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Genetic Risk (genetic + risk)
Terms modified by Genetic Risk Selected AbstractsAnalysis of Heritability of Hormonal Responses to Alcohol in Twins: Beta-Endorphin as a Potential Biomarker of Genetic Risk for AlcoholismALCOHOLISM, Issue 3 2000J. C. Froehlich Background: Hormonal responses to alcohol have been reported to differ in subjects with and without a family history of alcoholism which suggests that alcohol-induced hormonal changes might be used to identify individuals who are at elevated genetic risk for developing alcoholism. However, before a biological response can be used as a marker of genetic risk for disease, it must first be demonstrated that the response is, in fact, heritable. The present study was designed to determine whether hormonal responses to alcohol are heritable. Methods: The adrenocorticotropic hormone (ACTH), beta-endorphin (,-E), cortisol (CORT), and prolactin (PRL) responses to alcohol were examined in male and female identical (monozygotic or MZ) and fraternal (dizygotic or DZ) twin pairs. Male subjects consumed 0.35g ethanol/kg body weight (BW) and female consumed 0.325 g ethanol/kg BW in each of two alcohol drinking sessions administered 1 hr apar (total dose of 0.7 g/kg BW in males and 0.65 g/kg BW in females). Plasma hormone content was analyzed in samples collected before (resting conditions) and at 15, 60, 75, 120, 180, and 240 min after onset of drinking. Hormonal responses to alcohol were examined with twin analyses using the TWINAN90 program. A separate analysis was performed for each of the four hormones. A subset of subjects from each zygosity was seen on two separate occasions to establish retest reliability. Heritability of hormonal responses to alcohol was estimated using the intraclass correlation approach before and after removing the contribution of covariates that have the potential of influencing the plasma levels of these hormones. Results: Resting plasma levels of all four hormones were within the expected range, and the ,-E, ACTH, and PRL responses to the alcohol challenge evidenced good test-retest reliability. Of the four hormones examined, the only one that showed significant heritability after alcohol drinking was ,-E. Heritability estimates were not altered for any of the four hormones after removal of the variance contributed by covariates, such as gender and age. Conclusions: Taken together with other recent findings, the results suggest that the ,-E response to alcohol may represent a new biomarker that can be used to identify individuals who are at elevated genetic risk for developing alcoholism. [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] Validation Study of Genetic Associations with Coronary Artery Disease on Chromosome 3q13-21 and Potential Effect Modification by SmokingANNALS OF HUMAN GENETICS, Issue 6 2009Benjamin D. Horne Summary The CATHGEN study reported associations of chromosome 3q13-21 genes (KALRN, MYLK, CDGAP, and GATA2) with early-onset coronary artery disease (CAD). This study attempted to independently validate those associations. Eleven single nucleotide polymorphisms (SNPs) were examined (rs10934490, rs16834817, rs6810298, rs9289231, rs12637456, rs1444768, rs1444754, rs4234218, rs2335052, rs3803, rs2713604) in patients (N = 1618) from the Intermountain Heart Collaborative Study (IHCS). Given the higher smoking prevalence in CATHGEN than IHCS (41% vs. 11% in controls, 74% vs. 29% in cases), smoking stratification and genotype-smoking interactions were evaluated. Suggestive association was found for GATA2 (rs2713604, p = 0.057, OR = 1.2). Among smokers, associations were found in CDGAP (rs10934490, p = 0.019, OR = 1.6) and KALRN (rs12637456, p = 0.011, OR = 2.0) and suggestive association was found in MYLK (rs16834871, p = 0.051, OR = 1.8, adjusting for gender). No SNP association was found among non-smokers, but smoking/SNP interactions were detected for CDGAP (rs10934491, p = 0.017) and KALRN (rs12637456, p = 0.010). Similar differences in SNP effects by smoking status were observed on re-analysis of CATHGEN. CAD associations were suggestive for GATA2 and among smokers significant post hoc associations were found in KALRN, MYLK, and CDGAP. Genetic risk conferred by some of these genes may be modified by smoking. Future CAD association studies of these and other genes should evaluate effect modification by smoking. [source] Are children of older fathers at risk for genetic disorders?ANDROLOGIA, Issue 4 2003A. Jung Summary. Genetic risks related to paternal age should be of interest to clinical andrologists counselling older men who wish to father a child. Theoretically, the number of (pre-meiotic) mitotic cell divisions during spermatogenesis and their remarkable increase with ageing compared with oogenesis would be in favour of genetic risks for the offspring of older men. But for numerical and structural chromosomal anomalies, such an influence of paternal age has not been found. However, in several autosomal dominant disorders affecting three specific genes (fibroblast growth factor receptor 2 and 3, RET proto-oncogene) the risk for a child to be affected increases with paternal age at time of birth. For other autosomal dominant ,X chromosomal dominant or recessive disorders, the available data are sufficient to support the concept of a positive relationship between paternal age and de novo gene mutations. Studies analysing gene sequences of affected children and their parents would allow further evaluation of this topic. The impact of paternal age on disorders with a complex genetic background, however, is a matter of debate. A significant effect of paternal age could not be shown for nonfamilial Alzheimer's disease, congenital heart defects, nonfamilial schizophrenia, acute lymphoblastic leukaemia or prostate cancer. [source] Depression and obesity: do shared genes explain the relationship?DEPRESSION AND ANXIETY, Issue 9 2010Niloofar Afari Ph.D. Abstract Background: Studies have found a modest association between depression and obesity, especially in women. Given the substantial genetic contribution to both depression and obesity, we sought to determine whether shared genetic influences are responsible for the association between these two conditions. Methods: Data were obtained from 712 monozygotic and 281 dizygotic female twin pairs who are members of the community-based University of Washington Twin Registry. The presence of depression was determined by self-report of doctor-diagnosed depression. Obesity was defined as body mass index of ,30,kg/m2, based on self-reported height and weight. Generalized estimating regression models were used to assess the age-adjusted association between depression and obesity. Univariate and bivariate structural equation models estimated the components of variance attributable to genetic and environmental influences. Results: We found a modest phenotypic association between depression and obesity (odds ratio=1.6, 95% confidence interval=1.2,2.1). Additive genetic effects contributed substantially to depression (57%) and obesity (81%). The best-fitting bivariate model indicated that 12% of the genetic component of depression is shared with obesity. Conclusions: The association between depression and obesity in women may be in part due to shared genetic risk for both conditions. Future studies should examine the genetic, environmental, social, and cultural mechanisms underlying the relationship between this association. Depression and Anxiety, 2010. © 2010 Wiley-Liss, Inc. [source] Meeting risk with resilience: high daily life reward experience preserves mental healthACTA PSYCHIATRICA SCANDINAVICA, Issue 2 2010N. Geschwind Geschwind N, Peeters F, Jacobs N, Delespaul P, Derom C, Thiery E, van Os J, Wichers M. Meeting risk with resilience: high daily life reward experience preserves mental health. Objective:, To examine prospectively whether high reward experience (the ability to generate positive affect boosts from pleasurable daily events) protects against affective symptoms and whether environmental or genetic risk factors moderate protective effects. Method:, At baseline, 498 female twins participated in an experience sampling study measuring reward experience in daily life. They also completed questionnaires on childhood adversity and recent stressful life events (SLE). Affective symptoms were measured at baseline and at four follow-ups using SCL-90 anxiety and depression subscales. Co-twin affective symptoms were used as indicators of genetic risk. Results:, Baseline reward experience did not predict follow-up affective symptoms, regardless of level of genetic risk. However, high reward experience was associated with reduced future affective symptoms after previous exposure to childhood adversity or recent SLE. Conclusion:, High daily life reward experience increases resilience after environmental adversity; modification of reward experience may constitute a novel area of therapeutic intervention. [source] Investigation of Adducin 2 (beta) DNA polymorphisms in genetic predisposition to diabetic nephropathy in Type 1 diabetesDIABETIC MEDICINE, Issue 8 2008D. Currie Abstract Aims Adducin 2 (beta) (ADD2) is a biological and positional candidate gene proposed to confer genetic risk for diabetic nephropathy. This study aimed to comprehensively investigate all common and putatively functional polymorphisms in the genomic region encompassing this gene. Methods Tag single nucleotide polymorphisms (n = 23) derived from phase II of the International HapMap Project and in silico functional variants (n = 2) were genotyped in 1467 White individuals from the British Isles (cases, n = 718; control subjects, n = 749) by a combination of Sequenom iPLEX and TaqMan technologies. Results ,2 analysis of genotype and allele frequencies in cases vs. control subjects revealed weak evidence for association of one variant at the 5% level of significance (rs10164951, P = 0.02). Adjusting for multiple testing in the present case,control collection negated this association. Conclusions We selected an appropriate subset of variants suitable for genetic investigations of the ADD2 gene and report the first investigation of polymorphisms in ADD2 with diabetic nephropathy. Our results suggest that common polymorphisms and putatively functional variants in the ADD2 gene do not strongly influence genetic susceptibility to diabetic nephropathy in this White population with Type 1 diabetes. [source] Low-risk HLA genotype in Type 1 diabetes is associated with less destruction of pancreatic B-cells 12 months after diagnosisDIABETIC MEDICINE, Issue 12 2007M. Spoletini Abstract Aims The role of human leukocyte antigen (HLA) genes in the susceptibility to Type 1 diabetes (T1DM) is well known. However, we do not know whether the degree of pancreatic B-cell destruction depends on different HLA genetic risk. The aim of this study was to analyse the influence of DRB1* and DQB1* genes on the rate of pancreatic B-cell loss in a prospective series of 120 consecutive newly diagnosed T1DM subjects in the first 12 months after diagnosis. Methods Patients were typed for HLA-DRB1* and DQB1* loci by a reverse line blot assay using an array of immobilized sequence-specific oligonucleotide probes. C-peptide, insulin requirement and glycated haemoglobin (HbA1c) were determined at diagnosis and every 3 months for 12 months. The variance of C-peptide as evidence of B-cell loss during follow-up was analysed using the general linear model for repeated-measures procedure. Results Fasting C-peptide in T1DM subjects with low HLA genetic risk was significantly higher when compared with subjects with moderate or high HLA genetic risk from time of diagnosis up to 12 months (P = 0.007 and P = 0.0002, respectively). Nonetheless, the changes in C-peptide levels over a 12-month period did not differ significantly between T1DM subjects with different HLA genetic risks. Conclusions Low-risk HLA genotype in T1DM is associated with less destruction of pancreatic B-cells up to 12 months after diagnosis. These results are useful when designing trials for therapies aimed to prevent the progression of B-cell destruction in recent-onset T1DM. [source] The genetics of autismACTA PSYCHIATRICA SCANDINAVICA, Issue 6 2001M. Lauritsen Objective: To review systematically the empirical evidence for the involvement of genetic risk factors in infantile autism. Method: We aimed at including all relevant papers written in English. We conducted a Medline search in September 2000. In addition we searched the reference lists of related papers. Results: A relatively small number of reports including family and twin studies, comorbidity, cytogenetic and molecular genetic studies were reviewed. Conclusion: As well family, twin, cytogenetic and molecular genetic studies supported the importance of genetic risk factors in infantile autism. In most individual cases probably at least a few gene variants simultaneously determine the genetic risk. Presently the most interesting chromosome regions concerning the aetiology of autism are chromosomes 7q31,35, 15q11,13 and 16p13.3 which have been suggested by different lines of genetic research. [source] From language to reading and dyslexia,DYSLEXIA, Issue 1 2001Margaret J. Snowling Abstract This paper reviews evidence in support of the phonological deficit hypothesis of dyslexia. Findings from two experimental studies suggest that the phonological deficits of dyslexic children and adults cannot be explained in terms of impairments in low-level auditory mechanisms, but reflect higher-level language weaknesses. A study of individual differences in the pattern of reading skills in dyslexic children rejects the notion of ,sub-types'. Instead, the findings suggest that the variation seen in reading processes can be accounted for by differences in the severity of individual children's phonological deficits, modified by compensatory factors including visual memory, perceptual speed and print exposure. Children at genetic risk who go on to be dyslexic come to the task of reading with poorly specified phonological representations in the context of a more general delay in oral language development. Their prognosis (and that of their unaffected siblings) depends upon the balance of strengths and difficulties they show, with better language skills being a protective factor. Taken together, these findings suggest that current challenges to the phonological deficit theory can be met. Copyright © 2001 John Wiley & Sons, Ltd. [source] Interplay of genetic risk factors and parent monitoring in risk for nicotine dependenceADDICTION, Issue 10 2009Li-Shiun Chen ABSTRACT Background Several studies have found replicable associations between nicotine dependence and specific variants in the nicotinic receptor genes CHRNA5(rs16969968) and CHRNA3(rs3743078). How these newly identified genetic risks combine with known environmental risks is unknown. This study examined whether the level of parent monitoring during early adolescence modified the risk of nicotine dependence associated with these genetic variants. Methods In a cross-sectional case,control study of US-based community sample of 2027 subjects, we use a systematic series of regression models to examine the effect of parent monitoring on risk associated with two distinct variants in the nicotinic receptor genes CHRNA5(rs16969968) and CHRNA3(rs3743078). Results Low parent monitoring as well as the previously identified genetic variants were associated with an increased risk of nicotine dependence. An interaction was found between the SNP(rs16969968) and parent monitoring (P = 0.034). The risk for nicotine dependence increased significantly with the risk genotype of SNP(rs16969968) when combined with lowest-quartile parent monitoring. In contrast, there was no evidence of an interaction between SNP(rs3743078) and parent monitoring (P = 0.80). Conclusions The genetic risk of nicotine dependence associated with rs16969968 was modified by level of parent monitoring, while the genetic risk associated with rs3743078 was not, suggesting that the increased risk due to some genes may be mitigated by environmental factors such as parent monitoring. [source] Timing of first alcohol use and alcohol dependence: evidence of common genetic influencesADDICTION, Issue 9 2009Carolyn E. Sartor ABSTRACT Aims To estimate the magnitude of genetic and environmental influences on timing of first alcohol use and alcohol dependence (AD) and to quantify the overlap in these influences across the two alcohol-related outcomes. Participants The sample consisted of 5382 twins (2691 complete pairs), aged 24,36 years, from the Australian Twin Registry. Measurements History of alcohol use and DSM-IV alcohol dependence were assessed by structured telephone interview. Findings In both sexes, the relationship between age at first alcohol use and risk for AD followed a linear trend, such that the highest rates of AD were observed in individuals who began drinking at an earlier than average age (14 years or younger). Heritability estimates for timing of first alcohol use and AD were 36% and 53%, respectively. Shared environmental factors accounted for 15% of variance in initiation. There was no evidence of shared environmental influences on AD. The genetic correlation between timing of first alcohol use and AD was 0.59. Conclusions Findings highlight the substantial role of genetics in the development of AD and the early manifestation of that genetic risk in the timing of alcohol use initiation which, unlike AD, is also influenced to a modest degree by shared environmental factors. The considerable overlap in heritable influences,and the virtual absence of overlap in individual-specific environmental influences,on initiation of alcohol use and AD indicates that the association between age at first drink and AD is attributable in large part to common genetic sources of variance. [source] Molecular mimicry in innate immunity?EUROPEAN JOURNAL OF IMMUNOLOGY, Issue 7 2008The viral RNA recognition receptor TLR7 accelerates murine lupus Abstract Toll-like receptors (TLR), such as TLR7, were first described as innate pathogen recognition receptors that trigger appropriate antimircrobial immune responses upon exposure to pathogen-associated molecules, e.g. viral ssRNA. In parallel to ongoing studies on TLR-biology, mounting experimental evidence suggests that endogenous RNA-related autoantigens may also activate dendritic cells (DC) and B cells through TLR7. TLR7-mediated DC activation, autoantibody secretion, lymphoproliferation, and autoimmune tissue injury, are frequently observed in various murine models of systemic lupus and lupus nephritis. A paper in the current issue of the European Journal of Immunology, provide striking experimental evidence for this concept; the authors show that the Y chromosome-linked autoimmune accelerating (Yaa) translocation from the X-chromosome, consisting of 16 genes including Tlr7, largely mediates the autoimmune phenotype via the duplication of Tlr7. This finding highlights the need to address the significance of TLR7 in human lupus in terms of both genetic risk and as a therapeutic option. See accompanying article: http://dx.doi.org/10.1002/eji.200838138 [source] Huntington's disease with onset ages greater than 60 yearsGERIATRICS & GERONTOLOGY INTERNATIONAL, Issue 1 2007Kunihiro Yoshida We examined five patients with late-onset Huntington's disease (HD), who developed chorea as an initial symptom at age 60 or later. The mean disease duration from the onset of chorea was approximately 8 years (range, 2,16 years). All carried expanded HD alleles with 39 or 40 CAG repeats. Cognitive or psychiatric decline was observed in four patients, the mean duration of the disease being approximately 10 years. One of them had been institutionalized in a nursing home undiagnosed for a long time. Late-onset HD patients with shorter repeat expansions may be overlooked in Japan. Non-disabling chorea, mild cognitive or psychiatric decline in such patients are sometimes unrecognized or misunderstood as aging-related phenomena, and do not come to medical attention. Considering the potential genetic risk to younger generations, however, genetic testing on such late-onset HD patients should be conducted with careful genetic counseling and psychological support for their family members. [source] Genetic susceptibility to tobacco smoke toxicity and chronic obstructive pulmonary diseaseGERIATRICS & GERONTOLOGY INTERNATIONAL, Issue 1 2002Shinji Teramoto Because elderly patients with chronic obstructive pulmonary disease are often overlooked, screening efforts are at the moment directed at higher risk subjects such as heavy smokers with obstructive airways disease. Because only 10,20% of heavy smokers developed symptomatic airflow obstruction, a different genetic susceptibility to cigarette smoke-lung injury is implicated in the pathogenesis of chronic obstructive pulmonary disease. Several candidate gene polymorphisms are proposed as the genetic risk for the development of chronic obstructive pulmonary disease. The current candidates are the polymorphisms in the 3, non-coding region of the ,1-antitypsin gene, ,1-antichymotrypsin gene, tumor necrosis factor- , gene, microsomal epoxide hydrolase gene, and glutathione S- transferase P1 gene, and microsatellite polymorphism in the heme oxygenase-1 gene promoter. However, the results are variously reported between Japanese and Caucasians. The association studies of the polymorphisms with chronic obstructive pulmonary disease require further confirmation in different ethnic groups by other researchers using a large population. The current strategy and pitfalls of the gene explorations of chronic obstructive pulmonary disease are discussed. [source] Neural connectivity as an intermediate phenotype: Brain networks under genetic controlHUMAN BRAIN MAPPING, Issue 7 2009Andreas Meyer-Lindenberg Abstract Recent evidence suggests that default mode connectivity characterizes neural states that account for a sizable proportion of brain activity and energy expenditure, and therefore represent a plausible neural intermediate phenotype. This implies the possibility of genetic control over systems-level connectivity features. Imaging genetics is an approach to combine genetic assessment with multimodal neuroimaging to discover neural systems linked to genetic abnormalities or variation. In the present contribution, we report results obtained from applying this strategy to both structural connectivity and functional connectivity data. Using data for serotonergic (5-HTTLPR, MAO-A) and dopaminergic (DARPP-32) genes as examples, we show that systems-level connectivity networks under genetic control can be identified. Remarkable similarities are observed across modalities and scales of description. Features of connectivity often better account for behavioral effects of genetic variation than regional parameters of activation or structure. These data provide convergent evidence for genetic control in humans over connectivity systems, whose characterization has promise for identifying neural systems mediating genetic risk for complex human behavior and psychiatric disease. Hum Brain Mapp, 2009. © 2009 Wiley-Liss, Inc. [source] Fronto-striatal dysfunction and potential compensatory mechanisms in male adolescents with fragile X syndromeHUMAN BRAIN MAPPING, Issue 6 2007Fumiko Hoeft Abstract Response inhibition is an important facet of executive function. Fragile X syndrome (FraX), with a known genetic etiology (fragile X mental retardation-1 (FMR1) mutation) and deficits in response inhibition, may be an ideal condition for elucidating interactions among gene-brain-behavior relationships. Functional magnetic resonance imaging (fMRI) studies have shown evidence of aberrant neural activity when individuals with FraX perform executive function tasks, though the specific nature of this altered activity or possible compensatory processes has yet to be elucidated. To address this question, we examined brain activation patterns using fMRI during a go/nogo task in adolescent males with FraX and in controls. The critical comparison was made between FraX individuals and age, gender, and intelligent quotient (IQ)-matched developmentally delayed controls; in addition to a control group of age and gender-matched typically developing individuals. The FraX group showed reduced activation in the right ventrolateral prefrontal cortex (VLPFC) and right caudate head, and increased contralateral (left) VLPFC activation compared with both control groups. Individuals with FraX, but not controls, showed a significant positive correlation between task performance and activation in the left VLPFC. This potential compensatory activation was predicted by the interaction between FMR1 protein (FMRP) levels and right striatal dysfunction. These results suggest that right fronto-striatal dysfunction is likely an identifiable neuro-phenotypic feature of FraX and that activation of the left VLPFC during successful response inhibition may reflect compensatory processes. We further show that these putative compensatory processes can be predicted by a complex interaction between genetic risk and neural function. Hum Brain Mapp, 2007. © 2007 Wiley-Liss, Inc. [source] Atypical antipsychotic-induced diabetes mellitus: an update on epidemiology and postulated mechanismsINTERNAL MEDICINE JOURNAL, Issue 7 2008S. Buchholz Abstract Diabetic ketoacidosis and hyperglycaemic hyperosmolar syndrome are rare, but potentially fatal complications of antipsychotic-associated hyperglycaemia. The mechanisms for this remain unclear, but are probably multifactorial. The suggested reasons include drug-induced weight gain and adiposity, development of the metabolic syndrome, antagonism of serotonin (5-hydroxytryptamine) receptors, drug-induced leptin resistance, dyslipidaemia mediated pancreatic ,-cell damage and hepatocyte transcription factor dysregulation. Patients with schizophrenia are known to be at a higher genetic risk of developing diabetes mellitus and cardiovascular disease. This review emphasizes a rare case of hyperosmolar hyperglycaemic syndrome in a young man with schizophrenia and discusses proposed mechanisms for the development of antipsychotic-associated diabetes mellitus. [source] Interaction of Implantable Defibrillator Therapy with Angiotensin-Converting Enzyme Deletion/Insertion PolymorphismJOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY, Issue 10 2004MANINDER S. BEDI M.D. Introduction: The angiotensin-converting enzyme deletion allele (ACE D) decreases survival in patients with advanced heart failure. Whether the adverse impact on survival reflects an increased risk of pump failure or arrhythmic sudden death remains uncertain. If the ACE D genotype increases the risk of sudden death, implantable cardioverter defibrillator (ICD) therapy should diminish its negative impact. We sought to evaluate the effect of ICD therapy on ACE D genetic risk. Methods and Results: The Genetic Risk Assessment of Cardiac Events (GRACE) study enrolled 479 patients at the University of Pittsburgh between 1996 and 2001. Blood was genotyped for the ACE D/I (deletion/insertion) polymorphism. Of the 479 patients, 82 (77% male, 84% Caucasian, age 56 ± 11 years, 60% ischemic, left ventricular ejection fraction 0.23 ± 0.08) received an ICD and were selected for outcomes analysis (mean follow-up 871 ± 538 days). Transplant-free survival and survival alone were compared in ACE DD patients (n = 24, 29%) versus ACE DI/II patients (n = 58, 71%). Survival was significantly improved in ACE DI/II patients compared to those without an ICD (1 year: 93% vs 87%; 2 year: 89% vs 77%; P = 0.02) but not in ACE DD patients. Transplant-free survival among patients with an ICD was significantly worse in ACE DD versus ACE DI/II (1 year: 67% vs 88%, 2 year: 55% vs 80%, P = 0.03). Analysis of survival as a single endpoint revealed a similar result (1 year = 78% vs 94%; 2 year: 72% vs 88%; P = 0.05). ICD telemetry data showed a nonsignificant trend toward fewer individuals with arrhythmias in the ACE-DD group (46% vs 65%, P = 0.22) Conclusion: ICDs do not diminish the adverse influence of the ACE DD genotype on survival. This finding suggests that mortality in this high-risk genetic subset of patients is due to progression of heart failure rather than arrhythmic sudden death. [source] ,-thalassaemia carrier detection by ELISA: A simple screening strategy for developing countriesJOURNAL OF CLINICAL LABORATORY ANALYSIS, Issue 1 2005M. Shyla Ravindran Abstract The frequency of ,-thalassaemia in India ranges from 3.5% to 15% in the general population and of the 100,000 children born with thalassaemia major in the world, 10,000 are in India alone. Affected children do not die immediately, but treatment by regular transfusion is costly and leads to iron overload and death. Therefore, health services in lower-economic countries can sustain patients only if the numbers can be limited. Detecting carrier couples by simple blood test can prevent thalassaemia and at-risk couples can be identified and informed of their genetic risk before having children. A prevention programme including population screening, counselling, and prenatal diagnosis will markedly reduce the birth prevalence of affected individuals. Hemoglobin A2 (HbA2) measurement in human hemolysates has great significance, since its level can indicate ,-thalassaemia carrier status in otherwise healthy individuals. We have developed a rapid, simple, and inexpensive enzyme linked immunosorbent assay (ELISA) for the quantitation of HbA2, which can be used in carrier screening programmes in developing countries like India. In a limited trial for ,-thalassaemia carrier screening, the results obtained with ELISAs were compared with those obtained with the microcolumn chromatography method (r=0.89). J. Clin. Lab. Anal. 19:22,25, 2005. © 2005 Wiley-Liss, Inc. [source] The Relationship Between Genetic Influences on Alcohol Dependence and on Patterns of Alcohol ConsumptionALCOHOLISM, Issue 6 2010Kenneth S. Kendler Background:, Genetic factors impact substantially both on alcohol consumption (AC) and on the risk for alcohol dependence (AD). However, we know little about the degree to which measures of AC index the genetic risk for AD. Methods:, We assessed a lifetime history of AD by DSM-IV criteria and four measures of AC at the time of heaviest drinking (drink frequency, regular quantity, maximum quantity, and drunk frequency) in 5,073 adult twins from same-sex pairs from the Virginia Twin Registry. Structural models were fitted using Mx. Results:, We found evidence for different genetic structure in the sexes. In women, genetic risk for AD and for the four measures of AC was entirely shared. In men, the AC measures captured 85% of the genetic risk for AD. In women, the genetic relationship with AD was strongest for drunk frequency and in men for both drunk frequency and regular quantity. Conclusions:, In a population-based sample of twins, four relatively simple measures of AC obtained for the time of lifetime heaviest drinking were able to capture all (in women) or a very large proportion (in men) of the genetic risk for the complex multi-dimensional construct of AD. If replicated, these results have practical implications for studies aiming to assess genetic risk for AD. [source] Association Between Sweet Preference and Paternal History of Alcoholism in Psychiatric and Substance Abuse PatientsALCOHOLISM, Issue 12 2003A. B. Kampov-Polevoy Background: The relationship between preference for stronger sweet solutions and propensity to excessive alcohol drinking is supported by both animal and human studies. This study was designed to test the hypothesis that sweet preference is associated with the genetic risk of alcoholism as measured by a paternal history of alcoholism. Methods: Participants were 180 patients admitted to a residential treatment program for the treatment of alcoholism, drug dependence, or psychiatric conditions. In addition to a routine medical examination, patients completed the standard sweet preference test twice (on the 9th and 24th days after admission), and the family history of alcoholism was evaluated. Results: Sweet preference was shown to be stable over time. It was strongly associated with a paternal history of alcoholism, with family history,positive patients approximately 5 times more likely to prefer stronger sweet solutions than family history,negative subjects. Such factors as dependence on alcohol, cocaine, opiates, cannabis, other drugs (including prescription drugs), and tobacco smoking, as well as demographics (gender and age), did not significantly interfere with association between sweet preference and paternal history of alcoholism. Conclusions: These findings provide some support for the hypothesis that preference for stronger sweet solutions is associated with a genetic predisposition to alcoholism as measured by a paternal history of alcoholism. [source] Asymptomatic individuals at genetic risk of haemochromatosis take appropriate steps to prevent disease related to iron overloadLIVER INTERNATIONAL, Issue 3 2008Katrina J. Allen Abstract Background/Aims: If community screening for hereditary haemochromatosis is to be considered, compliance with preventative measures and absence of significant psychological morbidity must be demonstrated. Methods: Workplace screening for the HFE C282Y mutation and then clinical care for C282Y homozygotes was instituted. Data were collected on understanding of test results, perceived health status and anxiety for C282Y homozygotes compared with controls. Uptake of clinical care, compliance and response to treatment and changes in diet were monitored for up to 4 years for C282Y homozygotes. Results: After 11 307 individuals were screened, 40/47 (85%) newly identified C282Y homozygotes completed questionnaires 12 months after diagnosis compared with 79/126 (63%) of controls. Significantly more C282Y homozygotes correctly remembered their test result compared with controls (95 vs 51%, P<0.0001). No significant difference in perceived health status was observed within or between the two groups at 12 months compared with baseline. Anxiety levels decreased significantly for C282Y homozygotes at 12 months compared with before testing (P<0.05). Forty-five of the 47 (95.8%) C282Y homozygotes accessed clinical care for at least 12 months. All 22 participants requiring therapeutic venesection complied with treatment for at least 12 months (range 12,47 months). Conclusion: Individuals at a high genetic risk of developing haemochromatosis use clinical services appropriately, maintain their health and are not ,worried well'. Population genetic screening for haemochromatosis can be conducted in the work place in a way that is acceptable and beneficial to participants. [source] Parent responses to participation in genetic screening for diabetes riskPEDIATRIC DIABETES, Issue 4 2004Barbro Lernmark Abstract:, Screening for type 1 diabetes (T1DM) risk in newborns has little negative emotional impact on mothers. In this study, the impact on the mother and the father was evaluated both in the general population and in families with diabetes. All parents with a newborn in Skĺne, Sweden, were invited to a screening for T1DM risk in their children (the Diabetes Prediction in Skĺne (DiPiS)). Blood was obtained at delivery from the mother and the child. When the child was 2 months old, parents gave written consent and filled out questionnaires, but were not informed about the genetic risk. Of the 10 538 invited families, 6831 (64.8%) consented and 806 (7.7%) declined participation. Five questions addressing both parents were filled out by 6676 (63.4%) mothers and 6099 (57.8%) fathers. In 146/6676 (2.2%) families, one family member had diabetes (D-families). Participation in DiPiS did not affect most parents and the majority was satisfied with the information. The majority of parents (28.9%) were reassured and only 1.1% (140/12 670) reported increased worries because of participation, compared to 2.8% of the mothers in D-families. Parents in D-families more often ascribed diabetes risk to their child as well as the risk being higher. Mothers and fathers differed in their answers on four of the five study questions, with mothers being more satisfied with the information, reporting more knowledge of diabetes, estimating lower risk of their child to get diabetes, but reporting more worries of possible future chronic disease in the child. Parents with lower education, being born abroad, or being younger who reported worries of chronic disease in the child were also reassured by participation in the study. These results confirm that screening for T1DM risk in newborns does not create worries in most parents, but stress that fathers differ from mothers in opinions and reactions, that parents' reactions are affected by diabetes in the family, and that demographic factors might be important for the parents' reports. [source] Attitudes to prenatal and preimplantation diagnosis in Saudi parents at genetic riskPRENATAL DIAGNOSIS, Issue 11 2006Ayman Alsulaiman Abstract Background Prenatal diagnosis (PND) is only available for severe abnormality in Saudi Arabia, and preimplantation genetic diagnosis (PGD) has been proposed as a valuable alternative. The acceptability of PGD is unexplored, and may ultimately determine the value of this technology in Saudi Arabia. This study reports attitudes towards PND and PGD of Saudi couples offered genetic counselling following the birth of a child with a single gene or chromosomal condition. Methods Thirty couples attending the King Faisal Specialist Hospital and Research Centre in Riyadh were interviewed using a semi-structured questionnaire. One couple had previous experience of PND and none had experience of PGD or IVF. Results Eight of the 30 couples (27%) would only accept PGD; four (13%) only PND; three (10%) either technology; the remainder would accept neither test, or were unsure. The main concerns of those who would accept neither technology were related to personal religious views. Specific concerns about PGD related to the IVF procedure, the risk of multiple pregnancies, the chance of mistakes and the chance of not getting pregnant. A high proportion of couples (six out of seven; 86%) who had a child with thalassaemia expressed interest in PGD, and all would be prepared to use technology to avoid having an affected child. Views were more mixed for the other conditions. Conclusion PGD is acceptable to many couples and for some, it represents a valuable alternative to PND. However, parents' concerns are complex, and the acceptability of different reproductive technologies must be established on an individual basis. Copyright © 2006 John Wiley & Sons, Ltd. [source] Apolipoproteins and , Amyloid Transport PathwayPSYCHOGERIATRICS, Issue 3 2002Kouzin Kamino Abstract: Cholesterol metabolism has been viewed as an important step in the development of Alzheimer's disease, since it was shown that the ,4 allele of apolipoprotein E (APOE) gene is a genetic risk and modifies age-at-onset of Alzheimer's disease. Although the knowledge of the effect of cholesterol in the neuronal cell has been recently accumulated, the link between systemic and brain cholesterol metabolism remains to be elucidated. Lipoproteins in cerebrospinal fluid (CSF) are fractionated only to high-density lipoprotein (HDL), and contain apolipoprotein (apo) A-I, E, A-II, and J. Whereas apoE is produced in the brain, apoA-I and apoA-II in cerebrospinal fluid, the major components of plasma HDL cholesterol, originate from plasma. Plasma HDL is thought to act in reverse cholesterol transport, and in vitro experiments indicated that these apolipoproteins and albumin show a high affinity binding to , amyloid. In patients with Alzheimer's disease, plasma apoA-I and apoA-II levels are significantly decreased, which is possibly related to the deposition of , amyloid in the brain, and to the , amyloid transport pathway. [source] Communication and decision-making about seeking inherited cancer risk information: findings from female survivor-relative focus groupsPSYCHO-ONCOLOGY, Issue 3 2006Suzanne Mellon Abstract Dramatic advances in cancer genetics and identification of germline mutations in cancer genes such as BRCA1 and BRCA2 have led to new options in genetic risk assessment for families with histories of breast and ovarian cancer. However, little research has been carried out with individuals and their families regarding how cancer risk information is communicated within families and factors that may affect individuals and family members making informed decisions about their health. This study explored participants' knowledge of cancer risk, their perceptions and concerns regarding inherited cancer risk information, family communication patterns, and factors that may affect their decision to learn about inherited cancer risk in their families. Nine focus groups of family dyads were conducted (N=39) consisting of breast or ovarian cancer patients and close female relatives. All transcribed interviews were analyzed using qualitative software. Key findings showed diversity in how families communicated and made decisions about their health, persistent worry for their families, lack of knowledge about inherited cancer, vigilance in watching their health, and barriers present in communicating about genetic risk. Results from this study support inclusion of family members in addressing inherited cancer risk information and contextual family factors critical to consider in potentially high risk families. Copyright © 2005 John Wiley & Sons, Ltd. [source] Error rate on the antisaccade task: Heritability and developmental change in performance among preadolescent and late-adolescent female twin youthPSYCHOPHYSIOLOGY, Issue 5 2002Stephen M. Malone We examined heritability of error rate on the antisaccade task among female twin youths. This task appears to be sensitive to prefrontal functioning, providing a measure of individual differences in inhibitory control associated with genetic risk for schizophrenia. The sample consisted of 674 11-year-olds and 616 17-year-olds, comprising the two cohorts of female twins from the Minnesota Twin Family Study, a population-based investigation of substance abuse and related psychopathology. We used biometric model-fitting methods to determine the relative magnitude of genetic and environmental influences on performance. In both age cohorts, the best fitting model contained additive genes and nonshared environment. Despite substantial age-related differences in mean performance levels (effect size = .81), additive genes accounted for greater than half the variance in performance in both age cohorts. These results are consistent with the hypothesis that antisaccade error rate might serve as an endophenotype for behavior disorders reflecting frontal lobe dysfunction or problems with inhibitory control. [source] Which duration of postsaccadic slowing identifies anticipatory saccades during smooth pursuit eye movements?PSYCHOPHYSIOLOGY, Issue 2 2001Randal G. Ross Increased frequency of anticipatory saccades during smooth pursuit eye movements is a potential marker of genetic risk for schizophrenia. Postsaccadic slowing criteria are used to separate anticipatory from other types of saccades. However, the necessary duration of slowed pursuit required to identify an anticipatory saccade remains undetermined. We explored the effect of various postsaccadic slowing duration criteria on effect size in a comparison of younger and older schizophrenic and normal adults. For large anticipatory saccades, varying the duration of postsaccadic slowing criteria did not notably change effect size. For smaller leading saccades, a limited 50-ms duration postsaccadic slowing criterion produced the largest effect size (1.54), and maintained a similar effect size across a broad age range. Leading saccades with a limited duration postsaccadic slowing criteria are a possible marker of genetic risk for schizophrenia. [source] Genetic and environmental influences on the transmission of parental depression to children's depression and conduct disturbance: an extended Children of Twins studyTHE JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY AND ALLIED DISCIPLINES, Issue 6 2010Judy L. Silberg Background:, Despite the increased risk of depression and conduct problems in children of depressed parents, the mechanism by which parental depression affects their children's behavioral and emotional functioning is not well understood. The present study was undertaken to determine whether parental depression represents a genuine environmental risk factor in children's psychopathology, or whether children's depression/conduct can be explained as a secondary consequence of the genetic liability transmitted from parents to their offspring. Methods:, Children of Twins (COT) data collected on 2,674 adult female and male twins, their spouses, and 2,940 of their children were used to address whether genetic and/or family environmental factors best account for the association between depression in parents and depression and conduct problems in their children. Data collected on juvenile twins from the Virginia Twin Study of Adolescent Behavioral Development (VTSABD) were also included to estimate child-specific genetic and environmental influences apart from those effects arising from the transmission of the parental depression itself. The fit of alternative Children of Twin models were evaluated using the statistical program Mx. Results:, The most compelling model for the association between parental and juvenile depression was a model of direct environmental risk. Both family environmental and genetic factors accounted for the association between parental depression and child conduct disturbance. Conclusions:, These findings illustrate how a genetically mediated behavior such as parental depression can have both an environmental and genetic impact on children's behavior. We find developmentally specific genetic factors underlying risk to juvenile and adult depression. A shared genetic liability influences both parental depression and juvenile conduct disturbance, implicating child conduct disturbance (CD) as an early indicator of genetic risk for depression in adulthood. In summary, our analyses demonstrate differences in the impact of parental depression on different forms of child psychopathology, and at various stages of development. [source] | ||||||||||||||||||||||||||||||||||