, Dan; Rosset, Saharon

    2016-01-01

    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

  16. Predicting Phenotype from Genotype: Normal Pigmentation*

    PubMed Central

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

    2013-01-01

    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

  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. 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

  19. Inflammatory Genes and Psychological Factors Predict Induced Shoulder Pain Phenotype

    PubMed Central

    George, Steven Z.; Parr, Jeffrey J.; Wallace, Margaret R.; Wu, Samuel S.; Borsa, Paul A.; Dai, Yunfeng; Fillingim, Roger B.

    2014-01-01

    Purpose The pain experience has multiple influences but little is known about how specific biological and psychological factors interact to influence pain responses. The current study investigated the combined influences of genetic (pro-inflammatory) and psychological factors on several pre-clinical shoulder pain phenotypes. Methods An exercise-induced shoulder injury model was used, and a priori selected genetic (IL1B, TNF/LTA region, IL6 single nucleotide polymorphisms, SNPs) and psychological (anxiety, depressive symptoms, pain catastrophizing, fear of pain, kinesiophobia) factors were included as the predictors of interest. The phenotypes were pain intensity (5-day average and peak reported on numerical rating scale), upper-extremity disability (5-day average and peak reported on the QuickDASH instrument), and duration of shoulder pain (in days). Results After controlling for age, sex, and race, the genetic and psychological predictors were entered separately as main effects and interaction terms in regression models for each pain phenotype. Results from the recruited cohort (n = 190) indicated strong statistical evidence for the interactions between 1) TNF/LTA SNP rs2229094 and depressive symptoms for average pain intensity and duration and 2) IL1B two-SNP diplotype and kinesiophobia for average shoulder pain intensity. Moderate statistical evidence for prediction of additional shoulder pain phenotypes included interactions of kinesiophobia, fear of pain, or depressive symptoms with TNF/LTA rs2229094 and IL1B. Conclusion These findings support the combined predictive ability of specific genetic and psychological factors for shoulder pain phenotypes by revealing novel combinations that may merit further investigation in clinical cohorts, to determine their involvement in the transition from acute to chronic pain conditions. PMID:24598699

  20. Phenotypic plasticity and population viability: the importance of environmental predictability

    PubMed Central

    Reed, Thomas E.; Waples, Robin S.; Schindler, Daniel E.; Hard, Jeffrey J.; Kinnison, Michael T.

    2010-01-01

    Phenotypic plasticity plays a key role in modulating how environmental variation influences population dynamics, but we have only rudimentary understanding of how plasticity interacts with the magnitude and predictability of environmental variation to affect population dynamics and persistence. We developed a stochastic individual-based model, in which phenotypes could respond to a temporally fluctuating environmental cue and fitness depended on the match between the phenotype and a randomly fluctuating trait optimum, to assess the absolute fitness and population dynamic consequences of plasticity under different levels of environmental stochasticity and cue reliability. When cue and optimum were tightly correlated, plasticity buffered absolute fitness from environmental variability, and population size remained high and relatively invariant. In contrast, when this correlation weakened and environmental variability was high, strong plasticity reduced population size, and populations with excessively strong plasticity had substantially greater extinction probability. Given that environments might become more variable and unpredictable in the future owing to anthropogenic influences, reaction norms that evolved under historic selective regimes could imperil populations in novel or changing environmental contexts. We suggest that demographic models (e.g. population viability analyses) would benefit from a more explicit consideration of how phenotypic plasticity influences population responses to environmental change. PMID:20554553

  1. 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.

  2. Phenotype prediction based on genome-wide DNA methylation data

    PubMed Central

    2014-01-01

    Background DNA methylation (DNAm) has important regulatory roles in many biological processes and diseases. It is the only epigenetic mark with a clear mechanism of mitotic inheritance and the only one easily available on a genome scale. Aberrant cytosine-phosphate-guanine (CpG) methylation has been discussed in the context of disease aetiology, especially cancer. CpG hypermethylation of promoter regions is often associated with silencing of tumour suppressor genes and hypomethylation with activation of oncogenes. Supervised principal component analysis (SPCA) is a popular machine learning method. However, in a recent application to phenotype prediction from DNAm data SPCA was inferior to the specific method EVORA. Results We present Model-Selection-SPCA (MS-SPCA), an enhanced version of SPCA. MS-SPCA applies several models that perform well in the training data to the test data and selects the very best models for final prediction based on parameters of the test data. We have applied MS-SPCA for phenotype prediction from genome-wide DNAm data. CpGs used for prediction are selected based on the quantification of three features of their methylation (average methylation difference, methylation variation difference and methylation-age-correlation). We analysed four independent case–control datasets that correspond to different stages of cervical cancer: (i) cases currently cytologically normal, but will later develop neoplastic transformations, (ii, iii) cases showing neoplastic transformations and (iv) cases with confirmed cancer. The first dataset was split into several smaller case–control datasets (samples either Human Papilloma Virus (HPV) positive or negative). We demonstrate that cytology normal HPV+ and HPV- samples contain DNAm patterns which are associated with later neoplastic transformations. We present evidence that DNAm patterns exist in cytology normal HPV- samples that (i) predispose to neoplastic transformations after HPV infection and (ii

  3. Can the phenotype of inherited fibrinogen disorders be predicted?

    PubMed

    Casini, A; de Moerloose, P

    2016-09-01

    Congenital fibrinogen disorders are rare diseases affecting either the quantity (afibrinogenaemia and hypofibrinogenaemia) or the quality (dysfibrinogenaemia) or both (hypodysfibrinogenaemia) of fibrinogen. In addition to bleeding, unexpected thrombosis, spontaneous spleen ruptures, painful bone cysts and intrahepatic inclusions can complicate the clinical course of patients with quantitative fibrinogen disorders. Clinical manifestations of dysfibrinogenaemia include absence of symptoms, major bleeding or thrombosis as well as systemic amyloidosis. Although the diagnosis of any type of congenital fibrinogen disorders is usually not too difficult with the help of conventional laboratory tests completed by genetic studies, the correlation between all available tests and the clinical manifestations is more problematic in many cases. Improving accuracy of diagnosis, performing genotype, analysing function of fibrinogen variants and carefully investigating the personal and familial histories may lead to a better assessment of patients' phenotype and therefore help in identifying patients at increased risk of adverse clinical outcomes. This review provides an update of various tests (conventional and global assays, molecular testing, fibrin clot analysis) and clinical features, which may help to better predict the phenotype of the different types of congenital fibrinogen disorders. © 2016 John Wiley & Sons Ltd.

  4. Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

    PubMed

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

    2015-02-01

    Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have

  5. New genetic model for predicting phenotype traits in sports.

    PubMed

    Massidda, Myosotis; Scorcu, Marco; Calò, Carla M

    2014-05-01

    The aim of the current study was to construct a genetic model with a new algorithm for predicting athletic-performance variability based on genetic variations. The influence of 6 polymorphisms (ACE, ACTN-3, BDKRB2, VDR-ApaI, VDR-BsmI, and VDR-FokI) on vertical jump was studied in top-level male Italian soccer players (n = 90). First, the authors calculated the traditional total genotype score and then determined the total weighting genotype score (TWGS), which accounts for the proportion of significant phenotypic variance predicted by the polymorphisms. Genomic DNA was extracted from saliva samples using a standard protocol. Genotyping was performed using polymerase chain reaction (PCR). The results obtained from the new genetic model (TWGS) showed that only 3 polymorphisms entered the regression equation (ACTN-3, ACE, and BDKRB2), and these polymorphisms explained 17.68-24.24% of the vertical-jump variance. With the weighting given to each polymorphism, it may be possible to identify a polygenic profile that more accurately explains, at least in part, the individual variance of athletic-performance traits. This model may be used to create individualized training programs based on a player's genetic predispositions, as well as to identify athletes who need an adapted training routine to account for individual susceptibility to injury.

  6. 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. © 2016 John Wiley & Sons Ltd/CNRS.

  7. 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

    2015-07-02

    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. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  8. Qualitative and quantitative peptidomic and proteomic approaches to phenotyping chicken semen.

    PubMed

    Labas, Valérie; Grasseau, Isabelle; Cahier, Karine; Gargaros, Audrey; Harichaux, Grégoire; Teixeira-Gomes, Ana-Paula; Alves, Sabine; Bourin, Marie; Gérard, Nadine; Blesbois, Elisabeth

    2015-01-01

    Understanding of the avian male gamete biology is essential to improve the conservation of genetic resources and performance in farming. In this study, the chicken semen peptidome/proteome and the molecular phenotype related to sperm quality were investigated. Spermatozoa (SPZ) and corresponding seminal plasma (SP) from 11 males with different fertilizing capacity were analyzed using three quantitative strategies (fluid and intact cells MALDI-MS, SDS-PAGE combined to LC-MS/MS with spectral counting and XIC methods). Individual MALDI profiling in combination with top-down MS allowed to characterize specific profiles per male and to identify 16 biomolecules (e.g.VMO1, AvBD10 and AvBD9 including polymorphism). Qualitative analysis identified 1165 proteins mainly involved in oxidoreduction mechanisms, energy processes, proteolysis and protein localization. Comparative analyses between the most and the least fertile males were performed. The enzymes involved in energy metabolism, respiratory chain or oxido-reduction activity were over-represented in SPZ of the most fertile males. The SP of the most and the least fertile males differed also on many proteins (e.g. ACE, AvBD10 and AvBD9, NEL precursor, acrosin). Thus proteomic is a "phenomic molecular tool" that may help to discriminate avian males on their reproductive capacity. The data have been deposited with ProteomeXchange (identifiers PXD000287 and PXD001254). This peptidomic and proteomic study i) characterized for the first time the semen protein composition of the main domestic avian species (Gallus gallus) by analysis of ejaculated spermatozoa and corresponding seminal plasma; ii) established a characteristic molecular phenotype distinguishing semen and males at an individual level; and iii) proposedthe first evidence of biomarkers related to fertility. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Genotype-phenotype relationship in mucopolysaccharidosis II: predictive power of IDS variants for the neuronopathic phenotype.

    PubMed

    Vollebregt, Audrey A M; Hoogeveen-Westerveld, Marianne; Kroos, Marian A; Oussoren, Esmee; Plug, Iris; Ruijter, George J; van der Ploeg, Ans T; Pijnappel, W W M Pim

    2017-10-01

    Mucopolysaccharidosis type II (MPS II) is caused by variants in the iduronate-2-sulphatase gene (IDS). Patients can be either neuronopathic with intellectual disability, or non-neuronopathic. Few studies have reported on the IDS genotype-phenotype relationship and on the molecular effects involved. We addressed this in a cohort study of Dutch patients with MPS II. Intellectual performance was assessed for school performance, behaviour, and intelligence. Urinary glycosaminoglycans were quantified by mass spectrometry. IDS variants were analysed in expression studies for enzymatic activity and processing by immunoblotting. Six patients had a non-neuronopathic phenotype and 11 a neuronopathic phenotype, three of whom had epilepsy. Total deletion of IDS invariably resulted in the neuronopathic phenotype. Phenotypes of seven known IDS variants were consistent with the literature. Expression studies of nine variants were novel and showed impaired IDS enzymatic activity, aberrant intracellular processing, and elevated urinary excretion of heparan sulphate and dermatan sulphate irrespective of the MPS II phenotype. We speculate that very low or cell-type-specific IDS residual activity is sufficient to prevent the neuronal phenotype of MPS II. Whereas the molecular effects of IDS variants do not distinguish between MPS II phenotypes, the IDS genotype is a strong predictor. © 2017 Mac Keith Press.

  10. 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…

  11. 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…

  12. Predicting Homo pigmentation phenotype through genomic data: from Neanderthal to James Watson.

    PubMed

    Cerqueira, Caio C S; Paixão-Côrtes, Vanessa R; Zambra, Francis M B; Salzano, Francisco M; Hünemeier, Tábita; Bortolini, Maria-Cátira

    2012-01-01

    Human pigmentation is regulated by several genes acting at different stages of melanin formation. Functional and association studies have elucidated the role of several of these genes in pigmentation phenotypes. Forensic and evolutionary studies can benefit from this knowledge. To evaluate the reliability of the prediction of pigmentation phenotypes using a large database of genetic markers in individuals with known phenotypes; and from this try to predict the pigmentation phenotype of prehistoric Homo specimens and of contemporary individuals whose visible phenotypes are not known. We compared predicted and observed phenotypic data through an analysis of 124 single nucleotide polymorphisms in 33 genic and seven intergenic regions of 30 subjects, five of them prehistoric, whose complete nuclear genomes are available in UCSC and PSU UCSC public databases. For the molecular predicted versus observed phenotypes, the percentage of agreement was as follows: freckles: 91; skin: 64; hair: 44; eyes: 36; total: 59; while the molecular predicted versus probable (no visible observation available; inferences based on ethnic population characteristics) it was, respectively, 83, 60, 42, 67, and 63. The difference between two sets is statistically nonsignificant (P = 0.75). To our knowledge, this is the first article to examine the effect of a large number of genetics markers for phenotype prediction. The approach could be useful for forensic applications, as well as for the determination of possible phenotypes of extinct prehistoric individuals. Copyright © 2012 Wiley Periodicals, Inc.

  13. Perianal Crohn's disease: predictive factors and genotype-phenotype correlations.

    PubMed

    Kanaan, Ziad; Ahmad, Surriya; Bilchuk, Natalia; Vahrenhold, Crystal; Pan, Jianmin; Galandiuk, Susan

    2012-01-01

    To investigate genotype-phenotype correlations in patients with perianal Crohn's disease (PCD) in order to determine which factors predispose to development of perianal disease in Crohn's patients. Seven-hundred and ninety-five Caucasian individuals (317 CD patients and 478 controls without inflammatory bowel disease, IBD) were prospectively enrolled into a clinical/genetic database. Demographic and clinical data, as well as peripheral blood leukocyte DNA were obtained from all patients. The following were evaluated: three NOD2/CARD15 polymorphisms: R702W, G908R, and 1007insC; five IL-23r risk alleles: rs1004819, rs10489629, rs2201841, rs11465804, and rs11209026; a well-characterized single-nucleotide polymorphism (SNP) on the IBD5 risk haplotype (OCTN1) and two peripheral tag SNPs (IGR2060 and IGR3096). PCD occurred in 147 (46%) of CD patients. There was no significant difference in the age at disease diagnosis between non-PCD and PCD patients (33 vs. 29 years, respectively). PCD patients were more likely to have disease located in the colon and ileocolic regions (79 PCD vs. 57% non-PCD; n = 116 vs. n = 96; p < 0.001), whereas patients with non-PCD were more likely to have Crohn's within the terminal ileum and upper gastrointestinal tract (43% non-PCD vs. 21% PCD; n = 73 vs. n = 31; p < 0.05). Thirty-four percent of patients with PCD required a permanent ileostomy (n = 50) compared to only 4% of non-PCD patients (n = 6; p < 0.05). Mutations in CARD15/NOD2 and IL-23r were risk factors for CD overall; however, in contrast to prior reports, in this patient population, OCTN1 and IGR variations within the IBD5 haplotype were not significant predictors of PCD. Colon/ileocolic CD location appears to be a significant predictor of perianal manifestations of CD. Patients with PCD are more likely to require permanent fecal diversion. We did not identify any genetic variations or combination of clinical findings and genetic variations within the CARD15/NOD2, IL-23r, and OCTN1

  14. Prediction of gene-phenotype associations in humans, mice, and plants using phenologs.

    PubMed

    Woods, John O; Singh-Blom, Ulf Martin; Laurent, Jon M; McGary, Kriston L; Marcotte, Edward M

    2013-06-21

    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. 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. 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.

  15. 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

  16. 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.

  17. Cardio-facio-cutaneous syndrome: Does genotype predict phenotype?

    PubMed Central

    Allanson, Judith E; Annerén, Göran; Aoki, Yoki; Armour, Christine M; Bondeson, Marie-Louise; Cave, Helene; Gripp, Karen W; Kerr, Bronwyn; Nystrom, Anna-Maja; Sol-Church, Katia; Verloes, Alain; Zenker, Martin

    2011-01-01

    Cardio-facio-cutaneous syndrome is a sporadic multiple congenital anomalies/mental retardation condition principally caused by mutations in BRAF, MEK1, and MEK2. Mutations in KRAS and SHOC2 lead to a phenotype with overlapping features. In approximately 10–30% of individuals with a clinical diagnosis of cardio-facio-cutaneous, a mutation in one of these causative genes is not found. Cardinal features of cardio-facio-cutaneous include congenital heart defects, a characteristic facial appearance, and ectodermal abnormalities. Additional features include failure to thrive with severe feeding problems, moderate to severe intellectual disability and short stature with relative macrocephaly. First described in 1986, more than 100 affected individuals are reported. Following the discovery of the causative genes, more information has emerged on the breadth of clinical features. Little, however, has been published on genotype-phenotype correlations. This clinical study of 186 children and young adults with mutation-proven cardio-facio-cutaneous syndrome is the largest reported to date. BRAF mutations are documented in 140 individuals (~75%), while 46 (~25%) have a mutation in MEK 1 or MEK 2. The age range is 6 months to 32 years, the oldest individual being a female from the original report [Reynolds et al., 1986]. While some clinical data on 136 are in the literature, fifty are not previously published. We provide new details of the breadth of phenotype and discuss the frequency of particular features in each genotypic group. Pulmonary stenosis is the only anomaly that demonstrates a statistically significant genotype-phenotype correlation, being more common in individuals with a BRAF mutation. PMID:21495173

  18. Integrating gene set analysis and nonlinear predictive modeling of disease phenotypes using a Bayesian multitask formulation.

    PubMed

    Gönen, Mehmet

    2016-12-13

    Identifying molecular signatures of disease phenotypes is studied using two mainstream approaches: (i) Predictive modeling methods such as linear classification and regression algorithms are used to find signatures predictive of phenotypes from genomic data, which may not be robust due to limited sample size or highly correlated nature of genomic data. (ii) Gene set analysis methods are used to find gene sets on which phenotypes are linearly dependent by bringing prior biological knowledge into the analysis, which may not capture more complex nonlinear dependencies. Thus, formulating an integrated model of gene set analysis and nonlinear predictive modeling is of great practical importance. In this study, we propose a Bayesian binary classification framework to integrate gene set analysis and nonlinear predictive modeling. We then generalize this formulation to multitask learning setting to model multiple related datasets conjointly. Our main novelty is the probabilistic nonlinear formulation that enables us to robustly capture nonlinear dependencies between genomic data and phenotype even with small sample sizes. We demonstrate the performance of our algorithms using repeated random subsampling validation experiments on two cancer and two tuberculosis datasets by predicting important disease phenotypes from genome-wide gene expression data. We are able to obtain comparable or even better predictive performance than a baseline Bayesian nonlinear algorithm and to identify sparse sets of relevant genes and gene sets on all datasets. We also show that our multitask learning formulation enables us to further improve the generalization performance and to better understand biological processes behind disease phenotypes.

  19. Using Whole-Genome Sequence Data to Predict Quantitative Trait Phenotypes in Drosophila melanogaster

    PubMed Central

    Ober, Ulrike; Ayroles, Julien F.; Stone, Eric A.; Richards, Stephen; Zhu, Dianhui; Gibbs, Richard A.; Stricker, Christian; Gianola, Daniel; Schlather, Martin; Mackay, Trudy F. C.; Simianer, Henner

    2012-01-01

    Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP) genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP) model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012) for starvation resistance (startle response). The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP–based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms. PMID:22570636

  20. 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.

  1. Boolean network model predicts knockout mutant phenotypes of fission yeast.

    PubMed

    Davidich, Maria I; Bornholdt, Stefan

    2013-01-01

    networks of switches) are extremely simple mathematical models of biochemical signaling networks. Under certain circumstances, Boolean networks, despite their simplicity, are capable of predicting dynamical activation patterns of gene regulatory networks in living cells. For example, the temporal sequence of cell cycle activation patterns in yeasts S. pombe and S. cerevisiae are faithfully reproduced by Boolean network models. An interesting question is whether this simple model class could also predict a more complex cellular phenomenology as, for example, the cell cycle dynamics under various knockout mutants instead of the wild type dynamics, only. Here we show that a Boolean network model for the cell cycle control network of yeast S. pombe correctly predicts viability of a large number of known mutants. So far this had been left to the more detailed differential equation models of the biochemical kinetics of the yeast cell cycle network and was commonly thought to be out of reach for models as simplistic as Boolean networks. The new results support our vision that Boolean networks may complement other mathematical models in systems biology to a larger extent than expected so far, and may fill a gap where simplicity of the model and a preference for an overall dynamical blueprint of cellular regulation, instead of biochemical details, are in the focus.

  2. Boolean Network Model Predicts Knockout Mutant Phenotypes of Fission Yeast

    PubMed Central

    Davidich, Maria I.; Bornholdt, Stefan

    2013-01-01

    Boolean networks (or: networks of switches) are extremely simple mathematical models of biochemical signaling networks. Under certain circumstances, Boolean networks, despite their simplicity, are capable of predicting dynamical activation patterns of gene regulatory networks in living cells. For example, the temporal sequence of cell cycle activation patterns in yeasts S. pombe and S. cerevisiae are faithfully reproduced by Boolean network models. An interesting question is whether this simple model class could also predict a more complex cellular phenomenology as, for example, the cell cycle dynamics under various knockout mutants instead of the wild type dynamics, only. Here we show that a Boolean network model for the cell cycle control network of yeast S. pombe correctly predicts viability of a large number of known mutants. So far this had been left to the more detailed differential equation models of the biochemical kinetics of the yeast cell cycle network and was commonly thought to be out of reach for models as simplistic as Boolean networks. The new results support our vision that Boolean networks may complement other mathematical models in systems biology to a larger extent than expected so far, and may fill a gap where simplicity of the model and a preference for an overall dynamical blueprint of cellular regulation, instead of biochemical details, are in the focus. PMID:24069138

  3. Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

    PubMed Central

    Kou, Peng Meng; Pallassana, Narayanan; Bowden, Rebeca; Cunningham, Barry; Joy, Abraham; Kohn, Joachim; Babensee, Julia E.

    2011-01-01

    Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response towards the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R2prediction = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with R2prediction = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection. PMID:22136715

  4. 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

  5. Prediction of CYP2D6 phenotype from genotype across world populations

    PubMed Central

    Gaedigk, Andrea; Sangkuhl, Katrin; Whirl-Carrillo, Michelle; Klein, Teri; Leeder, J. Steven

    2017-01-01

    Purpose: Owing to its highly polymorphic nature and major contribution to the metabolism and bioactivation of numerous clinically used drugs, CYP2D6 is one of the most extensively studied drug-metabolizing enzymes and pharmacogenes. CYP2D6 alleles confer no, decreased, normal, or increased activity and cause a wide range of activity among individuals and between populations. However, there is no standard approach to translate diplotypes into predicted phenotype. Methods: We exploited CYP2D6 allele-frequency data that have been compiled for Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines (>60,000 subjects, 173 reports) in order to estimate genotype-predicted phenotype status across major world populations based on activity score (AS) assignments. Results: Allele frequencies vary considerably across the major ethnic groups predicting poor metabolizer status (AS = 0) between 0.4 and 5.4% across world populations. The prevalence of genotypic intermediate (AS = 0.5) and normal (AS = 1, 1.5, or 2) metabolizers ranges between 0.4 and 11% and between 67 and 90%, respectively. Finally, 1 to 21% of subjects (AS >2) are predicted to have ultrarapid metabolizer status. Conclusions: This comprehensive study summarizes allele frequencies, diplotypes, and predicted phenotype across major populations, providing a rich data resource for clinicians and researchers. Challenges of phenotype prediction from genotype data are highlighted and discussed. Genet Med 19 1, 69–76. PMID:27388693

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. Phenotype-optimized sequence ensembles substantially improve prediction of disease-causing mutation in cystic fibrosis.

    PubMed

    Masica, David L; Sosnay, Patrick R; Cutting, Garry R; Karchin, Rachel

    2012-08-01

    Cystic fibrosis transmembrane conductance regulator (CFTR) mutation is associated with a phenotypic spectrum that includes cystic fibrosis (CF). The disease liability of some common CFTR mutations is known, but rare mutations are seen in too few patients to categorize unequivocally, making genetic diagnosis difficult. Computational methods can predict the impact of mutation, but prediction specificity is often below that required for clinical utility. Here, we present a novel supervised learning approach for predicting CF from CFTR missense mutation. The algorithm begins by constructing custom multiple sequence alignments called phenotype-optimized sequence ensembles (POSEs). POSEs are constructed iteratively, by selecting sequences that optimize predictive performance on a training set of CFTR mutations of known clinical significance. Next, we predict CF disease liability from a different set of CFTR mutations (test-set mutations). This approach achieves improved prediction performance relative to popular methods recently assessed using the same test-set mutations. Of clinical significance, our method achieves 94% prediction specificity. Because databases such as HGMD and locus-specific mutation databases are growing rapidly, methods that automatically tailor their predictions for a specific phenotype may be of immediate utility. If the performance achieved here generalizes to other systems, the approach could be an excellent tool to help establish genetic diagnoses.

  11. Predicting quantitative and qualitative values of recreation participation

    Treesearch

    Elwood L., Jr. Shafer; George Moeller

    1971-01-01

    If future recreation consumption and associated intangible values can be predicted, the problem of rapid decision making in recreation-resource management can be reduced, and the problems of implementing those decisions can be anticipated. Management and research responsibilities for meeting recreation demand are discussed, and proved methods for forecasting recreation...

  12. Explaining the disease phenotype of intergenic SNP through predicted long range regulation.

    PubMed

    Chen, Jingqi; Tian, Weidong

    2016-10-14

    Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. Explaining the disease phenotype of intergenic SNP through predicted long range regulation

    PubMed Central

    Chen, Jingqi; Tian, Weidong

    2016-01-01

    Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes. PMID:27280978

  14. Demographic and phenotypic responses of juvenile steelhead trout to spatial predictability of food resources

    Treesearch

    Matthew R. Sloat; Gordon H. Reeves

    2014-01-01

    We manipulated food inputs among patches within experimental streams to determine how variation in foraging behavior influenced demographic and phenotypic responses of juvenile steelhead trout (Oncorhynchus mykiss) to the spatial predictability of food resources. Demographic responses included compensatory adjustments in fish abundance, mean fish...

  15. 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.

  16. Computational Models for Prediction of Yeast Strain Potential for Winemaking from Phenotypic Profiles

    PubMed Central

    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

  17. 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

  18. 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.

  19. SuSPect: Enhanced Prediction of Single Amino Acid Variant (SAV) Phenotype Using Network Features

    PubMed Central

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

    2014-01-01

    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

  20. 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. Copyright © 2014. Published by Elsevier Ltd.

  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.

  3. 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.

  4. 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

  5. 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

  6. Predicting adaptive phenotypes from multilocus genotypes in Sitka spruce (Picea sitchensis) using random forest.

    PubMed

    Holliday, Jason A; Wang, Tongli; Aitken, Sally

    2012-09-01

    Climate is the primary driver of the distribution of tree species worldwide, and the potential for adaptive evolution will be an important factor determining the response of forests to anthropogenic climate change. Although association mapping has the potential to improve our understanding of the genomic underpinnings of climatically relevant traits, the utility of adaptive polymorphisms uncovered by such studies would be greatly enhanced by the development of integrated models that account for the phenotypic effects of multiple single-nucleotide polymorphisms (SNPs) and their interactions simultaneously. We previously reported the results of association mapping in the widespread conifer Sitka spruce (Picea sitchensis). In the current study we used the recursive partitioning algorithm 'Random Forest' to identify optimized combinations of SNPs to predict adaptive phenotypes. After adjusting for population structure, we were able to explain 37% and 30% of the phenotypic variation, respectively, in two locally adaptive traits--autumn budset timing and cold hardiness. For each trait, the leading five SNPs captured much of the phenotypic variation. To determine the role of epistasis in shaping these phenotypes, we also used a novel approach to quantify the strength and direction of pairwise interactions between SNPs and found such interactions to be common. Our results demonstrate the power of Random Forest to identify subsets of markers that are most important to climatic adaptation, and suggest that interactions among these loci may be widespread.

  7. Population-level consequences of polymorphism, plasticity and randomized phenotype switching: a review of predictions.

    PubMed

    Wennersten, Lena; Forsman, Anders

    2012-08-01

    The consequences of among-individual phenotypic variation for the performance and ecological success of populations and species has attracted growing interest in recent years. Earlier reviews of this field typically address the consequences for population processes of one specific source of variation (plasticity or polymorphism), or consider one specific aspect of population performance, such as rate of speciation. Here we take a broader approach and study earlier reviews in order to summarize and compare predictions regarding several population-level consequences of phenotypic variation stemming from genetic polymorphism, developmental plasticity or randomized phenotype switching. Unravelling cause-dependent consequences of variation may increase our ability to understand the ecological dynamics of natural populations and communities, develop more informed management plans for protection of biodiversity, suggest possible routes to increased productivity and yield in natural and managed biological systems, and resolve inconsistencies in patterns and results seen in studies of different model systems. We find an overall agreement regarding the effects of higher levels of phenotypic variation generated by different sources, but also some differences between fine-grained and coarse-grained environments, modular and unitary organisms, mobile and sessile organisms, and between flexible and fixed traits. We propose ways to test the predictions and identify issues where current knowledge is limited and future lines of investigation promise to provide important novel insights. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.

  8. 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

  9. Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour.

    PubMed

    Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E; Kayser, Manfred

    2017-02-27

    Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing.

  10. Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour

    PubMed Central

    Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H.; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R.; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E.; Kayser, Manfred

    2017-01-01

    Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing. PMID:28240252

  11. Hypertriglyceridemic-waist phenotype predicts diabetes: a cohort study in Chinese urban adults

    PubMed Central

    2012-01-01

    Background Hypertriglycedemic-waist (HTGW) phenotype is a simple and inexpensive screening parameter to identify people at increased risk for cardiovascular disease. We evaluated whether the HTGW phenotype predicts prediabetes and diabetes in Chinese urban adults. Methods Two thousand nine hundred and eight (2908) subjects including 1957 men and 951 women, aged 20 years and older, free of prediabetes and diabetes at baseline were enrolled in 2008 and followed for 3 years. Meanwhile, new cases of prediabetes and diabetes were identified via annual physical examination. Cox proportional hazards models were used to assess the association of HTGW phenotype with the incidence of prediabetes and diabetes. Results One thousand five hundred and thirty-three (1533) new prediabetes and 90 new diabetes cases were diagnosed during the follow-up period. The accumulated incidence of prediabetes and diabetes was 52.7% and 3.1%, respectively. Compared with the normal waist normal triglyceride (NWNT) group, those in the HTGW group had higher incidence of prediabetes and diabetes for both men and women. The hazard ratio (HR) for developing prediabetes in the presence of HTGW phenotype at baseline was 1.51 (95% confidence interval [CI] =1.04-2.19) in women, not in men (HR=1.01; 95% CI = 0.82-1.24), after adjusting for age, body mass index, systolic blood pressure, total cholesterol and low density lipoprotein-cholesterol. The HR for developing diabetes were 4.46 (95% CI = 1.88-10.60) in men and 4.64 (95% CI = 1.20-17.97) in women for people who were HTGW phenotype at baseline, after adjusting for age, body mass index, systolic blood pressure, total cholesterol and low density lipoprotein-cholesterol. Conclusions The HTGW phenotype can be used as a simple screening approach to predict diabetes. By using this approach, it is possible to identify individuals at high-risk for diabetes, which is of great significance in reducing the incidence of diabetes among Chinese urban adults. PMID

  12. AudioGene: Predicting Hearing Loss Genotypes from Phenotypes to Guide Genetic Screening

    PubMed Central

    Taylor, Kyle R.; DeLuca, Adam P.; Shearer, A. Eliot; Hildebrand, Michael S.; Black-Ziegelbein, E. Ann; Anand, V. Nikhil; Sloan, Christina M.; Eppsteiner, Robert W.; Scheetz, Todd E.; Huygen, Patrick L. M.; Smith, Richard J. H.; Braun, Terry A.; Casavant, Thomas L.

    2013-01-01

    Autosomal Dominant Nonsyndromic Hearing Loss (ADNSHL) is a common and often progressive sensory deficit. ADNSHL displays a high degree of genetic heterogeneity, and varying rates of progression. Accurate, comprehensive and cost-effective genetic testing facilitates genetic counseling and provides valuable prognostic information to affected individuals. In this paper, we describe the algorithm underlying AudioGene, a software system employing machine-learning techniques that utilizes phenotypic information derived from audiograms to predict the genetic cause of hearing loss in persons segregating ADNSHL. Our data show that AudioGene has an accuracy of 68% in predicting the causative gene within its top three predictions, as compared to 44% for a Majority classifier. We also show that AudioGene remains effective for audiograms with high levels of clinical measurement noise. We identify audiometric outliers for each genetic locus and hypothesize that outliers may reflect modifying genetic effects. As personalized genomic medicine becomes more common, AudioGene will be increasingly useful as a phenotypic filter to assess pathogenicity of variants identified by massively parallel sequencing. PMID:23280582

  13. Phenotypic engineering of sperm-production rate confirms evolutionary predictions of sperm competition theory

    PubMed Central

    Sekii, Kiyono; Vizoso, Dita B.; Kuales, Georg; De Mulder, Katrien; Ladurner, Peter; Schärer, Lukas

    2013-01-01

    Sperm production is a key male reproductive trait and an important parameter in sperm competition theory. Under sperm competition, paternity success is predicted to depend strongly on male allocation to sperm production. Furthermore, because sperm production is inherently costly, individuals should economize in sperm expenditure, and conditional adjustment of the copulation frequency according to their sperm availability may be expected. However, experimental studies showing effects of sperm production on mating behaviour and paternity success have so far been scarce, mainly because sperm production is difficult to manipulate directly in animals. Here, we used phenotypic engineering to manipulate sperm-production rate, by employing dose-dependent RNA interference (RNAi) of a spermatogenesis-specific gene, macbol1, in the free-living flatworm Macrostomum lignano. We demonstrate (i) that our novel dose-dependent RNAi approach allows us to induce high variability in sperm-production rate; (ii) that a reduced sperm-production rate is associated with a decreased copulation frequency, suggesting conditional adjustment of mating behaviour; and (iii) that both sperm production and copulation frequency are important determinants of paternity success in a competitive situation, as predicted by sperm competition theory. Our study clearly documents the potential of phenotypic engineering via dose-dependent RNAi to test quantitative predictions of evolutionary theory. PMID:23446521

  14. Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models.

    PubMed

    Shihab, Hashem A; Gough, Julian; Cooper, David N; Stenson, Peter D; Barker, Gary L A; Edwards, Keith J; Day, Ian N M; Gaunt, Tom R

    2013-01-01

    The rate at which nonsynonymous single nucleotide polymorphisms (nsSNPs) are being identified in the human genome is increasing dramatically owing to advances in whole-genome/whole-exome sequencing technologies. Automated methods capable of accurately and reliably distinguishing between pathogenic and functionally neutral nsSNPs are therefore assuming ever-increasing importance. Here, we describe the Functional Analysis Through Hidden Markov Models (FATHMM) software and server: a species-independent method with optional species-specific weightings for the prediction of the functional effects of protein missense variants. Using a model weighted for human mutations, we obtained performance accuracies that outperformed traditional prediction methods (i.e., SIFT, PolyPhen, and PANTHER) on two separate benchmarks. Furthermore, in one benchmark, we achieve performance accuracies that outperform current state-of-the-art prediction methods (i.e., SNPs&GO and MutPred). We demonstrate that FATHMM can be efficiently applied to high-throughput/large-scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations. To illustrate this, we evaluated nsSNPs in wheat (Triticum spp.) to identify some of the important genetic variants responsible for the phenotypic differences introduced by intense selection during domestication. A Web-based implementation of FATHMM, including a high-throughput batch facility and a downloadable standalone package, is available at http://fathmm.biocompute.org.uk.

  15. 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

  16. CytoASP: a Cytoscape app for qualitative consistency reasoning, prediction and repair in biological networks.

    PubMed

    Kittas, Aristotelis; Barozet, Amélie; Sereshti, Jekaterina; Grabe, Niels; Tsoka, Sophia

    2015-07-11

    Qualitative reasoning frameworks, such as the Sign Consistency Model (SCM), enable modelling regulatory networks to check whether observed behaviour can be explained or if unobserved behaviour can be predicted. The BioASP software collection offers ideal tools for such analyses. Additionally, the Cytoscape platform can offer extensive functionality and visualisation capabilities. However, specialist programming knowledge is required to use BioASP and no methods exist to integrate both of these software platforms effectively. We report the implementation of CytoASP, an app that allows the use of BioASP for influence graph consistency checking, prediction and repair operations through Cytoscape. While offering inherent benefits over traditional approaches using BioASP, it provides additional advantages such as customised visualisation of predictions and repairs, as well as the ability to analyse multiple networks in parallel, exploiting multi-core architecture. We demonstrate its usage in a case study of a yeast genetic network, and highlight its capabilities in reasoning over regulatory networks. We have presented a user-friendly Cytoscape app for the analysis of regulatory networks using BioASP. It allows easy integration of qualitative modelling, combining the functionality of BioASP with the visualisation and processing capability in Cytoscape, and thereby greatly simplifying qualitative network modelling, promoting its use in relevant projects.

  17. Prediction of individual implant bone levels and the existence of implant "phenotypes".

    PubMed

    Papantonopoulos, Georgios; Gogos, Christos; Housos, Efthymios; Bountis, Tassos; Loos, Bruno G

    2017-07-01

    To cluster implants placed in patients of a private practice and identify possible implant "phenotypes" and predictors of individual implant mean bone levels (IIMBL). Clinical and radiographical variables were collected from 72 implant-treated patients with 237 implants and a mean 7.4 ± 3.5 years of function. We clustered implants using the k-means method guided by multidimensional unfolding. For predicting IIMBL, we used principal component analysis (PCA) as a variable reduction method for an ensemble selection (ES) and a support vector machines models (SVMs). Network analysis investigated variable interactions. We identified a cluster of implants susceptible to peri-implantitis (96% of the implants in the cluster were affected by peri-implantitis) and two overlapping clusters of implants resistant to peri-implantitis. The cluster susceptible to peri-implantitis showed a mean IIMBL of 5.2 mm and included implants placed mainly in the lower front jaw and in mouths having a mean of eight teeth. PCA extracted the parameters such as number of teeth, full-mouth plaque scores, implant surface, periodontitis severity, age and diabetes as significant in explaining the data variability. ES and SVMs showed good results in predicting IIMBL (root-mean-squared error of 0.133 and 0.149, 10-fold cross-validation error of 0.147 and 0.150, respectively). Network analysis revealed limited interdependencies of variables among peri-implantitis-affected and non-affected implants and supported the hypothesis of the existence of distinct implant "phenotypes." Two implant "phenotypes" were identified, one with susceptibility and another with resistance to peri-implantitis. Prediction of IIMBL could be achieved by using six variables. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. A Multiplex Cancer/Testis Antigen-Based Biomarker Panel to Predict the Aggressive Phenotype of Prostate Cancer

    DTIC Science & Technology

    2016-09-01

    AWARD NUMBER: W81XWH-12-1-0535 TITLE: A Multiplex Cancer /Testis Antigen-Based Biomarker Panel to Predict the Aggressive Phenotype of Prostate... Cancer PRINCIPAL INVESTIGATOR: Dr. Robert W. Veltri CONTRACTING ORGANIZATION: Johns Hopkins University Baltimore, MD 21218-2680 REPORT DATE...COVERED 30Sep2012 - 29Jun2016 4. TITLE AND SUBTITLE: A Multiplex Cancer /Testis Antigen-Based Biomarker Panel to Predict the Aggressive Phenotype of

  19. Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data.

    PubMed

    Guo, Wentian; Li, Hui; Zhu, Yitan; Lan, Li; Yang, Shengjie; Drukker, Karen; Morris, Elizabeth; Burnside, Elizabeth; Whitman, Gary; Giger, Maryellen L; Ji, Yuan

    2015-10-01

    Genomic and radiomic imaging profiles of invasive breast carcinomas from The Cancer Genome Atlas and The Cancer Imaging Archive were integrated and a comprehensive analysis was conducted to predict clinical outcomes using the radiogenomic features. Variable selection via LASSO and logistic regression were used to select the most-predictive radiogenomic features for the clinical phenotypes, including pathological stage, lymph node metastasis, and status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Cross-validation with receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) was employed as the prediction metric. Higher AUCs were obtained in the prediction of pathological stage, ER, and PR status than for lymph node metastasis and HER2 status. Overall, the prediction performances by genomics alone, radiomics alone, and combined radiogenomics features showed statistically significant correlations with clinical outcomes; however, improvement on the prediction performance by combining genomics and radiomics data was not found to be statistically significant, most likely due to the small sample size of 91 cancer cases with 38 radiomic features and 144 genomic features.

  20. Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data

    PubMed Central

    Guo, Wentian; Li, Hui; Zhu, Yitan; Lan, Li; Yang, Shengjie; Drukker, Karen; Morris, Elizabeth; Burnside, Elizabeth; Whitman, Gary; Giger, Maryellen L.; Ji, Yuan; TCGA Breast Phenotype Research Group

    2015-01-01

    Abstract. Genomic and radiomic imaging profiles of invasive breast carcinomas from The Cancer Genome Atlas and The Cancer Imaging Archive were integrated and a comprehensive analysis was conducted to predict clinical outcomes using the radiogenomic features. Variable selection via LASSO and logistic regression were used to select the most-predictive radiogenomic features for the clinical phenotypes, including pathological stage, lymph node metastasis, and status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Cross-validation with receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) was employed as the prediction metric. Higher AUCs were obtained in the prediction of pathological stage, ER, and PR status than for lymph node metastasis and HER2 status. Overall, the prediction performances by genomics alone, radiomics alone, and combined radiogenomics features showed statistically significant correlations with clinical outcomes; however, improvement on the prediction performance by combining genomics and radiomics data was not found to be statistically significant, most likely due to the small sample size of 91 cancer cases with 38 radiomic features and 144 genomic features. PMID:26835491

  1. Frequency of undetected CYP2D6 hybrid genes in clinical samples: impact on phenotype prediction.

    PubMed

    Black, John Logan; Walker, Denise L; O'Kane, Dennis J; Harmandayan, Maria

    2012-01-01

    Cytochrome P450 2D6 (CYP2D6) is highly polymorphic. CYP2D6-2D7 hybrid genes can be present in samples containing CYP2D6*4 and CYP2D6*10 alleles. CYP2D7-2D6 hybrid genes can be present in samples with duplication signals and in samples with homozygous genotyping results. The frequency of hybrid genes in clinical samples is unknown. We evaluated 1390 samples for undetected hybrid genes by polymerase chain reaction (PCR) amplification, PCR fragment analysis, TaqMan copy number assays, DNA sequencing, and allele-specific primer extension assay. Of 508 CYP2D6*4-containing samples, 109 (21.5%) harbored CYP2D6*68 + *4-like, whereas 9 (1.8%) harbored CYP2D6*4N + *4-like. Of 209 CYP2D6*10-containing samples, 44 (21.1%) were found to have CYP2D6*36 + *10. Of 332 homozygous samples, 4 (1.2%) harbored a single CYP2D7-2D6 hybrid, and of 341 samples with duplication signals, 25 (7.3%) harbored an undetected CYP2D7-2D6 hybrid. Phenotype before and after accurate genotyping was predicted using a method in clinical use. The presence of hybrid genes had no effect on the phenotype prediction of CYP2D6*4- and CYP2D6*10-containing samples. Four of four (100%) homozygous samples containing a CYP2D7-2D6 gene had a change in predicted phenotype, and 23 of 25 (92%) samples with a duplication signal and a CYP2D7-2D6 gene had a change in predicted phenotype. Four novel genes were identified (CYP2D6*13A1 variants 1 and 2, CYP2D6*13G1, and CYP2D6*13G2), and two novel hybrid tandem structures consisting of CYP2D6*13B + *68×2 + *4-like and CYP2D6*13A1 variant 2 + *1×N were observed.

  2. Prediction of radiosensitivity in human bladder cell lines using nuclear chromatin phenotype.

    PubMed

    Rajab, Nor F; McKenna, Declan J; Diamond, Jim; Williamson, Kate; Hamilton, Peter W; McKelvey-Martin, Valerie J

    2006-10-01

    Nuclear texture analysis measures phenotypic changes in chromatin distribution within a cell nucleus, while the alkaline Comet assay is a sensitive method for measuring the extent of DNA breakage in individual cells. The authors aim to use both methods to provide information about the sensitivity of cells to ionizing radiation. The alkaline Comet assay was performed on six human bladder carcinoma cell lines and one human urothelial cell line exposed to gamma-radiation doses from 0 to 10 Gy. Nuclear chromatin texture analysis of 40 features was then performed in the same cell lines exposed to 0, 2, and 6 Gy to explore if nuclear phenotype was related to radiation sensitivity. Comet assay results demonstrated that the cell lines exhibited different levels of radiosensitivity and could be divided into a radiosensitive and a radioresistant group at >6 Gy. Using stepwise discriminant analysis, a subset of important nuclear texture features that best discriminated between sensitive and resistant cell lines were identified A classification function, defined using these features, correctly classified 81.75% of all cells into their radiosensitive or radioresistant groups based on their pretreatment chromatin phenotype. Posttreatment chromatin changes also varied between cell lines, with sensitive cell lines showing a relaxed chromatin conformation following radiation, whereas resistant cell lines exhibited chromatin condensation. The authors conclude that the alkaline Comet assay and nuclear texture methodologies may prove to be valuable aids in predicting the response of tumor cells to radiotherapy.

  3. Predictive model for toluene degradation and microbial phenotypic profiles in flat plate vapor phase bioreactor

    SciTech Connect

    Mirpuri, R.; Sharp, W.; Villaverde, S.; Jones, W.; Lewandowski, Z.; Cunningham, A.

    1997-06-01

    A predictive model has been developed to describe degradation of toluene in a flat-plate vapor phase bioreactor (VPBR). The VPBR model incorporates kinetic, stoichiometric, injury, and irreversible loss coefficients from suspended culture studies for toluene degradation by P. putida 54G and measured values of Henry`s law constant and boundary layer thickness at the gas-liquid and liquid-biofilm interface. The model is used to estimate the performance of the reactor with respect to toluene degradation and to predict profiles of toluene concentration and bacterial physiological state within the biofilm. These results have been compared with experimentally determined values from a flat plate VPBR under electron acceptor and electron donor limiting conditions. The model accurately predicts toluene concentrations in the vapor phase and toluene degradation rate by adjusting only three parameters: biomass density and rates of death and endogenous decay. Qualitatively, the model also predicts gradients in the physiological state cells in the biofilm. This model provides a rational design for predicting an upper limit of toluene degradation capability in a VPBR and is currently being tested to assess applications for predicting performance of bench and pilot-scale column reactors.

  4. Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

    PubMed

    Wu, Mon-Ju; Mwangi, Benson; Bauer, Isabelle E; Passos, Ives C; Sanches, Marsal; Zunta-Soares, Giovana B; Meyer, Thomas D; Hasan, Khader M; Soares, Jair C

    2017-01-15

    Diagnosis, clinical management and research of psychiatric disorders remain subjective - largely guided by historically developed categories which may not effectively capture underlying pathophysiological mechanisms of dysfunction. Here, we report a novel approach of identifying and validating distinct and biologically meaningful clinical phenotypes of bipolar disorders using both unsupervised and supervised machine learning techniques. First, neurocognitive data were analyzed using an unsupervised machine learning approach and two distinct clinical phenotypes identified namely; phenotype I and phenotype II. Second, diffusion weighted imaging scans were pre-processed using the tract-based spatial statistics (TBSS) method and 'skeletonized' white matter fractional anisotropy (FA) and mean diffusivity (MD) maps extracted. The 'skeletonized' white matter FA and MD maps were entered into the Elastic Net machine learning algorithm to distinguish individual subjects' phenotypic labels (e.g. phenotype I vs. phenotype II). This calculation was performed to ascertain whether the identified clinical phenotypes were biologically distinct. Original neurocognitive measurements distinguished individual subjects' phenotypic labels with 94% accuracy (sensitivity=92%, specificity=97%). TBSS derived FA and MD measurements predicted individual subjects' phenotypic labels with 76% and 65% accuracy respectively. In addition, individual subjects belonging to phenotypes I and II were distinguished from healthy controls with 57% and 92% accuracy respectively. Neurocognitive task variables identified as most relevant in distinguishing phenotypic labels included; Affective Go/No-Go (AGN), Cambridge Gambling Task (CGT) coupled with inferior fronto-occipital fasciculus and callosal white matter pathways. These results suggest that there may exist two biologically distinct clinical phenotypes in bipolar disorders which can be identified from healthy controls with high accuracy and at an

  5. Phenotypic variance predicts symbiont population densities in corals: a modeling approach.

    PubMed

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

    2010-02-12

    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. 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 degrees 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 Island showed an emergence of high

  6. 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

  7. Experimental evolution of phenotypic plasticity: how predictive are cross-environment genetic correlations?

    PubMed

    Czesak, Mary Ellen; Fox, Charles W; Wolf, Jason B

    2006-09-01

    Genetic correlations are often predictive of correlated responses of one trait to selection on another trait. There are examples, however, in which genetic correlations are not predictive of correlated responses. We examine how well a cross-environment genetic correlation predicts correlated responses to selection and the evolution of phenotypic plasticity in the seed beetle Stator limbatus. This beetle exhibits adaptive plasticity in egg size by laying large eggs on a resistant host and small eggs on a high-quality host. From a half-sib analysis, the cross-environment genetic correlation estimate was large and positive (rA=0.99). However, an artificial-selection experiment on egg size found that the realized genetic correlations were positive but asymmetrical; that is, they depended on both the host on which selection was imposed and the direction of selection. The half-sib estimate poorly predicted the evolution of egg size plasticity; plasticity evolved when selection was imposed on one host but did not evolve when selection was imposed on the other host. We use a simple two-locus additive genetic model to explore the conditions that can generate the observed realized genetic correlation and the observed pattern of plasticity evolution. Our model and experimental results indicate that the ability of genetic correlations to predict correlated responses to selection depends on the underlying genetic architecture producing the genetic correlation.

  8. Network science meets respiratory medicine for OSAS phenotyping and severity prediction

    PubMed Central

    Mihaicuta, Stefan; Topirceanu, Alexandru; Udrescu, Lucretia

    2017-01-01

    Obstructive sleep apnea syndrome (OSAS) is a common clinical condition. The way that OSAS risk factors associate and converge is not a random process. As such, defining OSAS phenotypes fosters personalized patient management and population screening. In this paper, we present a network-based observational, retrospective study on a cohort of 1,371 consecutive OSAS patients and 611 non-OSAS control patients in order to explore the risk factor associations and their correlation with OSAS comorbidities. To this end, we construct the Apnea Patients Network (APN) using patient compatibility relationships according to six objective parameters: age, gender, body mass index (BMI), blood pressure (BP), neck circumference (NC) and the Epworth sleepiness score (ESS). By running targeted network clustering algorithms, we identify eight patient phenotypes and corroborate them with the co-morbidity types. Also, by employing machine learning on the uncovered phenotypes, we derive a classification tree and introduce a computational framework which render the Sleep Apnea Syndrome Score (SASScore); our OSAS score is implemented as an easy-to-use, web-based computer program which requires less than one minute for processing one individual. Our evaluation, performed on a distinct validation database with 231 consecutive patients, reveals that OSAS prediction with SASScore has a significant specificity improvement (an increase of 234%) for only 8.2% sensitivity decrease in comparison with the state-of-the-art score STOP-BANG. The fact that SASScore has bigger specificity makes it appropriate for OSAS screening and risk prediction in big, general populations. PMID:28503375

  9. Sphingoid Base Metabolism in Yeast: Mapping Gene Expression Patterns Into Qualitative Metabolite Time Course Predictions

    PubMed Central

    2001-01-01

    Can qualitative metabolite time course predictions be inferred from measured mRNA expression patterns? Speaking against this possibility is the large number of ‘decoupling’ control points that lie between these variables, i.e. translation, protein degradation, enzyme inhibition and enzyme activation. Speaking for it is the notion that these control points might be coordinately regulated such that action exerted on the mRNA level is informative of action exerted on the protein and metabolite levels. A simple kinetic model of sphingoid base metabolism in yeast is postulated. When the enzyme activities in this model are modulated proportional to mRNA expression levels measured in heat shocked yeast, the model yields a transient rise and fall in sphingoid bases followed by a permanent rise in ceramide. This finding is in qualitative agreement with experiments and is thus consistent with the aforementioned coordinated control system hypothesis. PMID:18629242

  10. Qualitative and semiquantitative polymerase chain reaction to predict Plasmodium falciparum treatment failure.

    PubMed

    Kain, K C; Kyle, D E; Wongsrichanalai, C; Brown, A E; Webster, H K; Vanijanonta, S; Looareesuwan, S

    1994-12-01

    Multidrug-resistant falciparum malaria is increasing in most malaria-endemic areas. Rapid methods for predicting treatment failure would aid management and control of drug-resistant infections. In this study, Plasmodium falciparum DNA clearance was examined by qualitative and semiquantitative polymerase chain reaction (PCR). Thai patients with acute falciparum malaria were prospectively followed by light microscopy and by PCR of P. falciparum DNA eluted from filter paper blood samples. A 206-bp P. falciparum sequence was amplified and detected radiometrically and by high-performance liquid chromatography. Clearance of P. falciparum DNA was significantly delayed in treatment failures compared with that in successfully treated patients (P = .02). Semiquantitative PCR levels did not drop to < 50% of pretreatment levels until day 3 or later in treatment failures compared with day 1 or earlier for successfully treated parasitemia-matched controls (P = .005). These results suggest that qualitative and semiquantitative PCR may be useful as a method for monitoring response to therapy.

  11. 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

  12. A 50-SNP assay for biogeographic ancestry and phenotype prediction in the U.S. population.

    PubMed

    Gettings, Katherine Butler; Lai, Ronald; Johnson, Joni L; Peck, Michelle A; Hart, Jessica A; Gordish-Dressman, Heather; Schanfield, Moses S; Podini, Daniele S

    2014-01-01

    When an STR DNA profile obtained from crime scene evidence does not match identified suspects or profiles from available databases, further DNA analyses targeted at inferring the possible ancestral origin and phenotypic characteristics of the perpetrator could yield valuable information. Single Nucleotide Polymorphisms (SNPs), the most common form of genetic polymorphisms, have alleles associated with specific populations and/or correlated to physical characteristics. We have used single base primer extension (SBE) technology to develop a 50 SNP assay (composed of three multiplexes) designed to predict ancestry among the primary U.S. populations (African American, East Asian, European American, and Hispanic American/Native American), as well as pigmentation phenotype (eye, hair, and skin color) among European American. We have optimized this assay to a sensitivity level comparable to current forensic DNA analyses, and shown robust performance on forensic-type samples. In addition, we developed a prediction model for ancestry in the U.S. population, based on the random match probability and likelihood ratio formulas already used in forensic laboratories. Lastly, we evaluated the biogeographic ancestry prediction model using a test set, and we evaluated an existing model for eye color with our U.S. sample set. Using these models with recommended thresholds, the 50 SNP assay provided accurate ancestry information in 98.6% of the test set samples, and provided accurate eye color information in 61% of the European samples tested (25% were inconclusive and 14% were incorrect). This method, which uses equipment already available in forensic DNA laboratories, is recommended for use in U.S. forensic casework to provide additional information about the donor of a DNA sample when the STR profile has not been linked to an individual. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Epigenetic Variation at SKA2 Predicts Suicide Phenotypes and Internalizing Psychopathology

    PubMed Central

    Sadeh, Naomi; Wolf, Erika J.; Logue, Mark W.; Hayes, Jasmeet P.; Stone, Annjanette; Griffin, L. Michelle; Schichman, Steven A.; Miller, Mark W.

    2016-01-01

    Background "DNA methylation of the SKA2 gene has recently been implicated as a biomarker of suicide risk and posttraumatic stress disorder (PTSD). To examine the specificity and reliability of these findings, we examined associations between SKA2 DNA methylation, broad dimensions of psychiatric symptoms, and suicide phenotypes in adults with high levels of trauma exposure. Methods A total of 466 White, non-Hispanic veterans and their intimate partners (65% male) underwent clinical assessment and had blood drawn for genotyping and methylation analysis. DNA methylation of the CpG locus cg13989295 and genotype at the methylation-associated single-nucleotide polymorphism (SNP) rs7208505 were examined in relation to current and lifetime PTSD, internalizing and externalizing psychopathology, and suicide phenotypes (ideation, plans, and attempts). Results DNA methylation at the previously implicated SKA2 CpG locus (cg13989295) was associated with current and lifetime symptoms of internalizing (but not externalizing) disorders. SKA2 methylation levels also predicted higher rates of current suicidal thoughts and behaviors, even after including well-established psychiatric risk factors for suicide in the model. Associations between PTSD and SKA2 were not significant, and genetic variation at the methylation-associated SNP (rs7208505) was not related to any of the phenotypes examined. Conclusions SKA2 methylation may index a general propensity to experience stress-related psychopathology, including internalizing disorders and suicidal thoughts and behaviors. This study demonstrates that SKA2 methylation levels explain unique variance in suicide risk not captured by clinical symptom interviews, providing further evidence of its potential utility as a biomarker of suicide risk and stress-related psychopathology. PMID:27038412

  14. Environmental metabolomics links genotype to phenotype and predicts genotype abundance in wild plant populations.

    PubMed

    Field, Katie J; Lake, Janice A

    2011-08-01

    'The Holy Grail' of plant ecology is to uncover rules that associate species and traits with environmental constraints, community composition and subsequent ecosystem functioning. These aims have been crystallized in recent years within the context of global climate change and environmental pollution, increasing the urgency of the need to predict how vegetation will respond across spatial scales. We investigated whether genetic diversity is associated with the way in which phenotypic plasticity within plant populations is realized and whether this is related to genotype abundance. We used environmental metabolomics to demonstrate biochemical variation between co-occurring genotypes of Carex caryophyllea L. A novel combined metabolomic/functional trait analysis was used to test the functionality of this variation in governing plasticity to variation in edaphic conditions, with particular reference to metabolic pathways that play important roles in growth-related traits. We show that genetic diversity within a wild C. caryophyllea population relates to differences in metabolic composition and functional traits in response to soil nutrient variation, influencing genotype abundance within a community. Our findings highlight the vital role genetic diversity plays within a population in facilitating plant phenotypic plasticity and the potential usefulness of environmental metabolomics to future ecological studies.

  15. Gene-expression patterns predict phenotypes of immune-mediated thrombosis

    PubMed Central

    Potti, Anil; Bild, Andrea; Dressman, Holly K.; Lewis, Deborah A.; Nevins, Joseph R.; Ortel, Thomas L.

    2006-01-01

    Antiphospholipid antibody syndrome (APS) is a complex autoimmune thrombotic disorder with defined clinical phenotypes. Although not all patients with elevated antiphospholipid antibody (aPLA) levels develop complications, the severity of these potential events mandates aggressive and extended lifelong anti-thrombotic therapy. One hundred twenty-nine patients (57 patients with APS and venous thromboembolism [VTE], 32 patients with VTE without aPLA, 32 patients with aPLA only, and 8 healthy patients) were enrolled. RNA from peripheral-blood collection was used for DNA microarray analysis. Patterns of gene expression that characterize APS as well as thrombosis in the presence of aPLA were identified by hierarchical clustering and binary regression methods. Gene-expression profiles identify and predict individuals with APS from patients with VTE without aPLA. Importantly, similar methods identified expression profiles that accurately predicted those patients with aPLA at high risk for thrombotic events. All profiles were validated in independent cohorts of patients. The ability to predict APS, but more importantly, those patients at risk for venous thrombosis, represents a paradigm for a genomic approach that can be applied to other populations of patients with venous thrombosis, providing for more effective clinical management of disease, while also reflecting the possible underlying biologic processes. PMID:16263789

  16. 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.

  17. Bacterial spores in food: how phenotypic variability complicates prediction of spore properties and bacterial behavior.

    PubMed

    Eijlander, Robyn T; Abee, Tjakko; Kuipers, Oscar P

    2011-04-01

    Bacillus spores are a known cause of food spoilage and their increased resistance poses a major challenge in efficient elimination. Recent studies on bacterial cultures at the single cell level have revealed how minor differences in essential spore properties, such as core water content or germinant receptor levels, can cause the observed differences in spore germination and outgrowth behavior. Moreover, heterogeneous behavior is influenced by commonly accepted food preservation techniques, such as heating or the usage of weak organic acids. Understanding the underlying molecular mechanisms and key players involved in phenotypic heterogeneity of spores, while taking the spore's history into account, will improve predictability of the spore's behavior to various treatments and triggers. Copyright © 2010 Elsevier Ltd. All rights reserved.

  18. 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.

  19. Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

    PubMed

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-03-01

    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.

  20. Circulating Tumor Cell Phenotype Predicts Recurrence and Survival in Pancreatic Adenocarcinoma

    PubMed Central

    Poruk, Katherine E.; Valero, Vicente; Saunders, Tyler; Blackford, Amanda L.; Griffin, James F.; Poling, Justin; Hruban, Ralph H.; Anders, Robert A.; Herman, Joseph; Zheng, Lei; Rasheed, Zeshaan A.; Laheru, Daniel A.; Ahuja, Nita; Weiss, Matthew J.; Cameron, John L.; Goggins, Michael; Iacobuzio-Donahue, Christine A.; Wood, Laura D.; Wolfgang, Christopher L.

    2016-01-01

    Objective We assessed circulating tumor cells (CTCs) with epithelial and mesenchymal phenotypes as a potential prognostic biomarker for patients with pancreatic adenocarcinoma (PDAC). Background PDAC is the fourth leading cause of cancer death in the United States. There is an urgent need to develop biomarkers that predict patient prognosis and allow for better treatment stratification. Methods Peripheral and portal blood samples were obtained from 50 patients with PDAC before surgical resection and filtered using the Isolation by Size of Epithelial Tumor cells method. CTCs were identified by immunofluorescence using commercially available antibodies to cytokeratin, vimentin, and CD45. Results Thirty-nine patients (78%) had epithelial CTCs that expressed cytokeratin but not CD45. Twenty-six (67%) of the 39 patients had CTCs which also expressed vimentin, a mesenchymal marker. No patients had cytokeratin-negative and vimentin-positive CTCs. The presence of cytokeratin-positive CTCs (P < 0.01), but not mesenchymal-like CTCs (P = 0.39), was associated with poorer survival. The presence of cytokeratin-positive CTCs remained a significant independent predictor of survival by multi-variable analysis after accounting for other prognostic factors (P < 0.01). The detection of CTCs expressing both vimentin and cytokeratin was predictive of recurrence (P = 0.01). Among patients with cancer recurrence, those with vimentin-positive and cytokeratin-expressing CTCs had decreased median time to recurrence compared with patients without CTCs (P = 0.02). Conclusions CTCs are an exciting potential strategy for understanding the biology of metastases, and provide prognostic utility for PDAC patients. CTCs exist as heterogeneous populations, and assessment should include phenotypic identification tailored to characterize cells based on epithelial and mesenchymal markers. PMID:26756760

  1. 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

  2. A qualitative method for prediction of amine oxidation in methanol and water.

    PubMed

    Bäcktorp, Carina; Örnskov, Eivor; Evertsson, Emma; Remmelgas, Johan; Broo, Anders

    2015-04-01

    We have developed a predictive method, based on quantum chemical calculations, that qualitatively predicts N-oxidation by hydrogen peroxides in drug structures. The method uses linear correlations of two complementary approaches to estimate the activation barrier without calculating it explicitly. This method can therefore be automated as it avoids demanding transition state calculations. As such, it may be used by chemists without experience in molecular modeling and provide additional understanding to experimental findings. The predictive method gives relative rates for N,N-dimethylbenzylamine and N-methylmorpholine in good agreement with experiments. In water, the experimental rate constants show that N,N-dimethylbenzylamine is oxidized three times faster than N-methylmorpholine and in methanol it is two times faster. The method suggests it to be two and five times faster, respectively. The method was also used to correlate experimental with predicted activation barriers, linear free-energy relationships, for a test set of tertiary amines. A correlation coefficient R(2) = 0.74 was obtained, where internal diagnostics in the method itself allowed identification of outliers. The method was applied to four drugs: caffeine, azelastine, buspirone, and clomipramine, all possessing several nitrogens. Both overall susceptibility and selectivity of oxidation were predicted, and verified by experiments.

  3. Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges.

    PubMed

    Daneshjou, Roxana; Wang, Yanran; Bromberg, Yana; Bovo, Samuele; Martelli, Pier L; Babbi, Giulia; Lena, Pietro Di; Casadio, Rita; Edwards, Matthew; Gifford, David; Jones, David T; Sundaram, Laksshman; Bhat, Rajendra Rana; Li, Xiaolin; Pal, Lipika R; Kundu, Kunal; Yin, Yizhou; Moult, John; Jiang, Yuxiang; Pejaver, Vikas; Pagel, Kymberleigh A; Li, Biao; Mooney, Sean D; Radivojac, Predrag; Shah, Sohela; Carraro, Marco; Gasparini, Alessandra; Leonardi, Emanuela; Giollo, Manuel; Ferrari, Carlo; Tosatto, Silvio C E; Bachar, Eran; Azaria, Johnathan R; Ofran, Yanay; Unger, Ron; Niroula, Abhishek; Vihinen, Mauno; Chang, Billy; Wang, Maggie H; Franke, Andre; Petersen, Britt-Sabina; Pirooznia, Mehdi; Zandi, Peter; McCombie, Richard; Potash, James B; Altman, Russ B; Klein, Teri E; Hoskins, Roger A; Repo, Susanna; Brenner, Steven E; Morgan, Alexander A

    2017-09-01

    Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships. © 2017 Wiley Periodicals, Inc.

  4. Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast.

    PubMed

    Wang, Zhuo; Danziger, Samuel A; Heavner, Benjamin D; Ma, Shuyi; Smith, Jennifer J; Li, Song; Herricks, Thurston; Simeonidis, Evangelos; Baliga, Nitin S; Aitchison, John D; Price, Nathan D

    2017-05-01

    Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.

  5. 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.

  6. Modularity-based credible prediction of disease genes and detection of disease subtypes on the phenotype-gene heterogeneous network.

    PubMed

    Yao, Xin; Hao, Han; Li, Yanda; Li, Shao

    2011-05-20

    Protein-protein interaction networks and phenotype similarity information have been synthesized together to discover novel disease-causing genes. Genetic or phenotypic similarities are manifested as certain modularity properties in a phenotype-gene heterogeneous network consisting of the phenotype-phenotype similarity network, protein-protein interaction network and gene-disease association network. However, the quantitative analysis of modularity in the heterogeneous network and its influence on disease-gene discovery are still unaddressed. Furthermore, the genetic correspondence of the disease subtypes can be identified by marking the genes and phenotypes in the phenotype-gene network. We present a novel network inference method to measure the network modularity, and in particular to suggest the subtypes of diseases based on the heterogeneous network. Based on a measure which is introduced to evaluate the closeness between two nodes in the phenotype-gene heterogeneous network, we developed a Hitting-Time-based method, CIPHER-HIT, for assessing the modularity of disease gene predictions and credibly prioritizing disease-causing genes, and then identifying the genetic modules corresponding to potential subtypes of the queried phenotype. The CIPHER-HIT is free to rely on any preset parameters. We found that when taking into account the modularity levels, the CIPHER-HIT method can significantly improve the performance of disease gene predictions, which demonstrates modularity is one of the key features for credible inference of disease genes on the phenotype-gene heterogeneous network. By applying the CIPHER-HIT to the subtype analysis of Breast cancer, we found that the prioritized genes can be divided into two sub-modules, one contains the members of the Fanconi anemia gene family, and the other contains a reported protein complex MRE11/RAD50/NBN. The phenotype-gene heterogeneous network contains abundant information for not only disease genes discovery but also

  7. Understanding and predicting effects of modified interactions through a qualitative analysis of community structure.

    PubMed

    Dambacher, Jeffrey M; Ramos-Jiliberto, Rodrigo

    2007-09-01

    Models of ecological communities are traditionally based on relationships between pairs of species, where the strengths of per capita interactions are fixed and independent of population abundance. A growing body of literature, however; describes interactions whose strength is modified by the density of either a third species or by one of the species involved in a pairwise interaction. These modified interactions have been treated as indirect effects, and the terminology addressing them is diverse and overlapping. In this paper we develop a general analytical framework based on a qualitative analysis of community structure to account for the consequence of modified interactions in complex ecological communities. Modified interactions are found to create both direct and indirect effects between species. The sign of a direct effect can change in some instances depending on the magnitude of a key variable or parameter, which leads to a threshold change in system structure and dynamics. By considering alternative structures of a community, we extend our ability to model perturbations that move the system far from a previous equilibrium. Using specific examples, we reinterpret existing results, develop hypotheses to guide experiments or management interventions, and explore the role of modified interactions and positive feedback in creating and maintaining alternative stable states. Through a qualitative analysis of community structure, system feedback is demonstrated as being key in understanding and predicting the dynamics of complex ecological communities.

  8. Phenotyping vs. genotyping for prediction of clopidogrel efficacy and safety: the PEGASUS-PCI study.

    PubMed

    Siller-Matula, J M; Delle-Karth, G; Lang, I M; Neunteufl, T; Kozinski, M; Kubica, J; Maurer, G; Linkowska, K; Grzybowski, T; Huber, K; Jilma, B

    2012-04-01

    Prognostic values of genotyping and phenotyping for assessment of clopidogrel responsiveness have been shown in independent studies. To compare different assays for prediction of events during long-term follow-up. In this prospective cohort study polymorphisms of CYP2C19*2 and CYP2C19*17 alleles, vasodilator-stimulated phosphoprotein phosphorylation (VASP) assay, multiple electrode aggregometry (MEA), cone and platelet analyser (CPA) and platelet function analyser (PFA-100) were performed in 416 patients undergoing percutaneous coronary intervention. The rates of events were recorded during a 12-month follow-up. Platelet aggregation by MEA predicted stent thrombosis (2.4%) better (c-index = 0.90; P < 0.001; sensitivity = 90%; specificity = 83%) than the VASP assay, CPA or PFA-100 (c-index < 0.70; P > 0.05; sensitivity < 70%; specificity < 70% for all) or even the CYP2C19*2 polymorphism (c-index < 0.56; P > 0.05; sensitivity = 30%; specificity = 71%). Survival analysis indicated that patients classified as poor responders by MEA had a substantially higher risk of developing stent thrombosis or MACE than clopidogrel responders (12.5% vs. 0.3%, P < 0.001, and 18.5% vs. 11.3%, P = 0.022, respectively), whereas poor metabolizers (CYP2C19*1/*2 or *2/*2 carriers) were not at increased risks (stent thrombosis, 2.7% vs. 2.5%, P > 0.05; MACE, 13.5% vs. 12.1%, P = 0.556). The incidence of major bleedings (2.6%) was numerically higher in patients with an enhanced vs. poor response to clopidogrel assessed by MEA (4% vs. 0%) or in ultra-metabolizers vs. regular metabolizers (CYP2C19*17/*17 vs. CYP2C19*1/*1; 9.5% vs. 2%). The classification tree analysis demonstrated that acute coronary syndrome at hospitalization and diabetes mellitus were the best discriminators for clopidogrel responder status.  Phenotyping of platelet response to clopidogrel was a better predictor of stent thrombosis than genotyping. © 2012 International Society on Thrombosis and Haemostasis.

  9. Both parental psychopathology and prenatal maternal alcohol dependency can predict the behavioral phenotype in children.

    PubMed

    Staroselsky, Arthur; Fantus, Ellen; Sussman, Reuven; Sandor, Paul; Koren, Gideon; Nulman, Irena

    2009-01-01

    To identify whether a child's behavior phenotype can be predicted by parental psychopathology and/or prenatal maternal alcohol dependency by using the Child Behavior List (CBCL) as a screening tool. A retrospective cohort of four non-exclusive groups of children (aged 8-15 years) was studied: (i) children exposed to alcohol in utero (n = 25); (ii) children not exposed to alcohol in utero (n = 46); (iii) children exposed to parental psychopathology (n = 37); (iv) children not exposed to parental psychopathology (n = 34). To distinguish between the effects of alcohol and parental psychopathology, the children were further subdivided into groups with alcohol exposure in utero and parental psychopathology (n = 23), and psychopathology without alchohol exposure (n = 14). Each child was assessed with the CBCL. Subscale scores and selected subscale items were compared between the groups using t-tests and regression analysis. Children exposed to alcohol in utero scored significantly lower than unexposed children on school competency (p = 0.015). They were more likely to attend special classes (p = 0.048), repeat a grade (p = 0.011), and display more disobedience (p = 0.039) and vandalism (p = 0.033). For special classes and disobedience at school, gender proved to be a significant predictor, while maternal alcohol dependency was a significant predictor of vandalism and repeated grades. Children with parental psychopathology differed from children without parental psychopathology in the anxious/depressed (p = 0.04), social problems (p = 0.004), and attention problems (p = 0.04) subscales. The subscale items that were significantly different between the groups were nervousness (p = 0.002), self-consciousness (p = 0.019), feelings of worthlessness (p = 0.041), loneliness (p = 0.005), and difficulty with concentration (p = 0.02). Parental psychopathology was a significant predictor of all five items. Age and gender, however, were significant predictors only of difficulty with

  10. Predicting the effect of surface texture on the qualitative form of prehension.

    PubMed

    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.

  11. The application of artificial neural networks for phenotypic drug resistance prediction: evaluation and comparison with other interpretation systems.

    PubMed

    Pasomsub, Ekawat; Sukasem, Chonlaphat; Sungkanuparph, Somnuek; Kijsirikul, Boonserm; Chantratita, Wasun

    2010-03-01

    Although phenotypic resistance testing provides more direct measurement of antiretroviral drug resistance than genotypic testing, it is costly and time-consuming. However, genotypic resistance testing has the advantages of being simpler and more accessible, and it might be possible to use the data obtained for predicting quantitative drug susceptibility to interpret complex mutation combinations. This study applied the Artificial Neural Network (ANN) system to predict the HIV-1 resistance phenotype from the genotype. A total of 7,598 pairs of HIV-1 sequences, with their corresponding phenotypic fold change values for 14 antiretroviral drugs, were trained, validated, and tested in ANN modeling. The results were compared with the HIV-SEQ and Geno2pheno interpretation systems. The prediction performance of the ANN models was measured by 10-fold cross-validation. The results indicated that by using the ANN, with an associated set of amino acid positions known to influence drug resistance for individual antiretroviral drugs, drug resistance was accurately predicted and generalized for individual HIV-1 subtypes. Therefore, high correlation with the experimental phenotype may help physicians choose optimal therapeutic regimens that might be an option, or supporting system, of FDA-approved genotypic resistance testing in heavily treatment-experienced patients.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  13. Correlation between gene expression and mutator phenotype predicts homologous recombination deficiency and outcome in ovarian cancer.

    PubMed

    Lu, Jianping; Wu, Di; Li, Chuanxing; Zhou, Meng; Hao, Dapeng

    2014-11-01

    New strategies are needed to predict response to platinum-based chemotherapy and outcome of ovarian cancers. We hypothesized that the mutator phenotype in the cancer genome represents the overuse of alternative DNA repair mechanisms, which might be a sign of homologous recombination (HR) deficiency and can be captured by gene expression. Multidimensional data of ovarian cancer patients and breast cancer patients from The Cancer Genome Atlas (TCGA) database were used for the development and validation of a potential clinical information-independent score that correlates with HR deficiency and predicts outcome. Correlation of the score with platinum response, outcome, and BRCA mutations was assessed. The score correlated with increased genomic mutation rate in both ovarian cancer and breast cancer cases that harbored a substantial subset of HR-deficient samples. Significantly improved outcomes were observed in the high-scoring group versus the low-scoring group in the TCGA dataset and in three large gene expression microarray datasets. A strong correlation was found between the score and the likelihood of achieving complete response to chemotherapy. The score was also found to be highly robust to noises in genomic mutations. Sixty-four patients harboring BRCA mutations were successfully divided into two groups based on scores, with the high-scoring group showing significantly improved outcomes compared with wild-type cases and the low-scoring group showing no significance in all the same analyses. The score was significantly correlated with the response to platinum therapy and outcome. Evaluation of the score as a prognostic tool in ovarian cancer patients is warranted. We develop a diagnostic signature for the HR-deficiency based on a novel hypothesis. HR-deficiency score is significantly correlated to platinum therapy and outcomes. HRDS was validated by its association with OS, PFS, DFS and CR in validation datasets. Evaluation of the score as a prognostic tool in

  14. Dextromethorphan as a phenotyping test to predict endoxifen exposure in patients on tamoxifen treatment.

    PubMed

    de Graan, Anne-Joy M; Teunissen, Sebastiaan F; de Vos, Filip Y F L; Loos, Walter J; van Schaik, Ron H N; de Jongh, Felix E; de Vos, Aad I; van Alphen, Robbert J; van der Holt, Bronno; Verweij, Jaap; Seynaeve, Caroline; Beijnen, Jos H; Mathijssen, Ron H J

    2011-08-20

    Tamoxifen, a widely used agent for the prevention and treatment of breast cancer, is mainly metabolized by CYP2D6 and CYP3A to form its most abundant active metabolite, endoxifen. Interpatient variability in toxicity and efficacy of tamoxifen is substantial. Contradictory results on the value of CYP2D6 genotyping to reduce the variable efficacy have been reported. In this pharmacokinetic study, we investigated the value of dextromethorphan, a known probe drug for both CYP2D6 and CYP3A enzymatic activity, as a potential phenotyping probe for tamoxifen pharmacokinetics. In this prospective study, 40 women using tamoxifen for invasive breast cancer received a single dose of dextromethorphan 2 hours after tamoxifen intake. Dextromethorphan, tamoxifen, and their respective metabolites were quantified. Exposure parameters of all compounds were estimated, log transformed, and subsequently correlated. A strong and highly significant correlation (r = -0.72; P < .001) was found between the exposures of dextromethorphan (0 to 6 hours) and endoxifen (0 to 24 hours). Also, the area under the plasma concentration-time curve of dextromethorphan (0 to 6 hours) and daily trough endoxifen concentration was strongly correlated (r = -0.70; P < .001). In a single patient using the potent CYP2D6 inhibitor paroxetine, the low endoxifen concentration was accurately predicted by dextromethorphan exposure. Dextromethorphan exposure after a single administration adequately predicted endoxifen exposure in individual patients with breast cancer taking tamoxifen. This test could contribute to the personalization and optimization of tamoxifen treatment, but it needs additional validation and simplification before being applicable in future dosing strategies.

  15. Prediction of phenotypes of missense mutations in human proteins from biological assemblies.

    PubMed

    Wei, Qiong; Xu, Qifang; Dunbrack, Roland L

    2013-02-01

    Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence-based and structure-based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure-based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X-ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease-associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e-5). When adding this information to sequence-based features such as the difference between wildtype and mutant position-specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence-based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease-associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins.

  16. Kinetic cellular phenotypic profiling: prediction, identification, and analysis of bioactive natural products.

    PubMed

    Fu, Huiying; Fu, Wenqing; Sun, Mingjiao; Shou, Qiyang; Zhai, Yunyan; Cheng, Hongqiang; Teng, Li; Mou, Xiaozhou; Li, Yanwei; Wan, Shuying; Zhang, Shanshan; Xu, Qinqin; Zhang, Xue; Wang, Jiucun; Zhu, Jenny; Wang, Xiaobo; Xu, Xiao; Lv, Guiyuan; Jin, Li; Guo, Wensheng; Ke, Yuehai

    2011-09-01

    Natural products have always been a major source of therapeutic agents; however, the development of traditional herbal products has been currently hampered by the lack of analytic methods suitable for both high-throughput screening and evaluating the mechanism of action. Cellular processes such as proliferation, apoptosis, and toxicity are well-orchestrated in real time. Monitoring these events and their perturbation by natural products can provide high-rich information about cell physiological relevancies being involved. Here, we report a novel cell-based phenotypic profiling strategy that uses electronic impedance readouts for real-time monitoring of cellular responses to traditional Chinese medicines (TCMs). The utility of this approach was used to screen natural herbs that have been historically documented to cure human diseases and that have been classified into seven clusters based on their mechanisms of action. The results suggest that herbal medicines with similar cellular mechanisms produce similar time/dose-dependent cell response profiles (TCRPs). By comparing the TCRPs produced by the Chinese medicinal Cordyceps sinensis with similar TCRPs of chemical compounds, we explored the potential use of herbal TCRPs for predicting cellular mechanisms of action, herbal authentications, and bioactive identification. Additionally, we further compared this novel TCRP technology with high-performance liquid chromatography (HPLC)-based methods for herbal origin-tracing authentication and identification of bioactive ingredients. Together, our findings suggest that using TCRP as an alternative to existing spectroscopic techniques can allow us to analyze natural products in a more convenient and physiologically relevant manner.

  17. 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.

  18. Predictive power of quantitative and qualitative fecal immunochemical tests for hemoglobin in population screening for colorectal neoplasm.

    PubMed

    Huang, Yanqin; Li, Qilong; Ge, Weiting; Cai, Shanrong; Zhang, Suzhan; Zheng, Shu

    2014-01-01

    The aim of this study was to evaluate the performance of qualitative and quantitative fecal immunochemical tests (FITs) in population screening for colorectal neoplasm. A total of 9000 participants aged between 40 and 74 years were enrolled in this study. Each participant received two stool sampling tubes and was asked to simultaneously submit two stool samples from the same bowel movement. The stool samples of each participant were tested using an immunogold labeling FIT dipstick (qualitative FIT) and an automated fecal blood analyzer (quantitative FIT). Colonoscopy was performed for those who test positive in either FIT. The positive predictive values and population detection rates of the FITs for predicting colorectal neoplasm were compared. A total of 6494 (72.16%) participants simultaneously submitted two stool samples. The diagnostic consistency for a positive result between quantitative and qualitative FITs was poor (κ=0.278, 95% confidence interval=0.223-0.333). The positive predictive values of the quantitative FIT were significantly higher than those of the qualitative FIT for predicting large (≥1 cm) adenomas (23 cases, 14.29% and 16 cases, 6.72%, P=0.013) and colorectal cancer (10 cases, 6.21% and 5 cases, 2.10%, P=0.034); however, the population detection rate for advanced neoplasm of the quantitative FIT was not significantly different from that of the qualitative FIT. Quantitative FIT is superior to qualitative FIT in predicting advanced colorectal neoplasm during colorectal cancer screening. Further studies are needed to elucidate the causes of the predictive superiority.

  19. Bateman's principle and immunity: phenotypically plastic reproductive strategies predict changes in immunological sex differences.

    PubMed

    McKean, Kurt A; Nunney, Leonard

    2005-07-01

    The sexes often differ in the reproductive trait limiting their fitness, an observation known as Bateman's principle. In many species, females are limited by their ability to produce eggs while males are limited by their ability to compete for and successfully fertilize those eggs. As well as promoting the evolution of sex-specific reproductive strategies, this difference may promote sex differences in other life-history traits due to their correlated effects. Sex differences in disease susceptibility and immune function are common. Two hypotheses based on Bateman's principle have been proposed to explain this pattern: that selection to prolong the period of egg production favors improved immune function in females, or that the expression of secondary sexual characteristics reduces immune function in males. Both hypotheses predict a relatively fixed pattern of reduced male immune function, at least in sexually mature individuals. An alternative hypothesis is that Bateman's principle does not dictate fixed patterns of reproductive investment, but favors phenotypically plastic reproductive strategies with males and females adaptively responding to variation in fitness-limiting resource availability. Under this hypothesis, neither sex is expected to possess intrinsically superior immune function, and immunological sex differences may vary in different environments. We demonstrate that sex-specific responses to experimental manipulation of fitness-limiting resources affects both the magnitude and direction of sex differences in immune function in Drosophila melanogaster. In the absence of sexual interactions and given abundant food, the immune function of adults was maximized in both sexes and there was no sex difference. Manipulation of food availability and sexual activity resulted in female-biased immune suppression when food was limited, and male-biased immune suppression when sexual activity was high and food was abundant. The immunological cost to males of

  20. 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

  1. Predicting Protein Function by Genomic Context: Quantitative Evaluation and Qualitative Inferences

    PubMed Central

    Huynen, Martijn; Snel, Berend; Lathe, Warren; Bork, Peer

    2000-01-01

    Various new methods have been proposed to predict functional interactions between proteins based on the genomic context of their genes. The types of genomic context that they use are Type I: the fusion of genes; Type II: the conservation of gene-order or co-occurrence of genes in potential operons; and Type III: the co-occurrence of genes across genomes (phylogenetic profiles). Here we compare these types for their coverage, their correlations with various types of functional interaction, and their overlap with homology-based function assignment. We apply the methods to Mycoplasma genitalium, the standard benchmarking genome in computational and experimental genomics. Quantitatively, conservation of gene order is the technique with the highest coverage, applying to 37% of the genes. By combining gene order conservation with gene fusion (6%), the co-occurrence of genes in operons in absence of gene order conservation (8%), and the co-occurrence of genes across genomes (11%), significant context information can be obtained for 50% of the genes (the categories overlap). Qualitatively, we observe that the functional interactions between genes are stronger as the requirements for physical neighborhood on the genome are more stringent, while the fraction of potential false positives decreases. Moreover, only in cases in which gene order is conserved in a substantial fraction of the genomes, in this case six out of twenty-five, does a single type of functional interaction (physical interaction) clearly dominate (>80%). In other cases, complementary function information from homology searches, which is available for most of the genes with significant genomic context, is essential to predict the type of interaction. Using a combination of genomic context and homology searches, new functional features can be predicted for 10% of M. genitalium genes. PMID:10958638

  2. NIBBS-search for fast and accurate prediction of phenotype-biased metabolic systems.

    PubMed

    Schmidt, Matthew C; Rocha, Andrea M; 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

  3. 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

  4. [Phenotype predictions of the pathogenic nonsynonymous single nucleotide polymorphisms in deafness-causing gene COCH].

    PubMed

    Xuli, Qian; Xin, Cao

    2015-07-01

    The COCH (Coagulation factor C homology) gene, located in human chromosome 14q12-q13, is the first gene identified to cause vestibular dysfunction. COCH encodes cochlin, which contains an N-terminal LCCL (Limulus factor C, cochlin, and late gestation lung protein Lgl1) domain and a C-temimal vWFA (Von Willebrand factor type A) domain. Recently, functional research of COCH mutations and cochlin have come under the spotlight in the field of hereditary deafness. Approximately 16 mutations in COCH have been confirmed to date, among which 13 non-synonymous single nucleotide polymorphisms (nsSNPs) are the most common form of genetic variations. Nonetheless, there is poor knowledge on the relationship between the genotype and the phenotype of the other nsSNPs in COCH. Here we analyzed deleterious nsSNPs from all SNPs in the COCH gene in the vWFA domain based on different computational methods and identified eight potential pathogenic nsSNPs (I176T, R180Q, G265E, V269L, I368N, I372T, R416C and Y424D) after combining literatures with 3D structures. Meanwhile, the protein structures of six reported pathogenic nsSNPs (P51S, G87W, I109N, I109T, W117R and F121S) in the LCCL domain have been constructed, and we identified aberrant structural changes in loops and chains. The prediction of pathogenic mutations for COCH nsSNPs will provide a blueprint for screening pathogenic mutations, and it will be beneficial to the functional research of COCH and cochlin in this field.

  5. 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.

  6. MALDI mass spectrometry based molecular phenotyping of CNS glial cells for prediction in mammalian brain tissue.

    PubMed

    Hanrieder, Jörg; Wicher, Grzegorz; Bergquist, Jonas; Andersson, Malin; Fex-Svenningsen, Asa

    2011-07-01

    The development of powerful analytical techniques for specific molecular characterization of neural cell types is of central relevance in neuroscience research for elucidating cellular functions in the central nervous system (CNS). This study examines the use of differential protein expression profiling of mammalian neural cells using direct analysis by means of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). MALDI-MS analysis is rapid, sensitive, robust, and specific for large biomolecules in complex matrices. Here, we describe a newly developed and straightforward methodology for direct characterization of rodent CNS glial cells using MALDI-MS-based intact cell mass spectrometry (ICMS). This molecular phenotyping approach enables monitoring of cell growth stages, (stem) cell differentiation, as well as probing cellular responses towards different stimulations. Glial cells were separated into pure astroglial, microglial, and oligodendroglial cell cultures. The intact cell suspensions were then analyzed directly by MALDI-TOF-MS, resulting in characteristic mass spectra profiles that discriminated glial cell types using principal component analysis. Complementary proteomic experiments revealed the identity of these signature proteins that were predominantly expressed in the different glial cell types, including histone H4 for oligodendrocytes and S100-A10 for astrocytes. MALDI imaging MS was performed, and signature masses were employed as molecular tracers for prediction of oligodendroglial and astroglial localization in brain tissue. The different cell type specific protein distributions in tissue were validated using immunohistochemistry. ICMS of intact neuroglia is a simple and straightforward approach for characterization and discrimination of different cell types with molecular specificity.

  7. Multifactorial Patterns of Gene Expression in Colonic Epithelial Cells Predict Disease Phenotypes in Experimental Colitis

    PubMed Central

    Frantz, Aubrey L.; Bruno, Maria E.C.; Rogier, Eric W.; Tuna, Halide; Cohen, Donald A.; Bondada, Subbarao; Chelvarajan, R. Lakshman; Brandon, J. Anthony; Jennings, C. Darrell; Kaetzel, Charlotte S.

    2012-01-01

    Background The pathogenesis of inflammatory bowel disease (IBD) is complex and the need to identify molecular biomarkers is critical. Epithelial cells play a central role in maintaining intestinal homeostasis. We previously identified 5 “signature” biomarkers in colonic epithelial cells (CEC) that are predictive of disease phenotype in Crohn’s disease. Here we investigate the ability of CEC biomarkers to define the mechanism and severity of intestinal inflammation. Methods We analyzed expression of RelA, A20, pIgR, TNF and MIP-2 in CEC of mice with DSS acute colitis or T cell-mediated chronic colitis. Factor analysis was used to combine the 5 biomarkers into 2 multifactorial principal components (PCs). PC scores for individual mice were correlated with disease severity. Results For both colitis models, PC1 was strongly weighted toward RelA, A20 and pIgR, and PC2 was strongly weighted toward TNF and MIP-2, while the contributions of other biomarkers varied depending on the etiology of inflammation. Disease severity was correlated with elevated PC2 scores in DSS colitis and reduced PC1 scores in T cell transfer colitis. Down-regulation of pIgR was a common feature observed in both colitis models and was associated with altered cellular localization of pIgR and failure to transport IgA. Conclusions A multifactorial analysis of epithelial gene expression may be more informative than examining single gene responses in IBD. These results provide insight into the homeostatic and pro-inflammatory functions of CEC in IBD pathogenesis and suggest that biomarker analysis could be useful for evaluating therapeutic options for IBD patients. PMID:23070952

  8. Use of qualitative environmental and phenotypic variables in the context of allele distribution models: detecting signatures of selection in the genome of Lake Victoria cichlids.

    PubMed

    Joost, Stéphane; Kalbermatten, Michael; Bezault, Etienne; Seehausen, Ole

    2012-01-01

    When searching for loci possibly under selection in the genome, an alternative to population genetics theoretical models is to establish allele distribution models (ADM) for each locus to directly correlate allelic frequencies and environmental variables such as precipitation, temperature, or sun radiation. Such an approach implementing multiple logistic regression models in parallel was implemented within a computing program named MATSAM: . Recently, this application was improved in order to support qualitative environmental predictors as well as to permit the identification of associations between genomic variation and individual phenotypes, allowing the detection of loci involved in the genetic architecture of polymorphic characters. Here, we present the corresponding methodological developments and compare the results produced by software implementing population genetics theoretical models (DFDIST: and BAYESCAN: ) and ADM (MATSAM: ) in an empirical context to detect signatures of genomic divergence associated with speciation in Lake Victoria cichlid fishes.

  9. 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

  10. High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling

    PubMed Central

    Watanabe, Kakeru; Guo, Wei; Arai, Keigo; Takanashi, Hideki; Kajiya-Kanegae, Hiromi; Kobayashi, Masaaki; Yano, Kentaro; Tokunaga, Tsuyoshi; Fujiwara, Toru; Tsutsumi, Nobuhiro; Iwata, Hiroyoshi

    2017-01-01

    Genomics-assisted breeding methods have been rapidly developed with novel technologies such as next-generation sequencing, genomic selection and genome-wide association study. However, phenotyping is still time consuming and is a serious bottleneck in genomics-assisted breeding. In this study, we established a high-throughput phenotyping system for sorghum plant height and its response to nitrogen availability; this system relies on the use of unmanned aerial vehicle (UAV) remote sensing with either an RGB or near-infrared, green and blue (NIR-GB) camera. We evaluated the potential of remote sensing to provide phenotype training data in a genomic prediction model. UAV remote sensing with the NIR-GB camera and the 50th percentile of digital surface model, which is an indicator of height, performed well. The correlation coefficient between plant height measured by UAV remote sensing (PHUAV) and plant height measured with a ruler (PHR) was 0.523. Because PHUAV was overestimated (probably because of the presence of taller plants on adjacent plots), the correlation coefficient between PHUAV and PHR was increased to 0.678 by using one of the two replications (that with the lower PHUAV value). Genomic prediction modeling performed well under the low-fertilization condition, probably because PHUAV overestimation was smaller under this condition due to a lower plant height. The predicted values of PHUAV and PHR were highly correlated with each other (r = 0.842). This result suggests that the genomic prediction models generated with PHUAV were almost identical and that the performance of UAV remote sensing was similar to that of traditional measurements in genomic prediction modeling. UAV remote sensing has a high potential to increase the throughput of phenotyping and decrease its cost. UAV remote sensing will be an important and indispensable tool for high-throughput genomics-assisted plant breeding. PMID:28400784

  11. High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling.

    PubMed

    Watanabe, Kakeru; Guo, Wei; Arai, Keigo; Takanashi, Hideki; Kajiya-Kanegae, Hiromi; Kobayashi, Masaaki; Yano, Kentaro; Tokunaga, Tsuyoshi; Fujiwara, Toru; Tsutsumi, Nobuhiro; Iwata, Hiroyoshi

    2017-01-01

    Genomics-assisted breeding methods have been rapidly developed with novel technologies such as next-generation sequencing, genomic selection and genome-wide association study. However, phenotyping is still time consuming and is a serious bottleneck in genomics-assisted breeding. In this study, we established a high-throughput phenotyping system for sorghum plant height and its response to nitrogen availability; this system relies on the use of unmanned aerial vehicle (UAV) remote sensing with either an RGB or near-infrared, green and blue (NIR-GB) camera. We evaluated the potential of remote sensing to provide phenotype training data in a genomic prediction model. UAV remote sensing with the NIR-GB camera and the 50th percentile of digital surface model, which is an indicator of height, performed well. The correlation coefficient between plant height measured by UAV remote sensing (PHUAV) and plant height measured with a ruler (PHR) was 0.523. Because PHUAV was overestimated (probably because of the presence of taller plants on adjacent plots), the correlation coefficient between PHUAV and PHR was increased to 0.678 by using one of the two replications (that with the lower PHUAV value). Genomic prediction modeling performed well under the low-fertilization condition, probably because PHUAV overestimation was smaller under this condition due to a lower plant height. The predicted values of PHUAV and PHR were highly correlated with each other (r = 0.842). This result suggests that the genomic prediction models generated with PHUAV were almost identical and that the performance of UAV remote sensing was similar to that of traditional measurements in genomic prediction modeling. UAV remote sensing has a high potential to increase the throughput of phenotyping and decrease its cost. UAV remote sensing will be an important and indispensable tool for high-throughput genomics-assisted plant breeding.

  12. 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.

  13. Cerebrospinal fluid total tau concentration predicts clinical phenotype in Huntington's disease.

    PubMed

    Rodrigues, Filipe Brogueira; Byrne, Lauren; McColgan, Peter; Robertson, Nicola; Tabrizi, Sarah J; Leavitt, Blair R; Zetterberg, Henrik; Wild, Edward J

    2016-10-01

    Huntington's disease (HD) is a hereditary neurodegenerative condition with no therapeutic intervention known to alter disease progression, but several trials are ongoing and biomarkers of disease progression are needed. Tau is an axonal protein, often altered in neurodegeneration, and recent studies pointed out its role on HD neuropathology. Our goal was to study whether cerebrospinal fluid (CSF) tau is a biomarker of disease progression in HD. After informed consent, healthy controls, pre-symptomatic and symptomatic gene expansion carriers were recruited from two HD clinics. All participants underwent assessment with the Unified HD Rating Scale '99 (UHDRS). CSF was obtained according to a standardized lumbar puncture protocol. CSF tau was quantified using enzyme-linked immunosorbent assay. Comparisons between two groups were tested using ancova. Pearson's correlation coefficients were calculated for disease progression. Significance level was defined as p < 0.05. Seventy-six participants were included in this cross-sectional multicenter international pilot study. Age-adjusted CSF tau was significantly elevated in gene expansion carriers compared with healthy controls (p = 0.002). UHDRS total functional capacity was significantly correlated with CSF tau (r = -0.29, p = 0.004) after adjustment for age, and UHDRS total motor score was significantly correlated with CSF tau after adjustment for age (r = 0.32, p = 0.002). Several UHDRS cognitive tasks were also significantly correlated with CST total tau after age-adjustment. This study confirms that CSF tau concentrations in HD gene mutation carriers are increased compared with healthy controls and reports for the first time that CSF tau concentration is associated with phenotypic variability in HD. These conclusions strengthen the case for CSF tau as a biomarker in HD. In the era of novel targeted approaches to Huntington's disease, reliable biomarkers are needed. We quantified Tau protein, a marker of

  14. QSTR modeling for qualitative and quantitative toxicity predictions of diverse chemical pesticides in honey bee for regulatory purposes.

    PubMed

    Singh, Kunwar P; Gupta, Shikha; Basant, Nikita; Mohan, Dinesh

    2014-09-15

    Pesticides are designed toxic chemicals for specific purposes and can harm nontarget species as well. The honey bee is considered a nontarget test species for toxicity evaluation of chemicals. Global QSTR (quantitative structure-toxicity relationship) models were established for qualitative and quantitative toxicity prediction of pesticides in honey bee (Apis mellifera) based on the experimental toxicity data of 237 structurally diverse pesticides. Structural diversity of the chemical pesticides and nonlinear dependence in the toxicity data were evaluated using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) QSTR models were constructed for classification (two and four categories) and function optimization problems using the toxicity end point in honey bees. The predictive power of the QSTR models was tested through rigorous validation performed using the internal and external procedures employing a wide series of statistical checks. In complete data, the PNN-QSTR model rendered a classification accuracy of 96.62% (two-category) and 95.57% (four-category), while the GRNN-QSTR model yielded a correlation (R(2)) of 0.841 between the measured and predicted toxicity values with a mean squared error (MSE) of 0.22. The results suggest the appropriateness of the developed QSTR models for reliably predicting qualitative and quantitative toxicities of pesticides in honey bee. Both the PNN and GRNN based QSTR models constructed here can be useful tools in predicting the qualitative and quantitative toxicities of the new chemical pesticides for regulatory purposes.

  15. Quantitative and qualitative models for carcinogenicity prediction for non-congeneric chemicals using CP ANN method for regulatory uses.

    PubMed

    Fjodorova, Natalja; Vračko, Marjan; Tušar, Marjan; Jezierska, Aneta; Novič, Marjana; Kühne, Ralph; Schüürmann, Gerrit

    2010-08-01

    The new European chemicals regulation Registration, Evaluation, Authorization and Restriction of Chemicals entered into force in June 2007 and accelerated the development of quantitative structure-activity relationship (QSAR) models for a variety of endpoints, including carcinogenicity. Here, we would like to present quantitative (continuous) and qualitative (categorical) models for non-congeneric chemicals for prediction of carcinogenic potency. A dataset of 805 substances was obtained after a preliminary screening of findings of rodent carcinogenicity for 1,481 chemicals accessible via Distributed Structure-Searchable Toxicity (DSSTox) Public Database Network originated from the Lois Gold Carcinogenic Potency Database (CPDB). Twenty seven two-dimensional MDL descriptors were selected using Kohonen mapping and principal component analysis. The counter propagation artificial neural network (CP ANN) technique was applied. Quantitative models were developed exploring the relationship between the experimental and predicted carcinogenic potency expressed as a tumorgenic dose TD(50) for rats. The obtained models showed low prediction power with correlation coefficient less than 0.5 for the test set. In the next step, qualitative models were developed. We found that the qualitative models exhibit good accuracy for the training set (92%). The model demonstrated good predicted performance for the test set. It was obtained accuracy (68%), sensitivity (73%), and specificity (63%). We believe that CP ANN method is a good in silico approach for modeling and predicting rodent carcinogenicity for non-congeneric chemicals and may find application for other toxicological endpoints.

  16. Using Computer-extracted Image Phenotypes from Tumors on Breast MRI to Predict Breast Cancer Pathologic Stage

    PubMed Central

    Burnside, Elizabeth S.; Drukker, Karen; Li, Hui; Bonaccio, Ermelinda; Zuley, Margarita; Ganott, Marie; Net, Jose M.; Sutton, Elizabeth; Brandt, Kathleen R.; Whitman, Gary; Conzen, Suzanne; Lan, Li; Ji, Yuan; Zhu, Yitan; Jaffe, Carl; Huang, Erich; Freymann, John; Kirby, Justin; Morris, Elizabeth; Giger, Maryellen

    2015-01-01

    Background To demonstrate that computer-extracted image phenotypes (CEIPs) of biopsy-proven breast cancer on MRI can accurately predict pathologic stage. Methods We used a dataset of de-identified breast MRIs organized by the National Cancer Institute in The Cancer Imaging Archive. We analyzed 91 biopsy-proven breast cancer cases with pathologic stage (stage I = 22; stage II = 58; stage III = 11) and surgically proven nodal status (negative nodes = 46, ≥ 1 positive node = 44, no nodes examined = 1). We characterized tumors by (a) radiologist measured size, and (b) CEIP. We built models combining two CEIPs to predict tumor pathologic stage and lymph node involvement, evaluated them in leave-one-out cross-validation with area under the ROC curve (AUC) as figure of merit. Results Tumor size was the most powerful predictor of pathologic stage but CEIPs capturing biologic behavior also emerged as predictive (e.g. stage I+II vs. III demonstrated AUC = 0.83). No size measure was successful in the prediction of positive lymph nodes but adding a CEIP describing tumor “homogeneity,” significantly improved this discrimination (AUC = 0.62, p=.003) over chance. Conclusions Our results indicate that MRI phenotypes show promise for predicting breast cancer pathologic stage and lymph node status. PMID:26619259

  17. Pushing the Frontier of Data-Oriented Geodynamic Modeling: from Qualitative to Quantitative to Predictive

    NASA Astrophysics Data System (ADS)

    Liu, L.; Hu, J.; Zhou, Q.

    2016-12-01

    The rapid accumulation of geophysical and geological data sets poses an increasing demand for the development of geodynamic models to better understand the evolution of the solid Earth. Consequently, the earlier qualitative physical models are no long satisfying. Recent efforts are focusing on more quantitative simulations and more efficient numerical algorithms. Among these, a particular line of research is on the implementation of data-oriented geodynamic modeling, with the purpose of building an observationally consistent and physically correct geodynamic framework. Such models could often catalyze new insights into the functioning mechanisms of the various aspects of plate tectonics, and their predictive nature could also guide future research in a deterministic fashion. Over the years, we have been working on constructing large-scale geodynamic models with both sequential and variational data assimilation techniques. These models act as a bridge between different observational records, and the superposition of the constraining power from different data sets help reveal unknown processes and mechanisms of the dynamics of the mantle and lithosphere. We simulate the post-Cretaceous subduction history in South America using a forward (sequential) approach. The model is constrained using past subduction history, seafloor age evolution, tectonic architecture of continents, and the present day geophysical observations. Our results quantify the various driving forces shaping the present South American flat slabs, which we found are all internally torn. The 3-D geometry of these torn slabs further explains the abnormal seismicity pattern and enigmatic volcanic history. An inverse (variational) model simulating the late Cenozoic western U.S. mantle dynamics with similar constraints reveals a different mechanism for the formation of Yellowstone-related volcanism from traditional understanding. Furthermore, important insights on the mantle density and viscosity structures

  18. Insulin resistance and systemic inflammation, but not metabolic syndrome phenotype, predict 9 years mortality in older adults

    PubMed Central

    Zuliani, Giovanni; Morieri, Mario Luca; Volpato, Stefano; Maggio, Marcello; Cherubini, Antonio; Francesconi, Daniela; Bandinelli, Stefania; Paolisso, Giuseppe; Guralnik, Jack M.; Ferrucci, Luigi

    2014-01-01

    Background Although metabolic syndrome (MS) is a typical condition of middle-aged/older person, the association between MS and mortality risk has not been confirmed in people over 65 years. We hypothesized that while in the elderly MS phenotype might lose its value in predicting mortality risk, the two core factors of MS, i.e. insulin resistance (IR) and low-grade systemic inflammation (LGSI) would not. Methods 1011 community-dwelling older individuals (InCHIANTI study) were included. MS phenotype was defined by NCEP-ATP-III criteria. IR was calculated by HOMA; high-sensitivity C-reactive protein was measured by ELISA. Subjects were divided into four groups based on presence/absence of IR (HOMA ≥2.27) and LGSI (hs-CRP ≥ 3g/L): Group 1: no IR/LGSI (reference); Group 2: LGSI only; Group 3: IR only; Group 4: IR+LGSI. Hazard Ratios (HR) for 9-years cardiovascular (CVD) and total mortality, according to IR/LGSI groups, were estimated in subjects with (n.311) and without MS by Cox model. Results 31.8% of subjects with MS phenotype had no IR, 45.3% had no LGSI; moreover, 51% of subjects with both IR and LGSI didn’t display the MS phenotype. MS phenotype was not associated with CVD (HR:1.29; 95%C.I.:0.92–1.81) or total (HR:1.07; 95%C.I.:0.86–1.34) mortality risk, whereas the presence of IR plus LGSI was associated with increased CVD (no MS: HR 2.07, 95%CI:1.12–3.72; MS: HR 9.88, 95%CI:2.18–4), and overall (no MS: HR 1.72, 95%CI:1.001–3.17; MS: HR 1.51, 95%CI:1.02–2.28) mortality risk. The presence of IR (HR: 6.90, 95%CI:1.45–32) or LGSI (HR 7.56, 95%CI:1.63–35) was associated with CVD mortality, only among individuals with MS phenotype. Conclusions Among community dwelling older individuals, IR and LGSI, but not MS phenotype, was associated with 9-years overall and CVD mortality risk. Since a reduced “overlap” between MS phenotype and its physiopathological core (IR and LGSI) might be present with aging, we suggest that the definition of MS might

  19. 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…

  20. 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…

  1. 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

    2015-10-30

    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.

  2. Qualitative and quantitative structure-activity relationship modelling for predicting blood-brain barrier permeability of structurally diverse chemicals.

    PubMed

    Gupta, S; Basant, N; Singh, K P

    2015-01-01

    In this study, structure-activity relationship (SAR) models have been established for qualitative and quantitative prediction of the blood-brain barrier (BBB) permeability of chemicals. The structural diversity of the chemicals and nonlinear structure in the data were tested. The predictive and generalization ability of the developed SAR models were tested through internal and external validation procedures. In complete data, the QSAR models rendered ternary classification accuracy of >98.15%, while the quantitative SAR models yielded correlation (r(2)) of >0.926 between the measured and the predicted BBB permeability values with the mean squared error (MSE) <0.045. The proposed models were also applied to an external new in vitro data and yielded classification accuracy of >82.7% and r(2) > 0.905 (MSE < 0.019). The sensitivity analysis revealed that topological polar surface area (TPSA) has the highest effect in qualitative and quantitative models for predicting the BBB permeability of chemicals. Moreover, these models showed predictive performance superior to those reported earlier in the literature. This demonstrates the appropriateness of the developed SAR models to reliably predict the BBB permeability of new chemicals, which can be used for initial screening of the molecules in the drug development process.

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

    PubMed Central

    Agyekum, Alex; Ai, Xiaoman; Ginn, Andrew N.; Zong, Zhiyong; Guo, Xuejun; Turnidge, John; Partridge, Sally R.

    2016-01-01

    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

  4. Longevity and lifetime reproductive success of barn swallow offspring are predicted by their hatching date and phenotypic quality.

    PubMed

    Saino, Nicola; Romano, Maria; Ambrosini, Roberto; Rubolini, Diego; Boncoraglio, Giuseppe; Caprioli, Manuela; Romano, Andrea

    2012-09-01

    1. Longevity is a major determinant of individual differences in Darwinian fitness. Several studies have analyzed the stochastic, time-dependent causes of variation in longevity, but little information exists from free-ranging animal populations on the effects that environmental conditions and phenotype early in ontogeny have on duration of life. 2. In this long-term (1993-2011) study of a migratory, colonial, passerine bird, the barn swallow (Hirundo rustica), we analyzed longevity and, in a subsample of individuals, lifetime reproductive success (LRS) of the offspring that reached sexual maturity in relation to hatching date, which can affect the rearing environment through a seasonal deterioration in ecological conditions. Moreover, we analyzed the consequences of variation in body size and, for the first time in any species, of a major component of immunity on longevity, both by looking at absolute phenotypic values and at deviations from the brood mean. 3. Accelerated failure time models showed that individuals of both sexes that hatched early in any breeding season enjoyed larger longevity and larger LRS, indicating directional selection for early breeding. Both male and female offspring with large T cell-mediated immune response relative to their siblings and female nestlings that dominated the brood size/age hierarchy had larger longevity than their siblings of inferior phenotypic quality/age. Conversely, absolute phenotypic values did not predict longevity. 4. Frailty modelling disclosed marked spatial heterogeneity in longevity among colonies of origin, again stressing the impact of rearing conditions on longevity. 5. This study therefore reinforces the notion that perinatal environment and maternal decisions over timing and site of breeding, and position in the brood hierarchy can have marked effects on progeny life history that extend well into adulthood. In addition, it provides the first evidence from any bird population in the wild that immune

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

    USDA-ARS?s Scientific Manuscript database

    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...

  6. Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

    PubMed

    Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

    2017-07-01

    High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

  7. 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.

  8. Comparison of phenotypic methods in predicting methicillin resistance in coagulase-negative Staphylococcus (CoNS) from animals.

    PubMed

    Zhang, Yifan; Wang, Xiaogang; LeJeune, Jeffrey T; Zervos, Marcus; Bhargava, Kanika

    2011-02-01

    Phenotypic detection of methicillin resistance in coagulase-negative Staphylococcus (CoNS) of animal origin has been challenging due to the heterogeneous expression of mecA. To compare different phenotypic methods in predicting the mecA presence in CoNS, a total of 87 CoNS isolates from agricultural animals were analyzed in this study by agar dilution, disk diffusion, and broth microdilution. mecA was present in 81 CoNS isolates. Broth microdilution demonstrated the highest sensitivity of 100% in predicting the mecA presence, followed by 72.8% by agar dilution and 70.4% by disk diffusion. The results indicate that broth microdilution may be more suitable for predicting the presence of mecA in CoNS from animals than the other two methods, although staphylococcal species may also be a factor affecting the sensitivities of the methods as the top three staphylococcal species in this study were Staphylococcus lentus, Staphylococcus sciuri, and Staphylococcus xylosus (a total of 75 of 87).

  9. Predicting neurological Adverse Drug Reactions based on biological, chemical and phenotypic properties of drugs using machine learning models.

    PubMed

    Jamal, Salma; Goyal, Sukriti; Shanker, Asheesh; Grover, Abhinav

    2017-04-13

    Adverse drug reactions (ADRs) have become one of the primary reasons for the failure of drugs and a leading cause of deaths. Owing to the severe effects of ADRs, there is an urgent need for the generation of effective models which can accurately predict ADRs during early stages of drug development based on integration of various features of drugs. In the current study, we have focused on neurological ADRs and have used various properties of drugs that include biological properties (targets, transporters and enzymes), chemical properties (substructure fingerprints), phenotypic properties (side effects (SE) and therapeutic indications) and a combinations of the two and three levels of features. We employed relief-based feature selection technique to identify relevant properties and used machine learning approach to generated learned model systems which would predict neurological ADRs prior to preclinical testing. Additionally, in order to explain the efficiency and applicability of the models, we tested them to predict the ADRs for already existing anti-Alzheimer drugs and uncharacterized drugs, respectively in side effect resource (SIDER) database. The generated models were highly accurate and our results showed that the models based on chemical (accuracy 93.20%), phenotypic (accuracy 92.41%) and combination of three properties (accuracy 94.18%) were highly accurate while the models based on biological properties (accuracy 82.11%) were highly informative.

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

    PubMed Central

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

    2015-01-01

    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

  11. Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage.

    PubMed

    Burnside, Elizabeth S; Drukker, Karen; Li, Hui; Bonaccio, Ermelinda; Zuley, Margarita; Ganott, Marie; Net, Jose M; Sutton, Elizabeth J; Brandt, Kathleen R; Whitman, Gary J; Conzen, Suzanne D; Lan, Li; Ji, Yuan; Zhu, Yitan; Jaffe, Carl C; Huang, Erich P; Freymann, John B; Kirby, Justin S; Morris, Elizabeth A; Giger, Maryellen L

    2016-03-01

    The objective of this study was to demonstrate that computer-extracted image phenotypes (CEIPs) of biopsy-proven breast cancer on magnetic resonance imaging (MRI) can accurately predict pathologic stage. The authors used a data set of deidentified breast MRIs organized by the National Cancer Institute in The Cancer Imaging Archive. In total, 91 biopsy-proven breast cancers were analyzed from patients who had information available on pathologic stage (stage I, n = 22; stage II, n = 58; stage III, n = 11) and surgically verified lymph node status (negative lymph nodes, n = 46; ≥ 1 positive lymph node, n = 44; no lymph nodes examined, n = 1). Tumors were characterized according to 1) radiologist-measured size and 2) CEIP. Then, models were built that combined 2 CEIPs to predict tumor pathologic stage and lymph node involvement, and the models were evaluated in a leave-1-out, cross-validation analysis with the area under the receiver operating characteristic curve (AUC) as the value of interest. Tumor size was the most powerful predictor of pathologic stage, but CEIPs that captured biologic behavior also emerged as predictive (eg, stage I and II vs stage III demonstrated an AUC of 0.83). No size measure was successful in the prediction of positive lymph nodes, but adding a CEIP that described tumor "homogeneity" significantly improved discrimination (AUC = 0.62; P = .003) compared with chance. The current results indicate that MRI phenotypes have promise for predicting breast cancer pathologic stage and lymph node status. Cancer 2016;122:748-757. © 2015 American Cancer Society. © 2015 American Cancer Society.

  12. Compound Mutations Cause Increased Cardiac Events in Children with Long QT Syndrome: Can the Sequence Homology-Based Tools be Applied for Prediction of Phenotypic Severity?

    PubMed

    Izumi, Gaku; Hayama, Emiko; Yamazawa, Hirokuni; Inai, Kei; Shimada, Mitsuyo; Furutani, Michiko; Nishizawa, Tsutomu; Furutani, Yoshiyuki; Matsuoka, Rumiko; Nakanishi, Toshio

    2016-06-01

    Long QT syndrome (LQTS) can cause syncope, ventricular fibrillation, and death. Recently, several disease-causing mutations in ion channel genes have been identified, and compound mutations have also been detected. It is unclear whether children who are carriers of compound mutations exhibit a more severe phenotype than those with single mutations. Although predicting phenotypic severity is clinically important, the availability of prediction tools for LQTS is unknown. To determine whether the severity of the LQTS phenotype can be predicted by the presence of compound mutations in children is needed. We detected 97 single mutations (Group S) and 13 compound mutations (Group C) between 1998 and 2012, age at diagnosis ranging 0-19 years old (median age is 9.0) and 18.0 years of follow-up period. The phenotypes and Kaplan-Meier event-free rates of the two groups were compared for cardiac events. This study investigated phenotypic severity in relation to the location of mutations in the protein sequence, which was analyzed using two sequence homology-based tools. In results, compound mutations in children were associated with a high incidence of syncope within the first decade (Group S: 32 % vs. Group C: 61 %), requiring an ICD in the second decade (Group S: 3 % vs. Group C: 56 %). Mortality in these patients was high within 5 years of birth (23 %). Phenotypic prediction tools correctly predicted the phenotypic severity in both Groups S and C, especially by using their coupling method. The coupling prediction method is useful in the initial evaluation of phenotypes both with single and compound mutations of LQTS patients. However, it should be noted that the compound mutation makes more severe phenotype.

  13. [Quantitative and qualitative evaluation of the interim PET/CT in lymphoma treatment in the prediction of complete metabolic response].

    PubMed

    Pilkington Woll, J P; García Vicente, A M; Talavera Rubio, M P; Palomar Muñoz, A M; Jiménez Londoño, G; León Martín, A; Calle Primo, C; Soriano Castejón, A M

    2013-03-01

    To compare two different methods for the interpretation of interim PET/CT (PET/CT-i) in lymphomas, and to establish which one best predicts a complete metabolic response (CMR) in the PET/CT study at the end of treatment (PET/CT-et). Retrospective longitudinal analysis of the PET/CT studies for staging (PET/CT-s), PET/CT-i and PET/CT-et of 65 patients, 35 Hodgkin's lymphoma (HL) and 30 Non-HL. The PET/CT-i was performed between the second and fourth chemotherapy cycle. It was interpreted using two different criteria: qualitative criteria (5 point visual scale), semiquantitative criteria (percentage difference between the lesion with more SUVmax in the PET/CT-s and PET/CT-i). We analyzed the likelihood of obtaining a CMR in the PET/CT-et according to the results obtained on the PET/CT-i with these two criteria. We obtained sensitivity (S), specificity (Sp), positive predictive values (PPV), negative predictive values (NPV) and likelihood ratio (LR) for the qualitative/semiquantitative method of 91%/80%, 76.2%/67%, 88.9%/83.3%, 80%/60.9% and 32%/7.8%, respectively, to predict a CMR in the PET/CT-et. There were no statistically significant differences between the LR of both methods (p=0.1942). We found clear differences in S, Sp, PPV and NPV between both interpretation criteria for the PET/CT-i to predict a CMR in the PET/CT-et. Nevertheless, we cannot confirm the superiority of the qualitative method over the semiqualitative method for this purpose as no statistically significance differences were found in their LR in our study. Copyright © 2012 Elsevier España, S.L. y SEMNIM. All rights reserved.

  14. 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. © 2016 Wiley Periodicals, Inc.

  15. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints.

    PubMed

    Sánchez, Benjamín J; Zhang, Cheng; Nilsson, Avlant; Lahtvee, Petri-Jaan; Kerkhoven, Eduard J; Nielsen, Jens

    2017-08-03

    Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model-based design in metabolic engineering. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

  16. 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

    2015-09-04

    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.

  17. ADMET Evaluation in Drug Discovery. Part 17: Development of Quantitative and Qualitative Prediction Models for Chemical-Induced Respiratory Toxicity.

    PubMed

    Lei, Tailong; Chen, Fu; Liu, Hui; Sun, Huiyong; Kang, Yu; Li, Dan; Li, Youyong; Hou, Tingjun

    2017-07-03

    As a dangerous end point, respiratory toxicity can cause serious adverse health effects and even death. Meanwhile, it is a common and traditional issue in occupational and environmental protection. Pharmaceutical and chemical industries have a strong urge to develop precise and convenient computational tools to evaluate the respiratory toxicity of compounds as early as possible. Most of the reported theoretical models were developed based on the respiratory toxicity data sets with one single symptom, such as respiratory sensitization, and therefore these models may not afford reliable predictions for toxic compounds with other respiratory symptoms, such as pneumonia or rhinitis. Here, based on a diverse data set of mouse intraperitoneal respiratory toxicity characterized by multiple symptoms, a number of quantitative and qualitative predictions models with high reliability were developed by machine learning approaches. First, a four-tier dimension reduction strategy was employed to find an optimal set of 20 molecular descriptors for model building. Then, six machine learning approaches were used to develop the prediction models, including relevance vector machine (RVM), support vector machine (SVM), regularized random forest (RRF), extreme gradient boosting (XGBoost), naïve Bayes (NB), and linear discriminant analysis (LDA). Among all of the models, the SVM regression model shows the most accurate quantitative predictions for the test set (q(2)ext = 0.707), and the XGBoost classification model achieves the most accurate qualitative predictions for the test set (MCC of 0.644, AUC of 0.893, and global accuracy of 82.62%). The application domains were analyzed, and all of the tested compounds fall within the application domain coverage. We also examined the structural features of the compounds and important fragments with large prediction errors. In conclusion, the SVM regression model and the XGBoost classification model can be employed as accurate prediction tools

  18. 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

  19. In silico prediction of efavirenz and rifampicin drug–drug interaction considering weight and CYP2B6 phenotype

    PubMed Central

    Rekić, Dinko; Röshammar, Daniel; Mukonzo, Jackson; Ashton, Michael

    2011-01-01

    AIMS This study aimed to test whether a pharmacokinetic simulation model could extrapolate nonclinical drug data to predict human efavirenz exposure after single and continuous dosing as well as the effects of concomitant rifampicin and further to evaluate the weight-based dosage recommendations used to counteract the rifampicin–efavirenz interaction. METHODS Efavirenz pharmacokinetics were simulated using a physiologically based pharmacokinetic model implemented in the Simcyp™ population-based simulator. Physicochemical and metabolism data obtained from the literature were used as input for prediction of pharmacokinetic parameters. The model was used to simulate the effects of rifampicin on efavirenz pharmacokinetics in 400 virtual patients, taking into account bodyweight and CYP2B6 phenotype. RESULTS Apart from the absorption phase, the simulation model predicted efavirenz concentration–time profiles reasonably well, with close agreement with clinical data. The simulated effects of rifampicin co-administration on efavirenz treatment showed only a minor decrease of 16% (95% confidence interval 13–19) in efavirenz area under the concentration–time curve, of the same magnitude as what has been clinically observed (22%). Efavirenz exposure depended on CYP2B6 phenotype and bodyweight. Increasing the efavirenz dose during concomitant rifampicin was predicted to be most successful in patients over 50 kg regardless of CYP2B6 status. CONCLUSIONS Our findings, although based on a simulation approach using limited in vitro data, support the current recommendations for using a 50 kg bodyweight cut-off for efavirenz dose increment when co-treating with rifampicin. PMID:21395646

  20. South Australian Scleroderma Register: autoantibodies as predictive biomarkers of phenotype and outcome.

    PubMed

    Graf, Scott W; Hakendorf, Paul; Lester, Sue; Patterson, Karen; Walker, Jenny G; Smith, Malcolm D; Ahern, Michael J; Roberts-Thomson, Peter J

    2012-02-01

    To investigate the relationship between scleroderma-specific autoantibodies and clinical phenotype and survival in South Australian patients with scleroderma. Two cohorts of patients were studied from the South Australian Scleroderma Register (SASR). In the first, the sera of 129 consecutive patients were analyzed for anticentromere (ACA), anti-Scl70, anti-RNA polymerase III, anti-U1RNP, anti-Th/To, anti-Pm/Scl, anti-Ku and anti-fibrillarin antibodies using the Euroline immunoblot assay. Statistical analysis was performed to look for a significant association between specific antibodies and various clinical features. In the second cohort survival from first symptom onset was analyzed in 285 patients in whom the autoantibody profile was available, including ACA, Anti-Scl70, anti-U1RNP and anti-RNA polymerase III measured using multiple methods. Survival analysis compared mortality between different groups of patients with specific antibodies. ACA, Th/To and Ku antibodies were associated with limited scleroderma, Scl70 and RNA Pol III antibodies were associated with diffuse scleroderma and antibodies to U1RNP were associated with overlap syndrome. Significant associations between Scl70 and interstitial lung disease (P = 0.004), RNA Pol III and renal crisis (P = 0.002), U1RNP and pulmonary hypertension (P = 0.006) and Th/To and pulmonary hypertension (P = 0.034) were seen. Trends were observed with an increased frequency of lung disease with Pm/Scl and Th/To and an increased frequency of myositis with Ku. The presence of Scl70, RNA Pol III and U1RNP was associated with significantly reduced survival as compared with patients with ACA. Scleroderma-specific autoantibodies are associated with clinical phenotype and survival. © 2011 The Authors. International Journal of Rheumatic Diseases © 2011 Asia Pacific League of Associations for Rheumatology and Blackwell Publishing Asia Pty Ltd.

  1. Maternal phenotype, independent of family economic capital, predicts educational attainment in lowland nepalese children

    PubMed Central

    Devakumar, Delan; Wells, Jonathan C.K.; Saville, Naomi; Reid, Alice; Costello, Anthony; Manandhar, Dharma S; Osrin, David

    2016-01-01

    Objectives Factors acting before children are born or reach school‐going age may explain why some do not complete primary education. Many relevant factors relate to maternal phenotype, but few studies have tested for independent associations of maternal factors relative to those characterizing the family in general. Methods Using data from a longitudinal study of 838 children in Dhanusha, Nepal, we used logistic regression models to test whether indices of maternal somatic and educational capital, or family economic capital, were independently associated with children having had ≤2 versus 3+ years of schooling at a mean age of 8.5 years. We also tested whether maternal age, children's early growth, and urban/rural location mediated such associations. Results Children had a higher risk of completing less schooling if their mothers were short, thin, anemic, and uneducated. Independently, lower family material assets and land acreage also increased children's odds of less schooling. There was an indication of gender differences, with the risk of poor educational attainment in girls associated with low maternal somatic and educational capital, whereas in boys the relevant factors were low maternal education and family land ownership. Conclusions Our analysis demonstrates that, independent of broader indices of family capital such as land or material assets, children's educational attainment is associated with factors embodied in maternal phenotype. Both somatic and educational maternal capital appeared important. A composite index of maternal capital could provide a new measurable proxy, prior to school entry, for identifying children at risk of completing fewer years of schooling. Am. J. Hum. Biol. 28:687–698, 2016. © 2016 Wiley Periodicals, Inc. PMID:27135632

  2. Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data.

    PubMed

    Zhang, Wen; Chen, Yanlin; Liu, Feng; Luo, Fei; Tian, Gang; Li, Xiaohong

    2017-01-05

    Drug-drug interactions (DDIs) are one of the major concerns in drug discovery. Accurate prediction of potential DDIs can help to reduce unexpected interactions in the entire lifecycle of drugs, and are important for the drug safety surveillance. Since many DDIs are not detected or observed in clinical trials, this work is aimed to predict unobserved or undetected DDIs. In this paper, we collect a variety of drug data that may influence drug-drug interactions, i.e., drug substructure data, drug target data, drug enzyme data, drug transporter data, drug pathway data, drug indication data, drug side effect data, drug off side effect data and known drug-drug interactions. We adopt three representative methods: the neighbor recommender method, the random walk method and the matrix perturbation method to build prediction models based on different data. Thus, we evaluate the usefulness of different information sources for the DDI prediction. Further, we present flexible frames of integrating different models with suitable ensemble rules, including weighted average ensemble rule and classifier ensemble rule, and develop ensemble models to achieve better performances. The experiments demonstrate that different data sources provide diverse information, and the DDI network based on known DDIs is one of most important information for DDI prediction. The ensemble methods can produce better performances than individual methods, and outperform existing state-of-the-art methods. The datasets and source codes are available at https://github.com/zw9977129/drug-drug-interaction/ .

  3. 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.

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

    PubMed Central

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

    2016-01-01

    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

  5. [A limited sampling strategy of phenotyping probe midazolam to predict inhibited activities of hepatic CYP3A in rats].

    PubMed

    Zhu, Xue-hui; Jiao, Jian-jie; Zhang, Cai-li; Lou, Jian-shi; Liu, Chang-xiao

    2008-09-01

    The present study was to evaluate feasibility of a limited sampling strategy (LSS) in the prediction of inhibited hepatic CYP3A activity with systemic clearance of midazolam (MDZ), a hepatic CYP3A activity phenotyping probe. Rats were pretreated with a serial doses of ketoconazole, a selective inhibitor on CYP3A. Blood samples were collected and detected for MDZ at specified time points after intravenous injection of MDZ. Stepwise regression analysis and a Jack-knife validation procedures were performed in one group of rats as training set to establish the most informative LSS model for accurately estimating the clearance of MDZ. Another group of rats with same treatment was used as validation set to estimate the individual clearance based on predictive equations derived from the training set. Bland-Altman plots showed a good agreement between the systemic clearance calculated from DAS (CLobs) and corresponding parameter that was derived from three LSS models (CLest). LSS models derived from two or three sampling time points, including 60, 90 min, 30, 60, 90 min and 30, 60, 120 min, exhibited a good accuracy and acceptable error for estimating the CLobs of MDZ to evaluate hepatic CYP3A activity, especially the 60, 90 min LSS model is most accurate and convenient. The results supported that limited plasma sampling to predict the systemic clearance of MDZ is easier than the usual method for estimating CYP3A phenotyping when the hepatic activity of CYP3A is reduced in the rat. The present study provided theoretical basis and laboratory evidence for LSS to clinically evaluate metabolizing function of liver and

  6. 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

  7. Pheochromocytoma catecholamine phenotypes and prediction of tumor size and location by use of plasma free metanephrines.

    PubMed

    Eisenhofer, Graeme; Lenders, Jacques W M; Goldstein, David S; Mannelli, Massimo; Csako, Gyorgy; Walther, McClellan M; Brouwers, Frederieke M; Pacak, Karel

    2005-04-01

    Measurements of plasma free metanephrines (normetanephrine and metanephrine) provide a useful test for diagnosis of pheochromocytoma and may provide other information about the nature of these tumors. We examined relationships of tumor size, location, and catecholamine content with plasma and urinary metanephrines or catecholamines in 275 patients with pheochromocytoma. We then prospectively examined whether measurements of plasma free metanephrines could predict tumor size and location in an additional 16 patients. Relative proportions of epinephrine and norepinephrine in tumor tissue were closely matched by relative increases of plasma or urinary metanephrine and normetanephrine, but not by epinephrine and norepinephrine. Tumor diameter showed strong positive relationships with summed plasma concentrations or urinary outputs of metanephrine and normetanephrine (r = 0.81 and 0.77; P <0.001), whereas relationships with plasma or urinary catecholamines were weaker (r = 0.41 and 0.44). All tumors in which increases in plasma metanephrine were >15% of the combined increases of normetanephrine and metanephrine either had adrenal locations or appeared to be recurrences of previously resected adrenal tumors. Measurements of plasma free metanephrines predicted tumor diameter to within a mean of 30% of actual diameter, and high plasma concentrations of free metanephrine relative to normetanephrine accurately predicted adrenal locations. Measurements of plasma free metanephrines not only provide information about the likely presence or absence of a pheochromocytoma, but when a tumor is present, can also help predict tumor size and location. This additional information may be useful for clinical decision-making during tumor localization procedures.

  8. Deep phenotyping to predict live birth outcomes in in vitro fertilization

    PubMed Central

    Banerjee, Prajna; Choi, Bokyung; Shahine, Lora K.; Jun, Sunny H.; O’Leary, Kathleen; Lathi, Ruth B.; Westphal, Lynn M.; Wong, Wing H.; Yao, Mylene W. M.

    2010-01-01

    Nearly 75% of in vitro fertilization (IVF) treatments do not result in live births and patients are largely guided by a generalized age-based prognostic stratification. We sought to provide personalized and validated prognosis by using available clinical and embryo data from prior, failed treatments to predict live birth probabilities in the subsequent treatment. We generated a boosted tree model, IVFBT, by training it with IVF outcomes data from 1,676 first cycles (C1s) from 2003–2006, followed by external validation with 634 cycles from 2007–2008, respectively. We tested whether this model could predict the probability of having a live birth in the subsequent treatment (C2). By using nondeterministic methods to identify prognostic factors and their relative nonredundant contribution, we generated a prediction model, IVFBT, that was superior to the age-based control by providing over 1,000-fold improvement to fit new data (p < 0.05), and increased discrimination by receiver–operative characteristic analysis (area-under-the-curve, 0.80 vs. 0.68 for C1, 0.68 vs. 0.58 for C2). IVFBT provided predictions that were more accurate for ∼83% of C1 and ∼60% of C2 cycles that were out of the range predicted by age. Over half of those patients were reclassified to have higher live birth probabilities. We showed that data from a prior cycle could be used effectively to provide personalized and validated live birth probabilities in a subsequent cycle. Our approach may be replicated and further validated in other IVF clinics. PMID:20643955

  9. Deep phenotyping to predict live birth outcomes in in vitro fertilization.

    PubMed

    Banerjee, Prajna; Choi, Bokyung; Shahine, Lora K; Jun, Sunny H; O'Leary, Kathleen; Lathi, Ruth B; Westphal, Lynn M; Wong, Wing H; Yao, Mylene W M

    2010-08-03

    Nearly 75% of in vitro fertilization (IVF) treatments do not result in live births and patients are largely guided by a generalized age-based prognostic stratification. We sought to provide personalized and validated prognosis by using available clinical and embryo data from prior, failed treatments to predict live birth probabilities in the subsequent treatment. We generated a boosted tree model, IVFBT, by training it with IVF outcomes data from 1,676 first cycles (C1s) from 2003-2006, followed by external validation with 634 cycles from 2007-2008, respectively. We tested whether this model could predict the probability of having a live birth in the subsequent treatment (C2). By using nondeterministic methods to identify prognostic factors and their relative nonredundant contribution, we generated a prediction model, IVF(BT), that was superior to the age-based control by providing over 1,000-fold improvement to fit new data (p<0.05), and increased discrimination by receiver-operative characteristic analysis (area-under-the-curve, 0.80 vs. 0.68 for C1, 0.68 vs. 0.58 for C2). IVFBT provided predictions that were more accurate for approximately 83% of C1 and approximately 60% of C2 cycles that were out of the range predicted by age. Over half of those patients were reclassified to have higher live birth probabilities. We showed that data from a prior cycle could be used effectively to provide personalized and validated live birth probabilities in a subsequent cycle. Our approach may be replicated and further validated in other IVF clinics.

  10. 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

  11. Taxonomy of breast cancer based on normal cell phenotype predicts outcome

    PubMed Central

    Santagata, Sandro; Thakkar, Ankita; Ergonul, Ayse; Wang, Bin; Woo, Terri; Hu, Rong; Harrell, J. Chuck; McNamara, George; Schwede, Matthew; Culhane, Aedin C.; Kindelberger, David; Rodig, Scott; Richardson, Andrea; Schnitt, Stuart J.; Tamimi, Rulla M.; Ince, Tan A.

    2014-01-01

    Accurate classification is essential for understanding the pathophysiology of a disease and can inform therapeutic choices. For hematopoietic malignancies, a classification scheme based on the phenotypic similarity between tumor cells and normal cells has been successfully used to define tumor subtypes; however, use of normal cell types as a reference by which to classify solid tumors has not been widely emulated, in part due to more limited understanding of epithelial cell differentiation compared with hematopoiesis. To provide a better definition of the subtypes of epithelial cells comprising the breast epithelium, we performed a systematic analysis of a large set of breast epithelial markers in more than 15,000 normal breast cells, which identified 11 differentiation states for normal luminal cells. We then applied information from this analysis to classify human breast tumors based on normal cell types into 4 major subtypes, HR0–HR3, which were differentiated by vitamin D, androgen, and estrogen hormone receptor (HR) expression. Examination of 3,157 human breast tumors revealed that these HR subtypes were distinct from the current classification scheme, which is based on estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Patient outcomes were best when tumors expressed all 3 hormone receptors (subtype HR3) and worst when they expressed none of the receptors (subtype HR0). Together, these data provide an ontological classification scheme associated with patient survival differences and provides actionable insights for treating breast tumors. PMID:24463450

  12. 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.

  13. Evaluation of the usefulness of 2 prediction models of clinical prediction models in physical therapy: a qualitative process evaluation.

    PubMed

    van Oort, Lieke; Verhagen, Arianne; Koes, Bart; de Vet, Riekie; Anema, Han; Heymans, Martijn

    2014-06-01

    The purposes of this study were to (1) evaluate the usefulness of 2 prediction models by assessing the actual use and advantages/disadvantages of application in daily clinical practice and (2) propose recommendations to enhance their implementation. Physical therapists working in 283 practices in the area of Breda (the Netherlands) were invited to participate in this study. Two prediction models were presented: (1) to predict persistent shoulder pain and (2) to predict the preferable treatment in nonspecific neck pain. Participants were asked to apply both models in practice. After 2 months, their opinions about the usefulness of both models were gathered during a focus group meeting or by using an online questionnaire in order to identify the most important advantages/disadvantages of each prediction model. In total, 46 physical therapists (13.8%) of 39 practices participated. Evaluative data were available from 32 participants who used the shoulder model 102 times and the neck model 126 times. For the shoulder model, the most frequent advantage (mentioned 14 times) was that it enabled physical therapists to estimate a motivated prognosis, that is, a prognosis based on the score of the model. The most frequent mentioned disadvantage was that participants expressed their doubts about the validity of the model because the model initially was developed for usage in a general practice setting. For the neck model, the most frequently mentioned advantage (29 times) was that the model was easy to interpret. The most important disadvantage (mentioned 14 times) was that the model only takes a few treatment options into account. The physical therapists participating in this study reported that both models evaluated in this study were not easy to use in daily practice. Based on the findings of this study, we recommend that these models are modified to meet the practical needs of the therapist, before assessing their impact on daily clinical care and patient outcomes

  14. Role of androgen ratios in the prediction of the metabolic phenotype in polycystic ovary syndrome.

    PubMed

    Minooee, Sonia; Ramezani Tehrani, Fahimeh; Tohidi, Maryam; Azizi, Fereidoun

    2017-05-01

    To identify the androgen ratio that best predicts insulin resistance and metabolic syndrome among women with polycystic ovary syndrome (PCOS). Data for 180 women with PCOS and 180 healthy controls were extracted from two previous studies in Iran (conducted during 2008-2010 and 2011-2013). The diagnosis of PCOS was based on the Rotterdam criteria. The serum concentration of different androgens was measured. Receiver operating characteristic curve analysis was used to assess the ability of various androgen ratios to predict insulin resistance and metabolic syndrome. Among women with PCOS, the testosterone-to-androstenedione ratio was the best predictor of insulin resistance (sensitivity 0.83, specificity 0.42) and metabolic syndrome (sensitivity 0.85, specificity 0.70). Among healthy controls, the ratio of free androgen index to testosterone was the best predictor of insulin resistance (sensitivity 0.84, specificity 0.33) and metabolic syndrome (sensitivity 0.91, specificity 0.17). The prediction of insulin resistance and metabolic syndrome among women with PCOS was best accomplished with the testosterone-to-androstenedione ratio. © 2017 International Federation of Gynecology and Obstetrics.

  15. 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.

  16. Impact of population diversity on the prediction of 7-SNP NAT2 phenotypes using the tagSNP rs1495741 or paired SNPs.

    PubMed

    Suarez-Kurtz, Guilherme; Sortica, Vinicius A; Vargens, Daniela D; Bruxel, Estela M; Petzl-Erler, Maria-Luiza; Petz-Erler, Maria-Luiza; Tsuneto, Luisa T; Hutz, Mara H

    2012-04-01

    A novel NAT2 tagSNP (rs1495741) and a 2-SNP genotype (rs1041983 and rs1801280) have been recently shown to accurately predict the NAT2 acetylator phenotypes in populations of exclusive or predominant European/White ancestry. We confirmed the accuracy of the tagSNP approach in White Brazilians, but not in Brown or Black Brazilians, sub-Saharan Mozambicans, and Guarani Amerindians. The combined rs1041983 and rs1801280 genotypes provided considerably better prediction of the NAT2 phenotype in Guarani, but no consistent improvement in Brown or Black Brazilians and Mozambicans. Best predictions of the NAT2 phenotype in Mozambicans using NAT2 SNP pairs were obtained with rs1801280 and rs1799930, but the accuracy of the estimates remained inadequate for clinical use or for investigations in this sub-Saharan group or in Brazilians with considerable African ancestry. In conclusion, the rs1495741 tagSNP cannot be applied to predict the NAT2 acetylation phenotype in Guarani and African-derived populations, whereas 2-SNP genotypes may accurately predict NAT2 phenotypes in Guarani, but not in Africans.

  17. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. A Testosterone-Related Structural Brain Phenotype Predicts Aggressive Behavior From Childhood to Adulthood

    PubMed Central

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

    2015-01-01

    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 to 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

  19. Broader autism phenotype in mothers predicts social responsiveness in young children with autism spectrum disorders.

    PubMed

    Hasegawa, Chiaki; Kikuchi, Mitsuru; Yoshimura, Yuko; Hiraishi, Hirotoshi; Munesue, Toshio; Nakatani, Hideo; Higashida, Haruhiro; Asada, Minoru; Oi, Manabu; Minabe, Yoshio

    2015-03-01

    The aim of this study was to identify phenotypes in mothers and fathers that are specifically associated with disturbances in reciprocal social interactions and communication in their young children with autism spectrum disorder (ASD) in a Japanese sample. Autistic traits in parents were evaluated using the Autism-spectrum Quotient (AQ), the Empathy Quotient (EQ) and the Systemizing Quotient (SQ) in 88 parents (44 mothers and corresponding fathers) of children with ASD and in 60 parents (30 mothers and corresponding fathers) of typically developing (TD) children. For the measurement of autistic traits in children, we employed the Social Responsiveness Scale (SRS). In two of the five AQ subscales (social skills and communication), the parents of ASD children scored significantly higher than did the parents of TD children, regardless of whether the parent was a mother or a father. In addition, in mothers of ASD children, there were significant positive correlations between two of the five AQ subscales (attention-switching and communication) and the SRS T-score in their children. This is the first study to demonstrate that the social skills and communication subscales in the AQ are more sensitive as autism traits in a Japanese sample and to demonstrate that some autistic traits in mothers are specifically associated with disturbances in the social ability of their young children with ASD, as measured by the SRS score. Further study is necessary to determine whether these results were caused by genetic or environmental factors. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.

  20. Omics AnalySIs System for PRecision Oncology (OASISPRO): A Web-based Omics Analysis Tool for Clinical Phenotype Prediction.

    PubMed

    Yu, Kun-Hsing; Fitzpatrick, Michael R; Pappas, Luke; Chan, Warren; Kung, Jessica; Snyder, Michael

    2017-09-12

    Precision oncology is an approach that accounts for individual differences to guide cancer management. Omics signatures have been shown to predict clinical traits for cancer patients. However, the vast amount of omics information poses an informatics challenge in systematically identifying patterns associated with health outcomes, and no general-purpose data-mining tool exists for physicians, medical researchers, and citizen scientists without significant training in programming and bioinformatics. To bridge this gap, we built the Omics AnalySIs System for PRecision Oncology (OASISPRO), a web-based system to mine the quantitative omics information from The Cancer Genome Atlas (TCGA). This system effectively visualizes patients' clinical profiles, executes machine-learning algorithms of choice on the omics data, and evaluates the prediction performance using held-out test sets. With this tool, we successfully identified genes strongly associated with tumor stage, and accurately predicted patients' survival outcomes in many cancer types, including mesothelioma and adrenocortical carcinoma. By identifying the links between omics and clinical phenotypes, this system will facilitate omics studies on precision cancer medicine and contribute to establishing personalized cancer treatment plans. This web-based tool is available at http://tinyurl.com/oasispro ;source codes are available at http://tinyurl.com/oasisproSourceCode .

  1. Severity of phenotype in cystinosis varies with mutations in the CTNS gene: predicted effect on the model of cystinosin.

    PubMed

    Attard, M; Jean, G; Forestier, L; Cherqui, S; van't Hoff, W; Broyer, M; Antignac, C; Town, M

    1999-12-01

    Infantile nephropathic cystinosis is a rare, autosomal recessive disease caused by a defect in the transport of cystine across the lysosomal membrane and characterized by early onset of renal proximal tubular dysfunction. Late-onset cystinosis, a rarer form of the disorder, is characterized by onset of symptoms between 12 and 15 years of age. We previously characterized the cystinosis gene, CTNS, and identified pathogenic mutations in patients with infantile nephropathic cystinosis, including a common, approximately 65 kb deletion which encompasses exons 1-10. Structure predictions suggested that the gene product, cystinosin, is a novel integral lysosomal membrane protein. We now examine the predicted effect of mutations on this model of cystinosin. In this study, we screened patients with infantile nephropathic cystinosis, those with late-onset cystinosis and patients whose phenotype does not fit the classical definitions. We found 23 different mutations in CTNS; 14 are novel mutations. Out of 25 patients with infantile nephropathic cystinosis, 12 have two severely truncating mutations, which is consistent with a loss of functional protein, and 13 have missense or in-frame deletions, which would result in disruption of transmembrane domains and loss of protein function. Mutations found in two late-onset patients affect functionally unimportant regions of cystinosin, which accounts for their milder phenotype. For three patients, the age of onset of cystinosis was <7 years but the course of the disease was milder than the infantile nephropathic form. This suggests that the missense mutations found in these individuals allow production of functional protein and may also indicate regions of cystinosin which are not functionally important.

  2. Impact of MS genetic loci on familial aggregation, clinical phenotype, and disease prediction

    PubMed Central

    Esposito, Federica; Guaschino, Clara; Sorosina, Melissa; Clarelli, Ferdinando; Ferre', Laura; Mascia, Elisabetta; Santoro, Silvia; Pagnesi, Matteo; Radaelli, Marta; Colombo, Bruno; Moiola, Lucia; Rodegher, Mariaemma; Stupka, Elia; Martinelli, Vittorio; Comi, Giancarlo

    2015-01-01

    Objective: To investigate the role of known multiple sclerosis (MS)-associated genetic variants in MS familial aggregation, clinical expression, and accuracy of disease prediction in sporadic and familial cases. Methods: A total of 1,443 consecutive patients were screened for MS and familial autoimmune history in a hospital-based Italian cohort. Among them, 461 sporadic and 93 familial probands were genotyped for 107 MS-associated polymorphisms. Their effect sizes were combined to calculate the weighted genetic risk score (wGRS). Results: Family history of MS was reported by 17.2% of probands, and 33.8% reported a familial autoimmune disorder, with autoimmune thyroiditis and psoriasis being the most frequent. No difference in wGRS was observed between sporadic and familial MS cases. In contrast, a lower wGRS was observed in probands with greater familial aggregation (>1 first-degree relative or >2 relatives with MS) (p = 0.03). Also, female probands of familial cases with greater familial aggregation had a lower wGRS than sporadic cases (p = 0.0009) and male probands of familial cases (p = 0.04). An inverse correlation between wGRS and age at onset was observed (p = 0.05). The predictive performance of the genetic model including all known MS variants was modest but greater in sporadic vs familial cases (area under the curve = 0.63 and 0.57). Conclusions: Additional variants outside the known MS-associated loci, rare variants, and/or environmental factors may explain disease occurrence within families; in females, hormonal and epigenetic factors probably have a predominant role in explaining familial aggregation. The inclusion of these additional factors in future versions of aggregated genetic measures could improve their predictive ability. PMID:26185776

  3. NY-ESO-1 expression predicts an aggressive phenotype of ovarian cancer.

    PubMed

    Szender, J Brian; Papanicolau-Sengos, Antonios; Eng, Kevin H; Miliotto, Anthony J; Lugade, Amit A; Gnjatic, Sacha; Matsuzaki, Junko; Morrison, Carl D; Odunsi, Kunle

    2017-06-01

    NY-ESO-1 is a cancer testis antigen and a promising target for immunotherapy. The purpose of this study was to determine the expression frequency, immunogenicity, and clinical impact of NY-ESO-1 in ovarian cancer. Immunohistochemistry (IHC), reverse-transcription polymerase chain reaction (RT-PCR), and quantitative-PCR (qRT-PCR) were utilized in an ovarian cancer (including Fallopian tube and primary peritoneal cancers) patient cohort; humoral responses against NY-ESO-1 were determined by ELISA. Clinicopathologic outcomes including progression-free (PFS) and overall (OS) survival were evaluated based on NY-ESO-1 expression. Cohen's kappa (κ) tested agreement between expression tests. NY-ESO-1 expression was detected by any method in 40.7% of 1002 patients' tumors (NY-ESO-1+) and baseline humoral response was identified in 19.0% of 689 tested patients. NY-ESO-1+ patients were older (p<0.001), higher stage (85% stage III/IV vs. 76.4%, p=0.015), less likely to have a complete response to initial therapy (53.9% vs. 68.9%, p=0.002), had more serous histotype (74.5% vs. 66.9%, p=0.011), and had more grade 3 tumors (83.7% vs. 70.8%, p<0.001). There was a trend towards shorter PFS (22.2 vs. 25.0months, p=0.07) and significantly shorter OS (42.9 vs. 50.0months, p=0.003) among NY-ESO-1+ patients. A subset analysis of NY-ESO-1+ patients that received immunotherapy demonstrated improved OS by >2years (52.6 vs. 27.2months, p<0.001). This study is the first demonstration of an association between NY-ESO-1 expression and an aggressive cancer phenotype. The relatively high expression frequency of NY-ESO-1 in ovarian cancer patients coupled with the poor clinical outcomes in NY-ESO-1+ patients reveals an underappreciated need for targeted therapy against this antigen. In support, our study reveals that NY-ESO-1+ patients enrolled on immunotherapy trials targeting the antigen exhibited an improvement in OS. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Prenatal diagnosis of Pierre Robin Sequence: accuracy and ability to predict phenotype and functional severity.

    PubMed

    Lind, Katia; Aubry, Marie-Cécile; Belarbi, Nadia; Chalouhi, Christel; Couly, Gérard; Benachi, Alexandra; Lyonnet, Stanislas; Abadie, Véronique

    2015-09-01

    To assess the outcome of fetuses who had sonographic features suggestive of Pierre Robin Sequence (PRS). All prenatal ultrasounds that mentioned 'posterior cleft palate', or 'micro or retrognathia' or 'PRS' over 13 and 20 years, respectively, at two obstetrical centers were reviewed. Medical records for children with isolated PRS monitored over 20 years at a PRS referral center for prenatal anomalies and the severity of neonatal feeding and respiratory functional disorders were utilized for comparison. From a prenatal ultrasound database of 166 000 cases, 157 had one or more of the sonographic signs suggestive of PRS and had follow-up available. Of them, 33 (21%) had confirmed PRS, 9 (6%) were normal and 115 (73%) had chromosomal aberrations, associated malformations or neurological anomalies. Visualization of a posterior cleft palate in addition to retro-micrognathia had a positive predictive value of 100% for PRS. The distribution of functional severity grades was similar in cases suspected prenatally as in 238 cases of PRS followed in the referral center in Necker Hospital. Only a minority of cases of fetal retrognathia have complete PRS; the majority have other severe conditions. Prenatal prediction of functional severity of isolated PRS is not possible. © 2015 John Wiley & Sons, Ltd.

  5. Qualitative Screening Method for Impact Assessment of Uncertain Building Geometry on Thermal Energy Demand Predictions

    NASA Astrophysics Data System (ADS)

    Wate, P.; Coors, V.; Robinson, D.; Iglesias, M.

    2016-10-01

    Virtual 3D models of cities are now being extensively employed for the estimation of thermal energy demand at varying spatial and temporal scales. Efforts in preparing and management of the datasets required for the simulations have reached an advanced stage. Thus allowing to perform city scale simulations using simplified thermal energy balance models. However, the uncertainty inherent in datasets and the reliability of their data sources are often not given due consideration. Such consideration to the uncertainty problem would need a paradigm shift in simulation practices from a single value assignment to uncertainty characterization followed by assessment of qualitative and quantitative impact on the simulation results. The proposed study establishes a mechanism to handle the uncertainty arising from the building geometry reconstruction process and its possible consequences on the thermal energy demand calculations.

  6. A toy model that predicts the qualitative role of bar bend in a push jerk.

    PubMed

    Santos, Aaron; Meltzer, Norman E

    2009-11-01

    In this work, we describe a simple coarse-grained model of a barbell that can be used to determine the qualitative role of bar bend during a jerk. In simulations of this model, we observed a narrow time window during which the lifter can leverage the elasticity of the bar in order to lift the weight to a maximal height. This time window shifted to later times as the weight was increased. In addition, we found that the optimal time to initiate the drive was strongly correlated with the time at which the bar had reached a maximum upward velocity after recoiling. By isolating the effect of the bar, we obtained a generalized strategy for lifting heavy weight in the jerk.

  7. Natural variation of macrophage activation as disease-relevant phenotype predictive of inflammation and cancer survival.

    PubMed

    Buscher, Konrad; Ehinger, Erik; Gupta, Pritha; Pramod, Akula Bala; Wolf, Dennis; Tweet, George; Pan, Calvin; Mills, Charles D; Lusis, Aldons J; Ley, Klaus

    2017-07-24

    Although mouse models exist for many immune-based diseases, the clinical translation remains challenging. Most basic and translational studies utilize only a single inbred mouse strain. However, basal and diseased immune states in humans show vast inter-individual variability. Here, focusing on macrophage responses to lipopolysaccharide (LPS), we use the hybrid mouse diversity panel (HMDP) of 83 inbred strains as a surrogate for human natural immune variation. Since conventional bioinformatics fail to analyse a population spectrum, we highlight how gene signatures for LPS responsiveness can be derived based on an Interleukin-12β and arginase expression ratio. Compared to published signatures, these gene markers are more robust to identify susceptibility or resilience to several macrophage-related disorders in humans, including survival prediction across many tumours. This study highlights natural activation diversity as a disease-relevant dimension in macrophage biology, and suggests the HMDP as a viable tool to increase translatability of mouse data to clinical settings.

  8. 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

  9. Visceral abdominal fat accumulation predicts the conversion of metabolically healthy obese subjects to an unhealthy phenotype.

    PubMed

    Hwang, Y-C; Hayashi, T; Fujimoto, W Y; Kahn, S E; Leonetti, D L; McNeely, M J; Boyko, E J

    2015-09-01

    A proportion of obese subjects appear metabolically healthy (MHO) but little is known about the natural history of MHO and factors predicting its future conversion to metabolically unhealthy obese (MUO). The aim was to determine prospectively the frequency of conversion of MHO to MUO and the clinical variables that independently predicted this conversion, with a particular focus on the role of body composition. We identified 85 Japanese Americans with MHO (56 men, 29 women), aged 34-73 years (mean age 49.8 years) who were followed at 2.5, 5 and 10 years after enrollment with measurements of metabolic characteristics, lifestyle and abdominal and thigh fat areas measured by computed tomography. Obesity was defined using the Asian body mass index criterion of ⩾25 kg m(-2). Metabolically healthy was defined as the presence of ⩽2 of 5 metabolic syndrome components proposed by the National Cholesterol Education Program Adult Treatment Panel III, while metabolically unhealthy was defined as ⩾3 components. Over 10 years of follow-up, 55 MHO individuals (64.7%) converted to MUO. Statistically significant univariate predictors of conversion included dyslipidemia, greater insulin resistance and greater visceral abdominal (VAT) and subcutaneous abdominal fat area (SAT). In multivariate analysis, VAT (odds ratio per 1-s.d. increment (95% confidence interval) 2.04 (1.11-3.72), P=0.021), high-density lipoprotein (HDL) cholesterol (0.24 (0.11-0.53), P<0.001), fasting plasma insulin (2.45 (1.07-5.62), P=0.034) and female sex (5.37 (1.14-25.27), P=0.033) were significantly associated with future conversion to MUO. However, SAT was not an independent predictor for future conversion to MUO. In this population, MHO was a transient state, with nearly two-thirds developing MUO over 10 years, with higher conversion to MUO independently associated with VAT, female sex, higher fasting insulin level and lower baseline HDL cholesterol level.

  10. A survey of French general practitioners and a qualitative study on their use and assessment of predictive clinical scores

    PubMed Central

    Sarazin, Marianne; Chiappe, Solange Gonzalez; Kasprzyk, Marie; Mismetti, Patrick; Lasserre, Andréa

    2013-01-01

    Background Predictive clinical scores, diagnostic as well as prognostic, are considered to be useful tools for making decisions under conditions of uncertainty. They are not intended to replace clinical judgment or medical experience, but to help physicians in the interpretation of clinical information. The general practitioner (GP), the gateway to care in the French health system, should be the main beneficiary of their utilization. However, there is no information on the prevalence of their use in general practice in France. Methods A national, transversal epidemiological survey was conducted by electronic mail among GPs belonging to the French Sentinelles network. GPs were asked about their use of scores, the context of their utilization and the expected benefit. A qualitative study (focus groups) was also carried out with three groups of GPs within the context of continuous medical education. Results The study consisted of 358 GPs. They were questioned on their use of seven predictive clinical scores (six diagnostic and one prognostic). Clinical scores were used by 75% of GPs, with no statistical difference with regard to their age or sex. The most often used were: the Mini Mental Status Examination (MMSE) (95%), Fagerström test (90%), Hamilton scale (65%), McIsaac scores (61%), DETA/CAGE (45%), Simple Calculated Osteoporosis Risk Estimation (SCORE) for osteoporosis (33%), and the only prognostic score CHADS2 (28%). Clinical scores were especially used when elderly people were involved (77%) and when the diagnosis was uncertain (63%). The qualitative study gave additional information on the barriers and obstacles to the use of predictive clinical scores. Conclusion This study, the first one in France, gives information on the perception of clinical scores and on the rationale for their use by GPs. Suggestions to improve the situation (availability and rate of utilization of clinical scores) are provided. PMID:23837004

  11. Stress hormones predict a host superspreader phenotype in the West Nile virus system

    USGS Publications Warehouse

    Gervasi, Stephanie; Burgan, Sarah; Hofmeister, Erik K.; Unnasch, Thomas R.; Martin, Lynn B.

    2017-01-01

    Glucocorticoid stress hormones, such as corticosterone (CORT), have profound effects on the behaviour and physiology of organisms, and thus have the potential to alter host competence and the contributions of individuals to population- and community-level pathogen dynamics. For example, CORT could alter the rate of contacts among hosts, pathogens and vectors through its widespread effects on host metabolism and activity levels. CORT could also affect the intensity and duration of pathogen shedding and risk of host mortality during infection. We experimentally manipulated songbird CORT, asking how CORT affected behavioural and physiological responses to a standardized West Nile virus (WNV) challenge. Although all birds became infected after exposure to the virus, only birds with elevated CORT had viral loads at or above the infectious threshold. Moreover, though the rate of mortality was faster in birds with elevated CORT compared with controls, most hosts with elevated CORT survived past the day of peak infectiousness. CORT concentrations just prior to inoculation with WNV and anti-inflammatory cytokine concentrations following viral exposure were predictive of individual duration of infectiousness and the ability to maintain physical performance during infection (i.e. tolerance), revealing putative biomarkers of competence. Collectively, our results suggest that glucocorticoid stress hormones could directly and indirectly mediate the spread of pathogens.

  12. Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

    NASA Astrophysics Data System (ADS)

    Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

    2017-05-01

    Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

  13. 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

  14. 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.

  15. 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.

  16. Prediction of tacrolimus metabolism and dosage requirements based on CYP3A4 phenotype and CYP3A5*3 genotype in Chinese renal transplant recipients

    PubMed Central

    Luo, Xi; Zhu, Li-jun; Cai, Ning-fang; Zheng, Li-yun; Cheng, Ze-neng

    2016-01-01

    Aim: To examine how the endogenous CYP3A4 phenotype and CYP3A5*3 genotype of Chinese renal transplant recipients influenced the dose-corrected trough concentration (C0/D) and weight-corrected daily dose (D/W) of tacrolimus. Methods: A total of 101 medically stable kidney transplant recipients were enrolled, and their blood and urine samples were gathered. The endogenous CYP3A4 phenotype was assessed by the ratio of 6β-hydroxycortisol and 6β-hydroxycortisone to cortisol and cortisone in urine. CYP3A5*3 genotype was determined using PCR-RELP. Results: In overall renal transplant recipients, a multiple regression analysis including the endogenous CYP3A4 phenotype, CYP3A5*3 genotype and post-operative period accounted for 60.1% of the variability in C0/D ratio; a regression equation consisting of the endogenous CYP3A4 phenotype, post-operative period, body mass index, CYP3A5*3 genotype, gender, total bilirubin and age explained 61.0% of the variability in D/W ratio. In CYP3A5*3/*3 subjects, a combination of the endogenous CYP3A4 phenotype, post-operative period and age was responsible for 65.3% of the variability in C0/D ratio; a predictive equation including the endogenous CYP3A4 phenotype, post-operative period, body mass index, gender and age explained 61.2% of the variability in the D/W ratio. Base on desired target range of tacrolimus trough concentrations, individual daily dosage regimen was calculated, and all the observed daily doses were within the predicted range. Conclusion: This study provides the equations to predict tacrolimus metabolism and dosage requirements based on the endogenous CYP3A4 phenotype, CYP3A5*3 genotype and other non-genetic variables. PMID:26924289

  17. 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.

  18. Stoichiometric Representation of Gene–Protein–Reaction Associations Leverages Constraint-Based Analysis from Reaction to Gene-Level Phenotype Prediction

    PubMed Central

    2016-01-01

    Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models. PMID:27711110

  19. Predicting data saturation in qualitative surveys with mathematical models from ecological research.

    PubMed

    Tran, Viet-Thi; Porcher, Raphael; Tran, Viet-Chi; Ravaud, Philippe

    2017-02-01

    Sample size in surveys with open-ended questions relies on the principle of data saturation. Determining the point of data saturation is complex because researchers have information on only what they have found. The decision to stop data collection is solely dictated by the judgment and experience of researchers. In this article, we present how mathematical modeling may be used to describe and extrapolate the accumulation of themes during a study to help researchers determine the point of data saturation. The model considers a latent distribution of the probability of elicitation of all themes and infers the accumulation of themes as arising from a mixture of zero-truncated binomial distributions. We illustrate how the model could be used with data from a survey with open-ended questions on the burden of treatment involving 1,053 participants from 34 different countries and with various conditions. The performance of the model in predicting the number of themes to be found with the inclusion of new participants was investigated by Monte Carlo simulations. Then, we tested how the slope of the expected theme accumulation curve could be used as a stopping criterion for data collection in surveys with open-ended questions. By doubling the sample size after the inclusion of initial samples of 25 to 200 participants, the model reliably predicted the number of themes to be found. Mean estimation error ranged from 3% to 1% with simulated data and was <2% with data from the study of the burden of treatment. Sequentially calculating the slope of the expected theme accumulation curve for every five new participants included was a feasible approach to balance the benefits of including these new participants in the study. In our simulations, a stopping criterion based on a value of 0.05 for this slope allowed for identifying 97.5% of the themes while limiting the inclusion of participants eliciting nothing new in the study. Mathematical models adapted from ecological research

  20. Phenylalanine hydroxylase deficiency in the Slovak population: genotype-phenotype correlations and genotype-based predictions of BH4-responsiveness.

    PubMed

    Polak, Emil; Ficek, Andrej; Radvanszky, Jan; Soltysova, Andrea; Urge, Otto; Cmelova, Eleonora; Kantarska, Dana; Kadasi, Ludevit

    2013-09-10

    We investigated the mutation spectrum of the phenylalanine hydroxylase gene (PAH) in a cohort of patients from 135 Slovak PKU families. Mutational screening of the known coding region, including conventional intron splice sites, was performed using high-resolution melting analysis, with subsequent sequencing analysis of the samples showing deviated melting profiles compared to control samples. The PAH gene was also screened for deletions and duplications using MLPA analysis. Forty-eight different disease causing mutations were identified in our patient group, including 30 missense, 8 splicing, 7 nonsense, 2 large deletions and 1 small deletion with frameshift; giving a detection rate of 97.6%. The most prevalent mutation was the p.R408W, occurring in 47% of all alleles, which concurs with results from neighboring and other Slavic countries. Other frequent mutations were: p.R158Q (5.3%), IVS12+1G>A (5.3%), p.R252W (5.1%), p.R261Q (3.9%) and p.A403V (3.6%). We also identified three novel missense mutations: p.F233I, p.R270I, p.F331S and one novel variant: c.-30A>T in the proximal part of the PAH gene promoter. A spectrum of 84 different genotypes was observed and a genotype based predictions of BH4-responsiveness were assessed. Among all genotypes, 36 were predicted to be BH4-responsive represented by 51 PKU families. In addition, genotype-phenotype correlations were performed.

  1. 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.

  2. Can audiometric results predict qualitative hearing improvements in bone-anchored hearing aid recipients?

    PubMed

    McNeil, M L; Gulliver, M; Morris, D P; Makki, F M; Bance, M

    2014-01-01

    Patients receiving a bone-anchored hearing aid have well-documented improvements in their quality of life and audiometric performance. However, the relationship between audiometric measurements and subjective improvement is not well understood. Adult patients enrolled in the Nova Scotia bone-anchored hearing aid programme were identified. The pure tone average for fitting the sound-field threshold, as well as the better and worse hearing ear bone conduction and air conduction levels, were collected pre-operatively. Recipients were asked to complete the Speech, Spatial and Qualities of Hearing questionnaire; their partners were asked to complete a pre- and post-bone anchored hearing aid fitting Hearing Handicap Inventory for Adults questionnaire. Forty-eight patients who completed and returned the Speech, Spatial and Qualities of Hearing questionnaire had partners who completed the Hearing Handicap Inventory for Adults questionnaire. The results from the Speech, Spatial and Qualities of Hearing questionnaire correlated with the sound-field hearing threshold post-bone-anchored hearing aid fitting and the pure tone average of the better hearing ear bone conduction (total Speech, Spatial and Qualities of Hearing Scale to the pre-operative better hearing ear air curve (r = 0.3); worse hearing ear air curve (r = 0.27); post-operative, bone-anchored hearing aid-aided sound-field thresholds (r = 0.35)). An improvement in sound-field threshold correlated only with spatial abilities. In the Hearing Handicap Inventory for Adults questionnaire, there was no correlation between the subjective evaluation of each patient and their partner. The subjective impressions of hearing aid recipients with regards to speech reception and the spatial qualities of hearing correlate well with pre-operative audiometric results. However, the overall magnitude of sound-field improvement predicts an improvement of spatial perception, but not other aspects of hearing, resulting in hearing aid

  3. Qualitative and Quantitative analysis of 3D predicted arachidonate 15-lipoxygenase-B (15-LOX-2) from Homo sapiens.

    PubMed

    Arora, Neha; Singh, Vinay Kumar; Shah, Kavita; Pandey-Rai, Shashi

    2012-01-01

    15-Lipoxygenase-2 protein has been reported to play an important role in normal development of prostate, lung, skin, and cornea tissues. It behaves as a suppressor of prostate cancer development by restricting cell cycle progression and implicating a possible protective role against tumor formation. On the basis of the above report, we selected 15-LOX-2 protein to study the structural classification and functional relationship with associated protein network at computational level. Sequence alignment and protein functional study shows that it contains a highly conserved LOX motif. PLAT domain with PF01477 and LH2 domain with PF00305 were successfully observed. Arachidonate 5-lipoxygenase (PDB ID: 3O8Y) was selected as a template with 42% identity. 3D structure was successfully predicted and verified. Qualitative analysis suggests that the predicted model was reliable and stable with best quality. Quantitative study shows that the model contained expected volume and area with best resolution. Predicted and best evaluated model has been successfully deposited to PMDB database with PMDB ID PM0078035. Active site identification revealed GLU(369), ALA(370), LEU(371), THR(372), HIS(373), LEU(374), HIS(376), SER(377), HIS(378), THR(385), LEU(389), HIS(394), PHE(399), LYS(400), LEU(401), ILE(403) and PRO(404) residues may play a major role during protein-protein, protein-drug and protein-cofactor interactions. STRING database result indicated that IL (4), GPX (2 and 4), PPARG, PTGS (1 and 2), CYP (2J2, 2C8, 4A11 and 2B6), PLA (2G2A, 2G4A, 2G1B and 2G6) and A LOX (5, 15, 12 and 12B) members from their respective gene families have network based functional association with 15-LOX-2.

  4. 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

  5. Familial combined hyperlipidemia and hyperlipoprotein(a) as phenotypic mimics of familial hypercholesterolemia: Frequencies, associations and predictions.

    PubMed

    Ellis, Katrina L; Pang, Jing; Chan, Dick C; Hooper, Amanda J; Bell, Damon A; Burnett, John R; Watts, Gerald F

    A significant proportion of index cases presenting with phenotypic familial hypercholesterolemia (FH) are not found to have a pathogenic mutation and may have other inherited conditions. Familial combined hyperlipidemia (FCHL) and elevated lipoprotein(a) [Lp(a)] may mimic FH, but the frequency and correlates of these disorders among mutation-negative FH patients have yet to be established. The frequency of FCHL and elevated Lp(a) was investigated in 206 FH mutation-negative index cases attending a specialist lipid clinic. An FCHL diagnostic nomogram was applied to each index case; a positive diagnosis was made in patients with a probability score exceeding 90%. Plasma Lp(a) concentration was measured by immunoassay, with an elevated level defined as ≥0.5 g/L. Clinical characteristics, including coronary artery disease (CAD) events, were compared between those with and without FCHL and hyper-Lp(a). Of mutation-negative FH patients, 51.9% had probable FCHL. These patients were older (P = .002), had a higher BMI (P = .019) and systolic (P = .001) and diastolic blood pressures (P = .001) compared with those without FCHL. Elevated Lp(a) was observed in 44.7% of cases, and there were no significant differences in clinical characteristics with Lp(a) status. The presence of elevated Lp(a) (P = .002), but not FCHL, predicted CAD events. This association was independent of established CAD risk factors (P = .032). FCHL and elevated Lp(a) are common disorders in patients with mutation-negative FH. Among such patients, FCHL co-expresses with components of the metabolic syndrome, and elevated Lp(a) is the major contributor to increased CAD risk. Copyright © 2016 National Lipid Association. Published by Elsevier Inc. All rights reserved.

  6. 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

  7. IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from sequence data using a flexible machine learning platform.

    PubMed

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

    2014-09-01

    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.

  8. Health practitioners’ perceptions of adopting clinical prediction rules in the management of musculoskeletal pain: a qualitative study in Australia

    PubMed Central

    Kelly, Joan; Sterling, Michele; Rebbeck, Trudy; Bandong, Aila Nica; Leaver, Andrew; Mackey, Martin; Ritchie, Carrie

    2017-01-01

    Objectives To investigate health practitioners’ understanding and practice behaviours with regards to clinical prediction rules (CPRs) and explore their perceptions of adopting a new whiplash CPR. Design Qualitative study using six semistructured focus groups. Setting Primary and secondary care in New South Wales and Queensland, Australia. Participants Physiotherapists (n=19), chiropractors (n=6) and osteopaths (n=3) were purposively sampled to include health practitioners who provide routine treatment to people with whiplash-associated disorders. Methods Focus group discussions (n=6) were audio-recorded, transcribed verbatim and analysed using an inductive thematic approach. Results Health practitioners’ understanding and use of CPRs were mixed. Clinicians considered components relating to acceptability (‘whether I agree with it’) and implementation (‘how I'll use it’) when deciding on whether to adopt a new CPR. Acceptability was informed by four themes: knowledge and understanding, CPR type, congruence and weighted value. Consideration of matters that promote implementation occurred once a CPR was deemed to be acceptable. Three themes were identified as potentially enhancing whiplash CPR implementation: the presence of an external driver of adoption, flexibility in how the CPR could be administered and guidance regarding communication of CPR output to patients. Conclusions Education on CPR purpose and fit with practice is needed to enhance the perceived acceptability of CPRs. Strategies that facilitate practitioner motivation, enable administrative flexibility and assist clinicians in communicating the results of the whiplash CPR could promote adoption of the whiplash CPR. PMID:28801412

  9. Emergent functionality of nucleobase radical cations in duplex DNA: prediction of reactivity using qualitative potential energy landscapes.

    PubMed

    Joseph, Joshy; Schuster, Gary B

    2006-05-10

    The one-electron oxidation of a series of DNA oligonucleotides was examined. Each oligomer contains a covalently linked anthraquinone (AQ) group. Irradiation of the AQ group with near-UV light results in a one-electron oxidation of the DNA that generates a radical cation (electron "hole"). The radical cation migrates through the DNA by a hopping mechanism and is trapped by reaction with water or molecular oxygen, which results in chemical reaction at particular nucleobases. This reaction is revealed as strand cleavage when the irradiated oligonucleotide is treated with piperidine. The specific oligomers examined reveal the existence of three categories of nucleobase sequences: charge shuttles, charge traps, and barriers to charge migration. The characterization of a sequence is not independent of the identity of other sequences in the oligonucleotide, and for this reason, the function of a particular sequence emerges from an analysis of the entire structure. Qualitative potential energy landscapes are introduced as a tool to assist in the rationalization and prediction of the reactions of nucleobases in oxidized DNA.

  10. Health practitioners' perceptions of adopting clinical prediction rules in the management of musculoskeletal pain: a qualitative study in Australia.

    PubMed

    Kelly, Joan; Sterling, Michele; Rebbeck, Trudy; Bandong, Aila Nica; Leaver, Andrew; Mackey, Martin; Ritchie, Carrie

    2017-08-11

    To investigate health practitioners' understanding and practice behaviours with regards to clinical prediction rules (CPRs) and explore their perceptions of adopting a new whiplash CPR. Qualitative study using six semistructured focus groups. Primary and secondary care in New South Wales and Queensland, Australia. Physiotherapists (n=19), chiropractors (n=6) and osteopaths (n=3) were purposively sampled to include health practitioners who provide routine treatment to people with whiplash-associated disorders. Focus group discussions (n=6) were audio-recorded, transcribed verbatim and analysed using an inductive thematic approach. Health practitioners' understanding and use of CPRs were mixed. Clinicians considered components relating to acceptability ('whether I agree with it') and implementation ('how I'll use it') when deciding on whether to adopt a new CPR. Acceptability was informed by four themes: knowledge and understanding, CPR type, congruence and weighted value. Consideration of matters that promote implementation occurred once a CPR was deemed to be acceptable. Three themes were identified as potentially enhancing whiplash CPR implementation: the presence of an external driver of adoption, flexibility in how the CPR could be administered and guidance regarding communication of CPR output to patients. Education on CPR purpose and fit with practice is needed to enhance the perceived acceptability of CPRs. Strategies that facilitate practitioner motivation, enable administrative flexibility and assist clinicians in communicating the results of the whiplash CPR could promote adoption of the whiplash CPR. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  11. Using whole genome sequencing to identify resistance determinants and predict antimicrobial resistance phenotypes for year 2015 invasive pneumococcal disease isolates recovered in the United States.

    PubMed

    Metcalf, B J; Chochua, S; Gertz, R E; Li, Z; Walker, H; Tran, T; Hawkins, P A; Glennen, A; Lynfield, R; Li, Y; McGee, L; Beall, B

    2016-12-01

    Our whole genome sequence (WGS) pipeline was assessed for accurate prediction of antimicrobial phenotypes. For 2316 invasive pneumococcal isolates recovered during 2015 we compared WGS pipeline data to broth dilution testing (BDT) for 18 antimicrobials. For 11 antimicrobials categorical discrepancies were assigned when WGS-predicted MICs and BDT MICs predicted different categorizations for susceptibility, intermediate resistance or resistance, ranging from 0.9% (tetracycline) to 2.9% (amoxicillin). For β-lactam antibiotics, the occurrence of at least four-fold differences in MIC ranged from 0.2% (meropenem) to 1.0% (penicillin), although phenotypic retesting resolved 25%-78% of these discrepancies. Non-susceptibility to penicillin, predicted by penicillin-binding protein types, was 2.7% (non-meningitis criteria) and 23.8% (meningitis criteria). Other common resistance determinants included mef (475 isolates), ermB (191 isolates), ermB + mef (48 isolates), tetM (261 isolates) and cat (51 isolates). Additional accessory resistance genes (tetS, tet32, aphA-3, sat4) were rarely detected (one to three isolates). Rare core genome mutations conferring erythromycin-resistance included a two-codon rplD insertion (rplD69-KG-70) and the 23S rRNA A2061G substitution (six isolates). Intermediate cotrimoxazole-resistance was associated with one or two codon insertions within folP (238 isolates) or the folA I100L substitution (38 isolates), whereas full cotrimoxazole-resistance was attributed to alterations in both genes (172 isolates). The two levofloxacin-resistant isolates contained parC and/or gyrA mutations. Of 11 remaining isolates with moderately elevated MICs to both ciprofloxacin and levofloxacin, seven contained parC or gyrA mutations. The two rifampin-resistant isolates contained rpoB mutations. WGS-based antimicrobial phenotype prediction was an informative alternative to BDT for invasive pneumococci.

  12. 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

  13. 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

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

    2015-01-01

    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. 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)]. 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. 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-C and IFLI-CB, should be useful for clinicians

  14. Mapping 136 Pathogenic Mutations into Functional Modules in Human DNA Polymerase γ Establishes Predictive Genotype-phenotype Correlations for the Complete Spectrum of POLG Syndromes

    PubMed Central

    Farnum, Gregory A.; Nurminen, Anssi; Kaguni, Laurie S.

    2014-01-01

    We establish the genotype-phenotype correlations for the complete spectrum of POLG syndromes, by refining our previously described protocol for mapping pathogenic mutations in the human POLG gene to functional clusters in the catalytic core of the mitochondrial replicase, Pol γ (1). We assigned 136 mutations to five clusters and identify segments of primary sequence that can be used to delimit the boundaries of each cluster. We report that compound heterozygotes with two mutations from different clusters manifested more severe, earlier onset POLG syndromes, whereas two mutations from the same cluster are less common and generally are associated with less severe, later onset POLG syndromes. We also show that specific cluster combinations are more severe than others, and have a higher likelihood to manifest at an earlier age. Our clustering method provides a powerful tool to predict the pathogenic potential and predicted disease phenotype of novel variants and mutations in POLG, the most common nuclear gene underlying mitochondrial disorders. We propose that such a prediction tool would be useful for routine diagnostics for mitochondrial disorders. PMID:24508722

  15. Defining 5S rRNA structure space: point mutation data can be used to predict the phenotype of multichange variants.

    PubMed

    Nayar, Madhavi; Fox, George E

    2011-09-01

    A portion of the 5S ribosomal RNA (rRNA) structure space in the vicinity of the Vibrio proteolyticus 5S rRNA sequence is explored in detail with the intention of establishing principles that will allow a priori prediction of which sequences would be valid members of a particular RNA structure space. Four hundred and one sequence variants differing from the V. proteolyticus 5S rRNA wild-type sequence in 1-7 positions were characterized using an in vivo assay system. Most significantly, it was found that in general, the phenotypic effects of single changes were independent of the phenotypic effect of a second change. As a result, it was possible to use the new data in conjunction with results from prior studies of the same RNA to develop "truth tables" to predict which multiple change variants would be functional and which would be nonfunctional. The actual phenotype of 93.8% of the multichange variants studied was consistent with the predictions made using truth tables thereby providing for perhaps the first time an upper limit estimate of how frequent unexpected interactions are. It was also observed that single changes at positions involved in secondary structure were no more likely to be invalid than changes in other regions. In particular, internal changes in long standard stems were in fact almost always tolerated. Changes at positions that were hypervariable in the context of an alignment of related sequences were, as expected, usually found to be valid. However, the potential validity of changes that were idiosyncratic to a single lineage of related sequences when placed in the V. proteolyticus 5S rRNA context was unpredictable.

  16. A network-based approach for predicting key enzymes explaining metabolite abundance alterations in a disease phenotype.

    PubMed

    Pey, Jon; Tobalina, Luis; de Cisneros, Joaquín Prada J; Planes, Francisco J

    2013-07-19

    The study of metabolism has attracted much attention during the last years due to its relevance in various diseases. The advance in metabolomics platforms allows us to detect an increasing number of metabolites in abnormal high/low concentration in a disease phenotype. Finding a mechanistic interpretation for these alterations is important to understand pathophysiological processes, however it is not an easy task. The availability of genome scale metabolic networks and Systems Biology techniques open new avenues to address this question. In this article we present a novel mathematical framework to find enzymes whose malfunction explains the accumulation/depletion of a given metabolite in a disease phenotype. Our approach is based on a recently introduced pathway concept termed Carbon Flux Paths (CFPs), which extends classical topological definition by including network stoichiometry. Using CFPs, we determine the Connectivity Curve of an altered metabolite, which allows us to quantify changes in its pathway structure when a certain enzyme is removed. The influence of enzyme removal is then ranked and used to explain the accumulation/depletion of such metabolite. For illustration, we center our study in the accumulation of two metabolites (L-Cystine and Homocysteine) found in high concentration in the brain of patients with mental disorders. Our results were discussed based on literature and found a good agreement with previously reported mechanisms. In addition, we hypothesize a novel role of several enzymes for the accumulation of these metabolites, which opens new strategies to understand the metabolic processes underlying these diseases. With personalized medicine on the horizon, metabolomic platforms are providing us with a vast amount of experimental data for a number of complex diseases. Our approach provides a novel apparatus to rationally investigate and understand metabolite alterations under disease phenotypes. This work contributes to the development of

  17. A network-based approach for predicting key enzymes explaining metabolite abundance alterations in a disease phenotype

    PubMed Central

    2013-01-01

    Background The study of metabolism has attracted much attention during the last years due to its relevance in various diseases. The advance in metabolomics platforms allows us to detect an increasing number of metabolites in abnormal high/low concentration in a disease phenotype. Finding a mechanistic interpretation for these alterations is important to understand pathophysiological processes, however it is not an easy task. The availability of genome scale metabolic networks and Systems Biology techniques open new avenues to address this question. Results In this article we present a novel mathematical framework to find enzymes whose malfunction explains the accumulation/depletion of a given metabolite in a disease phenotype. Our approach is based on a recently introduced pathway concept termed Carbon Flux Paths (CFPs), which extends classical topological definition by including network stoichiometry. Using CFPs, we determine the Connectivity Curve of an altered metabolite, which allows us to quantify changes in its pathway structure when a certain enzyme is removed. The influence of enzyme removal is then ranked and used to explain the accumulation/depletion of such metabolite. For illustration, we center our study in the accumulation of two metabolites (L-Cystine and Homocysteine) found in high concentration in the brain of patients with mental disorders. Our results were discussed based on literature and found a good agreement with previously reported mechanisms. In addition, we hypothesize a novel role of several enzymes for the accumulation of these metabolites, which opens new strategies to understand the metabolic processes underlying these diseases. Conclusions With personalized medicine on the horizon, metabolomic platforms are providing us with a vast amount of experimental data for a number of complex diseases. Our approach provides a novel apparatus to rationally investigate and understand metabolite alterations under disease phenotypes. This work

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

    PubMed

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

    2015-08-17

    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, N(2)-(β-1-glucosiduronyl)-2-(hydroxyamino)-1-methyl-6-phenylimidazo[4,5-b]pyridine (HON-PhIP-N(2)-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 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 intraindividual 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

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

    PubMed

    Dietz, Julia; Rupp, Daniel; 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.

  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. Longitudinal Use of a Line Probe Assay for Human Immunodeficiency Virus Type 1 Protease Predicts Phenotypic Resistance and Clinical Progression in Patients Failing Highly Active Antiretroviral Therapy

    PubMed Central

    Servais, Jean; Lambert, Christine; Plesséria, Jean-Marc; Fontaine, Elodie; Robert, Isabelle; Arendt, Vic; Staub, Thérèse; Hemmer, Robert; Schneider, François; Schmit, Jean-Claude

    2002-01-01

    An observational study assessed the longitudinal use of a new line probe assay for the detection of protease mutations. Probe assays for detection of reverse transcriptase (Inno-LiPA HIV-1 RT; Innogenetics) and protease (prototype kit Inno-LiPA HIV Protease; Innogenetics) mutations gave results for 177 of 199 sequential samples collected over 2 years from 26 patients failing two nucleoside reverse transcriptase inhibitors and one protease inhibitor (first line: indinavir, n = 6; ritonavir, n = 10; and saquinavir, n = 10). Results were compared to recombinant virus protease inhibitor susceptibility data (n = 87) and to clinical and virological data. Combinations of protease mutations (M46I, G48V, I54V, V82A or -F, I84V, and L90M) predicted phenotypic resistance to the protease inhibitor and to nelfinavir. The sum of protease mutations was associated with virological and clinical outcomes from 6 and 3 months on, respectively. Moreover, a poorer clinical outcome was linked to the sum of reverse transcriptase mutations. In conclusion, despite the limited number of patients studied and the restricted number of codons investigated, probe assay-based genotyping correlates with phenotypic drug resistance and predicts new Centers for Disease Control and Prevention stage B and C clinical events and virological outcome. Line probe assays provide additional prognostic information and should be prospectively investigated for their potential for treatment monitoring. PMID:12019110

  2. 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.

  3. Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping

    PubMed Central

    Durand, Jean-Baptiste; Allard, Alix; Guitton, Baptiste; van de Weg, Eric; Bink, Marco C. A. M.; Costes, Evelyne

    2017-01-01

    Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS) were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI) with an autoregressive coefficient (γg) efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γg and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species. PMID:28638387

  4. A Multiplex Cancer/Testis Antigen-Based Biomarker Panel to Predict Aggressive Phenotype of Prostate Cancer

    DTIC Science & Technology

    2015-10-01

    Antigen retrieval was performed under heat and adequate pH. After that, steps for endogenous peroxide activity and unspecific protein blocking were...predictive value 60.00% 100.00% 91.67% na 57.14% 73.91% 66.67% 53.66% Negative predictive value 53.49% 55.56% 95.83% 53.19% 59.26% 76.00% 76.19% na...obtained by ROC curve analysis and p values from Mann-Whitney non- parametric test. Those CTAs with AUC>0.70 (PAGE4, SPAG4 and SSX2) are those which

  5. The evolution of vertebrate eye size across an environmental gradient: phenotype does not predict genotype in a Trinidadian killifish.

    PubMed

    Beston, Shannon M; Wostl, Elijah; Walsh, Matthew R

    2017-08-01

    Vertebrates exhibit substantial variation in eye size. Eye size correlates positively with visual capacity and behaviors that enhance fitness, such as predator avoidance. This foreshadows a connection between predation and eye size evolution. Yet, the conditions that favor evolutionary shifts in eye size, besides the well-known role for light availability, are unclear. We tested the influence of predation on the evolution of eye size in Trinidadian killifish, Rivulus hartii. Rivulus are located across a series of communities where they coexist with visually oriented piscivores ("high predation" sites), and no predators ("Rivulus-only" sites). Wild-caught Rivulus from high predation sites generally exhibited a smaller relative eye size than communities that lack predators. Yet, such differences were inconsistent across rivers. Second-generation common garden reared fish revealed repeatable decreases in eye size in Rivulus from high predation sites. We performed additional experiments that tested the importance of light and resources on eye size evolution. Sites that differ in light or resource availability did not differ in eye size. Our results argue that differences in predator-induced mortality underlie genetically-based shifts in vertebrate eye size. We discuss the drivers of eye size evolution in light of the nonparallel trends between the phenotypic and common garden results. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

  6. Molecular and Clinical Analyses of Greig Cephalopolysyndactyly and Pallister-Hall Syndromes: Robust Phenotype Prediction from the Type and Position of GLI3 Mutations

    PubMed Central

    Johnston, Jennifer J.; Olivos-Glander, Isabelle; Killoran, Christina; Elson, Emma; Turner, Joyce T.; Peters, Kathryn F.; Abbott, Margaret H.; Aughton, David J.; Aylsworth, Arthur S.; Bamshad, Michael J.; Booth, Carol; Curry, Cynthia J.; David, Albert; Dinulos, Mary Beth; Flannery, David B.; Fox, Michelle A.; Graham, John M.; Grange, Dorothy K.; Guttmacher, Alan E.; Hannibal, Mark C.; Henn, Wolfram; Hennekam, Raoul C. M.; Holmes, Lewis B.; Hoyme, H. Eugene; Leppig, Kathleen A.; Lin, Angela E.; MacLeod, Patrick; Manchester, David K.; Marcelis, Carlo; Mazzanti, Laura; McCann, Emma; McDonald, Marie T.; Mendelsohn, Nancy J.; Moeschler, John B.; Moghaddam, Billur; Neri, Giovanni; Newbury-Ecob, Ruth; Pagon, Roberta A.; Phillips, John A.; Sadler, Laurie S.; Stoler, Joan M.; Tilstra, David; Walsh Vockley, Catherine M.; Zackai, Elaine H.; Zadeh, Touran M.; Brueton, Louise; Black, Graeme Charles M.; Biesecker, Leslie G.

    2005-01-01

    Mutations in the GLI3 zinc-finger transcription factor gene cause Greig cephalopolysyndactyly syndrome (GCPS) and Pallister-Hall syndrome (PHS), which are variable but distinct clinical entities. We hypothesized that GLI3 mutations that predict a truncated functional repressor protein cause PHS and that functional haploinsufficiency of GLI3 causes GCPS. To test these hypotheses, we screened patients with PHS and GCPS for GLI3 mutations. The patient group consisted of 135 individuals: 89 patients with GCPS and 46 patients with PHS. We detected 47 pathological mutations (among 60 probands); when these were combined with previously published mutations, two genotype-phenotype correlations were evident. First, GCPS was caused by many types of alterations, including translocations, large deletions, exonic deletions and duplications, small in-frame deletions, and missense, frameshift/nonsense, and splicing mutations. In contrast, PHS was caused only by frameshift/nonsense and splicing mutations. Second, among the frameshift/nonsense mutations, there was a clear genotype-phenotype correlation. Mutations in the first third of the gene (from open reading frame [ORF] nucleotides [nt] 1–1997) caused GCPS, and mutations in the second third of the gene (from ORF nt 1998–3481) caused primarily PHS. Surprisingly, there were 12 mutations in patients with GCPS in the 3′ third of the gene (after ORF nt 3481), and no patients with PHS had mutations in this region. These results demonstrate a robust correlation of genotype and phenotype for GLI3 mutations and strongly support the hypothesis that these two allelic disorders have distinct modes of pathogenesis. PMID:15739154

  7. Genetically Predicted Body Mass Index and Alzheimer’s Disease Related Phenotypes in Three Large Samples: Mendelian Randomization Analyses

    PubMed Central

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

    2015-01-01

    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 9,613 controls), the Health and Retirement Study (HRS: 8,403 participants with algorithm-predicted dementia status) and published associations from the Genetic and Environmental Risk for AD consortium (GERAD1: 3,177 AD cases and 7,277 controls). No evidence from individual SNPs or polygenic scores indicated BMI increased AD risk. Mendelian Randomization effect estimates per BMI point (95% confidence intervals) were: ADGC 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

  8. 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.

  9. Reliable prediction of complex phenotypes from a modular design in free energy space: an extensive exploration of the lac operon.

    PubMed

    Vilar, Jose M G; Saiz, Leonor

    2013-10-18

    The basic methodology for designing, altering, and constructing biological systems is increasingly relying on well-established engineering principles to move forward from trial and error approaches to reliably predicting the system behavior from the properties of the components and their interactions. The inherent complexity of even the simplest biological systems, however, often precludes achieving such predictive power. A prototypical example is the lac operon, one of the best-characterized genetic systems, which still poses serious challenges for understanding the results of combining its parts into novel setups. The reason is the pervasive complex hierarchy of events involved in gene regulation that extend from specific protein-DNA interactions to the combinatorial assembly of nucleoprotein complexes. Here, we integrate such complexity into a few-parameter model to accurately predict gene expression from a few simple rules to connect the parts. The model accurately reproduces the observed transcriptional activity of the lac operon over a 10,000-fold range for 21 different operator setups, different repressor concentrations, and tetrameric and dimeric forms of the repressor. Incorporation of the calibrated model into more complex scenarios accurately captures the induction curves for key operator configurations and the temporal evolution of the β-galactosidase activity of cell populations.

  10. Residual feed intake of lactating Holstein-Friesian cows predicted from high-density genotypes and phenotyping of growing heifers.

    PubMed

    Davis, S R; Macdonald, K A; Waghorn, G C; Spelman, R J

    2014-03-01

    A genomic prediction for residual feed intake (RFI) developed in growing dairy heifers (RFIgro) was used to predict and test breeding values for RFI in lactating cows (RFIlac) from an independent, industry population. A selection of 3,359 cows, in their third or fourth lactation during the study, of above average genetic merit for milk production, and identified as at least 15/16ths Holstein-Friesian breed, were selected for genotyping from commercial dairy herds. Genotyping was carried out using the bovine SNP50 BeadChip (Illumina Inc., San Diego, CA) on DNA extracted from ear-punch tissue. After quality control criteria were applied, genotypes were imputed to the 624,930 single nucleotide polymorphisms used in the growth study. Using these data, genomically estimated breeding values (GEBV) for RFIgro were calculated in the selected cow population based on a genomic prediction for RFIgro estimated in an independent group of growing heifers. Cows were ranked by GEBV and the top and bottom 310 identified for possible purchase. Purchased cows (n=214) were relocated to research facilities and intake and body weight (BW) measurements were undertaken in 99 "high" and 98 "low" RFIgro animals in 4 consecutive groups [beginning at d 61 ± 1.0 standard error (SE), 91 ± 0.5 SE, 145 ± 1.3 SE, and 191 ± 1.5 SE d in milk, respectively] to measure RFI during lactation (RFIlac). Each group of ~50 cows (~25 high and ~25 low RFIgro) was in a feed intake facility for 35 d, fed pasture-alfalfa cubes ad libitum, milked twice daily, and weighed every 2 to 3 d. Milk composition was determined 3 times weekly. Body weight change and BW at trial mid-point were estimated by regression of pre- and posttrial BW measurements. Residual feed intake in lactating cows was estimated from a linear model including BW, BW change, and milk component yield (as MJ/d); RFIlac differed consistently between the high and low selection classes, with the overall means for RFIlac being +0.32 and -0.31 kg of

  11. Design and validation of a pericentromeric BAC clone set aimed at improving diagnosis and phenotype prediction of supernumerary marker chromosomes

    PubMed Central

    2013-01-01

    lack of information about the covered region in the reference sequence (1/19) or sample insufficiency (6/19). Conclusions Our results demonstrate that this pericentromeric clone set is useful as an alternative tool for sSMC characterization, primarily in cases of very small SMCs that contain either heterochromatin exclusively or a tiny amount of euchromatic sequence, and also in cases of low-level or cryptic mosaicism. The resulting data will foster knowledge of human proximal euchromatic regions involved in chromosomal imbalances, thereby improving genotype–phenotype correlations. PMID:24171812

  12. Efficacy of qualitative response assessment interpretation criteria at 18F-FDG PET-CT for predicting outcome in locally advanced cervical carcinoma treated with chemoradiotherapy.

    PubMed

    Scarsbrook, Andrew; Vaidyanathan, Sriram; Chowdhury, Fahmid; Swift, Sarah; Cooper, Rachel; Patel, Chirag

    2017-04-01

    To evaluate the utility of a standardized qualitative scoring system for treatment response assessment at 18F-FDG PET-CT in patients undergoing chemoradiotherapy for locally advanced cervical carcinoma and correlate this with subsequent patient outcome. Ninety-six consecutive patients with locally advanced cervical carcinoma treated with radical chemoradiotherapy (CRT) in a single centre between 2011 and 2014 underwent 18F-FDG PET-CT approximately 3 months post-treatment. Tumour metabolic response was assessed qualitatively using a 5-point scale ranging from background level activity only through to progressive metabolic disease. Clinical and radiological (MRI pelvis) follow-up was performed in all patients. Progression-free (PFS) and overall survival (OS) was calculated using the Kaplan-Meier method (Mantel-Cox log-rank) and correlated with qualitative score using Chi-squared test. Forty patients (41.7 %) demonstrated complete metabolic response (CMR) on post-treatment PET-CT (Score 1/2) with 38 patients (95.0 %) remaining disease free after a minimum follow-up period of 18 months. Twenty-four patients (25.0 %) had indeterminate residual uptake (ID, Score 3) at primary or nodal sites after treatment, of these eight patients (33.3 %) relapsed on follow-up, including all patients with residual nodal uptake (n = 4Eleven11 of 17 patients (64.7 %) with significant residual uptake (partial metabolic response, PMR, Score 4) subsequently relapsed. In 15 patients (15.6 %) PET-CT demonstrated progressive disease (PD, Score 5) following treatment. Kaplan-Meier analysis showed a highly statistically significant difference in PFS and OS between patients with CMR, indeterminate uptake, PMR and PD (Log-rank, P < 0.0001). Chi-squared test demonstrated a highly statistically significant association between increasing qualitative score and risk of recurrence or death (P < 0.001). Use of a 5-point qualitative scoring system to assess metabolic response to CRT in locally

  13. 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.

  14. A simple and predictive phenotypic High Content Imaging assay for Plasmodium falciparum mature gametocytes to identify malaria transmission blocking compounds

    PubMed Central

    Lucantoni, Leonardo; Silvestrini, Francesco; Signore, Michele; Siciliano, Giulia; Eldering, Maarten; Dechering, Koen J.; Avery, Vicky M.; Alano, Pietro

    2015-01-01

    Plasmodium falciparum gametocytes, specifically the mature stages, are the only malaria parasite stage in humans transmissible to the mosquito vector. Anti-malarial drugs capable of killing these forms are considered essential for the eradication of malaria and tools allowing the screening of large compound libraries with high predictive power are needed to identify new candidates. As gametocytes are not a replicative stage it is difficult to apply the same drug screening methods used for asexual stages. Here we propose an assay, based on high content imaging, combining “classic” gametocyte viability readout based on gametocyte counts with a functional viability readout, based on gametocyte activation and the discrimination of the typical gamete spherical morphology. This simple and rapid assay has been miniaturized to a 384-well format using acridine orange staining of wild type P. falciparum 3D7A sexual forms, and was validated by screening reference antimalarial drugs and the MMV Malaria Box. The assay demonstrated excellent robustness and ability to identify quality hits with high likelihood of confirmation of transmission reducing activity in subsequent mosquito membrane feeding assays. PMID:26553647

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

    SciTech Connect

    Zuniga, 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

    2016-07-02

    The green microalgae 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. Moreover, 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.

  16. 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

  17. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

    PubMed Central

    Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

    2016-01-01

    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

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

    DOE PAGES

    Zuniga, Cristal; Li, Chien -Ting; Huelsman, Tyler; ...

    2016-07-02

    The green microalgae 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 organismmore » 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. Moreover, 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.« less

  19. Brain Lesions among Orally Fed and Gastrostomy-Fed Dysphagic Preterm Infants: Can Routine Qualitative or Volumetric Quantitative Magnetic Resonance Imaging Predict Feeding Outcomes?

    PubMed

    Kashou, Nasser H; Dar, Irfaan A; El-Mahdy, Mohamed A; Pluto, Charles; Smith, Mark; Gulati, Ish K; Lo, Warren; Jadcherla, Sudarshan R

    2017-01-01

    The usefulness of qualitative or quantitative volumetric magnetic resonance imaging (MRI) in early detection of brain structural changes and prediction of adverse outcomes in neonatal illnesses warrants further investigation. Our aim was to correlate certain brain injuries and the brain volume of feeding-related cortical and subcortical regions with feeding method at discharge among preterm dysphagic infants. Using a retrospective observational study design, we examined MRI data among 43 (22 male; born at 31.5 ± 0.8 week gestation) infants who went home on oral feeding or gastrostomy feeding (G-tube). MRI scans were segmented, and volumes of brainstem, cerebellum, cerebrum, basal ganglia, thalamus, and vermis were quantified, and correlations were made with discharge feeding outcomes. Chi-squared tests were used to evaluate MRI findings vs. feeding outcomes. ANCOVA was performed on the regression model to measure the association of maturity and brain volume between groups. Out of 43 infants, 44% were oral-fed and 56% were G-tube fed at hospital discharge (but not at time of the study). There was no relationship between qualitative brain lesions and feeding outcomes. Volumetric analysis revealed that cerebellum was greater (p < 0.05) in G-tube fed infants, whereas cerebrum volume was greater (p < 0.05) in oral-fed infants. Other brain regions did not show volumetric differences between groups. This study concludes that neither qualitative nor quantitative volumetric MRI findings correlate with feeding outcomes. Understanding the complexity of swallowing and feeding difficulties in infants warrants a comprehensive and in-depth functional neurological assessment.

  20. Molecular phenotype predicts sensitivity of squamous cell carcinoma of the head and neck to epidermal growth factor receptor inhibition.

    PubMed

    Young, Natalie R; Liu, Jing; Pierce, Carolyn; Wei, Tai-Fen; Grushko, Tatyana; Olopade, Olufunmilayo I; Liu, Wanqing; Shen, Christine; Seiwert, Tanguy Y; Cohen, Ezra E W

    2013-06-01

    Despite nearly universal expression of the wild-type epidermal growth factor receptor (EGFR) and reproducible activity of EGFR inhibitors in patients with squamous cell carcinoma of the head and neck (SCCHN), the majority of patients will not have objective responses. The mechanisms of this intrinsic resistance are not well established. We hypothesized that sensitivity to EGFR inhibitors can be predicted based on the inhibitors' effects on downstream signaling. Cell viability assays were used to assess sensitivity to the EGFR inhibitor gefitinib (ZD1839) in 8 SCCHN cell lines. Fluorescence in-situ hybridization showed the two most sensitive lines to be highly gene-amplified for EGFR. Western blotting confirmed that phosphoEGFR was inhibited at low concentrations of gefitinib in all lines tested. Phosphorylation of downstream signaling protein AKT was inhibited in sensitive lines while inhibition of phosphoERK displayed no relationship to gefitinib efficacy. Phosphatase and tensin homolog (PTEN) expression was evident in all cell lines. Activating PIK3CA mutations were found in two resistant cell lines where pAKT was not inhibited by gefitinib. In resistant cell lines harboring PIK3CA mutations, a PI3K inhibitor, LY294002, or AKT siRNA reduced cell viability with an additive effect demonstrated in combination with gefitinib. Additionally, LY294002 alone and in combination with gefitinib, was effective at treating PIK3CA mutated tumors xenografted into nude mice. Taken together this suggests that constitutively active AKT is a mechanism of intrinsic gefitinib resistance in SCCHN. This resistance can be overcome through targeting of the PI3K/AKT pathway in combination with EGFR inhibition.

  1. Metabolite Identification, Reaction Phenotyping and Retrospective Drug-Drug Interaction Predictions of 17-deacetylnorgestimate, the Active Component of the Oral Contraceptive Norgestimate.

    PubMed

    Ahire, Deepak; Sinha, Sarmistha; Brock, Barry; Iyer, Ramaswamy; Mandlekar, Sandhya; Subramanian, Murali

    2017-03-10

    Ortho-Tri-Cyclen® (OTC), a two drug cocktail comprising of ethinylestradiol (EE) and norgestimate (13-ethyl-17-acetoxy-18, 19-dinor-17α-pregn-4-en-20yn-3 oxime), is commonly prescribed to avert unwanted pregnancies in women of reproductive age. In vivo, norgestimate undergoes extensive and rapid deacetylation to produce 17-deacetylnorgestimate (NGMN), an active circulating metabolite that likely contributes significantly to norgestimate efficacy. Despite being of primary significance, the metabolism and reaction phenotyping of NGMN have not been previously reported. Hence, detailed biotransformation and reaction phenotyping studies of NGMN with recombinant cytochrome P450s (rCYPs), recombinant uridine 5'-diphospho-glucuronosyltransferases (rUGTs) and human liver microsomes (HLM) in the presence and absence of selective cytochrome P450 (CYP) inhibitors were conducted. It was found that cytochrome P450 3A4 (CYP3A4) plays a key role in NGNM metabolism with a fraction metabolized (fm) of 0.57. CYP2B6 and to an even lesser extent CYP2C9 were also observed to catalyze NGMN metabolism. Using this CYP3A4 fm, the predicted area under the plasma concentration vs. time curve (AUC) change in NGMN using a basic/mechanistic static model was found to be within 1.3-fold of reported NGMN AUC changes for four modulators of CYP3A4. In addition to NGMN, we have also elucidated the biotransformation of norgestrel (NG), a downstream norgestimate and NGMN metabolite, and found that CYP3A4 and UGT1A1 have a major contribution to the elimination of NG with a combined fm of 1. The data presented in this manuscript will lead to a better understanding and management of NGMN based drug-drug interactions (DDIs) when norgestimate is co-administered with CYP3A4 modulators.

  2. Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children's Oncology Group protocol AAML0531.

    PubMed

    Voigt, Andrew P; Eidenschink Brodersen, Lisa; Alonzo, Todd A; Gerbing, Robert B; Menssen, Andrew J; Wilson, Elisabeth R; Kahwash, Samir; Raimondi, Susana C; Hirsch, Betsy A; Gamis, Alan S; Meshinchi, Soheil; Wells, Denise A; Loken, Michael R

    2017-09-07

    Diagnostic biomarkers can be used to determine relapse risk in acute myeloid leukemia, and certain genetic aberrancies have prognostic relevance. A diagnostic immunophenotypic expression profile, which quantifies the amounts of distinct gene products, not just their presence or absence, was established to improve outcome prediction for patients with acute myeloid leukemia. The immunophenotypic expression profile, which defines each patient's leukemia as a location in 15-dimensional space, was generated for 769 patients enrolled in the Children's Oncology Group AAML0531 protocol. Unsupervised hierarchical clustering grouped patients with similar immunophenotypic expression profiles into eleven patient cohorts, demonstrating high associations among phenotype, genotype, morphology, and outcome. Of 95 patients with inv(16), 79% segregated in Cluster A. Of 109 patients with t(8;21), 92% segregated in Clusters A and B. Of 152 patients with 11q23 alterations, 78% segregated in Clusters D, E, F, G, or H. For both inv(16) and 11q23 abnormalities, differential phenotypic expression identified patient groups with different survival characteristics (P<0.05). Clinical outcome analysis revealed that Cluster B (predominantly t(8;21)) was associated with favorable outcome (P<0.001) and Clusters E, G, H, and K were associated with adverse outcomes (P<0.05). Multivariable regression analysis revealed that Clusters E, G, H, and K were independently associated with worse survival (P range <0.001 to 0.008). The Children's Oncology Group AAML0531 trial is registered at www.clinicaltrials.gov as NCT00372593. Copyright © 2017, Ferrata Storti Foundation.

  3. 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.

  4. Can current crop models be used in the phenotyping era for predicting the genetic variability of yield of plants subjected to drought or high temperature?

    PubMed

    Parent, Boris; Tardieu, François

    2014-11-01

    A crop model with genetic inputs can potentially simulate yield for a large range of genotypes, sites, and years, thereby indicating where and when a given combination of alleles confers a positive effect. We discuss to what extent current crop models, developed for predicting the effects of climate or cultivation techniques on a reference genotype, are adequate for ranking yields of a large number of genotypes in climatic scenarios with water deficit or high temperatures. We compare here the algorithms involved in 19 crop models. Marked differences exist in the representation of the combined effects of temperature and water deficit on plant development, and in the coordination of these effects with biomass production. The current literature suggests that these differences have a small impact on the yield prediction of a reference genotype because errors on the effects of different traits compensate each other. We propose that they have a larger impact if the crop model is used in a genetic context, because the model has to account for the genetic variability of studied traits. Models with explicit genetic inputs will be increasingly feasible because model parameters corresponding to each genotype can now be measured in phenotyping platforms for large plant collections. This will in turn allow prediction of parameter values from the allelic composition of genotypes. It is therefore timely to adapt crop models to this new context to simulate the allelic effects in present or future climatic scenarios with water or heat stresses. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  5. Impact of the Triglyceride/High-Density Lipoprotein Cholesterol Ratio and the Hypertriglyceremic-Waist Phenotype to Predict the Metabolic Syndrome and Insulin Resistance.

    PubMed

    von Bibra, Helene; Saha, Sarama; Hapfelmeier, Alexander; Müller, Gabriele; Schwarz, Peter E H

    2017-07-01

    Insulin resistance is the underlying mechanism for the metabolic syndrome and associated dyslipidaemia that theoretically implies a practical tool for identifying individuals at risk for cardiovascular disease and type-2-diabetes. Another screening tool is the hypertriglyceremic-waist phenotype (HTW). There is important impact of the ethnic background but a lack of studied European populations for the association of the triglyceride/high-density lipoprotein cholesterol (HDL-C) ratio and insulin resistance. This observational, retrospective study evaluated lipid ratios and the HTW for predicting the metabolic syndrome/insulin resistance in 1932 non-diabetic individuals from Germany in the fasting state and during a glucose tolerance test. The relations of triglyceride/HDL-C, total-cholesterol/HDL-C, and low-density lipoprotein cholesterol/HDL-C with 5 surrogate estimates of insulin resistance/sensitivity and metabolic syndrome were analysed by linear regression analysis and receiver operating characteristics (ROC) in participants with normal (n=1 333) or impaired fasting glucose (n=599), also for the impact of gender. Within the lipid ratios, triglyceride/HDL-C had the strongest associations with insulin resistance/sensitivity markers. In the prediction of metabolic syndrome, diagnostic accuracy was good for triglyceride/HDL-C (area under the ROC curve 0.817) with optimal cut-off points (in mg/dl units) of 2.8 for men (80% sensitivity, 71% specificity) and 1.9 for women (80% sensitivity, 75% specificity) and fair for HTW and HOMA-IR (area under the curve 0.773 and 0.761). These data suggest the triglyceride/HDL-C ratio as a physiologically relevant and practical index for predicting the concomitant presence of metabolic syndrome, insulin resistance and dyslipidaemia for therapeutic and preventive care in apparently healthy European populations. © Georg Thieme Verlag KG Stuttgart · New York.

  6. Patients' opinions about knowing their risk for depression and what to do about it. The predictD-qualitative study.

    PubMed

    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; Runte-Geidel, Ariadne; 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

    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. 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. 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. 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.

  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. 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

  9. Qualitative research.

    PubMed

    Gelling, Leslie

    2015-03-25

    Qualitative research has an important role in helping nurses and other healthcare professionals understand patient experiences of health and illness. Qualitative researchers have a large number of methodological options and therefore should take care in planning and conducting their research. This article offers a brief overview of some of the key issues qualitative researchers should consider.

  10. PET Imaging-Based Phenotyping as a Predictive Biomarker of Response to Tyrosine Kinase Inhibitor Therapy in Non-small Cell Lung Cancer: Are We There Yet?

    PubMed

    Gerbaudo, Victor H; Kim, Chun K

    2017-03-01

    The increased understanding of the molecular pathology of different malignancies, especially lung cancer, has directed investigational efforts to center on the identification of different molecular targets and on the development of targeted therapies against these targets. A good representative is the epidermal growth factor receptor (EGFR); a major driver of non-small cell lung cancer tumorigenesis. Today, tumor growth inhibition is possible after treating lung tumors expressing somatic mutations of the EGFR gene with tyrosine kinase inhibitors (TKI). This opened the doors to biomarker-directed precision or personalized treatments for lung cancer patients. The success of these targeted anticancer therapies depends in part on being able to identify biomarkers and their patho-molecular make-up in order to select patients that could respond to specific therapeutic agents. While the identification of reliable biomarkers is crucial to predict response to treatment before it begins, it is also essential to be able to monitor treatment early during therapy to avoid the toxicity and morbidity of futile treatment in non-responding patients. In this context, we share our perspective on the role of PET imaging-based phenotyping in the personalized care of lung cancer patients to non-invasively direct and monitor the treatment efficacy of TKIs in clinical practice.

  11. 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.

  12. 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

  13. Qualitative modeling.

    PubMed

    Forbus, Kenneth D

    2011-07-01

    Qualitative modeling concerns the representations and reasoning that people use to understand continuous aspects of the world. Qualitative models formalize everyday notions of causality and provide accounts of how to ground symbolic, relational representations in perceptual processes. This article surveys the basic ideas of qualitative modeling and their applications from a cognitive science perspective. It describes the basic principles of qualitative modeling, and a variety of qualitative representations that have been developed for quantities and for relationships between them, providing a kind of qualitative mathematics. Three ontological frameworks for organizing modeling knowledge (processes, components, and field) are summarized, along with research on automatically assembling models for particular tasks from such knowledge. Qualitative simulation and how it carves up time into meaningful units is discussed. We discuss several accounts of causal reasoning about dynamical systems, based on different choices of qualitative mathematics and ontology. Qualitative spatial reasoning is explored, both in terms of relational systems and visual reasoning. Applications of qualitative models of particular interest to cognitive scientists are described, including how they have been used to capture the expertise of scientists and engineers and how they have been used in education. Open questions and frontiers are also discussed, focusing on relationships between ideas developed in the qualitative modeling community and other areas of cognitive science. WIREs Cogni Sci 2011 2 374-391 DOI: 10.1002/wcs.115 For further resources related to this article, please visit the WIREs website.

  14. Short communication: Use of single nucleotide polymorphism genotypes and health history to predict future phenotypes for milk production, dry matter intake, body weight, and residual feed intake in dairy cattle.

    PubMed

    Yao, C; Armentano, L E; VandeHaar, M J; Weigel, K A

    2015-03-01

    As feed prices have increased, the efficiency of feed utilization in dairy cattle has attracted increasing attention. In this study, we used residual feed intake (RFI) as a measurement of feed efficiency along with its component traits, adjusted milk energy (aMilkE), adjusted dry matter intake (aDMI), and adjusted metabolic body weight (aMBW), where the adjustment was for environmental factors. These traits may also be affected by prior health problems. Therefore, the carryover effects of 3 health traits from the rearing period and 10 health traits from the lactating period (in the same lactation before phenotype measurements) on RFI, aMilkE, aDMI, and aMBW were evaluated. Cows with heavier birth weight and greater body weight at calving of this lactation had significant increases in aMilkE, aDMI, and aMBW. The only trait associated with RFI was the incidence of diarrhea early in the lactation. Mastitis and reproductive problems had negative carryover effects on aMilkE. The aMBW of cows with metabolic disorders early in the lactation was lower than that of unaffected cows. The incidence of respiratory disease during lactating period was associated with greater aMBW and higher aDMI. To examine the contribution of health traits to the accuracy of predicted phenotype, genomic predictions were computed with or without information regarding 13 health trait phenotypes using random forests (RF) and support vector machine algorithms. Adding health trait phenotypes increased prediction accuracies slightly, except for prediction of RFI using RF. In general, the accuracies were greater for support vector machine than RF, especially for RFI. The methods described herein can be used to predict future phenotypes for dairy replacement heifers, thereby facilitating culling decisions that can lead to decreased feed costs during the rearing period. For these decisions, prediction of the animal's own phenotype is of greater importance than prediction of the genetic superiority or

  15. Defining predictive values using three different platelet function tests for CYP2C19 phenotype status on maintenance dual antiplatelet therapy after PCI.

    PubMed

    Zhang, Hong-Zhe; Kim, Moo Hyun; Han, Jin-Yeong; Jeong, Young-Hoon

    2014-01-01

    Published data suggests that the presence of CYP2C19*2 or *3 loss of function (LOF) alleles is indicative of increased platelet aggregation and a higher risk of adverse cardiovascular events after clopidogrel administration. We sought to determine cut-off values using three different assays for prediction of the CYP2C19 phenotype in Korean percutaneous coronary intervention (PCI) patients. We enrolled 244 patients with drug-eluting stent implantation who were receiving clopidogrel and aspirin maintenance therapy for one month or more. Platelet reactivity was assessed with light transmittance aggregometry (LTA), multiple electrode aggregometry (MEA) and the VerifyNow P2Y12 assay (VN). The CYP2C19 genotype was analyzed by polymerase chain reaction (PCR) and snapshot method. The frequency of CYP2C19 LOF allele carriers was 58.6%. The cut-off values from LTA, MEA and VerifyNow for the identification of LOF allele carriers were as follows: 10 µM ADP-induced LTA ≥ 48 %, VN>242 PRU and MEA ≥ 37 U. Between the three tests, correlation was higher between LTA vs. VN assays (r=0.69) and LTA vs. MEA (r=0.56), with moderate agreement (κ=0.46 and κ=0.46), but between VN assay and MEA, both devices using whole blood showed a lower correlation (r=0.42) and agreement (κ=0.3). Our results provide guidance regarding cut-off levels for LTA, VerifyNow and MEA assays to detect the CYP2C19 LOF allele in patients during dual antiplatelet maintenance therapy.

  16. Post-discharge electrocardiogram Holter monitoring in recently hospitalised individuals with chronic atrial fibrillation to enhance therapeutic monitoring and identify potentially predictive phenotypes.

    PubMed

    Ball, Jocasta; Carrington, Melinda J; Thompson, David R; Horowitz, John D; Stewart, Simon

    2015-10-01

    Atrial fibrillation (AF) is the most common cardiac arrhythmia managed in clinical practice. Maintenance of intended rate or rhythm control following hospitalisation is a key therapeutic goal. The purpose of this study was to assess post-discharge maintenance of intended AF control and classify potentially predictive heart rate (HR) phenotypes via electrocardiogram (ECG) Holter monitoring. In a sub-study of a multicentre randomised controlled trial comparing AF-specific management with usual care, 24-hour ECG Holter monitoring was undertaken in 133 patients 7-14 days post-discharge. Intended rate and rhythm control were compared to Holter data. Analysis of the frequency distribution of mean hour-to-hour differences identified those with labile HRs. Mean age was 71 ± 10 years, 67 (50%) were male and mean HR was 72 ± 14 bpm. Most (89%) had persistent AF (median time in AF=39% (IQR 0-100%)). Uncontrolled HR (>90 bpm for >10% of recording) occurred in 35 (26%) patients and 49 (37%) patients did not achieve their intended rate (n=26) or rhythm control (n=23). Patients in the upper quartile of mean hour-to-hour HR variability were identified as persistently labile (n=33). A further group (n=22) with periodically labile HRs was identified. Those with coronary artery disease (OR 0.34; 95% CI 0.13-0.91, p=0.033) or renal disease/dysfunction (OR 0.24; 95% CI 0.06-0.98, p=0.047) were less likely to demonstrate HR stability (n=78). Post-discharge ECG Holter monitoring of AF patients represents a valuable tool to identify deviations in intended rhythm/rate control and adjust therapeutic management accordingly. It may also identify individuals who demonstrate labile HRs. © The European Society of Cardiology 2014.

  17. Prediction of Phenotypic Effects of Variants Observed in LOC_Os04g36720 of FRO1 Gene in Rice (Oryza sativa L.).

    PubMed

    Meena, Rakesh Kumar; Shome, Sayane; Thakur, Sanket

    2016-02-17

    In rice, ferric-chelate reductase-1 (FRO1) (LOC_Os04g36720) gene was present on chromosome number 4 and its beginning and ending coordinates where coding sequence lies are 22182599 and 22186943, respectively. It plays a vital role in metal homeostasis and iron transportation in plants. Based on the alignment results, location of single-nucleotide variants is located in open reading frame and their effects of variants were predicted using SIFT sequence tool. The non-synonymous variants at position 342 and 436 lies in helical and coil parts of the protein, respectively, as predicted by Psi-pred server. PSI-Blast which resulted in significant hits and the most similar protein sequence (Accession ID: NP_001052896) with available sequence features displayed 100 % identity with query cover of 99 %. Results suggest the non-synonymous variant at position 436 (Accession ID: TBGI204002) lies in FAD-binding domain and nsSNV at position 342 (Accession ID: TBGI203998) lies in periphery of NADP. The SNPs were also analyzed for the deleterious effect by PANTHER subPSEC scores and I-mutant score, and it was postulated that SNPs would be hampering on biological as well as molecular function of FRO 1 gene of rice. A cutoff of -3 corresponds to a 50 % probability that a score is deleterious. From this, the probability that a given variant will cause a deleterious effect on protein function is estimated by P deleterious, such that a subPSEC score of -4 corresponds to a P deleterious of 0.79. Hence, to study the phenotypic consequences of variant TBGI204002, we performed comparative molecular docking studies of native modeled protein and protein with induced mutation as receptors and FAD as ligand to be utilized for binding. The docking process was performed by AutoDock 4.2 software with Lamarckian Genetic algorithm as computational algorithm. Results suggest binding energies are higher in case of mutation-induced protein which suggests presence of variant TBGI204002 enhances

  18. Mouse phenotyping.

    PubMed

    Fuchs, Helmut; Gailus-Durner, Valérie; Adler, Thure; Aguilar-Pimentel, Juan Antonio; Becker, Lore; Calzada-Wack, Julia; Da Silva-Buttkus, Patricia; Neff, Frauke; Götz, Alexander; Hans, Wolfgang; Hölter, Sabine M; Horsch, Marion; Kastenmüller, Gabi; Kemter, Elisabeth; Lengger, Christoph; Maier, Holger; Matloka, Mikolaj; Möller, Gabriele; Naton, Beatrix; Prehn, Cornelia; Puk, Oliver; Rácz, Ildikó; Rathkolb, Birgit; Römisch-Margl, Werner; Rozman, Jan; Wang-Sattler, Rui; Schrewe, Anja; Stöger, Claudia; Tost, Monica; Adamski, Jerzy; Aigner, Bernhard; Beckers, Johannes; Behrendt, Heidrun; Busch, Dirk H; Esposito, Irene; Graw, Jochen; Illig, Thomas; Ivandic, Boris; Klingenspor, Martin; Klopstock, Thomas; Kremmer, Elisabeth; Mempel, Martin; Neschen, Susanne; Ollert, Markus; Schulz, Holger; Suhre, Karsten; Wolf, Eckhard; Wurst, Wolfgang; Zimmer, Andreas; Hrabě de Angelis, Martin

    2011-02-01

    Model organisms like the mouse are important tools to learn more about gene function in man. Within the last 20 years many mutant mouse lines have been generated by different methods such as ENU mutagenesis, constitutive and conditional knock-out approaches, knock-down, introduction of human genes, and knock-in techniques, thus creating models which mimic human conditions. Due to pleiotropic effects, one gene may have different functions in different organ systems or time points during development. Therefore mutant mouse lines have to be phenotyped comprehensively in a highly standardized manner to enable the detection of phenotypes which might otherwise remain hidden. The German Mouse Clinic (GMC) has been established at the Helmholtz Zentrum München as a phenotyping platform with open access to the scientific community (www.mousclinic.de; [1]). The GMC is a member of the EUMODIC consortium which created the European standard workflow EMPReSSslim for the systemic phenotyping of mouse models (http://www.eumodic.org/[2]). Copyright © 2010 Elsevier Inc. All rights reserved.

  19. Global phenotypic characterization of bacteria

    PubMed Central

    Bochner, Barry R

    2009-01-01

    The measure of the quality of a systems biology model is how well it can reproduce and predict the behaviors of a biological system such as a microbial cell. In recent years, these models have been built up in layers, and each layer has been growing in sophistication and accuracy in parallel with a global data set to challenge and validate the models in predicting the content or activities of genes (genomics), proteins (proteomics), metabolites (metabolomics), and ultimately cell phenotypes (phenomics). This review focuses on the latter, the phenotypes of microbial cells. The development of Phenotype MicroArrays, which attempt to give a global view of cellular phenotypes, is described. In addition to their use in fleshing out and validating systems biology models, there are many other uses of this global phenotyping technology in basic and applied microbiology research, which are also described. PMID:19054113

  20. An ontology for microbial phenotypes.

    PubMed

    Chibucos, Marcus C; Zweifel, Adrienne E; Herrera, Jonathan C; Meza, William; Eslamfam, Shabnam; Uetz, Peter; Siegele, Deborah A; Hu, James C; Giglio, Michelle G

    2014-11-30

    Phenotypic data are routinely used to elucidate gene function in organisms amenable to genetic manipulation. However, previous to this work, there was no generalizable system in place for the structured storage and retrieval of phenotypic information for bacteria. The Ontology of Microbial Phenotypes (OMP) has been created to standardize the capture of such phenotypic information from microbes. OMP has been built on the foundations of the Basic Formal Ontology and the Phenotype and Trait Ontology. Terms have logical definitions that can facilitate computational searching of phenotypes and their associated genes. OMP can be accessed via a wiki page as well as downloaded from SourceForge. Initial annotations with OMP are being made for Escherichia coli using a wiki-based annotation capture system. New OMP terms are being concurrently developed as annotation proceeds. We anticipate that diverse groups studying microbial genetics and associated phenotypes will employ OMP for standardizing microbial phenotype annotation, much as the Gene Ontology has standardized gene product annotation. The resulting OMP resource and associated annotations will facilitate prediction of phenotypes for unknown genes and result in new experimental characterization of phenotypes and functions.

  1. Loss of Somatostatin Receptor Subtype 2 in Prostate Cancer Is Linked to an Aggressive Cancer Phenotype, High Tumor Cell Proliferation and Predicts Early Metastatic and Biochemical Relapse

    PubMed Central

    Hennigs, Jan K.; Müller, Julia; Adam, Matti; Spin, Joshua M.; Riedel, Emilia; Graefen, Markus; Bokemeyer, Carsten; Sauter, Guido; Huland, Hartwig; Schlomm, Thorsten; Minner, Sarah

    2014-01-01

    Somatostatin receptor subtype 2 (SSTR2) is the most frequently expressed SSTR subtype in normal human tissues. SSTR2 expression is differentially regulated in various tumor types and therapeutic somatostatin analogs binding to SSTR2 are in clinical use. In prostate cancers highly contradictory results in terms of SSTR2 expression and its consequences have been published over the past years. The aim of this study was to clarify prevalence and clinical significance of SSTR2 expression in prostate cancer. Therefore, quantitative immunohistochemistry (IHC) using a tissue microarray containing samples from 3,261 prostate cancer patients with extensive clinical and molecular cancer characteristics and oncological follow-up data was performed. IHC data was compared to publicly available Gene Expression Omnibus datasets of human prostate cancer gene expression arrays. While membranous SSTR2 staining was always seen in normal prostate epithelium, SSTR2 staining was absent in more than half (56.1%) of 2,195 interpretable prostate cancer samples. About 13% of all analyzed prostate cancers showed moderate to strong cytoplasmic and membranous SSTR2 staining. Staining intensities were inversely correlated with high Gleason grade, advanced pT category, high tumor cell proliferation (p<0.0001 each), high pre-operative PSA levels, (p = 0.0011) and positive surgical margins (p = 0.006). In silico analysis confirmed lower SSTR2 gene expression in prostate cancers vs. normal adjacent tissue (p = 0.0424), prostate cancer metastases vs. primary cancers (p = 0.0011) and recurrent vs. non-recurrent prostate cancers (p = 0.0438). PSA-free survival gradually declined with SSTR2 staining intensity (p<0.0001). SSTR2-negative cancers were more likely to develop metastases over time (p<0.05). In conclusion, most prostate cancers are indeed SSTR2-negative and loss of SSTR2 strongly predicts an unfavorable tumor phenotype and poor prognosis. Therefore, SSTR2 expression seems

  2. Family function, Parenting Style and Broader Autism Phenotype as Predicting Factors of Psychological Adjustment in Typically Developing Siblings of Children with Autism Spectrum Disorders.

    PubMed

    Mohammadi, Mohammadreza; Zarafshan, Hadi

    2014-04-01

    Siblings of children with autism are at a greater risk of experiencing behavioral and social problems. Previous researches had focused on environmental variables such as family history of autism spectrum disorders (ASDs), behavior problems in the child with an ASD, parental mental health problems, stressful life events and "broader autism phenotype" (BAP), while variables like parenting style and family function that are shown to influence children's behavioral and psychosocial adjustment are overlooked. The aim of the present study was to reveal how parenting style and family function as well as BAP effect psychological adjustment of siblings of children with autism. The Participants included 65 parents who had one child with an Autism Spectrum Disorder and one typically developing child. Of the children with ASDs, 40 were boys and 25 were girls; and they were diagnosed with ASDs by a psychiatrist based on DSM-IV-TR criteria and Autism Diagnostic Interview-Revised (ADI-R). The Persian versions of the six scales were used to collect data from the families. Pearson's correlation test and regression analysis were used to determine which variables were related to the psychological adjustment of sibling of children with ASDs and which variables predicted it better. Significant relationships were found between Strengths and Difficulties Questionnaire (SDQ) total difficulties, prosocial behaviors and ASDs symptoms severity, parenting styles and some aspects of family function. In addition, siblings who had more BAP characteristics had more behavior problems and less prosocial behavior. Behavioral problems increased and prosocial behavior decreased with permissive parenting style. Besides, both of authoritarian and authoritative parenting styles led to a decrease in behavioral problems and an increase in prosocial behaviors. Our findings revealed that some aspects of family function (affective responsiveness, roles, problem solving and behavior control) were significantly

  3. Phenotypic plasticity and modularity allow for the production of novel mosaic phenotypes in ants.

    PubMed

    Londe, Sylvain; Monnin, Thibaud; Cornette, Raphaël; Debat, Vincent; Fisher, Brian L; Molet, Mathieu

    2015-01-01

    The origin of discrete novelties remains unclear. Some authors suggest that qualitative phenotypic changes may result from the reorganization of preexisting phenotypic traits during development (i.e., developmental recombination) following genetic or environmental changes. Because ants combine high modularity with extreme phenotypic plasticity (queen and worker castes), their diversified castes could have evolved by developmental recombination. We performed a quantitative morphometric study to investigate the developmental origins of novel phenotypes in the ant Mystrium rogeri, which occasionally produces anomalous 'intercastes.' Our analysis compared the variation of six morphological modules with body size using a large sample of intercastes. We confirmed that intercastes are conspicuous mosaics that recombine queen and worker modules. In addition, we found that many other individuals traditionally classified as workers or queens also exhibit some level of mosaicism. The six modules had distinct profiles of variation suggesting that each module responds differentially to factors that control body size and polyphenism. Mosaicism appears to result from each module responding differently yet in an ordered and predictable manner to intermediate levels of inducing factors that control polyphenism. The order of module response determines which mosaic combinations are produced. Because the frequency of mosaics and their canalization around a particular phenotype may evolve by selection on standing genetic variation that affects the plastic response (i.e., genetic accommodation), developmental recombination is likely to play an important role in the evolution of novel castes in ants. Indeed, we found that most mosaics have queen-like head and gaster but a worker-like thorax congruent with the morphology of ergatoid queens and soldiers, respectively. Ergatoid queens of M. oberthueri, a sister species of M. rogeri, could have evolved from intercastes produced ancestrally

  4. The T Allele of a Single-Nucleotide Polymorphism 13.9 kb Upstream of the Lactase Gene (LCT) (C−13.9kbT) Does Not Predict or Cause the Lactase-Persistence Phenotype in Africans

    PubMed Central

    Mulcare, Charlotte A.; Weale, Michael E.; Jones, Abigail L.; Connell, Bruce; Zeitlyn, David; Tarekegn, Ayele; Swallow, Dallas M.; Bradman, Neil; Thomas, Mark G.

    2004-01-01

    The ability to digest the milk sugar lactose as an adult (lactase persistence) is a variable genetic trait in human populations. The lactase-persistence phenotype is found at low frequencies in the majority of populations in sub-Saharan Africa that have been tested, but, in some populations, particularly pastoral groups, it is significantly more frequent. Recently, a CT polymorphism located 13.9 kb upstream of exon 1 of the lactase gene (LCT) was shown in a Finnish population to be closely associated with the lactase-persistence phenotype (Enattah et al. 2002). We typed this polymorphism in 1,671 individuals from 20 distinct cultural groups in seven African countries. It was possible to match seven of the groups tested with groups from the literature for whom phenotypic information is available. In five of these groups, the published frequencies of lactase persistence are ⩾25%. We found the T allele to be so rare that it cannot explain the frequency of the lactase-persistence phenotype throughout Africa. By use of a statistical procedure to take phenotyping and sampling errors into account, the T-allele frequency was shown to be significantly different from that predicted in five of the African groups. Only the Fulbe and Hausa from Cameroon possessed the T allele at a level consistent with phenotypic observations (as well as an Irish sample used for comparison). We conclude that the C−13.9kbT polymorphism is not a predictor of lactase persistence in sub-Saharan Africans. We also present Y-chromosome data that are consistent with previously reported evidence for a back-migration event into Cameroon, and we comment on the implications for the introgression of the −13.9kb*T allele. PMID:15106124

  5. The Immunogenicity of HLA Class II Mismatches: The Predicted Presentation of Nonself Allo-HLA-Derived Peptide by the HLA-DR Phenotype of the Recipient Is Associated with the Formation of DSA

    PubMed Central

    2017-01-01

    The identification of permissible HLA class II mismatches can prevent DSA in mismatched transplantation. The HLA-DR phenotype of recipients contributes to DSA formation by presenting allo-HLA-derived peptides to T-helper cells, which induces the differentiation of B cells into plasma cells. Comparing the binding affinity of self and nonself allo-HLA-derived peptides for recipients' HLA class II antigens may distinguish immunogenic HLA mismatches from nonimmunogenic ones. The binding affinities of allo-HLA-derived peptides to recipients' HLA-DR and HLA-DQ antigens were predicted using the NetMHCIIpan 3.1 server. HLA class II mismatches were classified based on whether they induced DSA and whether self or nonself peptide was predicted to bind with highest affinity to recipients' HLA-DR and HLA-DQ. Other mismatch characteristics (eplet, hydrophobic, electrostatic, and amino acid mismatch scores and PIRCHE-II) were evaluated. A significant association occurred between DSA formation and the predicted HLA-DR presentation of nonself peptides (P = 0.0169; accuracy = 80%; sensitivity = 88%; specificity = 63%). In contrast, mismatch characteristics did not differ significantly between mismatches that induced DSA and the ones that did not, except for PIRCHE-II (P = 0.0094). This methodology predicts DSA formation based on HLA mismatches and recipients' HLA-DR phenotype and may identify permissible HLA mismatches to help optimize HLA matching and guide donor selection. PMID:28331856

  6. Response to CYP2D6 substrate antidepressants is predicted by a CYP2D6 composite phenotype based on genotype and comedications with CYP2D6 inhibitors.

    PubMed

    Gressier, F; Verstuyft, C; Hardy, P; Becquemont, L; Corruble, E

    2015-01-01

    The cytochrome P450 2D6 (CYP2D6) is involved in the metabolism of most antidepressants. Comedication with a potent CYP2D6 inhibitor can convert patients with extensive metabolizer (EM) or ultra-rapid metabolizer (UM) genotypes into poor metabolizer (PM) phenotypes. Since comedication is frequent in depressed patients treated with antidepressants, we investigated the effect of the CYP2D6 composite phenotype on antidepressant efficacy, taking into account both the CYP2D6 genotype and comedication with CYP2D6 inhibitors. 87 Caucasian in patients with a major depressive episode were prospectively treated with flexible doses of antidepressant monotherapy as well as comedications and genotyped for the major CYP2D6 alleles (CYP2D6*3 rs35742686, *4 rs3892097, *5 del, *6 rs5030655, and *2xN). They were classified for CYP2D6 composite phenotype and assessed for antidepressant response after 4 weeks. In terms of genotypes (g), 6 subjects were UMg, 6 PMg, and 75 EMg. Ten patients were coprescribed a CYP2D6 inhibitor, resulting in the following composite phenotypes (cp): 5 UMcp, 16 PMcp, and 66 EMcp. Whereas none of the CYP2D6 genotypes were significantly associated with antidepressant response, UMcp had a lower antidepressant response than PMcp or EMcp (respectively: 39.0 ± 17.9, 50.0 ± 26.0, and 61.6 ± 23.4, p = 0.02). Despite small sample size, this study suggests that a CYP2D6 composite phenotype, taking into account both genotype and comedications with CYP2D6 inhibitors, could predict CYP2D6 substrate antidepressants response. Thus, to optimize antidepressant response, CYP2D6 genotype could be performed and comedications with CYP2D6 inhibitors should be avoided, when prescribing CYP2D6 substrate antidepressants.

  7. Tumour necrosis factor-α plus interleukin-10 low producer phenotype predicts acute kidney injury and death in intensive care unit patients

    PubMed Central

    Dalboni, M A; Quinto, B M R; Grabulosa, C C; Narciso, R; Monte, J C; Durão, M; Rizzo, L; Cendoroglo, M; Santos, O P; Batista, M C

    2013-01-01

    Genetic polymorphism studies of cytokines may provide an insight into the understanding of acute kidney injury (AKI) and death in intensive care unit (ICU) patients. The aim of this study was to investigate whether the genetic polymorphisms of −308 G < A tumour necrosis factor (TNF)-α, −174 G > C interleukin (IL)-6 and −1082 G > A IL-10 may predispose ICU patients to the development of AKI and/or death. In a prospective nested case–control study, 303 ICU patients and 244 healthy individuals were evaluated. The study group included ICU patients who developed AKI (n = 139) and 164 ICU patients without AKI. The GG genotype of TNF-α (low producer phenotype) was significantly lower in the with AKI than without AKI groups and healthy individuals (55 versus 62 versus 73%, respectively; P = 0·01). When genotypes were stratified into four categories of TNF-α/IL-10 combinations, it was observed that low TNF-α plus low IL-10 producer phenotypes were more prevalent in patients with AKI, renal replacement therapy and death (P < 0·05). In logistic regression analysis, low TNF-α producer plus low IL-10 producer phenotypes remained as independent risk factors for AKI and/or death [odds ratio (OR) = 2·37, 95% confidence interval (CI): 1·16–4·84; P = 0·02] and for renal replacement therapy (RRT) and/or death (OR = 3·82, 95% CI: 1·19–12·23; P = 0·02). In this study, the combination of low TNF-α plus low IL-10 producer phenotypes was an independent risk factor to AKI and/or death and RRT and/or death in critically ill patients. Our results should be validated in a larger prospective study with long-term follow-up to emphasize the combination of these genotypes as potential risk factors to AKI in critically ill patients. PMID:23607333

  8. Performance of a population-based HIV-1 tropism phenotypic assay and correlation with V3 genotypic prediction tools in recent HIV-1 seroconverters.

    PubMed

    de Mendoza, Carmen; Van Baelen, Kurt; Poveda, Eva; Rondelez, Evelien; Zahonero, Natalia; Stuyver, Lieven; Garrido, Carolina; Villacian, Jorge; Soriano, Vincent

    2008-07-01

    Pure X4 and X4R5 dual-tropic viruses may be recognized in approximately 15% of drug-naive HIV-1-positive patients. CCR5 antagonists are active against R5 viruses; therefore, HIV tropism should be known before their prescription. A population-based phenotypic assay was performed in 61 recent HIV-1 seroconverters. The results were compared with those obtained using 8 different predictor software programs (C4.5, C4.5 with 8 and 12, PART, SVM, Charge Rule, PSSMsinsi, PSSMx4r5, and geno2pheno), which are freely available at 3 different Web sites and use V3 sequences derived from patient's viruses. Phenotypic testing reported X4R5 dual-tropic viruses in 10 (16.4%) patients. CD4 cell counts and viral loads were significantly lower in X4R5 dual-tropic (450 cells/microL and 3.9 log HIV RNA copies/mL) than in R5 viruses (629 cells/microL, 4.5 log HIV RNA copies/mL) (P<0.05). The overall concordance of genotype and phenotype was relatively good (>80%). Although specificity was >90% using all but 1 genotypic predictor (geno2pheno), however, the sensitivity for the detection of X4 variants was low (<30%), except for SVM and geno2pheno (70%). The prevalence of X4 and X4/R5 dual-tropic viruses in recent HIV seroconverters is 16%. Current genotypic algorithms need to be improved for the estimation of HIV-1 coreceptor use before moving to the clinic. This information is crucial for the selection of candidates to receive CCR5 antagonists in places where phenotypic tropism assays may not be feasible.

  9. 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…

  10. Qualitative Research

    ERIC Educational Resources Information Center

    Roberson, Donald N., Jr.

    2005-01-01

    The purpose of this paper is to describe how a researcher may conduct a basic qualitative research. This paper deals specifically with research of learning, older adults, and in a rural area. This paper became the foundation for the research of my dissertation. I discuss the sample and the criteria for the sample. I also describe the sources of…

  11. Phenotype and function of CXCR5+CD45RA-CD4+ T cells were altered in HBV-related hepatocellular carcinoma and elevated serum CXCL13 predicted better prognosis.

    PubMed

    Duan, Zhaojun; Gao, Jian; Zhang, Ling; Liang, Hua; Huang, Xiangbo; Xu, Qiang; Zhang, Yu; Shen, Tao; Lu, Fengmin

    2015-12-29

    The present study reveals an immunological characterization of circulating and tumor-infiltrating T follicular helper cells (Tfh), namely CXCR5+CD45RA-CD4+ T cells, and their related cytokines in hepatitis B virus-related hepatocellular carcinoma (HCC) patients. In HCC patients, circulating Tfh cells showed a CCR7+ and/or ICOS+ phenotype with increased Th2-like cells and decreased Th1-like and Th17-like subsets. Although the bulk frequency of circulating Tfh cells was not altered in HCC patients, the frequency of infiltrated CXCR5+CD45RA-CD4+ CD3+cells was higher in tumor than in para-tumor tissues, and Th1-like cells were the predominant phenotype. Circulating Tfh cells in HCC patients were defective in the production of IL-21 in vitro, which was in accordance with lower IL-21 levels in tumor tissues than in para-tumor tissues. Serum CXCL13 was increased in HCC patients and associated with recurrence-free survival after hepatectomy. This was confirmed in an additional HCC cohort of 111 patients with up to 5 years follow-up. Immunohistochemical staining indicated that the percentage of CXCR5+ or CXCL13+ cells was higher in poorly differentiated than in well-differentiated tumors. In conclusion, patients with HBV-related HCC showed altered phenotypes and impaired function of Tfh cells or subpopulations. CXCL13 could be a potential biomarker for predicting recurrence in HCC patients after hepatectomy.

  12. Tumour necrosis factor-α plus interleukin-10 low producer phenotype predicts acute kidney injury and death in intensive care unit patients.

    PubMed

    Dalboni, M A; Quinto, B M R; Grabulosa, C C; Narciso, R; Monte, J C; Durão, M; Rizzo, L; Cendoroglo, M; Santos, O P; Batista, M C

    2013-08-01

    Genetic polymorphism studies of cytokines may provide an insight into the understanding of acute kidney injury (AKI) and death in intensive care unit (ICU) patients. The aim of this study was to investigate whether the genetic polymorphisms of -308 G < A tumour necrosis factor (TNF)-α, -174 G > C interleukin (IL)-6 and -1082 G > A IL-10 may predispose ICU patients to the development of AKI and/or death. In a prospective nested case-control study, 303 ICU patients and 244 healthy individuals were evaluated. The study group included ICU patients who developed AKI (n = 139) and 164 ICU patients without AKI. The GG genotype of TNF-α (low producer phenotype) was significantly lower in the with AKI than without AKI groups and healthy individuals (55 versus 62 versus 73%, respectively; P = 0·01). When genotypes were stratified into four categories of TNF-α/IL-10 combinations, it was observed that low TNF-α plus low IL-10 producer phenotypes were more prevalent in patients with AKI, renal replacement therapy and death (P < 0·05). In logistic regression analysis, low TNF-α producer plus low IL-10 producer phenotypes remained as independent risk factors for AKI and/or death [odds ratio (OR) = 2·37, 95% confidence interval (CI): 1·16-4·84; P = 0·02] and for renal replacement therapy (RRT) and/or death (OR = 3·82, 95% CI: 1·19-12·23; P = 0·02). In this study, the combination of low TNF-α plus low IL-10 producer phenotypes was an independent risk factor to AKI and/or death and RRT and/or death in critically ill patients. Our results should be validated in a larger prospective study with long-term follow-up to emphasize the combination of these genotypes as potential risk factors to AKI in critically ill patients. © 2013 British Society for Immunology.

  13. Qualitative research.

    PubMed

    Maher, Lisa; Dertadian, George

    2017-08-07

    This narrative review aims to highlight key insights from qualitative research on drug use and drug users by profiling a selection of classic works. Consensus methods were used to identify and select four papers published in 1938, 1969, 1973 and 1984 considered to be classics. These landmark qualitative studies included the first account of addiction as a social process, demonstrating that people have meaningful responses to drug use that cannot be reduced to their pharmacological effects; the portrayal of inner-city heroin users as exacting, energetic and engaged social agents; identification of the interactive social learning processes involved in becoming a drug user; the application of the 'career' concept to understanding transitions and trajectories of drug use over time; and the articulation of a framework for understanding drug use that incorporates the interaction between pharmacology, psychology and social environments. These classic sociological and anthropological studies deployed qualitative research methods to show how drug use is shaped by complex sets of factors situated within social contexts, viewing drug users as agents engaged actively in social processes and worlds. Their findings have been used to challenge stereotypes about drug use and drug users, develop a deeper understanding of drug use among hidden, hard-to-research and under-studied populations, and provide the foundations for significant developments in scientific knowledge about the nature of drug use. They continue to retain their relevance, providing important correctives to biomedical and behaviourist paradigms, reminding us that drug use is a social process, and demonstrating how the inductive approach of qualitative research can strengthen the way we understand and respond to drug use and related harms. © 2017 Society for the Study of Addiction.

  14. 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

  15. Mapping structural landmarks, ligand binding sites, and missense mutations to the collagen IV heterotrimers predicts major functional domains, novel interactions, and variation in phenotypes in inherited diseases affecting basement membranes.

    PubMed

    Parkin, J Des; San Antonio, James D; Pedchenko, Vadim; Hudson, Billy; Jensen, Shane T; Savige, Judy

    2011-02-01

    Collagen IV is the major protein found in basement membranes. It comprises three heterotrimers (α1α1α2, α3α4α5, and α5α5α6) that form distinct networks, and are responsible for membrane strength and integrity.We constructed linear maps of the collagen IV heterotrimers ("interactomes") that indicated major structural landmarks, known and predicted ligand-binding sites, and missense mutations, in order to identify functional and disease-associated domains, potential interactions between ligands, and genotype–phenotype relationships. The maps documented more than 30 known ligand-binding sites as well as motifs for integrins, heparin, von Willebrand factor (VWF), decorin, and bone morphogenetic protein (BMP). They predicted functional domains for angiogenesis and haemostasis, and disease domains for autoimmunity, tumor growth and inhibition, infection, and glycation. Cooperative ligand interactions were indicated by binding site proximity, for example, between integrins, matrix metalloproteinases, and heparin. The maps indicated that mutations affecting major ligand-binding sites, for example, for Von Hippel Lindau (VHL) protein in the α1 chain or integrins in the α5 chain, resulted in distinctive phenotypes (Hereditary Angiopathy, Nephropathy, Aneurysms, and muscle Cramps [HANAC] syndrome, and early-onset Alport syndrome, respectively). These maps further our understanding of basement membrane biology and disease, and suggest novel membrane interactions, functions, and therapeutic targets.

  16. 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

  17. HCG blood test - qualitative

    MedlinePlus

    ... qualitative; Serum HCG - qualitative; HCG in blood serum - qualitative ... Henry's Clinical Diagnosis and Management by Laboratory Methods. 22nd ed. Philadelphia, PA: Elsevier Saunders; 2011:chap ...

  18. 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

  19. How the cerebral serotonin homeostasis predicts environmental changes: a model to explain seasonal changes of brain 5-HTT as intermediate phenotype of the 5-HTTLPR.

    PubMed

    Kalbitzer, Jan; Kalbitzer, Urs; Knudsen, Gitte Moos; Cumming, Paul; Heinz, Andreas

    2013-12-01

    Molecular imaging studies with positron emission tomography have revealed that the availability of serotonin transporter (5-HTT) in the human brain fluctuates over the course of the year. This effect is most pronounced in carriers of the short allele of the 5-HTT promoter region (5-HTTLPR), which has in several previous studies been linked to an increased risk to develop mood disorders. We argue that long-lasting fluctuations in the cerebral serotonin transmission, which is regulated via the 5-HTT, are responsible for mediating responses to environmental changes based on an assessment of the expected "safety" of the environment; this response is obtained in part through serotonergic modulation of the hypothalamic-pituitary-adrenal (HPA) axis. We posit that the intermediate phenotype of the s-allele may properly be understood as mediating a trade-off, wherein increased responsiveness of cerebral serotonin transmission to seasonal and other forms of environmental change imparts greater behavioral flexibility, at the expense of increased vulnerability to stress. This model may explain the somewhat higher prevalence of the s-allele in some human populations dwelling at geographic latitudes with pronounced seasonal climatic changes, while this hypothesis does not rule out that genetic drift plays an additional or even exclusive role. We argue that s-allele manifests as an intermediate phenotype in terms of an increased responsiveness of the 5-HTT expression to number of daylight hours, which may serve as a stable surrogate marker of other environmental factors, such as availability of food and safety of the environment in populations that live closer to the geographic poles.

  20. A Novel Interaction between Tryptophan Hydroxylase 2 (TPH2) Gene Polymorphism (rs4570625) and BDNF Val66Met Predicts a High-Risk Emotional Phenotype in Healthy Subjects

    PubMed Central

    Latsko, Maeson S.; Gilman, T. Lee; Matt, Lindsey M.; Nylocks, K. Maria; Coifman, Karin G.; Jasnow, Aaron M.

    2016-01-01

    Poor inhibitory processing of negative emotional content is central to many psychiatric disorders, including depression and anxiety. Moreover, increasing evidence suggests that core aspects of emotion-inhibitory processing are largely inherited and as such may represent a key intermediate or risk-related phenotype for common affective diseases (e.g., unipolar depressive, anxiety disorders). The current study employed a candidate-gene approach in order to most effectively examine this complex behavioral phenotype. We examined the novel interaction between BDNF (Val66Met) and TPH2 (rs4570625) polymorphisms and their influence on behavioral inhibition of negative emotion in two independent investigations of healthy adults. BDNF Met carriers consistently report greater symptoms of affective disease and display corresponding behavioral rigidity, while TPH2 T carriers display poor inhibitory processing. These genotypes are traditionally perceived as ‘risk’ genotypes when compared to their respective major Val and G homozygous genotypes, but evidence is mixed. Recent studies in humans and mutant mouse models suggest biological epistasis between BDNF and genes involved in serotonin regulation. Moreover, polymorphisms in the TPH2 gene may have greater influence on serotonergic function than other more commonly studied polymorphisms (e.g., 5-HTTLPR). We observed consistent evidence across two different emotion-inhibition paradigms, one with high internal validity (Study 1, n = 119) and one with high ecological validity (Study 2, n = 115) that the combination of Val/Val and G/G genotypes was clearly associated with impaired inhibition of negative emotional content. This was followed by individuals carrying the BDNF—Met allele (including Met/Val and Met/Met) when combined with the TPH2—T allele (including T/G and T/T combinations). The consistency of these results across tasks and studies suggests that these two groups may be particularly vulnerable to the most common

  1. Integrating Quantitative Knowledge into a Qualitative Gene Regulatory Network

    PubMed Central

    Bourdon, Jérémie; Eveillard, Damien; Siegel, Anne

    2011-01-01

    Despite recent improvements in molecular techniques, biological knowledge remains incomplete. Any theorizing about living systems is therefore necessarily based on the use of heterogeneous and partial information. Much current research has focused successfully on the qualitative behaviors of macromolecular networks. Nonetheless, it is not capable of taking into account available quantitative information such as time-series protein concentration variations. The present work proposes a probabilistic modeling framework that integrates both kinds of information. Average case analysis methods are used in combination with Markov chains to link qualitative information about transcriptional regulations to quantitative information about protein concentrations. The approach is illustrated by modeling the carbon starvation response in Escherichia coli. It accurately predicts the quantitative time-series evolution of several protein concentrations using only knowledge of discrete gene interactions and a small number of quantitative observations on a single protein concentration. From this, the modeling technique also derives a ranking of interactions with respect to their importance during the experiment considered. Such a classification is confirmed by the literature. Therefore, our method is principally novel in that it allows (i) a hybrid model that integrates both qualitative discrete model and quantities to be built, even using a small amount of quantitative information, (ii) new quantitative predictions to be derived, (iii) the robustness and relevance of interactions with respect to phenotypic criteria to be precisely quantified, and (iv) the key features of the model to be extracted that can be used as a guidance to design future experiments. PMID:21935350

  2. 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.

  3. A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions.

    PubMed

    Cheung, C Y Maurice; Williams, Thomas C R; Poolman, Mark G; Fell, David A; Ratcliffe, R George; Sweetlove, Lee J

    2013-09-01

    Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade-off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper-osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper-osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance.

  4. 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.

  5. 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.

  6. 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

  7. Geographic atrophy phenotype identification by cluster analysis.

    PubMed

    Monés, Jordi; Biarnés, Marc

    2017-07-20

    To identify ocular phenotypes in patients with geographic atrophy secondary to age-related macular degeneration (GA) using a data-driven cluster analysis. This was a retrospective analysis of data from a prospective, natural history study of patients with GA who were followed for ≥6 months. Cluster analysis was used to identify subgroups within the population based on the presence of several phenotypic features: soft drusen, reticular pseudodrusen (RPD), primary foveal atrophy, increased fundus autofluorescence (FAF), greyish FAF appearance and subfoveal choroidal thickness (SFCT). A comparison of features between the subgroups was conducted, and a qualitative description of the new phenotypes was proposed. The atrophy growth rate between phenotypes was then compared. Data were analysed from 77 eyes of 77 patients with GA. Cluster analysis identified three groups: phenotype 1 was characterised by high soft drusen load, foveal atrophy and slow growth; phenotype 3 showed high RPD load, extrafoveal and greyish FAF appearance and thin SFCT; the characteristics of phenotype 2 were midway between phenotypes 1 and 3. Phenotypes differed in all measured features (p≤0.013), with decreases in the presence of soft drusen, foveal atrophy and SFCT seen from phenotypes 1 to 3 and corresponding increases in high RPD load, high FAF and greyish FAF appearance. Atrophy growth rate differed between phenotypes 1, 2 and 3 (0.63, 1.91 and 1.73 mm(2)/year, respectively, p=0.0005). Cluster analysis identified three distinct phenotypes in GA. One of them showed a particularly slow growth pattern. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  8. 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

  9. The distinct gene expression profiles of chronic lymphocytic leukemia and multiple myeloma suggest different anti-apoptotic mechanisms but predict only some differences in phenotype.

    PubMed

    Zent, Clive S; Zhan, Fenghuang; Schichman, Steven A; Bumm, Klaus H W; Lin, Pei; Chen, James B; Shaughnessy, John D

    2003-09-01

    We compared gene expression in purified tumor cells from untreated patients with chronic lymphocytic (CLL) (n=24) and newly diagnosed multiple myeloma (MM) (n=29) using the Affymetrix HuGeneFL microarray with probes for approximately 6800 genes. Hierarchical clustering analysis showed that CLL and MM have distinct expression profiles (class prediction). Gene and protein expression (measured by flow cytometry) correlated well for CD19, CD20, CD23, and CD138 in CLL and MM, but not for immunoglobulin light chain, CD38 and CD79b in CLL, or CD45 and CD52 in MM. CLL and MM differentially expressed 18% of 130 apoptosis related genes, suggesting differences in mechanisms of cell survival.

  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. 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.

  12. 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

  13. 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.

  14. 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.

    PubMed

    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(m) and V(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.

  15. Prediction of graft-versus-host disease by phenotypic analysis of early immune reconstitution after CD6-depleted allogeneic bone marrow transplantation.

    PubMed

    Soiffer, R J; Gonin, R; Murray, C; Robertson, M J; Cochran, K; Chartier, S; Cameron, C; Daley, J; Levine, H; Nadler, L M

    1993-10-01

    developed grades 2-4 GVHD. Our findings indicate that CD8+ T cells play an important role in the pathogenesis of GVHD in humans. Analysis of immune reconstitution early after BMT is useful in predicting the onset of GVHD and can help direct the implementation of treatment strategies before the appearance of clinical manifestations. Such interventions may decrease the morbidity and mortality associated with allogeneic BMT and ultimately improve overall survival.

  16. Qualitative genetics - examples from soybean and other crops

    USDA-ARS?s Scientific Manuscript database

    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. 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…

  18. 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…

  19. 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

  20. Viewing Knowledge Bases as Qualitative Models.

    ERIC Educational Resources Information Center

    Clancey, William J.

    The concept of a qualitative model provides a unifying perspective for understanding how expert systems differ from conventional programs. Knowledge bases contain qualitative models of systems in the world, that is, primarily non-numeric descriptions that provide a basis for explaining and predicting behavior and formulating action plans. The…

  1. Qualitative and quantitative analysis of diffusion-weighted imaging of gestational trophoblastic disease: Can it predict progression of molar pregnancy to persistent form of disease?

    PubMed

    Sefidbakht, Sepideh; Hosseini, Fatemeh; Bijan, Bijan; Hamedi, Bahareh; Azizi, Tayyebeh

    2017-03-01

    To describe the diffusion-weighted imaging (DWI) appearance of gestational trophoblastic disease (GTD) and to determine its apparent diffusion coefficient (ADC) values. To evaluate the feasibility of DWI to predict progression of hydatidiform mole (HM) to persistent disease. During a period of 6 months, women with preliminary diagnosis of GTD, based on ultrasound and ßhCG levels, underwent 1.5T MRI (T2 high-resolution and DWI; b values 50, 400, 800; sagittal and perpendicular to the endometrium; and T1, T2 Turbo Spin Echo [TSE] axial images). Patients were followed for 6-12 months to monitor progression to persistent form of the disease. ADC values and image characteristics were compared between HM and persistent neoplasia and between GTD and non-molar pregnancy using Mann-Whitney U and Fisher's exact tests, respectively. Among the 23 studied patients, 19 (83%) were classified as molar and 4 (17%) as non-molar, based on pathology reports. After 6-12 months of follow-up, 5 (26%) cases progressed to persistent disease and 14 (74%) cases were benign HM. There was no significant difference between ADC values for HM (1.93±0.33×10(-3)mm(2)/s) and persistent neoplasia (2.03±0.28×10(-3)mm(2)/s) (P=0.69). The ADC of non-molar pregnancies was (0.96±0.46×10(-3)mm(2)/s), which was significantly different from GTD (1.96 ±0.32×10(-3)mm(2)/s) (P=0.001). Heterogeneous snowstorm appearance, focal intratumoral hemorrhage, myometrial contraction, and prominent myometrial vascularity were more common in GTD compared to non-molar pregnancy (P<0.05). Heterogeneous snowstorm appearance, focal intratumoral hemorrhage, myometrial contraction, and prominent myometrial vascularity are among the imaging characteristics of GTD. We cannot use ADC values to predict progression to persistent disease. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  2. Quantitative and qualitative proteome characteristics extracted from in-depth integrated genomics and proteomics analysis.

    PubMed

    Low, Teck Yew; van Heesch, Sebastiaan; van den Toorn, Henk; Giansanti, Piero; Cristobal, Alba; Toonen, Pim; Schafer, Sebastian; Hübner, Norbert; van Breukelen, Bas; Mohammed, Shabaz; Cuppen, Edwin; Heck, Albert J R; Guryev, Victor

    2013-12-12

    Quantitative and qualitative protein characteristics are regulated at genomic, transcriptomic, and posttranscriptional levels. Here, we integrated in-depth transcriptome and proteome analyses of liver tissues from two rat strains to unravel the interactions within and between these layers. We obtained peptide evidence for 26,463 rat liver proteins. We validated 1,195 gene predictions, 83 splice events, 126 proteins with nonsynonymous variants, and 20 isoforms with nonsynonymous RNA editing. Quantitative RNA sequencing and proteomics data correlate highly between strains but poorly among each other, indicating extensive nongenetic regulation. Our multilevel analysis identified a genomic variant in the promoter of the most differentially expressed gene Cyp17a1, a previously reported top hit in genome-wide association studies for human hypertension, as a potential contributor to the hypertension phenotype in SHR rats. These results demonstrate the power of and need for integrative analysis for understanding genetic control of molecular dynamics and phenotypic diversity in a system-wide manner.

  3. 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

    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.

  4. 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

  5. Quantifying and predicting Drosophila larvae crawling phenotypes

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

    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.

  6. Quantifying and predicting Drosophila larvae crawling phenotypes.

    PubMed

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

    2016-06-21

    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.

  7. 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

  8. 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.

  9. Long-term phenotypic evolution of bacteria.

    PubMed

    Plata, Germán; Henry, Christopher S; Vitkup, Dennis

    2015-01-15

    For many decades comparative analyses of protein sequences and structures have been used to investigate fundamental principles of molecular evolution. In contrast, relatively little is known about the long-term evolution of species' phenotypic and genetic properties. This represents an important gap in our understanding of evolution, as exactly these proprieties play key roles in natural selection and adaptation to diverse environments. Here we perform a comparative analysis of bacterial growth and gene deletion phenotypes using hundreds of genome-scale metabolic models. Overall, bacterial phenotypic evolution can be described by a two-stage process with a rapid initial phenotypic diversification followed by a slow long-term exponential divergence. The observed average divergence trend, with approximately similar fractions of phenotypic properties changing per unit time, continues for billions of years. We experimentally confirm the predicted divergence trend using the phenotypic profiles of 40 diverse bacterial species across more than 60 growth conditions. Our analysis suggests that, at long evolutionary distances, gene essentiality is significantly more conserved than the ability to utilize different nutrients, while synthetic lethality is significantly less conserved. We also find that although a rapid phenotypic evolution is sometimes observed within the same species, a transition from high to low phenotypic similarity occurs primarily at the genus level.

  10. Geno- and phenotypic resistance tests.

    PubMed

    1998-09-01

    There are two types of experimental drug resistance tests, genotypic and phenotypic, that may be able to determine a person's level of resistance to certain HIV drugs. Genotypic resistance testing seeks mutations in the genetic structure of HIV. The analysis is typically conducted from a blood test, and several methods may be used to read the blood sample including a machine that reads gene sequences, a line probe assay, and the GeneChip, which scans blood samples into a computer. Phenotypic resistance testing assesses the quantity of a drug necessary to suppress the virus in a laboratory setting. Both tests require a patient to have a viral load over 1,000 HIV RNA copies, and both are relatively expensive. Neither test can predict which treatments will definitely be successful, as the results are likely to be subjective, depending on the laboratory. Pros and cons for each type of test are listed. Availability, cost, and contact information are provided.

  11. Long interspersed nuclear element-1 hypomethylation is a potential biomarker for the prediction of response to oral fluoropyrimidines in microsatellite stable and CpG island methylator phenotype-negative colorectal cancer.

    PubMed

    Kawakami, Kazuyuki; Matsunoki, Aika; Kaneko, Mami; Saito, Kenichiro; Watanabe, Go; Minamoto, Toshinari

    2011-01-01

    We investigated the clinical value of methylation of long interspersed nuclear element-1 (LINE-1) for the prognosis of colorectal cancer (CRC) and for the survival benefit from adjuvant chemotherapy with oral fluoropyrimidines. LINE-1 methylation in tumor DNA was measured by quantitative methylation-specific PCR in 155 samples of stage II and stage III CRC. The presence of microsatellite instability and CpG island methylator phenotype (CIMP) were assessed and 131 microsatellite stable/CIMP- cases were selected for survival analysis, of which 77 patients had received postoperative adjuvant chemotherapy with oral fluoropyrimidines. The CRC cell lines were used to investigate possible mechanistic links between LINE-1 methylation and effects of 5-fluorouracil (5-FU). High LINE-1 methylation was a marker for better prognosis in patients treated by surgery alone. Patients with low LINE-1 methylation who were treated with adjuvant chemotherapy survived longer than those treated by surgery alone, suggestive of a survival benefit from the use of oral fluoropyrimidines. In contrast, a survival benefit from chemotherapy was not observed for patients with high LINE-1 methylation. The CRC cell lines treated with 5-FU showed increased expression of LINE-1 mRNA. This was associated with upregulation of the phospho-histone H2A.X in cells with low LINE-1 methylation, but not in cells with high LINE-1 methylation. The 5-FU-mediated induction of phospho-histone H2A.X, a marker of DNA damage, was inhibited by knockdown of LINE-1. These results suggest that LINE-1 methylation is a novel predictive marker for survival benefit from adjuvant chemotherapy with oral fluoropyrimidines in CRC patients. This finding could be important for achieving personalized chemotherapy.

  12. Genetic epidemiology, prevalence, and genotype-phenotype correlations in the Swedish population with osteogenesis imperfecta.

    PubMed

    Lindahl, Katarina; Åström, Eva; Rubin, Carl-Johan; Grigelioniene, Giedre; Malmgren, Barbro; Ljunggren, Östen; Kindmark, Andreas

    2015-08-01

    Osteogenesis imperfecta (OI) is a rare hereditary bone fragility disorder, caused by collagen I mutations in 90% of cases. There are no comprehensive genotype-phenotype studies on >100 families outside North America, and no population-based studies determining the genetic epidemiology of OI. Here, detailed clinical phenotypes were recorded, and the COL1A1 and COL1A2 genes were analyzed in 164 Swedish OI families (223 individuals). Averages for bone mineral density (BMD), height and yearly fracture rate were calculated and related to OI and mutation type. N-terminal helical mutations in both the α1- and α2-chains were associated with the absence of dentinogenesis imperfecta (P<0.0001 vs 0.0049), while only those in the α1-chain were associated with blue sclera (P=0.0110). Comparing glycine with serine substitutions, α1-alterations were associated with more severe phenotype (P=0.0031). Individuals with type I OI caused by qualitative vs quantitative mutations were shorter (P<0.0001), but did not differ considering fractures or BMD. The children in this cohort were estimated to represent >95% of the complete Swedish pediatric OI population. The prevalence of OI types I, III, and IV was 5.16, 0.89, and 1.35/100 000, respectively (7.40/100 000 overall), corresponding to what has been estimated but not unequivocally proven in any population. Collagen I mutation analysis was performed in the family of 97% of known cases, with causative mutations found in 87%. Qualitative mutations caused 32% of OI type I. The data reported here may be helpful to predict phenotype, and describes for the first time the genetic epidemiology in >95% of an entire OI population.

  13. Genetic epidemiology, prevalence, and genotype–phenotype correlations in the Swedish population with osteogenesis imperfecta

    PubMed Central

    Lindahl, Katarina; Åström, Eva; Rubin, Carl-Johan; Grigelioniene, Giedre; Malmgren, Barbro; Ljunggren, Östen; Kindmark, Andreas

    2015-01-01

    Osteogenesis imperfecta (OI) is a rare hereditary bone fragility disorder, caused by collagen I mutations in 90% of cases. There are no comprehensive genotype–phenotype studies on >100 families outside North America, and no population-based studies determining the genetic epidemiology of OI. Here, detailed clinical phenotypes were recorded, and the COL1A1 and COL1A2 genes were analyzed in 164 Swedish OI families (223 individuals). Averages for bone mineral density (BMD), height and yearly fracture rate were calculated and related to OI and mutation type. N-terminal helical mutations in both the α1- and α2-chains were associated with the absence of dentinogenesis imperfecta (P<0.0001 vs 0.0049), while only those in the α1-chain were associated with blue sclera (P=0.0110). Comparing glycine with serine substitutions, α1-alterations were associated with more severe phenotype (P=0.0031). Individuals with type I OI caused by qualitative vs quantitative mutations were shorter (P<0.0001), but did not differ considering fractures or BMD. The children in this cohort were estimated to represent >95% of the complete Swedish pediatric OI population. The prevalence of OI types I, III, and IV was 5.16, 0.89, and 1.35/100 000, respectively (7.40/100 000 overall), corresponding to what has been estimated but not unequivocally proven in any population. Collagen I mutation analysis was performed in the family of 97% of known cases, with causative mutations found in 87%. Qualitative mutations caused 32% of OI type I. The data reported here may be helpful to predict phenotype, and describes for the first time the genetic epidemiology in >95% of an entire OI population. PMID:25944380

  14. 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.

  15. Phenotype definition in epilepsy.

    PubMed

    Winawer, Melodie R

    2006-05-01

    Phenotype definition consists of the use of epidemiologic, biological, molecular, or computational methods to systematically select features of a disorder that might result from distinct genetic influences. By carefully defining the target phenotype, or dividing the sample by phenotypic characteristics, we can hope to narrow the range of genes that influence risk for the trait in the study population, thereby increasing the likelihood of finding them. In this article, fundamental issues that arise in phenotyping in epilepsy and other disorders are reviewed, and factors complicating genotype-phenotype correlation are discussed. Methods of data collection, analysis, and interpretation are addressed, focusing on epidemiologic studies. With this foundation in place, the epilepsy subtypes and clinical features that appear to have a genetic basis are described, and the epidemiologic studies that have provided evidence for the heritability of these phenotypic characteristics, supporting their use in future genetic investigations, are reviewed. Finally, several molecular approaches to phenotype definition are discussed, in which the molecular defect, rather than the clinical phenotype, is used as a starting point.

  16. Understanding & Conducting Qualitative Research.

    ERIC Educational Resources Information Center

    Stainback, Susan; Stainback, William

    In this book, which applies the state of the art in qualitative research to special education, qualitative research is used as a generic term for investigative methodologies described variously as ethnographic, naturalistic, anthropological, field research, or participant-observer research. Chapter 1 introduces and defines qualitative research and…

  17. 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…

  18. 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…

  19. The Qualitative Dimension.

    ERIC Educational Resources Information Center

    Lodge-Peters, Dianne S.

    The qualitative dimension of educational research methodology is explored, and the literature of qualitative methodology is reviewed so researchers may (1) understand more fully the qualitative dimension as it, in turn, fits within the parameters of educational research as a whole, and (2) have more informed access to the sometimes daunting array…

  20. 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…

  1. 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…

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

    PubMed

    Yuan, Mengdie; Diao, Guoqing

    2011-11-29

    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.

  3. 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.

  4. Large phenotype jumps in biomolecular evolution

    NASA Astrophysics Data System (ADS)

    Bardou, F.; Jaeger, L.

    2004-03-01

    By defining the phenotype of a biopolymer by its active three-dimensional shape, and its genotype by its primary sequence, we propose a model that predicts and characterizes the statistical distribution of a population of biopolymers with a specific phenotype that originated from a given genotypic sequence by a single mutational event. Depending on the ratio g0 that characterizes the spread of potential energies of the mutated population with respect to temperature, three different statistical regimes have been identified. We suggest that biopolymers found in nature are in a critical regime with g0≃1 6, corresponding to a broad, but not too broad, phenotypic distribution resembling a truncated Lévy flight. Thus the biopolymer phenotype can be considerably modified in just a few mutations. The proposed model is in good agreement with the experimental distribution of activities determined for a population of single mutants of a group-I ribozyme.

  5. Qualitative research in psychiatry.

    PubMed

    Whitley, Rob; Crawford, Mike

    2005-02-01

    This paper is an overview of qualitative research and its application to psychiatry. It is introductory and attempts to describe both the aims of qualitative research and its underlying philosophical basis. We describe the practice and process of qualitative research and follow this with an overview of the 3 main methods of inquiry: interviews, focus groups, and participant observation. Throughout the paper, we offer examples of cases where qualitative research has illuminated, or has the potential to illuminate, important questions in psychiatric research. We describe methods of sampling and follow with an overview of qualitative analysis, appropriate checks on rigour, and the presentation of qualitative results. The paper concludes by arguing that qualitative methods may be an increasingly appropriate methodology to answer some of the demanding research questions being posed in 21st century psychiatry.

  6. The promises of qualitative inquiry.

    PubMed

    Gergen, Kenneth J; Josselson, Ruthellen; Freeman, Mark

    2015-01-01

    We address the significance and implications of the formal entry of qualitative inquiry into the American Psychological Association. In our view, the discipline is enriched in new and important ways. Most prominently, the qualitative movement brings with it a pluralist orientation to knowledge and to practices of inquiry. Adding to the traditional view of knowledge as empirically supported theory are research practices congenial with varying accounts of knowledge, including, for example, knowledge as hermeneutic understanding, social construction, and practice-based experience. Added to the goal of prediction are investments in increasing cultural understanding, challenging cultural conventions, and directly fostering social change. The qualitative movement also enriches the discipline as a whole through the special ways in which it inspires new ranges of theory, fosters minority inclusion, and invites interdisciplinary collaboration. Finally, the movement holds promise in terms of the discipline's contribution to society at large. Here we focus on the advantages of knowing with others in addition to about them, and on ways in which qualitative work enhances communication with the society and the world. Realizing these potentials will depend on developments in responsible research and reporting, academic and journal policies, along with the discipline's capacities for appreciating a more comprehensive orientation to inquiry. PsycINFO Database Record (c) 2015 APA, all rights reserved.

  7. 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.

  8. Buffered Qualitative Stability explains the robustness and evolvability of transcriptional networks.

    PubMed

    Albergante, Luca; Blow, J Julian; Newman, Timothy J

    2014-09-02

    The gene regulatory network (GRN) is the central decision-making module of the cell. We have developed a theory called Buffered Qualitative Stability (BQS) based on the hypothesis that GRNs are organised so that they remain robust in the face of unpredictable environmental and evolutionary changes. BQS makes strong and diverse predictions about the network features that allow stable responses under arbitrary perturbations, including the random addition of new connections. We show that the GRNs of E. coli, M. tuberculosis, P. aeruginosa, yeast, mouse, and human all verify the predictions of BQS. BQS explains many of the small- and large-scale properties of GRNs, provides conditions for evolvable robustness, and highlights general features of transcriptional response. BQS is severely compromised in a human cancer cell line, suggesting that loss of BQS might underlie the phenotypic plasticity of cancer cells, and highlighting a possible sequence of GRN alterations concomitant with cancer initiation.

  9. 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

  10. 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

  11. Effect of phenotypic variation on kin selection

    PubMed Central

    Boyd, Robert; Richerson, Peter J.

    1980-01-01

    An expression for the equilibrium of the mean phenotypic value of a quantitative character is derived for a model in which the fitness of an individual depends on its own phenotype and the mean phenotypic value of a group of related individuals. When selection is weak the equilibrium mean is well predicted by Hamilton's k > 1/r rule (k is the ratio of mean fitness gained by recipient of altruistic behavior to mean fitness lost by donor; r is mean coefficient of relationship between donor and recipient). When selection is strong, however, the equilibrium mean depends on the heritability of the character. Low heritability can lead to substantially more “altruism” than predicted by the k > 1/r rule. PMID:16592940

  12. 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.

  13. Histopathology reveals correlative and unique phenotypes in a high-throughput mouse phenotyping screen.

    PubMed

    Adissu, Hibret A; Estabel, Jeanne; Sunter, David; Tuck, Elizabeth; Hooks, Yvette; Carragher, Damian M; Clarke, Kay; Karp, Natasha A; Newbigging, Susan; Jones, Nora; Morikawa, Lily; White, Jacqueline K; McKerlie, Colin

    2014-05-01

    The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice.

  14. 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

  15. Histopathology reveals correlative and unique phenotypes in a high-throughput mouse phenotyping screen

    PubMed Central

    Adissu, Hibret A.; Estabel, Jeanne; Sunter, David; Tuck, Elizabeth; Hooks, Yvette; Carragher, Damian M.; Clarke, Kay; Karp, Natasha A.; Project, Sanger Mouse Genetics; Newbigging, Susan; Jones, Nora; Morikawa, Lily; White, Jacqueline K.; McKerlie, Colin

    2014-01-01

    The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice. PMID:24652767

  16. Being a qualitative researcher.

    PubMed

    Holloway, Immy; Biley, Francis C

    2011-07-01

    This article, from a keynote address, is the result of some of the things which I learned about qualitative research during my many years of doing and teaching it. The main point I make is that qualitative researchers should present a good story which is based on evidence but focused on meaning rather than measurement. In qualitative inquiry, the researchers' selves are involved, their experiences become a resource. Researchers cannot distance themselves from the other participants, although they cannot fully present their meaning and experience. I also discuss voice, paradigm, and innovation as potentially problematic issues in qualitative research. These are terms often used but not always examined for their meaning in qualitative inquiry. If researchers are aware and sensitive, rather than overemotional or self-absorbed, qualitative research can be enlightening, person-centered, and humanistic.

  17. What Is Qualitative Research?

    PubMed

    Otani, Takashi

    2017-01-01

     The article is an in-depth explanation of qualitative research, an approach increasingly prevalent among today's research communities. After discussing its present spread within the health sciences, the author addresses: 1. Its definition. 2. Its characteristics, as well as its theoretical and procedural background. 3. Its procedures. 4. Differences between qualitative and quantitative approaches. 5. Mixed methods incorporating quantitative research. And in conclusion: 6. The importance of establishing an epistemological perspective in qualitative research.

  18. Qualitative research in dentistry.

    PubMed

    Stewart, K; Gill, P; Chadwick, B; Treasure, E

    2008-03-08

    This paper is the first in a series of four that provides an overview of the key elements of qualitative research. In particular, it discusses issues such as what qualitative research is, when its use is appropriate, what it can offer dentistry and approaches to data collection and analysis. Where appropriate, examples of dental studies that have used qualitative methods are also provided for practical purposes.

  19. Qualitätsmanagementmethoden

    NASA Astrophysics Data System (ADS)

    Arndt, Klaus-Dieter

    Die Qualitätsmanagementmethoden dienen der Überwachung und Verfolgung von Prozessen. Die statistische Prozessregelung SPC (Statistical Process Control) ist in diesem Zusammenhang ein wichtiges Werkzeug.

  20. Critiquing qualitative research.

    PubMed

    Beck, Cheryl Tatano

    2009-10-01

    The ability to critique research is a valuable skill that is fundamental to a perioperative nurse's ability to base his or her clinical practice on evidence derived from research. Criteria differ for critiquing a quantitative versus a qualitative study (ie, statistics are evaluated in a quantitative study, but not in a qualitative study). This article provides on guidelines for assessing qualitative research. Excerpts from a published qualitative research report are summarized and then critiqued. Questions are provided that help evaluate different sections of a research study (eg, sample, data collection methods, data analysis).

  1. Overview of qualitative research.

    PubMed

    Grossoehme, Daniel H

    2014-01-01

    Qualitative research methods are a robust tool for chaplaincy research questions. Similar to much of chaplaincy clinical care, qualitative research generally works with written texts, often transcriptions of individual interviews or focus group conversations and seeks to understand the meaning of experience in a study sample. This article describes three common methodologies: ethnography, grounded theory, and phenomenology. Issues to consider relating to the study sample, design, and analysis are discussed. Enhancing the validity of the data, as well reliability and ethical issues in qualitative research are described. Qualitative research is an accessible way for chaplains to contribute new knowledge about the sacred dimension of people's lived experience.

  2. 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

  3. Phenotypic plasticity with instantaneous but delayed switches.

    PubMed

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

    2014-01-07

    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.

  4. 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…

  5. 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…

  6. 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…

  7. 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…

  8. Part two: Qualitative research.

    PubMed

    Quick, J; Hall, S

    2015-01-01

    This second article in the series Spotlight on Research focuses on qualitative research, its applications, principles and methodologies. It provides an insight into how this approach can be used within the perioperative setting and gives advice for practitioners looking to undertake a qualitative research study.

  9. Biolog phenotype microarrays.

    PubMed

    Shea, April; Wolcott, Mark; Daefler, Simon; Rozak, David A

    2012-01-01

    Phenotype microarrays nicely complement traditional genomic, transcriptomic, and proteomic analysis by offering opportunities for researchers to ground microbial systems analysis and modeling in a broad yet quantitative assessment of the organism's physiological response to different metabolites and environments. Biolog phenotype assays achieve this by coupling tetrazolium dyes with minimally defined nutrients to measure the impact of hundreds of carbon, nitrogen, phosphorous, and sulfur sources on redox reactions that result from compound-induced effects on the electron transport chain. Over the years, we have used Biolog's reproducible and highly sensitive assays to distinguish closely related bacterial isolates, to understand their metabolic differences, and to model their metabolic behavior using flux balance analysis. This chapter describes Biolog phenotype microarray system components, reagents, and methods, particularly as they apply to bacterial identification, characterization, and metabolic analysis.

  10. 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

  11. 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

  12. 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

  13. 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

  14. Inheritance of behavioral and neuroanatomical phenotypical variance: hybrid mice are not always more stable than inbreds.

    PubMed

    Crusio, Wim E

    2006-09-01

    Many investigators have attempted to confirm the prediction that increased levels of heterozygosity entail greater developmental stability, manifesting itself through decreased phenotypical variation. The evidence presented so far is equivocal. The predicted relationship has been found in some morphological studies, but not in others. I propose that the variability of a character should be seen as different from the character itself. For most morphological characters, natural selection promotes strong canalization of development but, to facilitate responses to environmental changes, the organism needs to retain malleability of physiological and behavioral traits. These different types of selection should lead to distinct genetic architectures for these phenotypes. I report on the results of a diallel cross between four inbred mouse strains. Qualitatively different genetic architectures were in fact revealed for variation in behaviors in the open-field. In a second study, variances of inbred and hybrid populations for hippocampal morphometry were studied. Again, hybrids were not always less variable than inbreds and sometimes even more variable. It follows that there exists no one-to-one relation between heterozygosity and developmental stability.

  15. 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…

  16. 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…

  17. High-throughput hyperdimensional vertebrate phenotyping

    PubMed Central

    Pardo-Martin, Carlos; Allalou, Amin; Medina, Jaime; Eimon, Peter M.; Wählby, Carolina; Yanik, Mehmet Fatih

    2013-01-01

    Most gene mutations and biologically active molecules cause complex responses in animals that cannot be predicted by cell culture models. Yet animal studies remain too slow and their analyses are often limited to only a few readouts. Here we demonstrate high-throughput optical projection tomography with micrometer resolution and hyperdimensional screening of entire vertebrates in tens of seconds using a simple fluidic system. Hundreds of independent morphological features and complex phenotypes are automatically captured in three dimensions with unprecedented speed and detail in semi-transparent zebrafish larvae. By clustering quantitative phenotypic signatures, we can detect and classify even subtle alterations in many biological processes simultaneously. We term our approach hyperdimensional in vivo phenotyping (HIP). To illustrate the power of HIP, we have analyzed the effects of several classes of teratogens on cartilage formation using 200 independent morphological measurements and identified similarities and differences that correlate well with their known mechanisms of actions in mammals. PMID:23403568

  18. Qualitative research in thanatology.

    PubMed

    Carverhill, Philip A

    2002-04-01

    A new research paradigm has been emerging which holds significant potential for the field of death studies. The qualitative project is a diverse collection of methodologies that focuses its interests on the words, narratives, and stories of individuals and groups. Part of its appeal may lie in the inherent closeness of fit between qualitative inquiry and applied work with the dying and the bereaved. The author introduces the individual articles in this special issue and outlines the development of the project as well as some current issues in qualitative research in thanatology.

  19. Population divergence in fish elemental phenotypes associated with trophic phenotypes and lake trophic state.

    PubMed

    Tuckett, Quenton M; Kinnison, Michael T; Saros, Jasmine E; Simon, Kevin S

    2016-11-01

    Studies of ecological stoichiometry typically emphasize the role of interspecific variation in body elemental content and the effects of species or family identity. Recent work suggests substantial variation in body stoichiometry can also exist within species. The importance of this variation will depend on insights into its origins and consequences at various ecological scales, including the distribution of elemental phenotypes across landscapes and their role in nutrient recycling. We investigated whether trophic divergence can produce predictable patterns of elemental phenotypes among populations of an invasive fish, the white perch (Morone americana), and whether elemental phenotypes predict nutrient excretion. White perch populations exhibited a gradient of trophic phenotypes associated with landscape-scale variation in lake trophic state. Perch body chemistry varied considerably among lakes (from 0.09 for % C to 0.31-fold for % P) casting doubt on the assumption of homogenous elemental phenotypes. This variation was correlated with divergence in fish body shape and other trophic traits. Elemental phenotypes covaried (r (2) up to 0.84) with lake trophic state. This covariation likely arose in contemporary time since many of these perch populations were introduced in the last century and the trophic state in many of the lakes has changed in the past few decades. Nutrient excretion varied extensively among populations, but was not readily related to fish body chemistry or lake trophic state. This suggests that predictable patterns of fish body composition can arise quickly through trophic specialization to lake conditions, but such elemental phenotypes may not translate to altered nutrient recycling by fish.

  20. Qualitative Reasoning in an Expert System Framework.

    DTIC Science & Technology

    1983-05-01

    the mini-world of the roller coaster and contributed the concept of envisionment . Envision- mont predicts system behavior through qualitative...about specific domain equations. His contribu- tions was a weak form of physical reasoning called envisionment which allowed the computer to predict...Administration. NASA-T-80194. [371 Kulpers. B. (1982). Getting the Envisionment Right. kriofinu gL Ih National Conferencej AtiUfia Zaekte". pp. 209-212. [381

  1. Qualitative Case Study Guidelines

    DTIC Science & Technology

    2013-11-01

    methods in public relations and marketing communications. New York, Routledge 166-185 13. Denzin , N. K. (1978) The Research Act: A Theoretical...Introduction to Sociological Methods. 2nd ed. New York, McGraw-Hill 14. Denzin , N. K. and Lincoln, Y. S. (2011) The SAGE Handbook of Qualitative...The Art of Science. In: Denzin , N. K. and Lincoln, Y. S. (eds.) Handbook of Qualitative Research. Thousand Oaks, Sage 19. GAO (1990) Case Study

  2. Phenotypic plasticity and experimental evolution.

    PubMed

    Garland, Theodore; Kelly, Scott A

    2006-06-01

    Natural or artificial selection that favors higher values of a particular trait within a given population should engender an evolutionary response that increases the mean value of the trait. For this prediction to hold, the phenotypic variance of the trait must be caused in part by additive effects of alleles segregating in the population, and also the trait must not be too strongly genetically correlated with other traits that are under selection. Another prediction, rarely discussed in the literature, is that directional selection should favor alleles that increase phenotypic plasticity in the direction of selection, where phenotypic plasticity is defined as the ability of one genotype to produce more than one phenotype when exposed to different environments. This prediction has received relatively little empirical attention. Nonetheless, many laboratory experiments impose selection regimes that could allow for the evolution of enhanced plasticity (e.g. desiccation trials with Drosophila that last for several hours or days). We review one example that involved culturing of Drosophila on lemon for multiple generations and then tested for enhanced plasticity of detoxifying enzymes. We also review an example with vertebrates that involves selective breeding for high voluntary activity levels in house mice, targeting wheel-running behavior on days 5+6 of a 6-day wheel exposure. This selection regime allows for the possibility of wheel running itself or subordinate traits that support such running to increase in plasticity over days 1-4 of wheel access. Indeed, some traits, such as the concentration of the glucose transporter GLUT4 in gastrocnemius muscle, do show enhanced plasticity in the selected lines over a 5-6 day period. In several experiments we have housed mice from both the Selected (S) and Control (C) lines with or without wheel access for several weeks to test for differences in plasticity (training effects). A variety of patterns were observed, including

  3. Optimization and phenotype allocation.

    PubMed

    Jost, Jürgen; Wang, Ying

    2014-01-01

    We study the phenotype allocation problem for the stochastic evolution of a multitype population in a random environment. Our underlying model is a multitype Galton–Watson branching process in a random environment. In the multitype branching model, different types denote different phenotypes of offspring, and offspring distributions denote the allocation strategies. Two possible optimization targets are considered: the long-term growth rate of the population conditioned on nonextinction, and the extinction probability of the lineage. In a simple and biologically motivated case, we derive an explicit formula for the long-term growth rate using the random Perron–Frobenius theorem, and we give an approximation to the extinction probability by a method similar to that developed by Wilkinson. Then we obtain the optimal strategies that maximize the long-term growth rate or minimize the approximate extinction probability, respectively, in a numerical example. It turns out that different optimality criteria can lead to different strategies.

  4. A Qualitative Simulation Framework in Smalltalk Based on Fuzzy Arithmetic

    Treesearch

    Richard L. Olson; Daniel L. Schmoldt; David L. Peterson

    1996-01-01

    For many systems, it is not practical to collect and correlate empirical data necessary to formulate a mathematical model. However, it is often sufficient to predict qualitative dynamics effects (as opposed to system quantities), especially for research purposes. In this effort, an object-oriented application framework (AF) was developed for the qualitative modeling of...

  5. Single cell dynamic phenotyping

    PubMed Central

    Patsch, Katherin; Chiu, Chi-Li; Engeln, Mark; Agus, David B.; Mallick, Parag; Mumenthaler, Shannon M.; Ruderman, Daniel

    2016-01-01

    Live cell imaging has improved our ability to measure phenotypic heterogeneity. However, bottlenecks in imaging and image processing often make it difficult to differentiate interesting biological behavior from technical artifact. Thus there is a need for new methods that improve data quality without sacrificing throughput. Here we present a 3-step workflow to improve dynamic phenotype measurements of heterogeneous cell populations. We provide guidelines for image acquisition, phenotype tracking, and data filtering to remove erroneous cell tracks using the novel Tracking Aberration Measure (TrAM). Our workflow is broadly applicable across imaging platforms and analysis software. By applying this workflow to cancer cell assays, we reduced aberrant cell track prevalence from 17% to 2%. The cost of this improvement was removing 15% of the well-tracked cells. This enabled detection of significant motility differences between cell lines. Similarly, we avoided detecting a false change in translocation kinetics by eliminating the true cause: varied proportions of unresponsive cells. Finally, by systematically seeking heterogeneous behaviors, we detected subpopulations that otherwise could have been missed, including early apoptotic events and pre-mitotic cells. We provide optimized protocols for specific applications and step-by-step guidelines for adapting them to a variety of biological systems. PMID:27708391

  6. Strategy Revealing Phenotypic Differences among Synthetic Oscillator Designs

    PubMed Central

    2015-01-01

    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

  7. [Phenotype specific therapy of COPD].

    PubMed

    Rothe, Thomas

    2014-12-10

    COPD is not a homogenous disease but consists of at least four different phenotypes: Emphysema, COPD with chronic bronchitis, asthma-COPD overlap syndrome (ACOS), and COPD with recurrent exacerbations. With differentiation, treatment can be designed phenotype-specific. Some modern drugs are not indicated in all phenotypes.

  8. 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.

  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. The landscape of microbial phenotypic traits and associated genes

    PubMed Central

    Brbić, Maria; Piškorec, Matija; Vidulin, Vedrana; Kriško, Anita; Šmuc, Tomislav; Supek, Fran

    2016-01-01

    Bacteria and Archaea display a variety of phenotypic traits and can adapt to diverse ecological niches. However, systematic annotation of prokaryotic phenotypes is lacking. We have therefore developed ProTraits, a resource containing ∼545 000 novel phenotype inferences, spanning 424 traits assigned to 3046 bacterial and archaeal species. These annotations were assigned by a computational pipeline that associates microbes with phenotypes by text-mining the scientific literature and the broader World Wide Web, while also being able to define novel concepts from unstructured text. Moreover, the ProTraits pipeline assigns phenotypes by drawing extensively on comparative genomics, capturing patterns in gene repertoires, codon usage biases, proteome composition and co-occurrence in metagenomes. Notably, we find that gene synteny is highly predictive of many phenotypes, and highlight examples of gene neighborhoods associated with spore-forming ability. A global analysis of trait interrelatedness outlined clusters in the microbial phenotype network, suggesting common genetic underpinnings. Our extended set of phenotype annotations allows detection of 57 088 high confidence gene-trait links, which recover many known associations involving sporulation, flagella, catalase activity, aerobicity, photosynthesis and other traits. Over 99% of the commonly occurring gene families are involved in genetic interactions conditional on at least one phenotype, suggesting that epistasis has a major role in shaping microbial gene content. PMID:27915291

  11. 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…

  12. Qualitative research strategies in rehabilitation.

    PubMed

    McReynolds, Connie J.; Koch, Lynn C.; Rumrill Jr, Phillip D.

    2001-01-01

    This article presents an overview of the qualitative research methods that social scientists use to explore human phenomena. The authors describe the philosophical and historical foundations of qualitative research, coupled with illustrations of specific qualitative designs. Applications of qualitative methods in the contemporary rehabilitation literature are also presented.

  13. 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

  14. 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.

  15. `Weak A' phenotypes

    PubMed Central

    Cartron, J. P.; Gerbal, A.; Hughes-Jones, N. C.; Salmon, C.

    1974-01-01

    Thirty-five weak A samples including fourteen A3, eight Ax, seven Aend, three Am and three Ae1 were studied in order to determine their A antigen site density, using an IgG anti-A labelled with 125I. The values obtained ranged between 30,000 A antigen sites for A3 individuals, and 700 sites for the Ae1 red cells. The hierarchy of values observed made it possible to establish a quantitative relationship between the red cell agglutinability of these phenotypes measured under standard conditions, and their antigen site density. PMID:4435836

  16. The cellular microscopy phenotype ontology.

    PubMed

    Jupp, Simon; Malone, James; Burdett, Tony; Heriche, Jean-Karim; Williams, Eleanor; Ellenberg, Jan; Parkinson, Helen; Rustici, Gabriella

    2016-01-01

    Phenotypic data derived from high content screening is currently annotated using free-text, thus preventing the integration of independent datasets, including those generated in different biological domains, such as cell lines, mouse and human tissues. We present the Cellular Microscopy Phenotype Ontology (CMPO), a species neutral ontology for describing phenotypic observations relating to the whole cell, cellular components, cellular processes and cell populations. CMPO is compatible with related ontology efforts, allowing for future cross-species integration of phenotypic data. CMPO was developed following a curator-driven approach where phenotype data were annotated by expert biologists following the Entity-Quality (EQ) pattern. These EQs were subsequently transformed into new CMPO terms following an established post composition process. CMPO is currently being utilized to annotate phenotypes associated with high content screening datasets stored in several image repositories including the Image Data Repository (IDR), MitoSys project database and the Cellular Phenotype Database to facilitate data browsing and discoverability.

  17. 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.

  18. RNA: State Memory and Mediator of Cellular Phenotype

    PubMed Central

    Kim, Junhyong; Eberwine, James

    2010-01-01

    It has become increasingly clear that the genome is dynamic and exquisitely sensitive, changing expression patterns in response to age, environmental stimuli and pharmacological and physiological manipulations. Similarly, cellular phenotype, traditionally viewed as a stable end-state, should be viewed as versatile and changeable. The phenotype of a cell is better defined as a “homeostatic phenotype” implying plasticity resulting from a dynamically-changing yet characteristic pattern of gene/protein expression. A stable change in phenotype is the result of the movement of a cell between different multi-dimensional identity spaces. Here, we describe a key driver of this transition and the stabilizer of phenotype: the relative abundances of the cellular RNAs. We argue that the quantitative state of RNA can be likened to a state memory, that when transferred between cells, alters the phenotype in a predictable manner. PMID:20382532

  19. Quantification of Microbial Phenotypes

    PubMed Central

    Martínez, Verónica S.; Krömer, Jens O.

    2016-01-01

    Metabolite profiling technologies have improved to generate close to quantitative metabolomics data, which can be employed to quantitatively describe the metabolic phenotype of an organism. Here, we review the current technologies available for quantitative metabolomics, present their advantages and drawbacks, and the current challenges to generate fully quantitative metabolomics data. Metabolomics data can be integrated into metabolic networks using thermodynamic principles to constrain the directionality of reactions. Here we explain how to estimate Gibbs energy under physiological conditions, including examples of the estimations, and the different methods for thermodynamics-based network analysis. The fundamentals of the methods and how to perform the analyses are described. Finally, an example applying quantitative metabolomics to a yeast model by 13C fluxomics and thermodynamics-based network analysis is presented. The example shows that (1) these two methods are complementary to each other; and (2) there is a need to take into account Gibbs energy errors. Better estimations of metabolic phenotypes will be obtained when further constraints are included in the analysis. PMID:27941694

  20. Towards a multidimensional healthy ageing phenotype.

    PubMed

    Mount, Sarah; Lara, Jose; Schols, Annemie M W J; Mathers, John C

    2016-11-01

    There is great interest in developing tools to measure healthy ageing and to identify early stages of health impairment, which may guide the implementation of interventions to prevent or delay the development of disease, disability, and mortality. Here, we review the most recent developments directed to operationalize, and test, definitions of healthy ageing. There is lack of consensus about how to define healthy ageing and, unsurprisingly, diversity in the instruments for its measurement. However, progress is being made in describing and in devising tools to capture the healthy ageing phenotype. Attempts to measure healthy ageing have relied primarily on cross-sectional data collected in older people. More recent studies have assessed the healthy ageing phenotype using markers of multiple functional domains and have used longitudinal data to model the dynamics and trajectories of healthy ageing. Given the complexity of the ageing process, no single measure is able to predict the ageing trajectory. Current attempts to operationalize the healthy ageing phenotype have relied on markers and data from earlier cohort studies and are limited by the tools used to collect data in those studies. Such data are often unsuitable to detect early subtle declines in function and/or are inappropriate for use in younger old adults. Future studies employing more objective and novel markers of healthy ageing are likely to offer opportunities to define and operationalize the healthy ageing phenotype.

  1. 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…

  2. Approximate Qualitative Temporal Reasoning

    DTIC Science & Technology

    2001-01-01

    A. G. Cohn, B. Bennett, J. Goodday , and N. Gotts. Qualitative spatial representation and reasoning with the region connection calculus. geoinformatica... Goodday and A. G. Cohn. Conceptual neighborhoods in temporal and spatial reasoning. In ECAI-94 Spatial and Temporal Reasoning Workshop, 1994. T

  3. Individualised Qualitative Evaluation.

    ERIC Educational Resources Information Center

    O'Sullivan, Denis

    1987-01-01

    The author discusses student evaluation in relation to adult and continuing education programs offered by the Department of Adult Education, University College, Cork. He highlights the need for a more individualized and interactive approach to evaluation, allowing the student to benefit from qualitative feedback in the process of being evaluated.…

  4. 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)

  5. 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)

  6. Qualitative Collection Evaluation.

    ERIC Educational Resources Information Center

    Craver, Kathleen W.

    1985-01-01

    Describes qualitative evaluation of library holdings in a high school science collection that involved two methods: impressionistic method (relies on professional judgement of subject specialists, librarians, or scholars to evaluate collection); list-checking (compared holdings with "American Association for the Advancement of Science Book…

  7. Individualised Qualitative Evaluation.

    ERIC Educational Resources Information Center

    O'Sullivan, Denis

    1987-01-01

    The author discusses student evaluation in relation to adult and continuing education programs offered by the Department of Adult Education, University College, Cork. He highlights the need for a more individualized and interactive approach to evaluation, allowing the student to benefit from qualitative feedback in the process of being evaluated.…

  8. 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…

  9. 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…

  10. First Semester Qualitative Analysis

    ERIC Educational Resources Information Center

    DeLap, James H.

    1969-01-01

    Describes a two-hour laboratory course entitled "Chemical Periodicity offered first semester of the freshman year. Three cation groups, one anion group, and a final unkown salt are qualitatively analyzed. Course fosters scientific thinking in experimentation by encouraging student-initiated schemes of analyses rather than "cookbook schemes. (RR)

  11. First Semester Qualitative Analysis

    ERIC Educational Resources Information Center

    DeLap, James H.

    1969-01-01

    Describes a two-hour laboratory course entitled "Chemical Periodicity offered first semester of the freshman year. Three cation groups, one anion group, and a final unkown salt are qualitatively analyzed. Course fosters scientific thinking in experimentation by encouraging student-initiated schemes of analyses rather than "cookbook schemes. (RR)

  12. 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…

  13. Advances in Qualitative Research.

    ERIC Educational Resources Information Center

    1998

    This document contains five papers from a symposium on advances in qualitative research in human resource development (HRD). "Case Study and Its Virtuoso Possibilities" (Verna J. Willis) asserts that the case study method is particularly well suited for research in HRD because its creative and investigative possibilities have not yet…

  14. Phenotype/genotype correlations in Gaucher disease type 1: Clinical and therapeutic implications

    SciTech Connect

    Sibille, A.; Eng, C.M.; Kim, S.J.; Pastores, G. ); Grabowski, G.A. Univ. of Cincinnati, OH )

    1993-06-01

    Gaucher disease is the most frequent lysosomal storage disease and the most prevalent genetic disease among Ashkenazi Jews. Gaucher disease type 1 is characterized by marked variability of the phenotype and by the absence of neuronopathic involvement. To test the hypothesis that this phenotypic variability was due to genetic compounds of several different mutant alleles, 161 symptomatic patients with Gaucher disease type 1 (> 90% Ashkenazi Jewish) were analyzed for clinical involvement, and their genotypes were determined. Qualitative and quantitative measures of disease involvement included age at onset of the disease manifestations, hepatic and splenic volumes, age at splenectomy, and severity of bony disease. High statistically significant differences (P < .005) were found in each clinical parameter in patients with the N370S/N370S genotype compared with those patients with the N370S/84GG, N370S/L444P, and N370/ genotypes. The symptomatic N370S homozygotes had onset of their disease two to three decades later than patients with the other genotypes. In addition, patients with the latter genotypes have much more severely involved livers, spleens, and bones and had a higher incidence of splenectomy at an earlier age. These predictive genotype analyses provide the basis for genetic care delivery and therapeutic recommendations in patients affected with Gaucher disease type 1. 38 refs., 1 fig., 4 tabs.

  15. 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

  16. The recent advances of phenotypes in acute exacerbations of COPD

    PubMed Central

    Zhou, Aiyuan; Zhou, Zijing; Zhao, Yiyang; Chen, Ping

    2017-01-01

    Exacerbations of COPD are clinically relevant events with therapeutic and prognostic implications. Yet, significant heterogeneity of clinical presentation and disease progression exists within acute exacerbations of COPD (AECOPD). Currently, different phenotypes have been widely used to describe the characteristics among patients with AECOPD. This has proved to be significant in the treatment and prediction of the outcomes of the disease. In this review of published literature, the phenotypes of AECOPD were classified according to etiology, inflammatory biomarkers, clinical manifestation, comorbidity, the frequency of exacerbations, and so on. This review concentrates on advancements in the use of phenotypes of AECOPD. PMID:28392685

  17. 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.

  18. Phenotypic characterization of glioblastoma identified through shape descriptors

    NASA Astrophysics Data System (ADS)

    Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

    2016-03-01

    This paper proposes quantitatively describing the shape of glioblastoma (GBM) tissue phenotypes as a set of shape features derived from segmentations, for the purposes of discriminating between GBM phenotypes and monitoring tumor progression. GBM patients were identified from the Cancer Genome Atlas, and quantitative MR imaging data were obtained from the Cancer Imaging Archive. Three GBM tissue phenotypes are considered including necrosis, active tumor and edema/invasion. Volumetric tissue segmentations are obtained from registered T1˗weighted (T1˗WI) postcontrast and fluid-attenuated inversion recovery (FLAIR) MRI modalities. Shape features are computed from respective tissue phenotype segmentations, and a Kruskal-Wallis test was employed to select features capable of classification with a significance level of p < 0.05. Several classifier models are employed to distinguish phenotypes, where a leave-one-out cross-validation was performed. Eight features were found statistically significant for classifying GBM phenotypes with p <0.05, orientation is uninformative. Quantitative evaluations show the SVM results in the highest classification accuracy of 87.50%, sensitivity of 94.59% and specificity of 92.77%. In summary, the shape descriptors proposed in this work show high performance in predicting GBM tissue phenotypes. They are thus closely linked to morphological characteristics of GBM phenotypes and could potentially be used in a computer assisted labeling system.

  19. 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

  20. Bronchiectasis: Phenotyping a Complex Disease.

    PubMed

    Chalmers, James D

    2017-03-15

    Bronchiectasis is a long-neglected disease currently experiencing a surge in interest. It is a highly complex condition with numerous aetiologies, co-morbidities and a heterogeneous disease presentation and clinical course. The past few years have seen major advances in our understanding of the disease, primarily through large real-life cohort studies. The main outcomes of interest in bronchiectasis are symptoms, exacerbations, treatment response, disease progression and death. We are now more able to identify clearly the radiological, clinical, microbiological and inflammatory contributors to these outcomes. Over the past couple of years, multidimensional scoring systems such as the Bronchiectasis Severity Index have been introduced to predict disease severity and mortality. Although there are currently no licensed therapies for bronchiectasis, an increasing number of clinical trials are planned or ongoing. While this emerging evidence is awaited, bronchiectasis guidelines will continue to be informed largely by real-life evidence from observational studies and patient registries. Key developments in the bronchiectasis field include the establishment of international disease registries and characterisation of disease phenotypes using cluster analysis and biological data.

  1. 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…

  2. 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…

  3. Phenotypic characteristics of local cattle in Madura Island

    NASA Astrophysics Data System (ADS)

    Maylinda, Sucik; Nugroho, H.; Busono, W.

    2017-05-01

    The aim of the research is to (1) analyze phenotypic variance both qualitative and quantitative characters in Madura cattle, (2) to analyze the relationship between that characters and body weight. Cattle studied were located in Waru and Pademawu subdistrict, Pamekasan district, Indonesia. The sampling technique was accidental sampling. Subject animals were 8-20 month-old cows, grouped into 2 age groups of <1 and >1 years old. Both qualitative and quantitative phenotypic characteristics were recorded. Qualitative characteristics were the color of the body, white color in bottom and leg, black color at the back, and the presence of horns. Quantitative characteristics were the head index, body weight, chest girth (CG), body height (BH), body length (BL), and body condition score (BCS). Data were analyzed with correlation and regression analyses. Results showed that qualitative characteristics of the Madura local cattle were all those of the reference Madura cattle standard, such as the white color of leg and bottom, with small head indexes. We found that (1) most of Madura Local cattle had the standard Madura cattle characteristics in both sexes, and (2) the best cattle, in terms of body weight, can be selected based on chest girth rather than other measurements, which is advantageous because measuring the chest circumference is quicker and easier than directly measuring cattle weight in rural villages.

  4. Qualitative science policy.

    PubMed

    Mitcham, Carl

    2007-12-01

    Qualitative research struggles against a tide of quantitative methods. To assist in this struggle, it is useful to consider the historical and philosophical origins of quantitative methods as well as criticisms that have been raised against them. Although these criticisms have often been restricted to discussions in the philosophy of science, they have become increasingly prominent in debates regarding science policy. This article thus reviews current science policy debates concerning scientific autonomy and the linear model of science-society relationships. Then, having considered the multiple meanings of quality, it argues for a science policy reassessment of quantitative research, for deeper engagements between science policy and the social sciences, and finally, for a more explicit alliance between science policy and qualitative methods.

  5. High-throughput mouse phenotyping.

    PubMed

    Gates, Hilary; Mallon, Ann-Marie; Brown, Steve D M

    2011-04-01

    Comprehensive phenotyping will be required to reveal the pleiotropic functions of a gene and to uncover the wider role of genetic loci within diverse biological systems. The challenge will be to devise phenotyping approaches to characterise the thousands of mutants that are being generated as part of international efforts to acquire a mutant for every gene in the mouse genome. In order to acquire robust datasets of broad based phenotypes from mouse mutants it is necessary to design and implement pipelines that incorporate standardised phenotyping platforms that are validated across diverse mouse genetics centres or mouse clinics. We describe here the rationale and methodology behind one phenotyping pipeline, EMPReSSslim, that was designed as part of the work of the EUMORPHIA and EUMODIC consortia, and which exemplifies some of the challenges facing large-scale phenotyping. EMPReSSslim captures a broad range of data on diverse biological systems, from biochemical to physiological amongst others. Data capture and dissemination is pivotal to the operation of large-scale phenotyping pipelines, including the definition of parameters integral to each phenotyping test and the associated ontological descriptions. EMPReSSslim data is displayed within the EuroPhenome database, where a variety of tools are available to allow the user to search for interesting biological or clinical phenotypes.

  6. 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

  7. Learning and Teaching Qualitative Research with Qualitative Data Analysis Software.

    ERIC Educational Resources Information Center

    Mahlamaki-Kultanen, Seija

    This study examined the way qualitative data analysis software and virtual teaching methods can support the learning of qualitative research. Study methodology was based on phenomenology, and data were gathered in a pilot course on qualitative research methodology in which 22 adult part time graduate students participated. The course was built…

  8. In vitro T cell function, delayed-type hypersensitivity skin testing, and CD4+ T cell subset phenotyping independently predict survival time in patients infected with human immunodeficiency virus.

    PubMed

    Dolan, M J; Clerici, M; Blatt, S P; Hendrix, C W; Melcher, G P; Boswell, R N; Freeman, T M; Ward, W; Hensley, R; Shearer, G M

    1995-07-01

    Human immunodeficiency virus type 1 (HIV-1)-infected patients (n = 335) in the US Air Force HIV Natural History Program were followed for 3 years (mean) after skin testing, immunophenotyping of CD4+ cell subsets, and measurement of in vitro interleukin-2 production after stimulation by phytohemagglutinin, alloantigens, tetanus toxoid, and influenza A virus. The T cell functional assay predicted survival time (P < .001) and time for progression to AIDS (P = .014). Skin testing for tetanus, mumps, and Candida antigen and the total number of positive tests (P < .001 for each) stratified patients for survival time. In a multivariable proportional hazards model, the T cell functional assay (P = .008), the absolute number of CD4+ T cells (P = .001), the percentage of CD4+ CD29+ cells (P = .06), and the number of reactive skin tests (P < .001) predicted survival time. Thus, cellular immune functional tests have significant predictive value for survival time in HIV-1-infected patients independent of CD4+ cell count.

  9. Qualitative Process Theory.

    DTIC Science & Technology

    1984-07-01

    AD-A148 987 QUALITATIVE PROCESS THEORY(U) MASSACHUSETTS INST OF 1/2 TEEH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB K D FORBUS JUL 84 RI-TR-789 N88814-80...NATIONAL BUREAU Of STAN ARDS IJ% A 4 I .7 Technical Report 789 Q[-----Qualitative• Process M° Theory . Kenneth Dale Forbus MIT Artificial Intelligence ...PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA& WORK UNIT NUMBERS 545 Technology Square Cambridge, Massachusetts 02139 iI

  10. Interviews in qualitative research.

    PubMed

    Peters, Kath; Halcomb, Elizabeth

    2015-03-01

    Interviews are a common method of data collection in nursing research. They are frequently used alone in a qualitative study or combined with other data collection methods in mixed or multi-method research. Semi-structured interviews, where the researcher has some predefined questions or topics but then probes further as the participant responds, can produce powerful data that provide insights into the participants' experiences, perceptions or opinions.

  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. Copyright © 2016. Published by Elsevier Masson SAS.

  12. Identification and phenotypic characterization of a second collagen adhesin, Scm, and genome-based identification and analysis of 13 other predicted MSCRAMMs, including four distinct pilus loci, in Enterococcus faecium

    PubMed Central

    Sillanpää, Jouko; Nallapareddy, Sreedhar R.; Prakash, Vittal P.; Qin, Xiang; Hook, Magnus; Weinstock, George M.; Murray, Barbara E.

    2009-01-01

    SUMMARY Attention has recently been drawn to Enterococcus faecium because of an increasing number of nosocomial infections caused by this species and its resistance to multiple antibacterial agents. However, relatively little is known about pathogenic determinants of this organism. We have previously identified a cell wall anchored collagen adhesin, Acm, produced by some isolates of E. faecium, and a secreted antigen, SagA, exhibiting broad spectrum binding to extracellular matrix proteins. Here, we analyzed the draft genome of strain TX0016 for potential MSCRAMMs (microbial surface component recognizing adhesive matrix molecules). Genome-based bioinformatics identified 22 predicted cell wall anchored E. faeciumsurface proteins (Fms) of which 15 (including Acm) have typical characteristics of MSCRAMMs including predicted folding into a modular architecture with multiple immunoglobulin-like domains. Functional characterization of one (Fms10, redesignated Scm for second collagen adhesin of E. faeciu m) revealed that recombinant Scm65 (A- and B-domains) and Scm36 (A-domain) bound efficiently to collagen type V in a concentration dependent manner, bound considerably less to collagen type I and fibrinogen, and differed from Acm in their binding specificities to collagen types IV and V. Results from far-UV circular dichroism of recombinant Scm36 and of Acm37 indicated that these proteins are rich in β-sheets, supporting our folding predictions. Whole-cell ELISA and FACS analyses unambiguously demonstrated surface expression of Scm in most E. faecium isolates. Strikingly, 11 of the 15 predicted MSCRAMMs clustered in four loci, each with a class C sortase gene; 9 of these showed similarity to Enterococcus faecalis Ebp pilus subunits and also contained motifs essential for pilus assembly. Antibodies against one of the predicted major pilus proteins, Fms9 (redesignated as EbpCfm), detected a “ladder” pattern of high-molecular weight protein bands in a Western blot

  13. Identification and phenotypic characterization of a second collagen adhesin, Scm, and genome-based identification and analysis of 13 other predicted MSCRAMMs, including four distinct pilus loci, in Enterococcus faecium.

    PubMed

    Sillanpää, Jouko; Nallapareddy, Sreedhar R; Prakash, Vittal P; Qin, Xiang; Höök, Magnus; Weinstock, George M; Murray, Barbara E

    2008-10-01

    Attention has recently been drawn to Enterococcus faecium because of an increasing number of nosocomial infections caused by this species and its resistance to multiple antibacterial agents. However, relatively little is known about the pathogenic determinants of this organism. We have previously identified a cell-wall-anchored collagen adhesin, Acm, produced by some isolates of E. faecium, and a secreted antigen, SagA, exhibiting broad-spectrum binding to extracellular matrix proteins. Here, we analysed the draft genome of strain TX0016 for potential microbial surface components recognizing adhesive matrix molecules (MSCRAMMs). Genome-based bioinformatics identified 22 predicted cell-wall-anchored E. faecium surface proteins (Fms), of which 15 (including Acm) had characteristics typical of MSCRAMMs, including predicted folding into a modular architecture with multiple immunoglobulin-like domains. Functional characterization of one [Fms10; redesignated second collagen adhesin of E. faecium (Scm)] revealed that recombinant Scm(65) (A- and B-domains) and Scm(36) (A-domain) bound to collagen type V efficiently in a concentration-dependent manner, bound considerably less to collagen type I and fibrinogen, and differed from Acm in their binding specificities to collagen types IV and V. Results from far-UV circular dichroism measurements of recombinant Scm(36) and of Acm(37) indicated that these proteins were rich in beta-sheets, supporting our folding predictions. Whole-cell ELISA and FACS analyses unambiguously demonstrated surface expression of Scm in most E. faecium isolates. Strikingly, 11 of the 15 predicted MSCRAMMs clustered in four loci, each with a class C sortase gene; nine of these showed similarity to Enterococcus faecalis Ebp pilus subunits and also contained motifs essential for pilus assembly. Antibodies against one of the predicted major pilus proteins, Fms9 (redesignated EbpC(fm)), detected a 'ladder' pattern of high-molecular-mass protein bands in a

  14. Quantitative and qualitative symptomatic differences in individuals at Ultra-High Risk for psychosis and healthy controls.

    PubMed

    Velthorst, Eva; Derks, Eske M; Schothorst, Patricia; Becker, Hiske; Durston, Sarah; Ziermans, Tim; Nieman, Dorien H; de Haan, Lieuwe

    2013-12-15

    Patients at Ultra-High Risk (UHR) for developing a first psychosis vary widely in their symptom presentation and illness course. An important aim in UHR research concerns the characterization of the clinical heterogeneity in this population. We aimed to identify qualitatively and quantitatively different clinical symptom profiles at baseline and at 2-year follow-up in a group of UHR subjects and healthy controls. We employed a Latent Class Factor Analysis (LCFA) to the 19 items of the Structured Interview for Prodromal Syndromes (SIPS) ratings at baseline and at 2-year follow-up in a sample of 147 UHR subjects and 141 controls from the Dutch Prediction of Psychosis Study (DUPS) in the Netherlands. Additionally, a stepwise logistic regression analysis was performed with transition to psychosis as a dependent variable and baseline latent variable scores as predictors. Variation in symptomatology at baseline was explained by both quantitative and qualitative differences; at 2-year follow-up qualitative differences between individuals were no longer observed. Quantitative differences showed moderate stability over time (range=0.109-0.42). Within the UHR sample, transition to psychosis was significantly associated with quantitative differences in baseline SIPS scores. The results of our study suggest a 'quasi'-continuous extended psychosis phenotype, a finding that merits replication in other samples.

  15. Ecosystems and People: Qualitative Insights

    EPA Science Inventory

    Both qualitative and quantitative techniques are crucial in researching human impacts from ecological changes. This matches the importance of ?mixed methods? approaches in other disciplines. Qualitative research helps explore the relevancy and transferability of the foundational ...

  16. Ecosystems and People: Qualitative Insights

    EPA Science Inventory

    Both qualitative and quantitative techniques are crucial in researching human impacts from ecological changes. This matches the importance of ?mixed methods? approaches in other disciplines. Qualitative research helps explore the relevancy and transferability of the foundational ...

  17. Comparison of quantitative and qualitative tests for glucose-6-phosphate dehydrogenase deficiency.

    PubMed

    LaRue, Nicole; Kahn, Maria; Murray, Marjorie; Leader, Brandon T; Bansil, Pooja; McGray, Sarah; Kalnoky, Michael; Zhang, Hao; Huang, Huiqiang; Jiang, Hui; Domingo, Gonzalo J

    2014-10-01

    A barrier to eliminating Plasmodium vivax malaria is inadequate treatment of infected patients. 8-Aminoquinoline-based drugs clear the parasite; however, people with glucose-6-phosphate dehydrogenase (G6PD) deficiency are at risk for hemolysis from these drugs. Understanding the performance of G6PD deficiency tests is critical for patient safety. Two quantitative assays and two qualitative tests were evaluated. The comparison of quantitative assays gave a Pearson correlation coefficient of 0.7585 with significant difference in mean G6PD activity, highlighting the need to adhere to a single reference assay. Both qualitative tests had high sensitivity and negative predictive value at a cutoff G6PD value of 40% of normal activity if interpreted conservatively and performed under laboratory conditions. The performance of both tests dropped at a cutoff level of 45%. Cytochemical staining of specimens confirmed that heterozygous females with > 50% G6PD-deficient cells can seem normal by phenotypic tests. © The American Society of Tropical Medicine and Hygiene.

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

    PubMed Central

    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

  19. Stability of the hybrid epithelial/mesenchymal phenotype

    PubMed Central

    Jolly, Mohit Kumar; Mooney, Steven M.; Celiktas, Muge; Hanash, Samir M.; Mani, Sendurai A.; Pienta, Kenneth J.; Ben-Jacob, Eshel; Levine, Herbert

    2016-01-01

    Epithelial-to-Mesenchymal Transition (EMT) and its reverse – Mesenchymal to Epithelial Transition (MET) – are hallmarks of cellular plasticity during embryonic development and cancer metastasis. During EMT, epithelial cells lose cell-cell adhesion and gain migratory and invasive traits either partially or completely, leading to a hybrid epithelial/mesenchymal (hybrid E/M) or a mesenchymal phenotype respectively. Mesenchymal cells move individually, but hybrid E/M cells migrate collectively as observed during gastrulation, wound healing, and the formation of tumor clusters detected as Circulating Tumor Cells (CTCs). Typically, the hybrid E/M phenotype has largely been tacitly assumed to be transient and ‘metastable’. Here, we identify certain ‘phenotypic stability factors’ (PSFs) such as GRHL2 that couple to the core EMT decision-making circuit (miR-200/ZEB) and stabilize hybrid E/M phenotype. Further, we show that H1975 lung cancer cells can display a stable hybrid E/M phenotype and migrate collectively, a behavior that is impaired by knockdown of GRHL2 and another previously identified PSF - OVOL. In addition, our computational model predicts that GRHL2 can also associate hybrid E/M phenotype with high tumor-initiating potential, a prediction strengthened by the observation that the higher levels of these PSFs may be predictive of poor patient outcome. Finally, based on these specific examples, we deduce certain network motifs that can stabilize the hybrid E/M phenotype. Our results suggest that partial EMT, i.e. a hybrid E/M phenotype, need not be ‘metastable’, and strengthen the emerging notion that partial EMT, but not necessarily a complete EMT, is associated with aggressive tumor progression. PMID:27008704

  20. Understanding and Evaluating Qualitative Research.

    ERIC Educational Resources Information Center

    Ambert, Anne-Marie; And Others

    1995-01-01

    Presents an overview of the goals and procedures of qualitative research, and discusses linkages between epistemologies and methodology. Reviews possible guidelines involved in the several steps of the evaluation process of qualitative research, emphasizing naturalistic research with families. Reviews common problems with qualitative research.…

  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. 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

    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

    2016-06-01

    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

  3. 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.

  4. An official American Thoracic Society Statement: pulmonary hypertension phenotypes.

    PubMed

    Dweik, Raed A; Rounds, Sharon; Erzurum, Serpil C; Archer, Stephen; Fagan, Karen; Hassoun, Paul M; Hill, Nicholas S; Humbert, Marc; Kawut, Steven M; Krowka, Michael; Michelakis, Evangelos; Morrell, Nicholas W; Stenmark, Kurt; Tuder, Rubin M; Newman, John

    2014-02-01

    Current classification of pulmonary hypertension (PH) is based on a relatively simple combination of patient characteristics and hemodynamics. This limits customization of treatment, and lacks the clarity of a more granular identification based on individual patient phenotypes. Rapid advances in mechanistic understanding of the disease, improved imaging methods, and innovative biomarkers now provide an opportunity to define PH phenotypes on the basis of biomarkers, advanced imaging, and pathobiology. This document organizes our current understanding of PH phenotypes and identifies gaps in our knowledge. A multidisciplinary committee with expertise in clinical care (pulmonary, cardiology, pediatrics, and pathology), clinical research, and/or basic science in the areas of PH identified important questions and reviewed and synthesized the literature. This document describes selected PH phenotypes and serves as an initial platform to define additional relevant phenotypes as new knowledge is generated. The biggest gaps in our knowledge stem from the fact that our present understanding of PH phenotypes has not come from any particularly organized effort to identify such phenotypes, but rather from reinterpreting studies and reports that were designed and performed for other purposes. Accurate phenotyping of PH can be used in research studies to increase the homogeneity of study cohorts. Once the ability of the phenotypes to predict outcomes has been validated, phenotyping may also be useful for determining prognosis and guiding treatment. This important next step in PH patient care can optimally be addressed through a consortium of study sites with well-defined goals, tasks, and structure. Planning and support for this could include the National Institutes of Health and the U.S. Food and Drug Administration, with industry and foundation partnerships.

  5. A multifaceted analysis of HIV-1 protease multidrug resistance phenotypes

    PubMed Central

    2011-01-01

    Background Great strides have been made in the effective treatment of HIV-1 with the development of second-generation protease inhibitors (PIs) that are effective against historically multi-PI-resistant HIV-1 variants. Nevertheless, mutation patterns that confer decreasing susceptibility to available PIs continue to arise within the population. Understanding the phenotypic and genotypic patterns responsible for multi-PI resistance is necessary for developing PIs that are active against clinically-relevant PI-resistant HIV-1 variants. Results In this work, we use globally optimal integer programming-based clustering techniques to elucidate multi-PI phenotypic resistance patterns using a data set of 398 HIV-1 protease sequences that have each been phenotyped for susceptibility toward the nine clinically-approved HIV-1 PIs. We validate the information content of the clusters by evaluating their ability to predict the level of decreased susceptibility to each of the available PIs using a cross validation procedure. We demonstrate the finding that as a result of phenotypic cross resistance, the considered clinical HIV-1 protease isolates are confined to ~6% or less of the clinically-relevant phenotypic space. Clustering and feature selection methods are used to find representative sequences and mutations for major resistance phenotypes to elucidate their genotypic signatures. We show that phenotypic similarity does not imply genotypic similarity, that different PI-resistance mutation patterns can give rise to HIV-1 isolates with similar phenotypic profiles. Conclusion Rather than characterizing HIV-1 susceptibility toward each PI individually, our study offers a unique perspective on the phenomenon of PI class resistance by uncovering major multidrug-resistant phenotypic patterns and their often diverse genotypic determinants, providing a methodology that can be applied to understand clinically-relevant phenotypic patterns to aid in the design of novel inhibitors that

  6. An Official American Thoracic Society Statement: Pulmonary Hypertension Phenotypes

    PubMed Central

    Dweik, Raed A.; Rounds, Sharon; Erzurum, Serpil C.; Archer, Stephen; Fagan, Karen; Hassoun, Paul M.; Hill, Nicholas S.; Humbert, Marc; Kawut, Steven M.; Krowka, Michael; Michelakis, Evangelos; Morrell, Nicholas W.; Stenmark, Kurt; Tuder, Rubin M.; Newman, John

    2014-01-01

    Background: Current classification of pulmonary hypertension (PH) is based on a relatively simple combination of patient characteristics and hemodynamics. This limits customization of treatment, and lacks the clarity of a more granular identification based on individual patient phenotypes. Rapid advances in mechanistic understanding of the disease, improved imaging methods, and innovative biomarkers now provide an opportunity to define PH phenotypes on the basis of biomarkers, advanced imaging, and pathobiology. This document organizes our current understanding of PH phenotypes and identifies gaps in our knowledge. Methods: A multidisciplinary committee with expertise in clinical care (pulmonary, cardiology, pediatrics, and pathology), clinical research, and/or basic science in the areas of PH identified important questions and reviewed and synthesized the literature. Results: This document describes selected PH phenotypes and serves as an initial platform to define additional relevant phenotypes as new knowledge is generated. The biggest gaps in our knowledge stem from the fact that our present understanding of PH phenotypes has not come from any particularly organized effort to identify such phenotypes, but rather from reinterpreting studies and reports that were designed and performed for other purposes. Conclusions: Accurate phenotyping of PH can be used in research studies to increase the homogeneity of study cohorts. Once the ability of the phenotypes to predict outcomes has been validated, phenotyping may also be useful for determining prognosis and guiding treatment. This important next step in PH patient care can optimally be addressed through a consortium of study sites with well-defined goals, tasks, and structure. Planning and support for this could include the National Institutes of Health and the U.S. Food and Drug Administration, with industry and foundation partnerships. PMID:24484330

  7. Emerging molecular phenotypes of asthma

    PubMed Central

    Ray, Anuradha; Oriss, Timothy B.

    2014-01-01

    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

  8. 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.

  9. gEM/GANN: A multivariate computational strategy for auto-characterizing relationships between cellular and clinical phenotypes and predicting disease progression time using high-dimensional flow cytometry data.

    PubMed

    Tong, Dong Ling; Ball, Graham R; Pockley, A Graham

    2015-07-01

    The dramatic increase in the complexity of flow cytometric datasets requires new computational approaches that can maximize the amount of information derived and overcome the limitations of traditional gating strategies. Herein, we present a multivariate computational analysis of the HIV-infected flow cytometry datasets that were provided as part of the FlowCAP-IV Challenge using unsupervised and supervised learning techniques. Out of 383 samples (stimulated and unstimulated), 191 samples were used as a training set (34 individuals whose disease did not progress, and 157 individuals whose disease did progress). Using the results from the training set, the participants in the Challenge were then asked to predict the condition and progression time of the remaining individuals (45 "nonprogressors" and 147 "progressors"). To achieve this, we first scaled down data resolution and then excluded doublet cells from the analysis using Expectation Maximization approaches. We then standardized all samples into histograms and used Genetic Algorithm-Neural Network to extract feature sets from the datasets, the reliability of which were examined using WEKA-implemented classifiers. The selected feature set resulted in a high sensitivity and specificity for the discrimination of progressors and nonprogressors in the training set (average True Positive Rate = 1.00 and average False Positive Rate = 0.033). The capacity of the feature set to predict real-time survival time was better when using data from the "unstimulated" training set (r = 0.825). The P-values and 95% confidence interval log-rank ratios between actual and predicted survival time in the test set were 0.682 and 0.9542 ± 0.24 for the unstimulated dataset, and 0.4451 and 0.9173 ± 0.23 for the stimulated dataset. Our analytic strategy has demonstrated a promising capacity to extract useful information from complex flow cytometry datasets, despite a significance imbalance and variation between the

  10. The Ecology and Evolution of Stoichiometric Phenotypes.

    PubMed

    Leal, Miguel C; Seehausen, Ole; Matthews, Blake

    2017-02-01

    Ecological stoichiometry has generated new insights into how the balance of elements affects ecological interactions and ecosystem processes, but little is known about the ecological and evolutionary dynamics of stoichiometric traits. Understanding the origins and drivers of stoichiometric trait variation between and within species will improve our understanding about the ecological responses of communities to environmental change and the ecosystem effects of organisms. In addition, studying the plasticity, heritability, and genetic basis of stoichiometric traits might improve predictions about how organisms adapt to changing environmental conditions, and help to identify interactions and feedbacks between phenotypic evolution and ecosystem processes.

  11. Qualitative Kinematics of Linkages

    DTIC Science & Technology

    1990-05-01

    links and the connections between them, the following algorithm computes an envisionment for that system . lotatioa(P1,P2) - CCV lotatioa(P1,P2) CCV...1988 Appendix A : Slider-Crank Envisionment Each qualitative state consists of a kinematic state representing the orientation of each link, and a...8 +++ 6 -- . f. 6 000 , 7 --0 7 ++0 8 +- -+ > 1 000 1 +0+ 8 000 8 000 7 --0 7 000 8 --- m 8 +++ Appendix B : Drag-Link Envisionment Kinematic State

  12. The geometry of the Pareto front in biological phenotype space

    PubMed Central

    Sheftel, Hila; Shoval, Oren; Mayo, Avi; Alon, Uri

    2013-01-01

    When organisms perform a single task, selection leads to phenotypes that maximize performance at that task. When organisms need to perform multiple tasks, a trade-off arises because no phenotype can optimize all tasks. Recent work addressed this question, and assumed that the performance at each task decays with distance in trait space from the best phenotype at that task. Under this assumption, the best-fitness solutions (termed the Pareto front) lie on simple low-dimensional shapes in trait space: line segments, triangles and other polygons. The vertices of these polygons are specialists at a single task. Here, we generalize this finding, by considering performance functions of general form, not necessarily functions that decay monotonically with distance from their peak. We find that, except for performance functions with highly eccentric contours, simple shapes in phenotype space are still found, but with mildly curving edges instead of straight ones. In a wide range of systems, complex data on multiple quantitative traits, which might be expected to fill a high-dimensional phenotype space, is predicted instead to collapse onto low-dimensional shapes; phenotypes near the vertices of these shapes are predicted to be specialists, and can thus suggest which tasks may be at play. PMID:23789060

  13. 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

  14. Arabidopsis Seed Content QTL Mapping Using High-Throughput Phenotyping: The Assets of Near Infrared Spectroscopy

    PubMed Central

    Jasinski, Sophie; Lécureuil, Alain; Durandet, Monique; Bernard-Moulin, Patrick; Guerche, Philippe

    2016-01-01

    Seed storage compounds are of crucial importance for human diet, feed and industrial uses. In oleo-proteaginous species like rapeseed, seed oil and protein are the qualitative determinants that conferred economic value to the harvested seed. To date, although the biosynthesis pathways of oil and storage protein are rather well-known, the factors that determine how these types of reserves are partitioned in seeds have to be identified. With the aim of implementing a quantitative genetics approach, requiring phenotyping of 100s of plants, our first objective was to establish near-infrared reflectance spectroscopic (NIRS) predictive equations in order to estimate oil, protein, carbon, and nitrogen content in Arabidopsis seed with high-throughput level. Our results demonstrated that NIRS is a powerful non-destructive, high-throughput method to assess the content of these four major components studied in Arabidopsis seed. With this tool in hand, we analyzed Arabidopsis natural variation for these four components and illustrated that they all displayed a wide range of variation. Finally, NIRS was used in order to map QTL for these four traits using seeds from the Arabidopsis thaliana Ct-1 × Col-0 recombinant inbred line population. Some QTL co-localized with QTL previously identified, but others mapped to chromosomal regions never identified so far for such traits. This paper illustrates the usefulness of NIRS predictive equations to perform accurate high-throughput phenotyping of Arabidopsis seed content, opening new perspectives in gene identification following QTL mapping and genome wide association studies. PMID:27891138

  15. Familial Transmission of Derived Phenotypes for Molecular Genetic Studies of Substance Use Disorders

    PubMed Central

    Faraone, Stephen V.; Adamson, Joel J.; Wilens, Timothy E.; Monuteaux, Michael C.; Biederman, Joseph

    2008-01-01

    Although family, twin, and adoption studies indicate that genes play a significant etiologic role in the development of substance use disorders (SUDs), detecting specific genes has been difficult due to uncertainties about how to define SUDs, genetic heterogeneity and variable phenotypic expression of SUD genotypes. We used data from families recruited into six contemporaneous studies of children and adults to derive candidate SUD phenotypes using principle factors factor analysis with varimax rotation. We previously found evidence of two SUD phenotypes in offspring: a psychopathology dimension and a cognitive impairment dimension. We found evidence for one SUD-related phenotype in adults that we term Psychopathology and Cognitive Impairment. Parental factor scores significantly predicted both offspring phenotypes, as well as parental SUD (OR=1.41,p<0.001) and offspring SUD (mother’s phenotype: OR=1.34,p=0.04; father’s phenotype: OR=1.33,p=0.01). Offspring phenotype predicted offspring SUD (psychopathology phenotype: OR=2.96,p<0.001; cognitive impairment: OR=1.33,p=0.04); in offspring, baseline psychopathology predicted SUD at follow-up assessments (OR=1.55,p=0.01). Results suggest that these candidate SUD phenotypes may be useful for genetic studies of SUD. PMID:17766060

  16. Co-clustering phenome-genome for phenotype classification and disease gene discovery.

    PubMed

    Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui

    2012-10-01

    Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype-gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype-gene association matrix under the prior knowledge from phenotype similarity network and protein-protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype-gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein-protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways.

  17. 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.

  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. Non-focal neurological symptoms associated with classical presentations of transient ischaemic attack: qualitative analysis of interviews with patients.

    PubMed

    Kirkpatrick, Susan; Locock, Louise; Giles, Matthew F; Lasserson, Daniel S

    2013-01-01

    Improving the recognition of transient ischaemic attack (TIA) at initial healthcare contact is essential as urgent specialist assessment and treatment reduces stroke risk. Accurate TIA detection could be achieved with clinical prediction rules but none have been validated in primary care. An alternative approach using qualitative analysis of patients' experiences of TIA may identify novel features of the TIA phenotype that are not detected routinely, as such techniques have revealed novel early features of other important conditions such as meningococcaemia. We sought to determine whether the patient's experience of TIA would reveal additional deficits that can be tested prospectively in cohort studies to determine their additional diagnostic and prognostic utility at the first healthcare contact. Qualitative semi-structured interviews with 25 patients who had experienced definite TIA as determined by a stroke specialist; framework analysis to map symptoms and key words or descriptive phrases used against each individual, with close attention to the detail of the language used. All interview transcripts were reviewed by a specialist clinician with experience in TIA/minor stroke. Patients described non-focal symptoms consistent with higher function deficits in spatial perception and awareness of deficit, as well as feelings of disconnection with their immediate surroundings. Of the classical features, weakness and speech disturbance were described in ways that did not meet the readily recognisable phenotype. Analysis of patients' narrative accounts reveals a set of overlooked features of the experience of TIA which may provide additional diagnostic utility so that providers of first contact healthcare can recognise TIA more easily. Future research is required in a prospective cohort of patients presenting with transient neurological symptoms to determine how frequent these features are, what they add to diagnostic information and whether they can refine measures to

  20. 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

  1. Phenomenology of COPD: interpreting phenotypes with the ECLIPSE study.

    PubMed

    Papi, Alberto; Magnoni, Maria Sandra; Muzzio, Carmelo Caio; Benso, Gianmarco; Rizzi, Andrea

    2016-10-14

    The Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE) study was a large 3-year observational multicentre international study aimed at defining COPD phenotypes and identifying biomarkers and/or genetic parameters that help to predict disease progression. The study has contributed to a better understanding of COPD heterogeneity, with the characterization of clinically important subtypes/phenotypes of patients, such as the frequent exacerbators or patient with persistent systemic inflammation, who may have different prognosis or treatment requirements. Because of the big amount of information that is starting to be produced from metabolomic, proteomic and genomic approaches, one of the biggest challenges is the integration of data in a biological prospective such as clinical prognosis and response to medicinal products. In this article we highlight some of the progress in phenotyping the heterogeneity of the disease that have been made thanks to the analyses of this longitudinal study.

  2. 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.

  3. Finding our way through phenotypes.

    PubMed

    Deans, Andrew R; Lewis, Suzanna E; Huala, Eva; Anzaldo, Salvatore S; Ashburner, Michael; Balhoff, James P; Blackburn, David C; Blake, Judith A; Burleigh, J Gordon; Chanet, Bruno; Cooper, Laurel D; Courtot, Mélanie; Csösz, Sándor; Cui, Hong; Dahdul, Wasila; Das, Sandip; Dececchi, T Alexander; Dettai, Agnes; Diogo, Rui; Druzinsky, Robert E; Dumontier, Michel; Franz, Nico M; Friedrich, Frank; Gkoutos, George V; Haendel, Melissa; Harmon, Luke J; Hayamizu, Terry F; He, Yongqun; Hines, Heather M; Ibrahim, Nizar; Jackson, Laura M; Jaiswal, Pankaj; James-Zorn, Christina; Köhler, Sebastian; Lecointre, Guillaume; Lapp, Hilmar; Lawrence, Carolyn J; Le Novère, Nicolas; Lundberg, John G; Macklin, James; Mast, Austin R; Midford, Peter E; Mikó, István; Mungall, Christopher J; Oellrich, Anika; Osumi-Sutherland, David; Parkinson, Helen; Ramírez, Martín J; Richter, Stefan; Robinson, Peter N; Ruttenberg, Alan; Schulz, Katja S; Segerdell, Erik; Seltmann, Katja C; Sharkey, Michael J; Smith, Aaron D; Smith, Barry; Specht, Chelsea D; Squires, R Burke; Thacker, Robert W; Thessen, Anne; Fernandez-Triana, Jose; Vihinen, Mauno; Vize, Peter D; Vogt, Lars; Wall, Christine E; Walls, Ramona L; Westerfeld, Monte; Wharton, Robert A; Wirkner, Christian S; Woolley, James B; Yoder, Matthew J; Zorn, Aaron M; Mabee, Paula

    2015-01-01

    Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.

  4. Finding Our Way through Phenotypes

    PubMed Central

    Deans, Andrew R.; Lewis, Suzanna E.; Huala, Eva; Anzaldo, Salvatore S.; Ashburner, Michael; Balhoff, James P.; Blackburn, David C.; Blake, Judith A.; Burleigh, J. Gordon; Chanet, Bruno; Cooper, Laurel D.; Courtot, Mélanie; Csösz, Sándor; Cui, Hong; Dahdul, Wasila; Das, Sandip; Dececchi, T. Alexander; Dettai, Agnes; Diogo, Rui; Druzinsky, Robert E.; Dumontier, Michel; Franz, Nico M.; Friedrich, Frank; Gkoutos, George V.; Haendel, Melissa; Harmon, Luke J.; Hayamizu, Terry F.; He, Yongqun; Hines, Heather M.; Ibrahim, Nizar; Jackson, Laura M.; Jaiswal, Pankaj; James-Zorn, Christina; Köhler, Sebastian; Lecointre, Guillaume; Lapp, Hilmar; Lawrence, Carolyn J.; Le Novère, Nicolas; Lundberg, John G.; Macklin, James; Mast, Austin R.; Midford, Peter E.; Mikó, István; Mungall, Christopher J.; Oellrich, Anika; Osumi-Sutherland, David; Parkinson, Helen; Ramírez, Martín J.; Richter, Stefan; Robinson, Peter N.; Ruttenberg, Alan; Schulz, Katja S.; Segerdell, Erik; Seltmann, Katja C.; Sharkey, Michael J.; Smith, Aaron D.; Smith, Barry; Specht, Chelsea D.; Squires, R. Burke; Thacker, Robert W.; Thessen, Anne; Fernandez-Triana, Jose; Vihinen, Mauno; Vize, Peter D.; Vogt, Lars; Wall, Christine E.; Walls, Ramona L.; Westerfeld, Monte; Wharton, Robert A.; Wirkner, Christian S.; Woolley, James B.; Yoder, Matthew J.; Zorn, Aaron M.; Mabee, Paula

    2015-01-01

    Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility. PMID:25562316

  5. 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.

  6. Phenotypic variation explains food web structural patterns.

    PubMed

    Gibert, Jean P; DeLong, John P

    2017-10-02

    Food webs (i.e., networks of species and their feeding interactions) share multiple structural features across ecosystems. The factors explaining such similarities are still debated, and the role played by most organismal traits and their intraspecific variation is unknown. Here, we assess how variation in traits controlling predator-prey interactions (e.g., body size) affects food web structure. We show that larger phenotypic variation increases connectivity among predators and their prey as well as total food intake rate. For predators able to eat only a few species (i.e., specialists), low phenotypic variation maximizes intake rates, while the opposite is true for consumers with broader diets (i.e., generalists). We also show that variation sets predator trophic level by determining interaction strengths with prey at different trophic levels. Merging these results, we make two general predictions about the structure of food webs: (i) trophic level should increase with predator connectivity, and (ii) interaction strengths should decrease with prey trophic level. We confirm these predictions empirically using a global dataset of well-resolved food webs. Our results provide understanding of the processes structuring food webs that include functional traits and their naturally occurring variation. Published under the PNAS license.

  7. Situating methodology within qualitative research.

    PubMed

    Kramer-Kile, Marnie L

    2012-01-01

    Qualitative nurse researchers are required to make deliberate and sometimes complex methodological decisions about their work. Methodology in qualitative research is a comprehensive approach in which theory (ideas) and method (doing) are brought into close alignment. It can be difficult, at times, to understand the concept of methodology. The purpose of this research column is to: (1) define qualitative methodology; (2) illuminate the relationship between epistemology, ontology and methodology; (3) explicate the connection between theory and method in qualitative research design; and 4) highlight relevant examples of methodological decisions made within cardiovascular nursing research. Although there is no "one set way" to do qualitative research, all qualitative researchers should account for the choices they make throughout the research process and articulate their methodological decision-making along the way.

  8. 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.