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Selected AbstractsA novel and sensitive test for rapid determination of water toxicityENVIRONMENTAL TOXICOLOGY, Issue 3 2002S. Ulitzur Abstract The performance of a novel, rapid, and sensitive test for detecting chemical toxicants in water is described in this article. The bioassay utilizes a highly sensitive variant of the luminescent bacterium Photobacterium leiognathi that allows the detection in water at levels below milligrams per liter of diverse groups of toxicants, including heavy metals, pesticides, PCBs, polycyclic aromatic hydrocarbons, and fuel traces. For most toxic agents reported in this study, the new assay was markedly more sensitive than the MicrotoxÔVibrio fischeri assay according to the bacterial bioluminescence toxicity data reported in the literature. Additional features of the new bioassay include the ability to discriminate between cationic heavy metals and organic toxicants and the option of being run at ambient temperatures (18°C,27°C), thereby enabling on-site testing with low-cost luminometers. In addition, the stability of the freeze-dried bacterial reagent preparation at ambient temperatures precludes the need for refrigeration or freezing during shipment, which contributes to further reducing overall operational costs. © 2002 Wiley Periodicals, Inc. Environ Toxicol 17: 291,296, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/tox.10060 [source] A hybrid FVM,LBM method for single and multi-fluid compressible flow problemsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 4 2010Himanshu Joshi Abstract The lattice Boltzmann method (LBM) has established itself as an alternative approach to solve the fluid flow equations. In this work we combine LBM with the conventional finite volume method (FVM), and propose a non-iterative hybrid method for the simulation of compressible flows. LBM is used to calculate the inter-cell face fluxes and FVM is used to calculate the node parameters. The hybrid method is benchmarked for several one-dimensional and two-dimensional test cases. The results obtained by the hybrid method show a steeper and more accurate shock profile as compared with the results obtained by the widely used Godunov scheme or by a representative flux vector splitting scheme. Additional features of the proposed scheme are that it can be implemented on a non-uniform grid, study of multi-fluid problems is possible, and it is easily extendable to multi-dimensions. These features have been demonstrated in this work. The proposed method is therefore robust and can possibly be applied to a variety of compressible flow situations. Copyright © 2009 John Wiley & Sons, Ltd. [source] Sea-urchin granuloma: histologic profile.JOURNAL OF CUTANEOUS PATHOLOGY, Issue 5 2001A pathologic study of 50 biopsies Background: Sea-urchin granuloma is a chronic granulomatous skin lesion caused by injury with sea-urchin spines. Frequently these lesions occur on the hands and develop several months after the initial injury. Classified as an allergic foreign-body reaction, their most common histological pattern resembles sarcoid. The purpose of this study was to evaluate the light microscopic features of biopsies from lesions clinically diagnosed of sea-urchin granolomas. Methods: We retrospectively reviewed 50 biopsy specimens corresponding to 35 patients with sea-urchin granulomas. These lesions were caused by injuries with the spines of the sea-urchin Paracentrotus lividus. Data were collected between 1990 and 1999 from patients in the seashore of Galicia (NW Atlantic coast, Spain). Results: The cohort consisted of 35 patients (31 males, 4 females), with a median age of 35 years (range 14,60 years). The median duration of the disease was 7.5 months (range 2,60 months). We identified different histopathologic patterns. A granulomatous reaction was observed in 39 biopsies (78%). In 70% corresponding to 35 biopsies this granulomatous reaction was predominant. Foreign-body, sarcoidal, tuberculoid, necrobiotic and suppurative granulomas were identified. The remaining 15 biopsies (30%) showed a predominant inflammatory reaction with features of non-specific chronic inflammation or suppurative dermatitis. A panel of histopathologic features, including epidermal and dermal changes were evaluated. Presence of focal necrosis and microabscesses were common findings. In 50% of our specimens we found umbilication and/or perforation. Additional features included the presence of inclusion epidermoid cysts in four cases and squamous syringometaplasia in one case. Conclusions: Our observations suggest that sea-urchin granuloma span a wide morphologic spectrum. A granulomatous inflammatory reaction was predominant, with the foreign body and sarcoidal types the most frequent patterns. Other histopathologic patterns with non granulomatous inflammation can be noted. Some features, such as the frequency of perforation and the presence of necrobiotic granulomas have not previously been recognized in the literature. [source] An autopsy case of Fabry disease with neuropathological investigation of the pathogenesis of associated dementiaNEUROPATHOLOGY, Issue 5 2008Riki Okeda The pathogenesis of dementia associated with Fabry disease was examined neuropathologically in an autopsy case. The patient was a 47-year-old computer programmer who developed renal failure at the age of 36, necessitating peritoneal dialysis, and thereafter suffered in succession episodic pulmonary congestion, bradyacusia, heart failure, and dementia, before dying of acute myocardial infarction. MRI of the brain demonstrated leuko-araiosis. The CNS parenchyma showed widespread segmental hydropic swelling of axons in the bilateral cerebral and cerebellar deep white matter in addition to neuronal ballooning due to glycolipid storage in a few restricted nuclei and multiple tiny lacunae. Hydropic axonal swelling was also sparsely distributed in the pyramidal tract, pedunculus cerebellaris superior and brachium colliculi inferioris, but wallerian degeneration of these tracts was absent. Additional features included angiopathy of the subarachnoidal arteries due to Fabry disease, such as medial thickening resulting from glycolipid deposition in smooth muscle cells (SMCs) and adventitial fibrosis with lymphocytic infiltration, together with widespread subtotal or total replacement of medial SMCs by fibrosis, associated with prominent intimal fibrous thickening and undulation of the internal elastic membrane of medium-sized (1000,100 ,m diameter) arteries. The findings in this case suggest that axonopathic leukoencephalopathy due to multisegmental hydropic swelling of axons in the bilateral cerebral deep white matter is responsible for the dementia associated with Fabry disease, and may be caused by ischemia resulting from widespread narrowing and stiffening of medium-sized subarachnoidal arteries and progressive heart failure. [source] Partial cerebellar hypoplasia in a patient with Prader-Willi syndromeACTA PAEDIATRICA, Issue 7 2006Luigi Titomanlio Abstract We report a 3-y-old male infant with Prader-Willi syndrome (PWS) caused by a de novo interstitial deletion of 15q11-q13. Additional features included a right cerebellar hemisphere hypoplasia. The extent of deletion was determined by FISH analysis using an SNRPN PW/AS probe that maps in the PWS/AS critical region (CR) and with specific 15q BACs. We unravelled an interstitial 15q11.2-q13.1 deletion spanning about 3 Mb. Conclusion: To date only a few other PWS patients,including autopsy cases,with CNS structural anomalies have been described. Our case report adds knowledge to the issue of brain involvement in Prader-Willi syndrome. Further MRI studies of PWS patients will be helpful to clarify a correlation between PWS and brain abnormalities. [source] A branch-and-price algorithm for parallel machine scheduling with time windows and job prioritiesNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 1 2006Jonathan F. Bard Abstract This paper presents a branch-and-price algorithm for scheduling n jobs on m nonhomogeneous parallel machines with multiple time windows. An additional feature of the problem is that each job falls into one of , priority classes and may require two operations. The objective is to maximize the weighted number of jobs scheduled, where a job in a higher priority class has "infinitely" more weight or value than a job in a lower priority class. The methodology makes use of a greedy randomized adaptive search procedure (GRASP) to find feasible solutions during implicit enumeration and a two-cycle elimination heuristic when solving the pricing subproblems. Extensive computational results are presented based on data from an application involving the use of communications relay satellites. Many 100-job instances that were believed to be beyond the capability of exact methods, were solved within minutes. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006 [source] Suboptimal temperature favors reserve formation in biennial carrot (Daucus carota) plantsPHYSIOLOGIA PLANTARUM, Issue 1 2009María V. González In response to suboptimal temperatures, temperate annual plants often increase root:shoot ratios, build-up carbohydrates and display typical morphological and anatomical changes. We know less about the responses of biennials such as carrot. As a model plant, carrot has the additional feature of two functionally and morphologically distinct root parts: the taproot, which stores carbohydrate and other compounds, and the fibrous root system involved in acquisition of water and nutrients. Here, we analyze the effects of temperature (12 vs 25°C) on growth, carbohydrate accumulation and whole-plant morphology in two carrot cultivars. Our working hypothesis is that suboptimal temperature favors active formation of reserve structures, rather than passive accumulation of storage carbohydrates. In comparison with plants grown at 25°C, plants grown at 12°C had: (1) higher fibrous root:shoot ratio (13%) , (2) thicker (10,15%) and smaller (up to two- to three-fold) leaves, (3) lower leaf cuticular permeance (two- to four-fold), (4) higher taproot:shoot ratio (two-fold), (5) higher phloem:xylem ratios in taproot (two- to six-fold), (6) unchanged percentage dry matter content (%DMC) in leaves, petioles or fibrous roots and (7) higher %DMC in taproot (20%). However, %DMC of individual taproot tissues (phloem and xylem) was unaffected by temperatures and was consistently higher in the phloem (up to 30%). Therefore, the higher %DMC of whole taproots at 12°C was attributed solely to the increased development of phloem tissue. Carrot, therefore, shares many of the most conspicuous elements of temperate plant responses to low temperatures. Consistently with our hypothesis, however, carrots grown at suboptimal temperature promoted reserve structures, rather than the increase in carbohydrate concentration typical of most temperate annual species and woody perennials. [source] Using Multimember District Elections to Estimate the Sources of the Incumbency AdvantageAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 2 2009Shigeo Hirano In this article we use a novel research design that exploits unique features of multimember districts to estimate and decompose the incumbency advantage in state legislative elections. Like some existing related studies we also use repeated observations on the same candidates to account for unobserved factors that remain constant across observations. Multimember districts have the additional feature of copartisans competing for multiple seats within the same district. This allows us to identify both the direct office-holder benefits and the incumbent quality advantage over nonincumbent candidates from the same party. We find that the overall incumbency advantage is of similar magnitude as that found in previous studies. We attribute approximately half of this advantage to incumbents' quality advantage over open-seat candidates and the remainder to direct office-holder benefits. However, we also find some evidence that direct office-holder benefits are larger in competitive districts than in safe districts and in states with relatively large legislative budgets per capita. [source] European Mathematical Genetics Meeting, Heidelberg, Germany, 12th,13th April 2007ANNALS OF HUMAN GENETICS, Issue 4 2007Article first published online: 28 MAY 200 Saurabh Ghosh 11 Indian Statistical Institute, Kolkata, India High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both. In this study, we develop statistical methods to extract the contribution of a common QTL to the total correlation between the components of a bivariate phenotype. Using data on bivariate phenotypes and marker genotypes for sib-pairs, we propose a test for linkage between a common QTL and a marker locus based on the conditional cross-sib trait correlations (trait 1 of sib 1 , trait 2 of sib 2 and conversely) given the identity-by-descent sharing at the marker locus. The null hypothesis cannot be rejected unless there exists a common QTL. We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from the Collaborative Study On The Genetics Of Alcoholism project. Rémi Kazma 1 , Catherine Bonaďti-Pellié 1 , Emmanuelle Génin 12 INSERM UMR-S535 and Université Paris Sud, Villejuif, 94817, France Keywords: Gene-environment interaction, sibling recurrence risk, exposure correlation Gene-environment interactions may play important roles in complex disease susceptibility but their detection is often difficult. Here we show how gene-environment interactions can be detected by investigating the degree of familial aggregation according to the exposure of the probands. In case of gene-environment interaction, the distribution of genotypes of affected individuals, and consequently the risk in relatives, depends on their exposure. We developed a test comparing the risks in sibs according to the proband exposure. To evaluate the properties of this new test, we derived the formulas for calculating the expected risks in sibs according to the exposure of probands for various values of exposure frequency, relative risk due to exposure alone, frequencies of latent susceptibility genotypes, genetic relative risks and interaction coefficients. We find that the ratio of risks when the proband is exposed and not exposed is a good indicator of the interaction effect. We evaluate the power of the test for various sample sizes of affected individuals. We conclude that this test is valuable for diseases with moderate familial aggregation, only when the role of the exposure has been clearly evidenced. Since a correlation for exposure among sibs might lead to a difference in risks among sibs in the different proband exposure strata, we also add an exposure correlation coefficient in the model. Interestingly, we find that when this correlation is correctly accounted for, the power of the test is not decreased and might even be significantly increased. Andrea Callegaro 1 , Hans J.C. Van Houwelingen 1 , Jeanine Houwing-Duistermaat 13 Dept. of Medical Statistics and Bioinformatics, Leiden University Medical Center, The Netherlands Keywords: Survival analysis, age at onset, score test, linkage analysis Non parametric linkage (NPL) analysis compares the identical by descent (IBD) sharing in sibling pairs to the expected IBD sharing under the hypothesis of no linkage. Often information is available on the marginal cumulative hazards (for example breast cancer incidence curves). Our aim is to extend the NPL methods by taking into account the age at onset of selected sibling pairs using these known marginal hazards. Li and Zhong (2002) proposed a (retrospective) likelihood ratio test based on an additive frailty model for genetic linkage analysis. From their model we derive a score statistic for selected samples which turns out to be a weighed NPL method. The weights depend on the marginal cumulative hazards and on the frailty parameter. A second approach is based on a simple gamma shared frailty model. Here, we simply test whether the score function of the frailty parameter depends on the excess IBD. We compare the performance of these methods using simulated data. Céline Bellenguez 1 , Carole Ober 2 , Catherine Bourgain 14 INSERM U535 and University Paris Sud, Villejuif, France 5 Department of Human Genetics, The University of Chicago, USA Keywords: Linkage analysis, linkage disequilibrium, high density SNP data Compared with microsatellite markers, high density SNP maps should be more informative for linkage analyses. However, because they are much closer, SNPs present important linkage disequilibrium (LD), which biases classical nonparametric multipoint analyses. This problem is even stronger in population isolates where LD extends over larger regions with a more stochastic pattern. We investigate the issue of linkage analysis with a 500K SNP map in a large and inbred 1840-member Hutterite pedigree, phenotyped for asthma. Using an efficient pedigree breaking strategy, we first identified linked regions with a 5cM microsatellite map, on which we focused to evaluate the SNP map. The only method that models LD in the NPL analysis is limited in both the pedigree size and the number of markers (Abecasis and Wigginton, 2005) and therefore could not be used. Instead, we studied methods that identify sets of SNPs with maximum linkage information content in our pedigree and no LD-driven bias. Both algorithms that directly remove pairs of SNPs in high LD and clustering methods were evaluated. Null simulations were performed to control that Zlr calculated with the SNP sets were not falsely inflated. Preliminary results suggest that although LD is strong in such populations, linkage information content slightly better than that of microsatellite maps can be extracted from dense SNP maps, provided that a careful marker selection is conducted. In particular, we show that the specific LD pattern requires considering LD between a wide range of marker pairs rather than only in predefined blocks. Peter Van Loo 1,2,3 , Stein Aerts 1,2 , Diether Lambrechts 4,5 , Bernard Thienpont 2 , Sunit Maity 4,5 , Bert Coessens 3 , Frederik De Smet 4,5 , Leon-Charles Tranchevent 3 , Bart De Moor 2 , Koen Devriendt 3 , Peter Marynen 1,2 , Bassem Hassan 1,2 , Peter Carmeliet 4,5 , Yves Moreau 36 Department of Molecular and Developmental Genetics, VIB, Belgium 7 Department of Human Genetics, University of Leuven, Belgium 8 Bioinformatics group, Department of Electrical Engineering, University of Leuven, Belgium 9 Department of Transgene Technology and Gene Therapy, VIB, Belgium 10 Center for Transgene Technology and Gene Therapy, University of Leuven, Belgium Keywords: Bioinformatics, gene prioritization, data fusion The identification of genes involved in health and disease remains a formidable challenge. Here, we describe a novel bioinformatics method to prioritize candidate genes underlying pathways or diseases, based on their similarity to genes known to be involved in these processes. It is freely accessible as an interactive software tool, ENDEAVOUR, at http://www.esat.kuleuven.be/endeavour. Unlike previous methods, ENDEAVOUR generates distinct prioritizations from multiple heterogeneous data sources, which are then integrated, or fused, into one global ranking using order statistics. ENDEAVOUR prioritizes candidate genes in a three-step process. First, information about a disease or pathway is gathered from a set of known "training" genes by consulting multiple data sources. Next, the candidate genes are ranked based on similarity with the training properties obtained in the first step, resulting in one prioritized list for each data source. Finally, ENDEAVOUR fuses each of these rankings into a single global ranking, providing an overall prioritization of the candidate genes. Validation of ENDEAVOUR revealed it was able to efficiently prioritize 627 genes in disease data sets and 76 genes in biological pathway sets, identify candidates of 16 mono- or polygenic diseases, and discover regulatory genes of myeloid differentiation. Furthermore, the approach identified YPEL1 as a novel gene involved in craniofacial development from a 2-Mb chromosomal region, deleted in some patients with DiGeorge-like birth defects. Finally, we are currently evaluating a pipeline combining array-CGH, ENDEAVOUR and in vivo validation in zebrafish to identify novel genes involved in congenital heart defects. Mark Broom 1 , Graeme Ruxton 2 , Rebecca Kilner 311 Mathematics Dept., University of Sussex, UK 12 Division of Environmental and Evolutionary Biology, University of Glasgow, UK 13 Department of Zoology, University of Cambridge, UK Keywords: Evolutionarily stable strategy, parasitism, asymmetric game Brood parasites chicks vary in the harm that they do to their companions in the nest. In this presentation we use game-theoretic methods to model this variation. Our model considers hosts which potentially abandon single nestlings and instead choose to re-allocate their reproductive effort to future breeding, irrespective of whether the abandoned chick is the host's young or a brood parasite's. The parasite chick must decide whether or not to kill host young by balancing the benefits from reduced competition in the nest against the risk of desertion by host parents. The model predicts that three different types of evolutionarily stable strategies can exist. (1) Hosts routinely rear depleted broods, the brood parasite always kills host young and the host never then abandons the nest. (2) When adult survival after deserting single offspring is very high, hosts always abandon broods of a single nestling and the parasite never kills host offspring, effectively holding them as hostages to prevent nest desertion. (3) Intermediate strategies, in which parasites sometimes kill their nest-mates and host parents sometimes desert nests that contain only a single chick, can also be evolutionarily stable. We provide quantitative descriptions of how the values given to ecological and behavioral parameters of the host-parasite system influence the likelihood of each strategy and compare our results with real host-brood parasite associations in nature. Martin Harrison 114 Mathematics Dept, University of Sussex, UK Keywords: Brood parasitism, games, host, parasite The interaction between hosts and parasites in bird populations has been studied extensively. Game theoretical methods have been used to model this interaction previously, but this has not been studied extensively taking into account the sequential nature of this game. We consider a model allowing the host and parasite to make a number of decisions, which depend on a number of natural factors. The host lays an egg, a parasite bird will arrive at the nest with a certain probability and then chooses to destroy a number of the host eggs and lay one of it's own. With some destruction occurring, either natural or through the actions of the parasite, the host chooses to continue, eject an egg (hoping to eject the parasite) or abandon the nest. Once the eggs have hatched the game then falls to the parasite chick versus the host. The chick chooses to destroy or eject a number of eggs. The final decision is made by the host, choosing whether to raise or abandon the chicks that are in the nest. We consider various natural parameters and probabilities which influence these decisions. We then use this model to look at real-world situations of the interactions of the Reed Warbler and two different parasites, the Common Cuckoo and the Brown-Headed Cowbird. These two parasites have different methods in the way that they parasitize the nests of their hosts. The hosts in turn have a different reaction to these parasites. Arne Jochens 1 , Amke Caliebe 2 , Uwe Roesler 1 , Michael Krawczak 215 Mathematical Seminar, University of Kiel, Germany 16 Institute of Medical Informatics and Statistics, University of Kiel, Germany Keywords: Stepwise mutation model, microsatellite, recursion equation, temporal behaviour We consider the stepwise mutation model which occurs, e.g., in microsatellite loci. Let X(t,i) denote the allelic state of individual i at time t. We compute expectation, variance and covariance of X(t,i), i=1,,,N, and provide a recursion equation for P(X(t,i)=z). Because the variance of X(t,i) goes to infinity as t grows, for the description of the temporal behaviour, we regard the scaled process X(t,i)-X(t,1). The results furnish a better understanding of the behaviour of the stepwise mutation model and may in future be used to derive tests for neutrality under this model. Paul O'Reilly 1 , Ewan Birney 2 , David Balding 117 Statistical Genetics, Department of Epidemiology and Public Health, Imperial, College London, UK 18 European Bioinformatics Institute, EMBL, Cambridge, UK Keywords: Positive selection, Recombination rate, LD, Genome-wide, Natural Selection In recent years efforts to develop population genetics methods that estimate rates of recombination and levels of natural selection in the human genome have intensified. However, since the two processes have an intimately related impact on genetic variation their inference is vulnerable to confounding. Genomic regions subject to recent selection are likely to have a relatively recent common ancestor and consequently less opportunity for historical recombinations that are detectable in contemporary populations. Here we show that selection can reduce the population-based recombination rate estimate substantially. In genome-wide studies for detecting selection we observe a tendency to highlight loci that are subject to low levels of recombination. We find that the outlier approach commonly adopted in such studies may have low power unless variable recombination is accounted for. We introduce a new genome-wide method for detecting selection that exploits the sensitivity to recent selection of methods for estimating recombination rates, while accounting for variable recombination using pedigree data. Through simulations we demonstrate the high power of the Ped/Pop approach to discriminate between neutral and adaptive evolution, particularly in the context of choosing outliers from a genome-wide distribution. Although methods have been developed showing good power to detect selection ,in action', the corresponding window of opportunity is small. In contrast, the power of the Ped/Pop method is maintained for many generations after the fixation of an advantageous variant Sarah Griffiths 1 , Frank Dudbridge 120 MRC Biostatistics Unit, Cambridge, UK Keywords: Genetic association, multimarker tag, haplotype, likelihood analysis In association studies it is generally too expensive to genotype all variants in all subjects. We can exploit linkage disequilibrium between SNPs to select a subset that captures the variation in a training data set obtained either through direct resequencing or a public resource such as the HapMap. These ,tag SNPs' are then genotyped in the whole sample. Multimarker tagging is a more aggressive adaptation of pairwise tagging that allows for combinations of two or more tag SNPs to predict an untyped SNP. Here we describe a new method for directly testing the association of an untyped SNP using a multimarker tag. Previously, other investigators have suggested testing a specific tag haplotype, or performing a weighted analysis using weights derived from the training data. However these approaches do not properly account for the imperfect correlation between the tag haplotype and the untyped SNP. Here we describe a straightforward approach to testing untyped SNPs using a missing-data likelihood analysis, including the tag markers as nuisance parameters. The training data is stacked on top of the main body of genotype data so there is information on how the tag markers predict the genotype of the untyped SNP. The uncertainty in this prediction is automatically taken into account in the likelihood analysis. This approach yields more power and also a more accurate prediction of the odds ratio of the untyped SNP. Anke Schulz 1 , Christine Fischer 2 , Jenny Chang-Claude 1 , Lars Beckmann 121 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany 22 Institute of Human Genetics, University of Heidelberg, Germany Keywords: Haplotype, haplotype sharing, entropy, Mantel statistics, marker selection We previously introduced a new method to map genes involved in complex diseases, using haplotype sharing-based Mantel statistics to correlate genetic and phenotypic similarity. Although the Mantel statistic is powerful in narrowing down candidate regions, the precise localization of a gene is hampered in genomic regions where linkage disequilibrium is so high that neighboring markers are found to be significant at similar magnitude and we are not able to discriminate between them. Here, we present a new approach to localize susceptibility genes by combining haplotype sharing-based Mantel statistics with an iterative entropy-based marker selection algorithm. For each marker at which the Mantel statistic is evaluated, the algorithm selects a subset of surrounding markers. The subset is chosen to maximize multilocus linkage disequilibrium, which is measured by the normalized entropy difference introduced by Nothnagel et al. (2002). We evaluated the algorithm with respect to type I error and power. Its ability to localize the disease variant was compared to the localization (i) without marker selection and (ii) considering haplotype block structure. Case-control samples were simulated from a set of 18 haplotypes, consisting of 15 SNPs in two haplotype blocks. The new algorithm gave correct type I error and yielded similar power to detect the disease locus compared to the alternative approaches. The neighboring markers were clearly less often significant than the causal locus, and also less often significant compared to the alternative approaches. Thus the new algorithm improved the precision of the localization of susceptibility genes. Mark M. Iles 123 Section of Epidemiology and Biostatistics, LIMM, University of Leeds, UK Keywords: tSNP, tagging, association, HapMap Tagging SNPs (tSNPs) are commonly used to capture genetic diversity cost-effectively. However, it is important that the efficacy of tSNPs is correctly estimated, otherwise coverage may be insufficient. If the pilot sample from which tSNPs are chosen is too small or the initial marker map too sparse, tSNP efficacy may be overestimated. An existing estimation method based on bootstrapping goes some way to correct for insufficient sample size and overfitting, but does not completely solve the problem. We describe a novel method, based on exclusion of haplotypes, that improves on the bootstrap approach. Using simulated data, the extent of the sample size problem is investigated and the performance of the bootstrap and the novel method are compared. We incorporate an existing method adjusting for marker density by ,SNP-dropping'. We find that insufficient sample size can cause large overestimates in tSNP efficacy, even with as many as 100 individuals, and the problem worsens as the region studied increases in size. Both the bootstrap and novel method correct much of this overestimate, with our novel method consistently outperforming the bootstrap method. We conclude that a combination of insufficient sample size and overfitting may lead to overestimation of tSNP efficacy and underpowering of studies based on tSNPs. Our novel approach corrects for much of this bias and is superior to the previous method. Sample sizes larger than previously suggested may still be required for accurate estimation of tSNP efficacy. This has obvious ramifications for the selection of tSNPs from HapMap data. Claudio Verzilli 1 , Juliet Chapman 1 , Aroon Hingorani 2 , Juan Pablo-Casas 1 , Tina Shah 2 , Liam Smeeth 1 , John Whittaker 124 Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, UK 25 Division of Medicine, University College London, UK Keywords: Meta-analysis, Genetic association studies We present a Bayesian hierarchical model for the meta-analysis of candidate gene studies with a continuous outcome. Such studies often report results from association tests for different, possibly study-specific and non-overlapping markers (typically SNPs) in the same genetic region. Meta analyses of the results at each marker in isolation are seldom appropriate as they ignore the correlation that may exist between markers due to linkage disequlibrium (LD) and cannot assess the relative importance of variants at each marker. Also such marker-wise meta analyses are restricted to only those studies that have typed the marker in question, with a potential loss of power. A better strategy is one which incorporates information about the LD between markers so that any combined estimate of the effect of each variant is corrected for the effect of other variants, as in multiple regression. Here we develop a Bayesian hierarchical linear regression that models the observed genotype group means and uses pairwise LD measurements between markers as prior information to make posterior inference on adjusted effects. The approach is applied to the meta analysis of 24 studies assessing the effect of 7 variants in the C-reactive protein (CRP) gene region on plasma CRP levels, an inflammatory biomarker shown in observational studies to be positively associated with cardiovascular disease. Cathryn M. Lewis 1 , Christopher G. Mathew 1 , Theresa M. Marteau 226 Dept. of Medical and Molecular Genetics, King's College London, UK 27 Department of Psychology, King's College London, UK Keywords: Risk, genetics, CARD15, smoking, model Recently progress has been made in identifying mutations that confer susceptibility to complex diseases, with the potential to use these mutations in determining disease risk. We developed methods to estimate disease risk based on genotype relative risks (for a gene G), exposure to an environmental factor (E), and family history (with recurrence risk ,R for a relative of type R). ,R must be partitioned into the risk due to G (which is modelled independently) and the residual risk. The risk model was then applied to Crohn's disease (CD), a severe gastrointestinal disease for which smoking increases disease risk approximately 2-fold, and mutations in CARD15 confer increased risks of 2.25 (for carriers of a single mutation) and 9.3 (for carriers of two mutations). CARD15 accounts for only a small proportion of the genetic component of CD, with a gene-specific ,S, CARD15 of 1.16, from a total sibling relative risk of ,S= 27. CD risks were estimated for high-risk individuals who are siblings of a CD case, and who also smoke. The CD risk to such individuals who carry two CARD15 mutations is approximately 0.34, and for those carrying a single CARD15 mutation the risk is 0.08, compared to a population prevalence of approximately 0.001. These results imply that complex disease genes may be valuable in estimating with greater precision than has hitherto been possible disease risks in specific, easily identified subgroups of the population with a view to prevention. Yurii Aulchenko 128 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Compression, information, bzip2, genome-wide SNP data, statistical genetics With advances in molecular technology, studies accessing millions of genetic polymorphisms in thousands of study subjects will soon become common. Such studies generate large amounts of data, whose effective storage and management is a challenge to the modern statistical genetics. Standard file compression utilities, such as Zip, Gzip and Bzip2, may be helpful to minimise the storage requirements. Less obvious is the fact that the data compression techniques may be also used in the analysis of genetic data. It is known that the efficiency of a particular compression algorithm depends on the probability structure of the data. In this work, we compared different standard and customised tools using the data from human HapMap project. Secondly, we investigate the potential uses of data compression techniques for the analysis of linkage, association and linkage disequilibrium Suzanne Leal 1 , Bingshan Li 129 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, USA Keywords: Consanguineous pedigrees, missing genotype data Missing genotype data can increase false-positive evidence for linkage when either parametric or nonparametric analysis is carried out ignoring intermarker linkage disequilibrium (LD). Previously it was demonstrated by Huang et al (2005) that no bias occurs in this situation for affected sib-pairs with unrelated parents when either both parents are genotyped or genotype data is available for two additional unaffected siblings when parental genotypes are missing. However, this is not the case for consanguineous pedigrees, where missing genotype data for any pedigree member within a consanguinity loop can increase false-positive evidence of linkage. The false-positive evidence for linkage is further increased when cryptic consanguinity is present. The amount of false-positive evidence for linkage is highly dependent on which family members are genotyped. When parental genotype data is available, the false-positive evidence for linkage is usually not as strong as when parental genotype data is unavailable. Which family members will aid in the reduction of false-positive evidence of linkage is highly dependent on which other family members are genotyped. For a pedigree with an affected proband whose first-cousin parents have been genotyped, further reduction in the false-positive evidence of linkage can be obtained by including genotype data from additional affected siblings of the proband or genotype data from the proband's sibling-grandparents. When parental genotypes are not available, false-positive evidence for linkage can be reduced by including in the analysis genotype data from either unaffected siblings of the proband or the proband's married-in-grandparents. Najaf Amin 1 , Yurii Aulchenko 130 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Genomic Control, pedigree structure, quantitative traits The Genomic Control (GC) method was originally developed to control for population stratification and cryptic relatedness in association studies. This method assumes that the effect of population substructure on the test statistics is essentially constant across the genome, and therefore unassociated markers can be used to estimate the effect of confounding onto the test statistic. The properties of GC method were extensively investigated for different stratification scenarios, and compared to alternative methods, such as the transmission-disequilibrium test. The potential of this method to correct not for occasional cryptic relations, but for regular pedigree structure, however, was not investigated before. In this work we investigate the potential of the GC method for pedigree-based association analysis of quantitative traits. The power and type one error of the method was compared to standard methods, such as the measured genotype (MG) approach and quantitative trait transmission-disequilibrium test. In human pedigrees, with trait heritability varying from 30 to 80%, the power of MG and GC approach was always higher than that of TDT. GC had correct type 1 error and its power was close to that of MG under moderate heritability (30%), but decreased with higher heritability. William Astle 1 , Chris Holmes 2 , David Balding 131 Department of Epidemiology and Public Health, Imperial College London, UK 32 Department of Statistics, University of Oxford, UK Keywords: Population structure, association studies, genetic epidemiology, statistical genetics In the analysis of population association studies, Genomic Control (Devlin & Roeder, 1999) (GC) adjusts the Armitage test statistic to correct the type I error for the effects of population substructure, but its power is often sub-optimal. Turbo Genomic Control (TGC) generalises GC to incorporate co-variation of relatedness and phenotype, retaining control over type I error while improving power. TGC is similar to the method of Yu et al. (2006), but we extend it to binary (case-control) in addition to quantitative phenotypes, we implement improved estimation of relatedness coefficients, and we derive an explicit statistic that generalizes the Armitage test statistic and is fast to compute. TGC also has similarities to EIGENSTRAT (Price et al., 2006) which is a new method based on principle components analysis. The problems of population structure(Clayton et al., 2005) and cryptic relatedness (Voight & Pritchard, 2005) are essentially the same: if patterns of shared ancestry differ between cases and controls, whether distant (coancestry) or recent (cryptic relatedness), false positives can arise and power can be diminished. With large numbers of widely-spaced genetic markers, coancestry can now be measured accurately for each pair of individuals via patterns of allele-sharing. Instead of modelling subpopulations, we work instead with a coancestry coefficient for each pair of individuals in the study. We explain the relationships between TGC, GC and EIGENSTRAT. We present simulation studies and real data analyses to illustrate the power advantage of TGC in a range of scenarios incorporating both substructure and cryptic relatedness. References Clayton, D. G.et al. (2005) Population structure, differential bias and genomic control in a large-scale case-control association study. Nature Genetics37(11) November 2005. Devlin, B. & Roeder, K. (1999) Genomic control for association studies. Biometics55(4) December 1999. Price, A. L.et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics38(8) (August 2006). Voight, B. J. & Pritchard, J. K. (2005) Confounding from cryptic relatedness in case-control association studies. Public Library of Science Genetics1(3) September 2005. Yu, J.et al. (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics38(2) February 2006. Hervé Perdry 1 , Marie-Claude Babron 1 , Françoise Clerget-Darpoux 133 INSERM U535 and Univ. Paris Sud, UMR-S 535, Villejuif, France Keywords: Modifier genes, case-parents trios, ordered transmission disequilibrium test A modifying locus is a polymorphic locus, distinct from the disease locus, which leads to differences in the disease phenotype, either by modifying the penetrance of the disease allele, or by modifying the expression of the disease. The effect of such a locus is a clinical heterogeneity that can be reflected by the values of an appropriate covariate, such as the age of onset, or the severity of the disease. We designed the Ordered Transmission Disequilibrium Test (OTDT) to test for a relation between the clinical heterogeneity, expressed by the covariate, and marker genotypes of a candidate gene. The method applies to trio families with one affected child and his parents. Each family member is genotyped at a bi-allelic marker M of a candidate gene. To each of the families is associated a covariate value; the families are ordered on the values of this covariate. As the TDT (Spielman et al. 1993), the OTDT is based on the observation of the transmission rate T of a given allele at M. The OTDT aims to find a critical value of the covariate which separates the sample of families in two subsamples in which the transmission rates are significantly different. We investigate the power of the method by simulations under various genetic models and covariate distributions. Acknowledgments H Perdry is funded by ARSEP. Pascal Croiseau 1 , Heather Cordell 2 , Emmanuelle Génin 134 INSERM U535 and University Paris Sud, UMR-S535, Villejuif, France 35 Institute of Human Genetics, Newcastle University, UK Keywords: Association, missing data, conditionnal logistic regression Missing data is an important problem in association studies. Several methods used to test for association need that individuals be genotyped at the full set of markers. Individuals with missing data need to be excluded from the analysis. This could involve an important decrease in sample size and a loss of information. If the disease susceptibility locus (DSL) is poorly typed, it is also possible that a marker in linkage disequilibrium gives a stronger association signal than the DSL. One may then falsely conclude that the marker is more likely to be the DSL. We recently developed a Multiple Imputation method to infer missing data on case-parent trios Starting from the observed data, a few number of complete data sets are generated by Markov-Chain Monte Carlo approach. These complete datasets are analysed using standard statistical package and the results are combined as described in Little & Rubin (2002). Here we report the results of simulations performed to examine, for different patterns of missing data, how often the true DSL gives the highest association score among different loci in LD. We found that multiple imputation usually correctly detect the DSL site even if the percentage of missing data is high. This is not the case for the naďve approach that consists in discarding trios with missing data. In conclusion, Multiple imputation presents the advantage of being easy to use and flexible and is therefore a promising tool in the search for DSL involved in complex diseases. Salma Kotti 1 , Heike Bickeböller 2 , Françoise Clerget-Darpoux 136 University Paris Sud, UMR-S535, Villejuif, France 37 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany Keywords: Genotype relative risk, internal controls, Family based analyses Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRRs. We will analytically derive the GRR estimators for the 1:1 and 1:3 matching and will present the results at the meeting. Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRR. We will analytically derive the GRR estimator for the 1:1 and 1:3 matching and will present the results at the meeting. Luigi Palla 1 , David Siegmund 239 Department of Mathematics,Free University Amsterdam, The Netherlands 40 Department of Statistics, Stanford University, California, USA Keywords: TDT, assortative mating, inbreeding, statistical power A substantial amount of Assortative Mating (AM) is often recorded on physical and psychological, dichotomous as well as quantitative traits that are supposed to have a multifactorial genetic component. In particular AM has the effect of increasing the genetic variance, even more than inbreeding because it acts across loci beside within loci, when the trait has a multifactorial origin. Under the assumption of a polygenic model for AM dating back to Wright (1921) and refined by Crow and Felsenstein (1968,1982), the effect of assortative mating on the power to detect genetic association in the Transmission Disequilibrium Test (TDT) is explored as parameters, such as the effective number of genes and the allelic frequency vary. The power is reflected by the non centrality parameter of the TDT and is expressed as a function of the number of trios, the relative risk of the heterozygous genotype and the allele frequency (Siegmund and Yakir, 2007). The noncentrality parameter of the relevant score statistic is updated considering the effect of AM which is expressed in terms of an ,effective' inbreeding coefficient. In particular, for dichotomous traits it is apparent that the higher the number of genes involved in the trait, the lower the loss in power due to AM. Finally an attempt is made to extend this relation to the Q-TDT (Rabinowitz, 1997), which involves considering the effect of AM also on the phenotypic variance of the trait of interest, under the assumption that AM affects only its additive genetic component. References Crow, & Felsenstein, (1968). The effect of assortative mating on the genetic composition of a population. Eugen.Quart.15, 87,97. Rabinowitz,, 1997. A Transmission Disequilibrium Test for Quantitative Trait Loci. Human Heredity47, 342,350. Siegmund, & Yakir, (2007) Statistics of gene mapping, Springer. Wright, (1921). System of mating.III. Assortative mating based on somatic resemblance. Genetics6, 144,161. Jérémie Nsengimana 1 , Ben D Brown 2 , Alistair S Hall 2 , Jenny H Barrett 141 Leeds Institute of Molecular Medicine, University of Leeds, UK 42 Leeds Institute for Genetics, Health and Therapeutics, University of Leeds, UK Keywords: Inflammatory genes, haplotype, coronary artery disease Genetic Risk of Acute Coronary Events (GRACE) is an initiative to collect cases of coronary artery disease (CAD) and their unaffected siblings in the UK and to use them to map genetic variants increasing disease risk. The aim of the present study was to test the association between CAD and 51 single nucleotide polymorphisms (SNPs) and their haplotypes from 35 inflammatory genes. Genotype data were available for 1154 persons affected before age 66 (including 48% before age 50) and their 1545 unaffected siblings (891 discordant families). Each SNP was tested for association to CAD, and haplotypes within genes or gene clusters were tested using FBAT (Rabinowitz & Laird, 2000). For the most significant results, genetic effect size was estimated using conditional logistic regression (CLR) within STATA adjusting for other risk factors. Haplotypes were assigned using HAPLORE (Zhang et al., 2005), which considers all parental mating types consistent with offspring genotypes and assigns them a probability of occurence. This probability was used in CLR to weight the haplotypes. In the single SNP analysis, several SNPs showed some evidence for association, including one SNP in the interleukin-1A gene. Analysing haplotypes in the interleukin-1 gene cluster, a common 3-SNP haplotype was found to increase the risk of CAD (P = 0.009). In an additive genetic model adjusting for covariates the odds ratio (OR) for this haplotype is 1.56 (95% CI: 1.16-2.10, p = 0.004) for early-onset CAD (before age 50). This study illustrates the utility of haplotype analysis in family-based association studies to investigate candidate genes. References Rabinowitz, D. & Laird, N. M. (2000) Hum Hered50, 211,223. Zhang, K., Sun, F. & Zhao, H. (2005) Bioinformatics21, 90,103. Andrea Foulkes 1 , Recai Yucel 1 , Xiaohong Li 143 Division of Biostatistics, University of Massachusetts, USA Keywords: Haploytpe, high-dimensional, mixed modeling The explosion of molecular level information coupled with large epidemiological studies presents an exciting opportunity to uncover the genetic underpinnings of complex diseases; however, several analytical challenges remain to be addressed. Characterizing the components to complex diseases inevitably requires consideration of synergies across multiple genetic loci and environmental and demographic factors. In addition, it is critical to capture information on allelic phase, that is whether alleles within a gene are in cis (on the same chromosome) or in trans (on different chromosomes.) In associations studies of unrelated individuals, this alignment of alleles within a chromosomal copy is generally not observed. We address the potential ambiguity in allelic phase in this high dimensional data setting using mixed effects models. Both a semi-parametric and fully likelihood-based approach to estimation are considered to account for missingness in cluster identifiers. In the first case, we apply a multiple imputation procedure coupled with a first stage expectation maximization algorithm for parameter estimation. A bootstrap approach is employed to assess sensitivity to variability induced by parameter estimation. Secondly, a fully likelihood-based approach using an expectation conditional maximization algorithm is described. Notably, these models allow for characterizing high-order gene-gene interactions while providing a flexible statistical framework to account for the confounding or mediating role of person specific covariates. The proposed method is applied to data arising from a cohort of human immunodeficiency virus type-1 (HIV-1) infected individuals at risk for therapy associated dyslipidemia. Simulation studies demonstrate reasonable power and control of family-wise type 1 error rates. Vivien Marquard 1 , Lars Beckmann 1 , Jenny Chang-Claude 144 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Genotyping errors, type I error, haplotype-based association methods It has been shown in several simulation studies that genotyping errors may have a great impact on the type I error of statistical methods used in genetic association analysis of complex diseases. Our aim was to investigate type I error rates in a case-control study, when differential and non-differential genotyping errors were introduced in realistic scenarios. We simulated case-control data sets, where individual genotypes were drawn from a haplotype distribution of 18 haplotypes with 15 markers in the APM1 gene. Genotyping errors were introduced following the unrestricted and symmetric with 0 edges error models described by Heid et al. (2006). In six scenarios, errors resulted from changes of one allele to another with predefined probabilities of 1%, 2.5% or 10%, respectively. A multiple number of errors per haplotype was possible and could vary between 0 and 15, the number of markers investigated. We examined three association methods: Mantel statistics using haplotype-sharing; a haplotype-specific score test; and Armitage trend test for single markers. The type I error rates were not influenced for any of all the three methods for a genotyping error rate of less than 1%. For higher error rates and differential errors, the type I error of the Mantel statistic was only slightly and of the Armitage trend test moderately increased. The type I error rates of the score test were highly increased. The type I error rates were correct for all three methods for non-differential errors. Further investigations will be carried out with different frequencies of differential error rates and focus on power. Arne Neumann 1 , Dörthe Malzahn 1 , Martina Müller 2 , Heike Bickeböller 145 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany 46 GSF-National Research Center for Environment and Health, Neuherberg & IBE-Institute of Epidemiology, Ludwig-Maximilians University München, Germany Keywords: Interaction, longitudinal, nonparametric Longitudinal data show the time dependent course of phenotypic traits. In this contribution, we consider longitudinal cohort studies and investigate the association between two candidate genes and a dependent quantitative longitudinal phenotype. The set-up defines a factorial design which allows us to test simultaneously for the overall gene effect of the loci as well as for possible gene-gene and gene time interaction. The latter would induce genetically based time-profile differences in the longitudinal phenotype. We adopt a non-parametric statistical test to genetic epidemiological cohort studies and investigate its performance by simulation studies. The statistical test was originally developed for longitudinal clinical studies (Brunner, Munzel, Puri, 1999 J Multivariate Anal 70:286-317). It is non-parametric in the sense that no assumptions are made about the underlying distribution of the quantitative phenotype. Longitudinal observations belonging to the same individual can be arbitrarily dependent on one another for the different time points whereas trait observations of different individuals are independent. The two loci are assumed to be statistically independent. Our simulations show that the nonparametric test is comparable with ANOVA in terms of power of detecting gene-gene and gene-time interaction in an ANOVA favourable setting. Rebecca Hein 1 , Lars Beckmann 1 , Jenny Chang-Claude 147 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Indirect association studies, interaction effects, linkage disequilibrium, marker allele frequency Association studies accounting for gene-environment interactions (GxE) may be useful for detecting genetic effects and identifying important environmental effect modifiers. Current technology facilitates very dense marker spacing in genetic association studies; however, the true disease variant(s) may not be genotyped. In this situation, an association between a gene and a phenotype may still be detectable, using genetic markers associated with the true disease variant(s) (indirect association). Zondervan and Cardon [2004] showed that the odds ratios (OR) of markers which are associated with the disease variant depend highly on the linkage disequilibrium (LD) between the variant and the markers, and whether the allele frequencies match and thereby influence the sample size needed to detect genetic association. We examined the influence of LD and allele frequencies on the sample size needed to detect GxE in indirect association studies, and provide tables for sample size estimation. For discordant allele frequencies and incomplete LD, sample sizes can be unfeasibly large. The influence of both factors is stronger for disease loci with small rather than moderate to high disease allele frequencies. A decline in D' of e.g. 5% has less impact on sample size than increasing the difference in allele frequencies by the same percentage. Assuming 80% power, large interaction effects can be detected using smaller sample sizes than those needed for the detection of main effects. The detection of interaction effects involving rare alleles may not be possible. Focussing only on marker density can be a limited strategy in indirect association studies for GxE. Cyril Dalmasso 1 , Emmanuelle Génin 2 , Catherine Bourgain 2 , Philippe Broët 148 JE 2492 , Univ. Paris-Sud, France 49 INSERM UMR-S 535 and University Paris Sud, Villejuif, France Keywords: Linkage analysis, Multiple testing, False Discovery Rate, Mixture model In the context of genome-wide linkage analyses, where a large number of statistical tests are simultaneously performed, the False Discovery Rate (FDR) that is defined as the expected proportion of false discoveries among all discoveries is nowadays widely used for taking into account the multiple testing problem. Other related criteria have been considered such as the local False Discovery Rate (lFDR) that is a variant of the FDR giving to each test its own measure of significance. The lFDR is defined as the posterior probability that a null hypothesis is true. Most of the proposed methods for estimating the lFDR or the FDR rely on distributional assumption under the null hypothesis. However, in observational studies, the empirical null distribution may be very different from the theoretical one. In this work, we propose a mixture model based approach that provides estimates of the lFDR and the FDR in the context of large-scale variance component linkage analyses. In particular, this approach allows estimating the empirical null distribution, this latter being a key quantity for any simultaneous inference procedure. The proposed method is applied on a real dataset. Arief Gusnanto 1 , Frank Dudbridge 150 MRC Biostatistics Unit, Cambridge UK Keywords: Significance, genome-wide, association, permutation, multiplicity Genome-wide association scans have introduced statistical challenges, mainly in the multiplicity of thousands of tests. The question of what constitutes a significant finding remains somewhat unresolved. Permutation testing is very time-consuming, whereas Bayesian arguments struggle to distinguish direct from indirect association. It seems attractive to summarise the multiplicity in a simple form that allows users to avoid time-consuming permutations. A standard significance level would facilitate reporting of results and reduce the need for permutation tests. This is potentially important because current scans do not have full coverage of the whole genome, and yet, the implicit multiplicity is genome-wide. We discuss some proposed summaries, with reference to the empirical null distribution of the multiple tests, approximated through a large number of random permutations. Using genome-wide data from the Wellcome Trust Case-Control Consortium, we use a sub-sampling approach with increasing density to estimate the nominal p-value to obtain family-wise significance of 5%. The results indicate that the significance level is converging to about 1e-7 as the marker spacing becomes infinitely dense. We considered the concept of an effective number of independent tests, and showed that when used in a Bonferroni correction, the number varies with the overall significance level, but is roughly constant in the region of interest. We compared several estimators of the effective number of tests, and showed that in the region of significance of interest, Patterson's eigenvalue based estimator gives approximately the right family-wise error rate. Michael Nothnagel 1 , Amke Caliebe 1 , Michael Krawczak 151 Institute of Medical Informatics and Statistics, University Clinic Schleswig-Holstein, University of Kiel, Germany Keywords: Association scans, Bayesian framework, posterior odds, genetic risk, multiplicative model Whole-genome association scans have been suggested to be a cost-efficient way to survey genetic variation and to map genetic disease factors. We used a Bayesian framework to investigate the posterior odds of a genuine association under multiplicative disease models. We demonstrate that the p value alone is not a sufficient means to evaluate the findings in association studies. We suggest that likelihood ratios should accompany p values in association reports. We argue, that, given the reported results of whole-genome scans, more associations should have been successfully replicated if the consistently made assumptions about considerable genetic risks were correct. We conclude that it is very likely that the vast majority of relative genetic risks are only of the order of 1.2 or lower. Clive Hoggart 1 , Maria De Iorio 1 , John Whittakker 2 , David Balding 152 Department of Epidemiology and Public Health, Imperial College London, UK 53 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: Genome-wide association analyses, shrinkage priors, Lasso Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants of small effect, which is a plausible scenario for many complex diseases. Moreover, many simulation studies assume a single causal variant and so more complex realities are ignored. Analysing large numbers of variants simultaneously is now becoming feasible, thanks to developments in Bayesian stochastic search methods. We pose the problem of SNP selection as variable selection in a regression model. In contrast to single SNP tests this approach simultaneously models the effect of all SNPs. SNPs are selected by a Bayesian interpretation of the lasso (Tibshirani, 1996); the maximum a posterior (MAP) estimate of the regression coefficients, which have been given independent, double exponential prior distributions. The double exponential distribution is an example of a shrinkage prior, MAP estimates with shrinkage priors can be zero, thus all SNPs with non zero regression coefficients are selected. In addition to the commonly-used double exponential (Laplace) prior, we also implement the normal exponential gamma prior distribution. We show that use of the Laplace prior improves SNP selection in comparison with single -SNP tests, and that the normal exponential gamma prior leads to a further improvement. Our method is fast and can handle very large numbers of SNPs: we demonstrate its performance using both simulated and real genome-wide data sets with 500 K SNPs, which can be analysed in 2 hours on a desktop workstation. Mickael Guedj 1,2 , Jerome Wojcik 2 , Gregory Nuel 154 Laboratoire Statistique et Génome, Université d'Evry, Evry France 55 Serono Pharmaceutical Research Institute, Plan-les-Ouates, Switzerland Keywords: Local Replication, Local Score, Association In gene-mapping, replication of initial findings has been put forwards as the approach of choice for filtering false-positives from true signals for underlying loci. In practice, such replications are however too poorly observed. Besides the statistical and technical-related factors (lack of power, multiple-testing, stratification, quality control,) inconsistent conclusions obtained from independent populations might result from real biological differences. In particular, the high degree of variation in the strength of LD among populations of different origins is a major challenge to the discovery of genes. Seeking for Local Replications (defined as the presence of a signal of association in a same genomic region among populations) instead of strict replications (same locus, same risk allele) may lead to more reliable results. Recently, a multi-markers approach based on the Local Score statistic has been proposed as a simple and efficient way to select candidate genomic regions at the first stage of genome-wide association studies. Here we propose an extension of this approach adapted to replicated association studies. Based on simulations, this method appears promising. In particular it outperforms classical simple-marker strategies to detect modest-effect genes. Additionally it constitutes, to our knowledge, a first framework dedicated to the detection of such Local Replications. Juliet Chapman 1 , Claudio Verzilli 1 , John Whittaker 156 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: FDR, Association studies, Bayesian model selection As genomewide association studies become commonplace there is debate as to how such studies might be analysed and what we might hope to gain from the data. It is clear that standard single locus approaches are limited in that they do not adjust for the effects of other loci and problematic since it is not obvious how to adjust for multiple comparisons. False discovery rates have been suggested, but it is unclear how well these will cope with highly correlated genetic data. We consider the validity of standard false discovery rates in large scale association studies. We also show that a Bayesian procedure has advantages in detecting causal loci amongst a large number of dependant SNPs and investigate properties of a Bayesian FDR. Peter Kraft 157 Harvard School of Public Health, Boston USA Keywords: Gene-environment interaction, genome-wide association scans Appropriately analyzed two-stage designs,where a subset of available subjects are genotyped on a genome-wide panel of markers at the first stage and then a much smaller subset of the most promising markers are genotyped on the remaining subjects,can have nearly as much power as a single-stage study where all subjects are genotyped on the genome-wide panel yet can be much less expensive. Typically, the "most promising" markers are selected based on evidence for a marginal association between genotypes and disease. Subsequently, the few markers found to be associated with disease at the end of the second stage are interrogated for evidence of gene-environment interaction, mainly to understand their impact on disease etiology and public health impact. However, this approach may miss variants which have a sizeable effect restricted to one exposure stratum and therefore only a modest marginal effect. We have proposed to use information on the joint effects of genes and a discrete list of environmental exposures at the initial screening stage to select promising markers for the second stage [Kraft et al Hum Hered 2007]. This approach optimizes power to detect variants that have a sizeable marginal effect and variants that have a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. As an example, I discuss a proposed genome-wide association scan for Type II diabetes susceptibility variants based in several large nested case-control studies. Beate Glaser 1 , Peter Holmans 158 Biostatistics and Bioinformatics Unit, Cardiff University, School of Medicine, Heath Park, Cardiff, UK Keywords: Combined case-control and trios analysis, Power, False-positive rate, Simulation, Association studies The statistical power of genetic association studies can be enhanced by combining the analysis of case-control with parent-offspring trio samples. Various combined analysis techniques have been recently developed; as yet, there have been no comparisons of their power. This work was performed with the aim of identifying the most powerful method among available combined techniques including test statistics developed by Kazeem and Farrall (2005), Nagelkerke and colleagues (2004) and Dudbridge (2006), as well as a simple combination of ,2-statistics from single samples. Simulation studies were performed to investigate their power under different additive, multiplicative, dominant and recessive disease models. False-positive rates were determined by studying the type I error rates under null models including models with unequal allele frequencies between the single case-control and trios samples. We identified three techniques with equivalent power and false-positive rates, which included modifications of the three main approaches: 1) the unmodified combined Odds ratio estimate by Kazeem & Farrall (2005), 2) a modified approach of the combined risk ratio estimate by Nagelkerke & colleagues (2004) and 3) a modified technique for a combined risk ratio estimate by Dudbridge (2006). Our work highlights the importance of studies investigating test performance criteria of novel methods, as they will help users to select the optimal approach within a range of available analysis techniques. David Almorza 1 , M.V. Kandus 2 , Juan Carlos Salerno 2 , Rafael Boggio 359 Facultad de Ciencias del Trabajo, University of Cádiz, Spain 60 Instituto de Genética IGEAF, Buenos Aires, Argentina 61 Universidad Nacional de La Plata, Buenos Aires, Argentina Keywords: Principal component analysis, maize, ear weight, inbred lines The objective of this work was to evaluate the relationship among different traits of the ear of maize inbred lines and to group genotypes according to its performance. Ten inbred lines developed at IGEAF (INTA Castelar) and five public inbred lines as checks were used. A field trial was carried out in Castelar, Buenos Aires (34° 36' S , 58° 39' W) using a complete randomize design with three replications. At harvest, individual weight (P.E.), diameter (D.E.), row number (N.H.) and length (L.E.) of the ear were assessed. A principal component analysis, PCA, (Infostat 2005) was used, and the variability of the data was depicted with a biplot. Principal components 1 and 2 (CP1 and CP2) explained 90% of the data variability. CP1 was correlated with P.E., L.E. and D.E., meanwhile CP2 was correlated with N.H. We found that individual weight (P.E.) was more correlated with diameter of the ear (D.E.) than with length (L.E). Five groups of inbred lines were distinguished: with high P.E. and mean N.H. (04-70, 04-73, 04-101 and MO17), with high P.E. but less N.H. (04-61 and B14), with mean P.E. and N.H. (B73, 04-123 and 04-96), with high N.H. but less P.E. (LP109, 04-8, 04-91 and 04-76) and with low P.E. and low N.H. (LP521 and 04-104). The use of PCA showed which variables had more incidence in ear weight and how is the correlation among them. Moreover, the different groups found with this analysis allow the evaluation of inbred lines by several traits simultaneously. Sven Knüppel 1 , Anja Bauerfeind 1 , Klaus Rohde 162 Department of Bioinformatics, MDC Berlin, Germany Keywords: Haplotypes, association studies, case-control, nuclear families The area of gene chip technology provides a plethora of phase-unknown SNP genotypes in order to find significant association to some genetic trait. To circumvent possibly low information content of a single SNP one groups successive SNPs and estimates haplotypes. Haplotype estimation, however, may reveal ambiguous haplotype pairs and bias the application of statistical methods. Zaykin et al. (Hum Hered, 53:79-91, 2002) proposed the construction of a design matrix to take this ambiguity into account. Here we present a set of functions written for the Statistical package R, which carries out haplotype estimation on the basis of the EM-algorithm for individuals (case-control) or nuclear families. The construction of a design matrix on basis of estimated haplotypes or haplotype pairs allows application of standard methods for association studies (linear, logistic regression), as well as statistical methods as haplotype sharing statistics and TDT-Test. Applications of these methods to genome-wide association screens will be demonstrated. Manuela Zucknick 1 , Chris Holmes 2 , Sylvia Richardson 163 Department of Epidemiology and Public Health, Imperial College London, UK 64 Department of Statistics, Oxford Center for Gene Function, University of Oxford, UK Keywords: Bayesian, variable selection, MCMC, large p, small n, structured dependence In large-scale genomic applications vast numbers of markers or genes are scanned to find a few candidates which are linked to a particular phenotype. Statistically, this is a variable selection problem in the "large p, small n" situation where many more variables than samples are available. An additional feature is the complex dependence structure which is often observed among the markers/genes due to linkage disequilibrium or their joint involvement in biological processes. Bayesian variable selection methods using indicator variables are well suited to the problem. Binary phenotypes like disease status are common and both Bayesian probit and logistic regression can be applied in this context. We argue that logistic regression models are both easier to tune and to interpret than probit models and implement the approach by Holmes & Held (2006). Because the model space is vast, MCMC methods are used as stochastic search algorithms with the aim to quickly find regions of high posterior probability. In a trade-off between fast-updating but slow-moving single-gene Metropolis-Hastings samplers and computationally expensive full Gibbs sampling, we propose to employ the dependence structure among the genes/markers to help decide which variables to update together. Also, parallel tempering methods are used to aid bold moves and help avoid getting trapped in local optima. Mixing and convergence of the resulting Markov chains are evaluated and compared to standard samplers in both a simulation study and in an application to a gene expression data set. Reference Holmes, C. C. & Held, L. (2006) Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis1, 145,168. Dawn Teare 165 MMGE, University of Sheffield, UK Keywords: CNP, family-based analysis, MCMC Evidence is accumulating that segmental copy number polymorphisms (CNPs) may represent a significant portion of human genetic variation. These highly polymorphic systems require handling as phenotypes rather than co-dominant markers, placing new demands on family-based analyses. We present an integrated approach to meet these challenges in the form of a graphical model, where the underlying discrete CNP phenotype is inferred from the (single or replicate) quantitative measure within the analysis, whilst assuming an allele based system segregating through the pedigree. [source] Quantum-Statistical Equation-of-State Models of Dense Plasmas: High-Pressure Hugoniot Shock AdiabatsCONTRIBUTIONS TO PLASMA PHYSICS, Issue 6 2007J. C. Pain Abstract We present a detailed comparison of two self-consistent equation-of-state models which differ from their electronic contribution: the atom in a spherical cell and the atom in a jellium of charges. It is shown that both models are well suited for the calculation of Hugoniot shock adiabats in the high pressure range (1 Mbar-10 Gbar), and that the atom-in-a-jellium model provides a better treatment of pressure ionization. Comparisons with experimental data are also presented. Shell effects on shock adiabats are reviewed in the light of these models. They lead to additional features not only in the variations of pressure versus density, but also in the variations of shock velocity versus particle velocity. Moreover, such effects are found to be responsible for enhancement of the electronic specific heat. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Designing mouse behavioral tasks relevant to autistic-like behaviors,DEVELOPMENTAL DISABILITIES RESEARCH REVIEW, Issue 4 2004Jacqueline N. Crawley Abstract The importance of genetic factors in autism has prompted the development of mutant mouse models to advance our understanding of biological mechanisms underlying autistic behaviors. Mouse models of human neuropsychiatric diseases are designed to optimize (1) face validity, i.e., resemblance to the human symptoms; (2) construct validity, i.e., similarity to the underlying causes of the disease; and (3) predictive validity, i.e., expected responses to treatments that are effective in the human disease. There is a growing need for mouse behavioral tasks with all three types of validity for modeling the symptoms of autism. We are in the process of designing a set of tasks with face validity for the defining features of autism: deficits in appropriate reciprocal social interactions, deficits in verbal social communication, and high levels of ritualistic repetitive behaviors. Social approach is tested in an automated three-chambered apparatus that offers the subject a choice between a familiar environment, a novel environment, and a novel environment containing a stranger mouse. Preference for social novelty is tested in the same apparatus, with a choice between the start chamber, the chamber containing a familiar mouse, and the chamber containing a stranger mouse. Social communication is evaluated by measuring the ultrasonic distress vocalizations emitted by infant mouse pups and the parental response of retrieving the pup to the nest. Resistance to change in ritualistic repetitive behaviors is modeled by forcing a change in habit, including reversal of the spatial location of a reinforcer in a T-maze task and in the Morris water maze. Mouse behavioral tasks that may model additional features of autism are discussed, including tasks relevant to anxiety, seizures, sleep disturbances, and sensory hypersensitivity. Applications of these tests include (1) behavioral phenotyping of transgenic and knockout mice with mutations in genes relevant to autism, (2) characterization of mutant mice derived from random chemical mutagenesis, (3) DNA microarray analyses of genes in inbred strains of mice that differ in social interaction, social communication and resistance to change in habit, and (4) evaluation of proposed therapeutics for the treatment of autism. Published 2004 Wiley-Liss, Inc. MRDD Research Reviews 2004;10:248,258. [source] A metabolic syndrome of hypertension, hyperinsulinaemia and hypercholesterolaemia in the New Zealand obese mouseEUROPEAN JOURNAL OF CLINICAL INVESTIGATION, Issue 3 2000Ortlepp Background New Zealand obese (NZO) mice exhibit a polygenic obesity associated with hyperinsulinaemia and hyperglycaemia. Here we show that the strain presents additional features of a metabolic syndrome, i.e. elevated blood pressure, serum cholesterol and serum triglyceride levels. Materials and methods A back-cross model of NZO mice with the lean Swiss Jackson Laboratory (SJL) strain was established in order to investigate further the correlation between hypertension, obesity, serum insulin and hyperglycaemia. Results Systolic blood pressure was significantly elevated at 6 weeks of age and appeared to parallel the weight gain of the animals. Serum insulin levels, presumably reflecting insulin resistance, and systolic blood pressure values were significantly correlated with the body mass index (r2 = 0.707 and 0.486, respectively) in the back-cross mice. In contrast, blood pressure was only weakly correlated with serum insulin (r2 = 0.288) in non-diabetic mice, and was independent of serum insulin levels in diabetic animals. Conclusion The data are consistent with the concept that hypertension and insulin resistance are a characteristic consequence of the genetic constellation leading to obesity in the NZO strain, and that these traits reflect related mechanisms. It appears unlikely, however, that hypertension is a direct consequence of hyperinsulinaemia. [source] Extensive flow cytometric characterization of plasmacytoid dendritic cell leukemia cellsEUROPEAN JOURNAL OF HAEMATOLOGY, Issue 4 2005Laszlo Gopcsa Abstract:,Objectives:,Accumulating evidence suggests that non-T, non-B cell CD4+CD56+ neoplasms with lymphoblastic morphology include clinically and immunophenotypically diverse entities. Although their cells of origin or classification are still controversial several entities clearly represent a distinct type of neoplasms that are clinically aggressive. Methods:,In this work we present the immunophenotypic and genotypic features of bone marrow (BM), peripheral blood (PB), lymph node and skin lymphocytes from a patient diagnosed as plasmacytoid dendritic cell leukemia involving the skin, BM, PB, lymph nodes, liver and spleen. For determination of immunophenotypic characteristics of malignant plasmacytoid dendritic cells 73 monoclonal antibodies detecting lineage markers, chemokine receptors, cytokine receptors, activation, and co-stimulatory molecules were used. Results and conclusion:,The malignant cells proved to express CD4+, CD56+ lineage negative leukemia phenotype characteristically positive for CD36, CD38, CD40, CD45, CD45RA, CD68, CD123, CD184, HLA-DR, BDCA2, and granzyme-B corresponding to the preplasmacytoid dendritic cell developmental stage. The presence of CD11a/CD18, CD84, CD91, CD95, ,v,5, CDw197, and the absence of CD52 and CD133 in this case can be regarded as additional features of malignant cells. Completing the immunophenotypes with multidrug resistance function can provide additional information for characterizing pDC leukemia. [source] Genetic variants in IRF6 and the risk of facial clefts: single-marker and haplotype-based analyses in a population-based case-control study of facial clefts in NorwayGENETIC EPIDEMIOLOGY, Issue 5 2008Astanand Jugessur Abstract Mutations in the gene encoding interferon regulatory factor 6 (IRF6) underlie a common form of syndromic clefting known as Van der Woude syndrome. Lip pits and missing teeth are the only additional features distinguishing the syndrome from isolated clefts. Van der Woude syndrome, therefore, provides an excellent model for studying the isolated forms of clefting. From a population-based case-control study of facial clefts in Norway (1996,2001), we selected 377 cleft lip with or without cleft palate (CL/P), 196 cleft palate only (CPO), and 763 control infant-parent triads for analysis. We genotyped six single nucleotide polymorphisms within the IRF6 locus and estimated the relative risks (RR) conferred on the child by alleles and haplotypes of the child and of the mother. On the whole, there were strong statistical associations with CL/P but not CPO in our data. In single-marker analyses, mothers with a double-dose of the ,a'-allele at rs4844880 had an increased risk of having a child with CL/P (RR=1.85, 95% confidence interval: 1.04,3.25; P=0.036). An RR of 0.38 (95% confidence interval: 0.16,0.92; P=0.031) was obtained when the child carried a single-dose of the ,a'-allele at rs2235371 (the p.V274I polymorphism). The P -value for the overall test was <0.001. In haplotype analyses, several of the fetal and maternal haplotype relative risks were statistically significant individually but were not strong enough to show up on the overall test (P=0.113). Taken together, these findings further support a role for IRF6 variants in clefting of the lip and provide specific risk estimates in a Norwegian population. Genet. Epidemiol. 2008. © 2008 Wiley-Liss, Inc. [source] Being liked activates primary reward and midline self-related brain regionsHUMAN BRAIN MAPPING, Issue 4 2010Christopher G. Davey Abstract The experience of being liked is a key social event and fundamental to motivating human behavior, though little is known about its neural underpinnings. In this study, we examined the experience of being liked in a group of 15- to 24-year-old: a cohort for whom forming friendships has a great degree of salience, and for whom the explicit representation of relationships is familiar from their frequent use of social networking technologies. Study participants (n = 19) were led to believe that other participants had formed an opinion on their likability based on their appearance in a photograph, and during fMRI scanning viewed the photographs of people who had purportedly responded favorably to them (alongside photographs of control participants). Results indicated that being liked activated primary reward- and self-related regions, including the nucleus accumbens, midbrain (in an area corresponding to the ventral tegmentum), ventromedial prefrontal cortex, posterior cingulate cortex (including retrosplenial cortex), amygdala, and insula/opercular cortex. Participants showed greater activation of ventromedial prefrontal cortex and amygdala in response to being liked by people that they regarded highly compared to those they regarded less so. Finally, being liked by the opposite compared to the same gender activated the right caudal orbitofrontal cortex and right anterior insula: areas important for the representation of primary somatic rewards. This study demonstrates that neural response to being liked has features that are consistent with response to other rewarding events, but it has additional features that reflect its intrinsically interpersonal character. Hum Brain Mapp, 2010. © 2009 Wiley-Liss, Inc. [source] Microdeletions involving the SCN1A gene may be common in SCN1A -mutation-negative SMEI patients,HUMAN MUTATION, Issue 9 2006Arvid Suls Abstract Severe myoclonic epilepsy of infancy (SMEI) or Dravet syndrome is a rare epilepsy syndrome. In 30 to 70% of SMEI patients, truncating and missense mutations in the neuronal voltage-gated sodium-channel ,-subunit gene (SCN1A) have been identified. The majority of patients have truncating mutations that are predicted to be loss-of-function alleles. Because mutation detection studies use PCR-based sequencing or conformation sensitive gel electrophoresis (CSGE), microdeletions, which are also predicted to be loss-of-function alleles, can easily escape detection. We selected 11 SMEI patients with or without additional features who had no SCN1A mutation detectable with sequencing analysis. In addition, none of the patients was heterozygous for any of the SNPs in SCN1A, indicating that they were either homozygous for all SNPs or hemizygous due to a microdeletion of the gene. We subsequently analyzed these patients for the presence of microdeletions in SCN1A using a quantitative PCR method named multiplex amplicon quantification (MAQ), and observed three patients missing one copy of the SCN1A gene. All three microdeletions were confirmed by fluorescence in situ hybridization (FISH). These findings demonstrate that a substantial percentage of SCN1A -mutation-negative SMEI patients with or without additional features carry a chromosomal microdeletion comprising the SCN1A gene and that haploinsufficiency of the SCN1A gene is a cause of SMEI. Hum Mutat 27(9), 914,920, 2006. © 2006 Wiley-Liss, Inc. [source] Atypical X-linked ichthyosis in a patient with a large deletion involving the steroid sulfatase (STS) geneINTERNATIONAL JOURNAL OF DERMATOLOGY, Issue 2 2009Luz Gonzalez-Huerta MD A 70-year-old male presented with very large, thick, tightly adherent, dark-brown scales on the front of his lower extremities. His face, neck, back, abdomen, upper extremities, flexural areas, palms and soles as well as hair and nails were not involved. Family history was negative for similar lesions. Otherwise, the patient had a normal development. Onset of symptoms occurred during childhood with scales on lower extremities with no more additional features. Treatment included emollients exclusively with partial and temporary remission of cutaneous lesions. Recently, the patient had not received topical or systemic medical treatment. Laboratory investigations were within normal limits. The patient had undetectable levels of STS activity when compared with normal control (0.00 pmol mg -1 protein h -1) which confirmed the diagnosis of X-linked ichthyosis (XLI) . PCR analysis showed deletion of the STS gene, markers DXS1139 and DXF22S1and the 5, end of the VCX3A gene. The patient had scales present on lower extremities only with no medical treatment that corresponded to an unusual clinical manifestation of XLI. Clinical manifestations of XLI are due to a great variety of environmental, genetic and individual factors that should be considered in XLI diagnosis. [source] A7445G mtDNA mutation present in a Portuguese family exhibiting hereditary deafness and palmoplantar keratodermaJOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY & VENEREOLOGY, Issue 4 2005H Caria ABSTRACT Mitochondrial DNA (mtDNA) A7445G point mutation has been shown to be responsible for familial nonepidermolytic palmoplantar keratoderma (NEPPK) associated with deafness without any additional features. To date, only a few cases have been described. We report a Portuguese pedigree presenting an inherited combination of NEPPK and sensorineural deafness compatible with maternal transmission. Clinical expression and age of onset of NEPPK and deafness were variable. Normal expression patterns of epidermal keratins and filaggrin, intercellular junction proteins including connexin 26, loricrin and cornified envelope proteins, were observed. Molecular analysis revealed that all the affected members, previously screened for Cx26 mutations with negative results, presented the mtDNA A7445G point mutation in the homoplasmic form. To our knowledge, this is the fifth family in whom inherited NEPPK and hearing loss are related to this mitochondrial mutation. [source] Doping-dependence of subband energies in quantized electron accumulation at InN surfacesPHYSICA STATUS SOLIDI (A) APPLICATIONS AND MATERIALS SCIENCE, Issue 2 2007T. D. Veal Abstract Electron tunnelling spectroscopy is used to investigate the quantized electron accumulation at the surfaces of wurtzite InN with different doping levels. The tunnelling spectra of InN-oxide-tip junctions recorded in air at room temperature exhibit a ,0.6 V plateau, corresponding to the band gap of InN, and a gap between onsets of 1.3 V, consistent with the separation between the valence band maximum and the pinned Fermi level at the oxidized InN surface. Also observed within the tunnelling spectra are additional features between the conduction band minimum and the pinned Fermi level. These features are attributed to surface-bound quantized states associated with the potential well formed by the downward band bending at the InN-oxide interface. Their energetic positions are dependent upon the doping level of the InN films and coincide with calculated subband energies. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Virtual Cities From Digital ImageryTHE PHOTOGRAMMETRIC RECORD, Issue 96 2000E. Gülch Increasing interest is being expressed in the use of virtual cities for many fields of application, ranging from planning and simulation to business, advertising and the games industry. Currently, the extraction of buildings from imagery is costly. However, recent developments in digital photogrammetry aim to produce more rapid and efficient methods of modelling three dimensional objects in urban environments. This paper presents a semi-automatic system for the extraction of buildings from digital aerial imagery with the aid of volumetric primitives. The user is supported by automated tools, for example matching tools, in order to reach the necessary efficiency. With an extraction time of about 20 s per building primitive, this method is competitive in terms of the performance of classical photogrammetric procedures, and also offers additional features for analysis, texture mapping and Internet applications. [source] Structure,function studies of the RNA polymerase II elongation complexACTA CRYSTALLOGRAPHICA SECTION D, Issue 2 2009Florian Brueckner RNA polymerase II (Pol II) is the eukaryotic enzyme that is responsible for transcribing all protein-coding genes into messenger RNA (mRNA). The mRNA-transcription cycle can be divided into three stages: initiation, elongation and termination. During elongation, Pol II moves along a DNA template and synthesizes a complementary RNA chain in a processive manner. X-ray structural analysis has proved to be a potent tool for elucidating the mechanism of Pol II elongation. Crystallographic snapshots of different functional states of the Pol II elongation complex (EC) have elucidated mechanistic details of nucleotide addition and Pol II translocation. Further structural studies in combination with in vitro transcription experiments led to a mechanistic understanding of various additional features of the EC, including its inhibition by the fungal toxin ,-amanitin, the tunability of the active site by the elongation factor TFIIS, the recognition of DNA lesions and the use of RNA as a template. [source] Low frequency resonance Raman spectra of isolated , and , subunits of hemoglobin and their deuterated analoguesBIOPOLYMERS, Issue 5 2006Edyta Podstawka Abstract In an attempt to gain further insight into the nature of the low frequency vibrational modes of hemoglobin and its isolated subunits, a comprehensive study of several different isotopically labeled analogues has been undertaken and is reported herein. Specifically, the resonance Raman spectra, between 200 and 500 cm,1, are reported for the deoxy and ligated (CO and O2) forms of the isolated , and , subunits containing the natural abundance or various deuterated analogues of protoheme. The deuterated protoheme analogues studied include the 1,3,5,8-C2H3 -protoheme (d12- protoheme), the 1,3-C2H3 -protoheme (1,3- d6-protoheme), the 5,8-C2H3 -protoheme (5,8- d6-protoheme), and the meso-C2H4 -protoheme (d4-protoheme). The entire set of acquired spectra has been analyzed using a deconvolution procedure to help correlate the shifted modes with their counterparts in the spectra of the native forms. Interestingly, modes previously associated with so-called vinyl bending modes or propionate deformation modes are shown to be quite sensitive to deuteration of the peripheral methyl groups of the macrocycle, shifting by up to 12,15 cm,1, revealing their complex nature. Of special interest is the fact that shifts observed for the 1,3- d6- and 5,8- d6-protoheme analogues confirm the fact that certain modes are associated with a given portion of the macrocycle; i.e., only certain modes shift upon deuteration of the 1 and 3 methyl groups, while others shift upon deuteration of the 5 and 8 methyl groups. Compared with the spectra previously reported for the corresponding myoglobin derivatives, the data reported here reveal the appearance of several additional features that imply splitting of modes associated with the propionate groups or that are indicative of greater distortion of the heme prosthetic groups. © 2006 Wiley Periodicals, Inc. Biopolymers 83: 455,466, 2006 This article was originally published online as an accepted preprint. The "Published Online" date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com [source] | |||||||||||||||||||||||||