Suchergebnisse

AbstractGenetic and environmental sources of covariation among cognitive measures of verbal IQ, performance IQ (PIQ), academic achievement, 2-choice reaction time (CRT), inspection time (IT) and the 6 Openness facets of the NEO Personality Inventory-Revised (NEO PI-R) were examined. The number of twin and twin–sibling pairs ranged from 432 (182 MZ, 350 DZ/sibling) to 1023 (273 MZ, 750 DZ/sibling) for cognitive measures, and between 432 (90 MZ, 342 DZ/sibling) — 437 (91 MZ, 346 DZ/sibling) for Openness facets. Structural equation modeling best supported a model with a 3-factor additive genetic structure. A genetic general factor subsumed the 5 cognitive measures and 5 of the 6 Openness facets (Actions did not load significantly). A second additive genetic factor incorporated the 6 Openness facets, and a third additive genetic factor incorporated the 5 cognitive measures. Specific additive and dominance genetic effects were also evident, as were shared common and shared unique environmental influences, and specific unique environmental effects. The Openness facets of Ideas and Values evidenced the strongest phenotypic correlations with cognitive indices, particularly verbal measures. The genetic correlations among Openness facets and cognitive measures ranged from −.06 to .79. Results were interpreted as suggesting that Openness is related to general cognitive ability (g) through a genetic mechanism and thatgengenders a minor but discernable disposition towards Openness for the majority of facets.

AbstractThis study examined the genetic and environmental relationships among 5 academic achievement skills of a standardized test of academic achievement, the Queensland Core Skills Test (QCST; Queensland Studies Authority, 2003a). QCST participants included 182 monozygotic pairs and 208 dizygotic pairs (mean 17 years ± 0.4 standard deviation). IQ data were included in the analysis to correct for ascertainment bias. A genetic general factor explained virtually all genetic variance in the component academic skills scores, and accounted for 32% to 73% of their phenotypic variances. It also explained 56% and 42% of variation in Verbal IQ and Performance IQ respectively, suggesting that this factor is genetic g. Modest specific genetic effects were evident for achievement in mathematical problem solving and written expression. A single common factor adequately explained common environmental effects, which were also modest, and possibly due to assortative mating. The results suggest that general academic ability, derived from genetic influences and to a lesser extent common environmental influences, is the primary source of variation in component skills of the QCST.

AbstractSimultaneous 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% CI 0.00–7.67%), with the majority of the variance, 74.53%, explained by factors unique to the individual (95% CI 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.

AbstractAmultidisciplinary collaborative study examining cognition in a large sample of twins is outlined. A common experimental protocol and design is used in The Netherlands, Australia and Japan to measure cognitive ability using traditional IQ measures (i.e., psychometric IQ), processing speed (e.g., reaction time [RT] and inspection time [IT]), and working memory (e.g., spatial span, delayed response [DR] performance). The main aim is to investigate the genetic covariation among these cognitive phenotypes in order to use the correlated biological markers in future linkage and association analyses to detect quantitativetrait loci (QTLs). We outline the study and methodology, and report results from our preliminary analyses that examines the heritability of processing speed and working memory indices, and their phenotypic correlation with IQ. Heritability of Full Scale IQ was 87% in the Netherlands, 83% in Australia, and 71% in Japan. Heritability estimates for processing speed and working memory indices ranged from 33–64%. Associations of IQ with RT and IT (−0.28 to −0.36) replicated previous findings with those of higher cognitive ability showing faster speed of processing. Similarly, significant correlations were indicated between IQ and the spatial span working memory task (storage [0.31], executive processing [0.37]) and the DR working memory task (0.25), with those of higher cognitive ability showing better memory performance. These analyses establish the heritability of the processing speed and working memory measures to be used in our collaborative twin study of cognition, and support the findings that individual differences in processing speed and working memory may underlie individual differences in psychometric IQ.