2,024 research outputs found

    Ovarian reserve and anti-Mullerian hormone (AMH) in mothers of dizygotic twins

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    This study aimed to explore if natural dizygotic (DZ) twinning is associated with earlier menopause and lower anti-Mullerian hormone (AMH) values. We investigated if advanced biological reproductive aging, which can be responsible for the multiple follicle growth in familial twinning, is similar to mechanisms that occur in normal ovarian aging, reflected by earlier menopause in mothers of DZ twins and lower levels of AMH. A total of 16 mothers of DZ twins enrolled with the Netherlands Twin Register (average age at first assessment: 35.9 +/- 3.0 years) and 14 control mothers (35.1 +/- 3 years) took part in a prospective study. Fifteen years after entry into the study, which included follicle-stimulating hormone (FSH) assessment, AMH was measured in stored serum samples and menopause status was evaluated. Average AMH levels were not significantly different between DZ twin mothers and controls (2.1 +/- 2.4 mu g/L vs. 1.9 +/- 1.9 mu g/L). Among the 16 mothers of twins, 7 had an elevated (FSH) value over 10 U/L at first assessment. Their AMH levels were lower than the nine twin mothers with normal FSH values: 0.6 +/- 0.4 versus 3.4 +/- 2.6 mu g/L (p = .01). Of the mothers of twins, eight mothers had entered menopause at the second assessment compared with only one control mother (p = .07). Thus, slightly more DZ mothers were in menopause than the control mothers, although this difference was not significant. The subgroup of DZ twin mothers who had an increased FSH concentration 15 years ago had a limited ovarian reserve as reflected by lower AMH levels. These data indicate that advanced ovarian aging can be a feature in familial DZ twinning, particularly with elevated early follicular phase FSH

    Effects of Censoring on Parameter Estimates and Power in Genetic Modeling

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    Heritability of testosterone levels in 12-year-old twins and its relation to pubertal development

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    The aim of this study was to estimate the heritability of variation in testosterone levels in 12-year-old children, and to explore the overlap in genetic and environmental influences on circulating testosterone levels and androgen dependent pubertal development. Midday salivary testosterone samples were collected on two consecutive days in a sample of 183 unselected twin pairs. Androgen induced pubertal development was assessed using self report Tanner scales of pubic hair development (boys and girls) and genital development (boys). A significant contribution of genetic effects to the variance in testosterone levels was found. Heritability was approximately 50% in both boys and girls. The remaining proportion of the variance in testosterone levels could be explained by non-shared environmental influences. The relatively high correlation between testosterone levels of opposite sex dizygotic twins suggests that sex differences in genes influencing variation in testosterone levels have not yet developed in pre- and early puberty. Variance in pubertal development was explained by a large genetic component, moderate shared environmental influences, and a small non-shared environmental effect. Testosterone levels correlated moderately (r = .31) with pubertal development; the covariance between testosterone levels and pubertal development was entirely accounted for by genetic influences

    Variance Decomposition Using an IRT Measurement Model

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    Large scale research projects in behaviour genetics and genetic epidemiology are often based on questionnaire or interview data. Typically, a number of items is presented to a number of subjects, the subjects’ sum scores on the items are computed, and the variance of sum scores is decomposed into a number of variance components. This paper discusses several disadvantages of the approach of analysing sum scores, such as the attenuation of correlations amongst sum scores due to their unreliability. It is shown that the framework of Item Response Theory (IRT) offers a solution to most of these problems. We argue that an IRT approach in combination with Markov chain Monte Carlo (MCMC) estimation provides a flexible and efficient framework for modelling behavioural phenotypes. Next, we use data simulation to illustrate the potentially huge bias in estimating variance components on the basis of sum scores. We then apply the IRT approach with an analysis of attention problems in young adult twins where the variance decomposition model is extended with an IRT measurement model. We show that when estimating an IRT measurement model and a variance decomposition model simultaneously, the estimate for the heritability of attention problems increases from 40% (based on sum scores) to 73%

    On the etiology of aesthetic chills: a behavioral genetic study

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    Aesthetic chills, broadly defined as a somatic marker of peak emotional-hedonic responses, are experienced by individuals across a variety of human cultures. Yet individuals vary widely in the propensity of feeling them. These individual differences have been studied in relation to demographics, personality, and neurobiological and physiological factors, but no study to date has explored the genetic etiological sources of variation. To partition genetic and environmental sources of variation in the propensity of feeling aesthetic chills, we fitted a biometrical genetic model to data from 14,127 twins (from 8995 pairs), collected by the Netherlands Twin Register. Both genetic and unique environmental factors accounted for variance in aesthetic chills, with heritability estimated at 0.36 ([0.33, 0.39] 95% CI). We found females more prone than males to report feeling aesthetic chills. However, a test for genotype x sex interaction did not show evidence that heritability differs between sexes. We thus show that the propensity of feeling aesthetic chills is not shaped by nurture alone, but it also reflects underlying genetic propensities

    Statistical power to detect genetic and environmental influences in the presence of data missing at random.

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    We study the situation in which a cheap measure (X) is observed in a large, representative twin sample, and a more expensive measure (Y) is observed in a selected subsample. The aim of this study is to investigate the optimal selection design in terms of the statistical power to detect genetic and environmental influences on the variance of Y and on the covariance of X and Y. Data were simulated for 4000 dizygotic and 2000 monozygotic twins. Missingness (87% vs. 97%) was then introduced in accordance with 7 selection designs: (i) concordant low + individual high design; (ii) extreme concordant design; (iii) extreme concordant and discordant design (EDAC); (iv) extreme discordant design; (v) individual score selection design; (vi) selection of an optimal number of MZ and DZ twins; and (vii) missing completely at random. The statistical power to detect the influence of additive and dominant genetic and shared environmental effects on the variance of Y and on the covariance between X and Y was investigated. The best selection design is the individual score selection design. The power to detect additive genetic effects is high irrespective of the percentage of missingness or selection design. The power to detect shared environmental effects is acceptable when the percentage of missingness is 87%, but is low when the percentage of missingness is 97%, except for the individual score selection design, in which the power remains acceptable. The power to detect D is low, irrespective of selection design or percentage of missingness. The individual score selection design is therefore the best design for detecting genetic and environmental influences on the variance of Y and on the covariance of X and Y. However, the EDAC design may be preferred when an additional purpose of a study is to detect quantitative trait loci effects
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