231 resultados para 110311 Medical Genetics (excl. Cancer Genetics)


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Background: The low-activity variant of the aldehyde dehydrogenase 2 (ALDH2) gene found in East Asian populations leads to the alcohol flush reaction and reduces alcohol consumption and risk of alcohol dependence (AD). We have tested whether other polymorphisms in the ALDH2 gene have similar effects in people of European ancestry. Methods: Serial measurements of blood and breath alcohol, subjective intoxication, body sway, skin temperature, blood pressure, and pulse were obtained in 412 twins who took part in an alcohol challenge study. Participants provided data on alcohol reactions, alcohol consumption, and symptoms related to AD at the time of the study and subsequently. Haplotypes based on 5 single-nucleotide polymorphisms (SNPs) were used in tests of the effects of variation in the ALDH2 gene on alcohol metabolism and alcohol's effects. Results: The typed SNPs were in strong linkage disequilibrium and 2 complementary haplotypes comprised 83% of those observed. Significant effects of ALDH2 haplotype were observed for breath alcohol concentration, with similar but smaller and nonsignificant effects on blood alcohol. Haplotype-related variation in responses to alcohol, and reported alcohol consumption, was small and not consistently in the direction predicted by the effects on alcohol concentrations. Conclusions: Genetic variation in ALDH2 affects alcohol metabolism in Europeans. However, the data do not support the hypothesis that this leads to effects on alcohol sensitivity, consumption, or risk of dependence.

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Background: The objective was to determine whether the pattern of environmental and genetic influences on deviant personality scores differs from that observed for the normative range of personality, comparing results in adolescent and adult female twins. Methods: A sample of 2,796 female adolescent twins ascertained from birth records provided Junior Eysenck Personality Questionnaire data. The average age of the sample was 17.0 years ( S. D. 2.3). Genetic analyses of continuous and extreme personality scores were conducted. Results were compared for 3,178 adult female twins. Results: Genetic analysis of continuous traits in adolescent female twins were similar to findings in adult female twins, with genetic influences accounting for between 37% and 44% of the variance in Extraversion (Ex), Neuroticism (N), and Social Non-Conformity (SNC), with significant evidence of shared environmental influences (19%) found only for SNC in the adult female twins. Analyses of extreme personality characteristics, defined categorically, in the adolescent data and replicated in the adult female data, yielded estimates for high N and high SNC that deviated substantially (p < .05) from those obtained in the continuous trait analyses, and provided suggestive evidence that shared family environment may play a more important role in determining personality deviance than has been previously found when personality is viewed continuously. However, multiple-threshold models that assumed the same genetic and environmental determinants of both normative range variation and extreme scores gave acceptable fits for each personality dimension. Conclusions: The hypothesis of differences in genetic or environmental factors responsible for N and SNC among female twins with scores in the extreme versus normative ranges was partially supported, but not for Ex.

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Background: Plasma cholinesterase activity is known to be correlated with plasma triglycerides, HDL- and LDL-cholesterol, and other features of the metabolic syndrome. A role in triglyceride metabolism has been proposed. Genetic variants that decrease activity have been studied extensively, but the factors contributing to overall variation in the population are poorly understood. We studied plasma cholinesterase activity in a sample of 2200 adult twins to assess covariation with cardiovascular risk factors and components of the metabolic syndrome, to determine the degree of genetic effects on enzyme activity, and to search for quantitative trait loci affecting activity. Methods and Results: Cholinesterase activity was lower in women than in men before the age of 50, but increased to activity values similar to those in males after that age. There were highly significant correlations with variables associated with the metabolic syndrome: plasma triglyceride, HDL- and LDL-cholesterol, apolipoprotein B and E, urate, and insulin concentrations; gamma-glutamyltransferase and aspartate and alanine aminotransferase activities; body mass index; and blood pressure. The heritability of plasma cholinesterase activity was 65%. Linkage analysis with data from the dizygotic twin pairs showed suggestive linkage on chromosome 3 at the location of the cholinesterase WHO gene and also on chromosome 5. Conclusions: Our results confirm and extend the connection between cholinesterase, cardiovascular risk factors, and metabolic syndrome. They establish a substantial heritability for plasma cholinesterase activity that might be attributable to variation near the structural gene and at an independent locus. (c) 2006 American Association for Clinical Chemistry.

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Background: Intermediate phenotypes are often measured as a proxy for asthma. It is largely unclear to what extent the same set of environmental or genetic factors regulate these traits. Objective: Estimate the environmental and genetic correlations between self-reported and clinical asthma traits. Methods: A total of 3073 subjects from 802 families were ascertained through a twin proband. Traits measured included self-reported asthma, airway histamine responsiveness (AHR), skin prick response to common allergens including house dust mite (Dermatophagoides pteronyssinus [D. pter]), baseline lung function, total serum immunoglobulin E (IgE) and eosinophilia. Bivariate and multivariate analyses of eight traits were performed with adjustment for ascertainment and significant covariates. Results: Overall 2716 participants completed an asthma questionnaire and 2087 were clinically tested, including 1289 self-reported asthmatics (92% previously diagnosed by a doctor). Asthma, AHR, markers of allergic sensitization and eosinophilia had significant environmental correlations with each other (range: 0.23-0.89). Baseline forced expiratory volume in 1 s (FEV1) showed low environmental correlations with most traits. Fewer genetic correlations were significantly different from zero. Phenotypes with greatest genetic similarity were asthma and atopy (0.46), IgE and eosinophilia (0.44), AHR and D. pter (0.43) and AHR and airway obstruction (-0.43). Traits with greatest genetic dissimilarity were FEV1 and atopy (0.05), airway obstruction and IgE (0.07) and FEV1 and D. pter (0.11). Conclusion: These results suggest that the same set of environmental factors regulates the variation of many asthma traits. In addition, although most traits are regulated to great extent by specific genetic factors, there is still some degree of genetic overlap that could be exploited by multivariate linkage approaches.

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The heritability of conscientiousness has been one of the least explored of the NEO PI domains. Here we focus on the facet scales of the conscientiousness domain, estimating both their heritability and their correlations with measures of IQ and academic achievement (Queensland Core Skills Test; QCST) in a sample of adolescent twins and their non-twin siblings. Our findings confirmed positive associations between IQ and the facets of Competence and Dutifulness (ranging 0.11-0.27), with academic achievement showing correlations of 0.27 and 0.15 with these same facets and 0.15 with Deliberation. All conscientiousness facets were influenced by genes (broad sense heritabilities ranging 0.18-0.49) and unique environment, but common environment was judged unimportant. A multivariate genetic analysis including Competence, Dutifulness, IQ (verbal, performance) and QCST scores showed that common variance was primarily explained by a general additive genetic factor (loadings ranging 0.15-0.84). Future multivariate genetic analysis which incorporates Openness to Experience dimensions may improve the interpretation of these findings. (c) 2005 Elsevier Ltd. All rights reserved.

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The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036). The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within- family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will allow the estimation of genetic variation for disease susceptibility and quantitative traits that is free from confounding with non-genetic factors and will allow partitioning of genetic variation into additive and non-additive components.

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The aim of the study was to perform a genetic linkage analysis for eye color, for comparative data. Similarity in eye color of mono- and dizygotic twins was rated by the twins' mother, their father and/or the twins themselves. For 4748 twin pairs the similarity in eye color was available on a three point scale (not at all alike-somewhat alike-completely alike), absolute eye color on individuals was not assessed. The probability that twins were alike for eye color was calculated as a weighted average of the different responses of all respondents on several different time points. The mean probability of being alike for eye color was 0.98 for MZ twins (2167 pairs), whereas the mean probability for DZ twins was 0.46 (2537 pairs), suggesting very high heritability for eye color. For 294 DZ twin pairs genome-wide marker data were available. The probability of being alike for eye color was regressed on the average amount of IBD sharing. We found a peak LOD-score of 2.9 at chromosome 15q, overlapping with the region recently implicated for absolute ratings of eye color in Australian twins [Zhu, G., Evans, D. M., Duffy, D. L., Montgomery, G. W., Medland, S. E., Gillespie, N. A., Ewen, K. R., Jewell, M., Liew, Y. W., Hayward, N. K., Sturm, R. A., Trent, J. M., and Martin, N. G. (2004). Twin Res. 7:197-210] and containing the OCA2 gene, which is the major candidate gene for eye color [Sturm, R. A. Teasdale, R. D, and Box, N. F. (2001). Gene 277:49-62]. Our results demonstrate that comparative measures on relatives can be used in genetic linkage analysis.

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A genome-wide linkage scan of 795 microsatellite markers (761 autosomal, 34 X chromosome) was performed on Multidimensional Aptitude Battery subtests and verbal, performance and full scale scores, the WAIS-R Digit Symbol subtest, and two word-recognition tests (Schonell Graded Word Reading Test, Cambridge Contextual Reading Test) highly predictive of IQ. The sample included 361 families comprising 2-5 siblings who ranged in age from 15.7 to 22.2 years; genotype, but not phenotype, data were available for 81% of parents. A variance components analysis which controlled for age and sex effects showed significant linkage for the Cambridge reading test and performance IQ to the same region on chromosome 2, with respective LOD scores of 4.15 and 3.68. Suggestive linkage (LOD score > 2.2) for various measures was further supported on chromosomes 6, 7, 11, 14, 21 and 22. Where location of linkage peaks converged for IQ subtests within the same scale, the overall scale score provided increased evidence for linkage to that region over any individual subtest. Association studies of candidate genes, particularly those involved in neural transmission and development, will be directed to genes located under the linkage peaks identified in this study.

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Many twin studies have identified sex differences in the influence of genetic and environmental factors on smoking behaviors. We explore the evidence for sex differences for smoking initiation and cigarette consumption in a sample of Australian twin families, and extend these models to incorporate sex differences in linkage analyses for these traits. We further examine the impact of including or excluding non-smokers in genetic analyses of tobacco consumption. Accounting for sex differences improved linkage results in some instances. We identified one region suggestive of linkage on chromosome 11p12. This locus, as well as another region identified on chromosome 6p12, replicates regions identified in previous studies.

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Background Non-random mating affects population variation for substance use and dependence. Developmentally, mate selection leading to positive spousal correlations for genetic similarity may result in increased risk for substance use and misuse in offspring. Mate selection varies by cohort and thus, assortative mating in one generation may produce marked changes in rates of substance use in the next. We aim to clarify the mechanisms contributing to spousal similarity for cigarette smoking and alcohol consumption. Methods Using data from female twins and their male spouses, we fit univariate and bivariate twin models to examine the contribution of primary assortative mating and reciprocal marital interaction to spousal resemblance for regular cigarette smoking and nicotine dependence, and for regular alcohol use and alcohol dependence. Results We found that assortative mating significantly influenced regular smoking, regular alcohol use, nicotine dependence and alcohol dependence. The bivariate models for cigarette smoking and alcohol consumption also highlighted the importance of primary assortative mating on all stages of cigarette smoking and alcohol consumption, with additional evidence for assortative mating across the two stages of alcohol consumption. Conclusions Women who regularly used, and subsequently were dependent on cigarettes or alcohol were more likely to marry men with similar behaviors. After mate selection had occurred, one partner's cigarette or alcohol involvement did not significantly modify the other partner's involvement with these psychoactive substances.

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Motivation: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. Results: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

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Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

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Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD

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Marfan syndrome (MFS) is a multisystem disorder of connective tissue that is inherited in an autosomal dominant fashion, and results from mutations in the FBN1 gene on chromosome 15. Diagnosis is challenging as it requires definition of diverse clinical features and input from a variety of specialists. Genetic testing of FBN1 is time consuming, expensive and complex, and may not solve the diagnostic dilemma. Failure to make a diagnosis or making an inappropriate diagnosis of MFS has social, lifestyle and medical consequences for the individual as well as the family.

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Simultaneous analysis of handedness data from 35 samples of twins (with a combined sample size of 21,127 twin pairs) found a small but significant additive genetic effect accounting for 25.47% of the variance (95% confidence interval [CI] 15.69-29.51%). No common environmental influences were detected (C = 0.00; 95% Cl 0.00-7.67%), with the majority of the variance, 74.53%, explained by factors unique to the individual (95% Cl 70.49-78.67%). No significant heterogeneity was observed within studies that used similar methods to assess handedness, or across studies that used different methods. At an individual level the majority of studies had insufficient power to reject a purely unique environmental model due to insufficient power to detect familial aggregation. This lack of power is seldom mentioned within studies, and has contributed to the misconception that twin studies of handedness are not informative.