2,813 research outputs found
A note on the statistical power in extended twin designs
this paper. a trait can not be ascribed to genes because the statistical power to detect sources of genetic variation is insufficient (Svikis, Velz & Pickens, 1994; Pickens, Svikis, McGue, Lykken, et al., 1991). This will preclude further searching for effects of QTL's on that particular trait, even though such QTL's may be presen
Environmental Factors Determine Where the Dutch Live: Results From the Netherlands Twin Register
The heritability of the degree of residential area urbanization in twins and their siblings in the Dutch population was examined. The postal code was known for 6879 twins and 2724 siblings registered with the Netherlands Twin Register and born between 1940 and 1983. Using data from Statistics Netherlands (Centraal Bureau voor de Statistiek, 2001), these postal codes could be related to residential area characteristics, including urbanization level. The degree of urbanization was assessed on a 5-point scale: very heavy, heavy, moderate, low and not urbanized. Genetic model-fitting was carried out in three age cohorts: young adults (born 1975 to 1983), adults (born 1965 to 1974) and older adults (born 1940 to 1964). Twin and sibling resemblance in urbanization level was expressed in polychoric correlations. These correlations decreased from the youngest cohort (.66 to .86) to the oldest cohort (.20 to .58). In all 3 age cohorts, genetic factors did not contribute to familial resemblance. The influence of common environment decreased in importance from the young cohort (70% to 83%) to the old cohort (46% to 47%) and was lower in women than in men in all but the oldest age cohort. This study did not replicate Australian findings of a genetic contribution in the older cohorts; common environmental factors and, increasingly with age, unique environmental factors determine where the Dutch live. Future studies in European and other populations will reveal whether these results are specific to the Dutch population
Estimation of individual genetic and environmental profiles in longitudinal designs
Parameter estimates obtained in the genetic analysis of longitudinal data can be used to construct individual genetic and environmental profiles across time. Such individual profiles enable the attribution of individual phenotypic change to changes in the underlying genetic or environmental processes and may lead to practical applications in genetic counseling and epidemiology. Simulations show that individual estimates of factor scores can be reliably obtained. Decomposition of univariate, and to a lesser extent of bivariate, phenotypic time series may yield estimates of independent individual G(t) and E(t), however, that are intercorrelated. The magnitude of these correlations depends somewhat on the autocorrelation structure of the underlying series, but to obtain completely independent estimates of genetic and environmental individual profiles, at least three measured indicators are needed at each point in time. KEY WORDS: longitudinal genetic analysis; environmental profiles; genetic profiles; factor scores; Kalman filter
Perceptual speed and IQ are associated through common genetic factors
Individual differences in inspection time explain about 20% of IQ test variance. To determine whether the association between inspection time and IQ is mediated by common genes or by a common environmental factor, inspection time and IQ were assessed in an extended twin design. Data from 688 participants from 271 families were collected as part of a large ongoing project on the genetics of adult brain function and cognition. The sample consisted of a young adult cohort (mean age 26.2 years) and an older adult cohort (mean age 50.4 years). IQ was assessed with the Dutch version of the WAIS-3R. Inspection time was measured in the so-called II-paradigm, in which a subject is asked to decide which leg of the II-figure is longest at varying display times of the II-figure. The number of correct inspections per second (i.e., the reciprocal of inspection time) was used to index perceptual speed. For Verbal IQ and Performance IQ, heritabilities were 85% and 69%, respectively. For perceptual speed, 46% of the total variance was explained by genetic variance. No differences in heritability estimates across age cohorts or sexes were found. Across the whole sample, a significant phenotypic correlation was found between perceptual speed and Verbal IQ (0.19) and between perceptual speed and Performance IQ (0.27). These correlations were entirely due to a common genetic factor that accounted for 10% of the genetic variance in verbal IQ and for 22% of the genetic variance in performance IQ. This factor is hypothesized to reflect the influence of genetic factors that determine axonal myelination in the central nervous system
Spontaneous CP-violation in the strong interaction at theta = pi
Spontaneous CP-violation in the strong interaction is analyzed at theta = pi
within the framework of the two-flavor NJL model. It is found that the
occurrence of spontaneous CP-violation at theta = pi depends on the strength of
the 't Hooft determinant interaction, which describes the effect of instanton
interactions. The dependence of the phase structure, and in particular of the
CP-violating phase, on the quark masses, temperature, baryon and isospin
chemical potential is examined in detail. When available a comparison to
earlier results from chiral perturbation theory is made. From our results we
conclude that spontaneous CP-violation in the strong interaction is an
inherently low-energy phenomenon. In all cases we find agreement with the
Vafa-Witten theorem, also at nonzero density and temperature. Meson masses and
mixing in the CP-violating phase display some unusual features as a function of
instanton interaction strength. A modification of the condition for charged
pion condensation at nonzero isospin chemical potential and a novel phase of
charged a_0 mesons are discussed.Comment: 15 pages, 11 eps figures; matches version published in Phys. Rev. D,
reference added, corrected Eq. 16, modified discussion Ref.
A longitudinal genetic study of vocabulary knowledge in adults.
Vocabulary test scores were obtained from a total of 997 adults, all twins or a sibling of twins in this study. Some (N = 217) individuals were tested twice, around 6 years apart. Heritability varied from 50% at the first test occasion to 63% at the second test occasion. The correlation of scores across time was .74. Structural equation modelling showed that stability in vocabulary knowledge over time can largely (around 76%) be explained by genetic factors. Part of the non-shared environmental variance was stable over time also. Any influence from shared environmental factors could not be detected. Results were similar for the two sexes, except that males generally outperformed females. Results were also similar for two age cohorts, except that the older cohort generally outperformed the younger cohort
ADHD: Sibling interaction or dominance: An evaluation of statistical power
Sibling interaction effects are suggested by a difference in phenotypic variance between monozygotic (MZ) twins and dizygotic (DZ) twins, and a pattern of twin correlations that is inconsistent with additive genetic influences. Notably, negative sibling interaction will result in MZ correlations which are more than twice as high as DZ correlations, a pattern also seen in the presence of genetic dominance. Negative sibling interaction effects have been reported in most genetic studies on Attention Deficit Hyperactivity Disorder (ADHD) and related phenotypes, while the presence of genetic dominance is not always considered in these studies. In the present paper the statistical power to detect both negative sibling interaction effects and genetic dominance is explored. Power calculations are presented for univariate models including sources of variation due to additive genetic influences, unique environmental influences, dominant genetic influences and a negative sibling interaction (i.e., contrast effect) between phenotypes of twins. Parameter values for heritability and contrast effects are chosen in accordance with published behavior genetic studies on ADHD and associated phenotypes. Results show that when both genetic dominance and contrast effects are truly present and using a classical twin design, genetic dominance is more likely to go undetected than the contrast effect. Failure to detect the presence of genetic dominance consequently gives rise to slightly biased estimates of additive genetic effects, unique environmental effects, and the contrast effect. Contrast effects are more easily detected in the absence of genetic dominance. If the significance of the contrast effect is evaluated while also including genetic dominance, small contrast effects are likely to go undetected, resulting in a relatively large bias in estimates of the other parameters. Alternative genetic designs, such as adding pairs of unrelated siblings reared together to a classical twin design, or adding non-twin siblings to twin pairs, greatly enhances the statistical power to detect contrast effects as well as the power to distinguish between genetic dominance and contrast effects
Using factor scores to detect G x E interactive origin of "pure" genetic or environmental factors obtained in genetic covariance structure analysis
Moment expressions for individual factor scores can serve as simple tests for the presence of a particular class of interaction factors that are disguised as pure genetic and/or environmental factors. That is, individual genetic and environmental factor scores may be used to construct fourth‐order moments of these factors in order to test whether a common genetic or environmental factor in the multivariate genetic factor model is in fact of the interactive origin concerned. Expected fourth‐order moments are derived for cases with and without interaction. Application of fourth‐order moments of factor scores to detect interactive origin of common factors is illustrated with simulated twin data. Copyright © 1990 Wiley‐Liss, Inc., A Wiley Compan
A whole-genome scan for 24-hour respiration rate: a major locus at 10q26 influences respiration during sleep.
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