997 resultados para Twin Data


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We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

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We examined early social influences across stages of smoking within the context of a twin study using an environmental exposure specific to smoking: whether twins started smoking at the same time (simultaneous smoking initiation: SSI). We expected that SSI would be a good index of shared social influences on smoking initiation. Rates of SSI were indeed significantly higher in MZ twins and in twins who shared peers and classes, as well as in male twins. With the exception of regular smoking in females, we found no significant difference in estimates of genetic and environmental parameters between SSI and non-SSI pairs for any of the smoking measures that we examined (DSM-IV and Fagerstrom HSI measures of nicotine dependence; DSM-IV nicotine withdrawal; heavy smoking; and in males, regular smoking). For regular smoking in females, allowing for additional shared environmental influences associated with SSI only modestly reduced our estimates of additive genetic variance (56% vs. 68%). These results indicate the important social influences that may occur for smoking initiation do not appear to seriously bias estimates of genetic effects on later stages of smoking.

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Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.

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A major component of variation in body height is due to genetic differences, but environmental factors have a substantial contributory effect. In this study we aimed to analyse whether the genetic architecture of body height varies between affluent western societies. We analysed twin data from eight countries comprising 30,111 complete twin pairs by using the univariate genetic model of the Mx statistical package. Body height and zygosity were self-reported in seven populations and measured directly in one population. We found that there was substantial variation in mean body height between countries; body height was least in Italy (177 cm in men and 163 cm in women) and greatest in the Netherlands (184 cm and 171 cm, respectively). In men there was no corresponding variation in heritability of body height, heritability estimates ranging from 0.87 to 0.93 in populations under an additive genes/unique environment (AE) model. Among women the heritability estimates were generally lower than among men with greater variation between countries, ranging from 0.68 to 0.84 when an additive genes/shared environment/unique environment (ACE) model was used. In four populations where an AE model fit equally well or better, heritability ranged from 0.89 to 0.93. This difference between the sexes was mainly due to the effect of the shared environmental component of variance, which appears to be more important among women than among men in our study populations. Our results indicate that, in general, there are only minor differences in the genetic architecture of height between affluent Caucasian populations, especially among men.

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Neurodevelopmental disruptions caused by obstetric complications play a role in the etiology of several phenotypes associated with neuropsychiatric diseases and cognitive dysfunctions. Importantly, it has been noticed that epigenetic processes occurring early in life may mediate these associations. Here, DNA methylation signatures at IGF2 (insulin-like growth factor 2) and IGF2BP1-3 (IGF2-binding proteins 1-3) were examined in a sample consisting of 34 adult monozygotic (MZ) twins informative for obstetric complications and cognitive performance. Multivariate linear regression analysis of twin data was implemented to test for associations between methylation levels and both birth weight (BW) and adult working memory (WM) performance. Familial and unique environmental factors underlying these potential relationships were evaluated. A link was detected between DNA methylation levels of two CpG sites in the IGF2BP1 gene and both BW and adult WM performance. The BW-IGF2BP1 methylation association seemed due to non-shared environmental factors influencing BW, whereas the WM-IGF2BP1 methylation relationship seemed mediated by both genes and environment. Our data is in agreement with previous evidence indicating that DNA methylation status may be related to prenatal stress and later neurocognitive phenotypes. While former reports independently detected associations between DNA methylation and either BW or WM, current results suggest that these relationships are not confounded by each other.

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Investigators interested in whether a disease aggregates in families often collect case-control family data, which consist of disease status and covariate information for families selected via case or control probands. Here, we focus on the use of case-control family data to investigate the relative contributions to the disease of additive genetic effects (A), shared family environment (C), and unique environment (E). To this end, we describe a ACE model for binary family data and then introduce an approach to fitting the model to case-control family data. The structural equation model, which has been described previously, combines a general-family extension of the classic ACE twin model with a (possibly covariate-specific) liability-threshold model for binary outcomes. Our likelihood-based approach to fitting involves conditioning on the proband’s disease status, as well as setting prevalence equal to a pre-specified value that can be estimated from the data themselves if necessary. Simulation experiments suggest that our approach to fitting yields approximately unbiased estimates of the A, C, and E variance components, provided that certain commonly-made assumptions hold. These assumptions include: the usual assumptions for the classic ACE and liability-threshold models; assumptions about shared family environment for relative pairs; and assumptions about the case-control family sampling, including single ascertainment. When our approach is used to fit the ACE model to Austrian case-control family data on depression, the resulting estimate of heritability is very similar to those from previous analyses of twin data.

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Biometrical genetics is the science concerned with the inheritance of quantitative traits. In this review we discuss how the analytical methods of biometrical genetics are based upon simple Mendelian principles. We demonstrate how the phenotypic covariance between related individuals provides information on the relative importance of genetic and environmental factors influencing that trait, and how factors such as assortative mating, gene-environment correlation and genotype-environment interaction complicate such interpretations. Twin and adoption studies are discussed as well as their assumptions and limitations. Structural equation modeling (SEM) is introduced and we illustrate how this approach may be applied to genetic problems. In particular, we show how SEM can be used to address complicated issues such as analyzing the causes of correlation between traits or determining the direction of causation (DOC) between variables. (C) 2002 Elsevier Science B.V. All rights reserved.

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Este tutorial pretende apresentar, de forma sumária: 1) a importância dos estudos gemelares em Educação Física e Ciências do Desporto; 2) a estrutura básica deste tipo de delineamento; 3) as etapas da análise descritiva inicial; 4) os procedimentos de análise em grau crescente de complexidade - da análise de variância, à modelação de estruturas de covariância; 5) bem como a relevância da exploração da disocordância intrapar de gêmeos monozigóticos. Esta processologia, baseada num tutorial, recorrerá aos valores do fenótipo índice de atividade física nos tempos de lazer, com base numa amostra de 207 pares de gêmeos mono e dizigóticos. Todas as etapas da análise são comentadas e será interpretado o signifi cado dos resultados, salientando o fato do fenótipo em causa ser explicado pelos fatores genéticos em cerca de 63%.

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This article applies methods of latent class analysis (LCA) to data on lifetime illicit drug use in order to determine whether qualitatively distinct classes of illicit drug users can be identified. Self-report data on lifetime illicit drug use (cannabis, stimulants, hallucinogens, sedatives, inhalants, cocaine, opioids and solvents) collected from a sample of 6265 Australian twins (average age 30 years) were analyzed using LCA. Rates of childhood sexual and physical abuse, lifetime alcohol and tobacco dependence, symptoms of illicit drug abuse/dependence and psychiatric comorbidity were compared across classes using multinomial logistic regression. LCA identified a 5-class model: Class 1 (68.5%) had low risks of the use of all drugs except cannabis; Class 2 (17.8%) had moderate risks of the use of all drugs; Class 3 (6.6%) had high rates of cocaine, other stimulant and hallucinogen use but lower risks for the use of sedatives or opioids. Conversely, Class 4 (3.0%) had relatively low risks of cocaine, other stimulant or hallucinogen use but high rates of sedative and opioid use. Finally, Class 5 (4.2%) had uniformly high probabilities for the use of all drugs. Rates of psychiatric comorbidity were highest in the polydrug class although the sedative/opioid class had elevated rates of depression/suicidal behaviors and exposure to childhood abuse. Aggregation of population-level data may obscure important subgroup differences in patterns of illicit drug use and psychiatric comorbidity. Further exploration of a 'self-medicating' subgroup is needed.

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Ordinal and comparative rating measures of mosquito attraction and mosquito bite frequency and symptoms were administered in a self-report questionnaire format to a sample of 197 monozygotic and 326 dizygotic Australian adolescent twin pairs at age 12 between 1992 and 1999, in order to investigate the environmental and possibly genetic determinants of variation between individuals. Repeat measures were obtained from the twin pairs at age 14. Ordinal variable measures, although providing some support for genetic effects on mosquito susceptibility, were affected by low repeatability. However, analysis of a comparative rating variable compared with your twin, who is bitten by mosquitoes more often? indicated a strong genetic influence on frequency of being bitten by mosquitoes, with no significant differences observed between males and females. Comparative rating questionnaire items are a potentially valuable tool for complementing and improving the results obtained from more conventional absolute measures. (C) 2000 Wiley-Liss, Inc.

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The newly inaugurated Navile District of the University of Bologna is a complex created along the Navile canal, that now houses various teaching and research activities for the disciplines of Chemistry, Industrial Chemistry, Pharmacy, Biotechnology and Astronomy. A Building Information Modeling system (BIM) gives staff of the Navile campus several ways to monitor buildings in the complex throughout their life cycle, one of which is the ability to access real-time environmental data such as room temperature, humidity, air composition, and more, thereby simplifying operations like finding faults and optimizing environmental resource usage. But smart features at Navile are not only available to the staff: AlmaMap Navile is a web application, whose development is documented in this thesis, that powers the public touch kiosks available throughout the campus, offering maps of the district and indications on how to reach buildings and spaces. Even if these two systems, BIM and AlmaMap, don't seem to have many similarities, they share the common intent of promoting awareness for informed decision making in the campus, and they do it while relying on web standards for communication. This opens up interesting possibilities, and is the idea behind AlmaMap Navile 2.0, an app that interfaces with the BIM system and combines real-time sensor data with a comfort calculation algorithm, giving users the ability not just to ask for directions to a space, but also to see its comfort level in advance and, should they want to, check environmental measurements coming from each sensor in a granular manner. The end result is a first step towards building a smart campus Digital Twin, that can support all the people who are part of the campus life in their daily activities, improving their efficiency and satisfaction, giving them the ability to make informed decisions, and promoting awareness and sustainability.

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The aim of this study is to test the feasibility and reproducibility of diffusion-weighted magnetic resonance imaging (DW-MRI) evaluations of the fetal brains in cases of twin-twin transfusion syndrome (TTTS). From May 2011 to June 2012, 24 patients with severe TTTS underwent MRI scans for evaluation of the fetal brains. Datasets were analyzed offline on axial DW images and apparent diffusion coefficient (ADC) maps by two radiologists. The subjective evaluation was described as the absence or presence of water diffusion restriction. The objective evaluation was performed by the placement of 20-mm(2) circular regions of interest on the DW image and ADC maps. Subjective interobserver agreement was assessed by the kappa correlation coefficient. Objective intraobserver and interobserver agreements were assessed by proportionate Bland-Altman tests. Seventy-four DW-MRI scans were performed. Sixty of them (81.1%) were considered to be of good quality. Agreement between the radiologists was 100% for the absence or presence of diffusion restriction of water. For both intraobserver and interobserver agreement of ADC measurements, proportionate Bland-Altman tests showed average percentage differences of less than 1.5% and 95% CI of less than 18% for all sites evaluated. Our data demonstrate that DW-MRI evaluation of the fetal brain in TTTS is feasible and reproducible.

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The growing interest in solar twins is motivated by the possibility of comparing them directly to the Sun. To carry on this kind of analysis, we need to know their physical characteristics with precision. Our first objective is to use asteroseismology and interferometry on the brightest of them: 18 Sco. We observed the star during 12 nights with HARPS for seismology and used the PAVO beam-combiner at CHARA for interferometry. An average large frequency separation 134.4+/-0.3 mu Hz and angular and linear radiuses of 0.6759 +/- 0.0062 mas and 1.010 +/- 0.009 R(circle dot) were estimated. We used these values to derive the mass of the star, 1.02 +/- 0.03 M(circle dot).

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Intelligence (IQ) can be seen as the efficiency of mental processes or cognition, as can basic information processing (IP) tasks like those used in our ongoing Memory, Attention and Problem Solving (MAPS) study. Measures of IQ and IP are correlated and both have a genetic component, so we are studying how the genetic variance in IQ is related to the genetic variance in IP. We measured intelligence with five subscales of the Multidimensional Aptitude Battery (MAB). The IP tasks included four variants of choice reaction time (CRT) and a visual inspection time (IT). The influence of genetic factors on the variances in each of the IQ, IP, and IT tasks was investigated in 250 identical and nonidentical twin pairs aged 16 years. For a subset of 50 pairs we have test–retest data that allow us to estimate the stability of the measures. MX was used for a multivariate genetic analysis that addresses whether the variance in IQ and IP measures is possibly mediated by common genetic factors. Analyses that show the modeled genetic and environmental influences on these measures of cognitive efficiency will be presented and their relevance to ideas on intelligence will be discussed.

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Few studies have focused on the language acquisition of higher multiple birth sets. In this study, the communication skills of 51 triplet children are described. The measures used were: mean length of utterance; type-token ratio; conversational nets; phoneme repertoire; and number of different types of phonological processes used. The data gained were used to compare the communication skills of triplets with those of twins, singletons and normative data available in the literature. Siblings within triplet sets were also compared using language samples obtained from adult-child interactions and when the three children were playing together. The results indicated that the triplets' early communication skills were different from those of both singletons and twins. The triplets' difficulties included delayed syntactic development, limited use of different language functions and delayed phonological development. In contrast, twins' communication profile is characterised by disordered phonological development.