How specific is second language-learning ability? A twin study exploring the contributions of first language achievement and intelligence to second language achievement

Learning a second language is crucially important in an increasingly global society, yet surprisingly little is known about why individuals differ so substantially in second language (SL) achievement. We used the twin design to assess the nature, nurture and mediators of individual differences in SL achievement. For 6263 twin pairs, we analyzed scores from age 16 UK-wide standardized tests, the General Certificate of Secondary Education (GCSE). We estimated genetic and environmental influences on the variance of SL for specific languages, the links between SL and English and the extent to which the links between SL and English are explained by intelligence. All SL measures showed substantial heritability, although heritability was nonsignificantly lower for German (36%) than the other languages (53–62%). Multivariate genetic analyses indicated that a third of genetic influence in SL is shared with intelligence, a third with English independent of intelligence and a further third is unique to SL

Genetic and environmental underpinnings of spatial abilities and their role in predicting academic achievement and success in STEM

Behavior Genetics Association 45th Annual Meeting Abstract: Spatial abilities encompass several factors that are differentiable from general cognitive ability (intelligence). Importantly, spatial abilities have been shown to be significant predictors of many life outcomes, even after controlling for intelligence. Quantitative genetic studies have shown that diverse measures of spatial ability are moderately heritable (30–50 %), although some important aspects of spatial ability such as navigation and map-reading have been neglected. Little is known about the factor structure of spatial measures or their links with academic achievement, especially STEM subjects (science, technology, engineering, mathematics). For these reasons, we launched a program of research creating novel online gamified measures of diverse spatial abilities including mental rotation, spatial visualization, spatial scanning, navigation, and map-reading. We piloted the measures on 100 unrelated individuals; all measures produced good test–retest reliability (0.7 on average). The battery was administered online to 1000 twin pairs (age 19–21) from the UK representative Twins Early Development Study (TEDS). Phenotypically, the results provided some evidence for the multifactorial nature of spatial ability, independent of intelligence, despite substantial correlations among the factors. Univariate genetic analyses yielded moderate heritability for all tests and factors. One of the most interesting findings was that these spatial factors correlated with success in STEM subjects, especially with achievement in mathematics, even after controlling for intelligence, and genetic factors largely accounted for these phenotypic associations TEDS is supported by a program grant to RP from the UK Medical Research Council [G0901245; and previously G0500079], with additional support from the US National Institutes of Health [HD044454; HD059215]. NS and KR are supported by Medical Research Council

Pleiotropy across academic subjects at the end of compulsory education

Research has shown that genes play an important role in educational achievement. A key question is the extent to which the same genes affect different academic subjects before and after controllin

Investigating the genetic and environmental aetiologies of non-suicidal and suicidal self-harm: a twin study

BACKGROUND: Self-harm is a major health concern, not only as a signal of distress but also as a strong predictor of later suicide. Self-harm can be further refined into suicidal self-harm (SSH, i.e. suicide attempt) and non-suicidal self-harm (NSSH). Understanding the aetiologies of NSSH and SSH can help inform suicide prevention strategies. Using a twin design, we investigated the phenotypic and aetiological relationships between NSSH and SSH, and their aetiological overlap with mental health problems. METHODS: We analysed data from the Twins Early Development Study using structural equation modelling. At age 21 years, 9063 twins (62.4% female) answered questions related to self-harm. At age 16 years, 19 self- or parent-reported mental health measures were administered, including measures of internalising and externalising problems, psychotic-like experiences and substance abuse. RESULTS: Prevalences for NSSH and SSH were 21.9% and 10.5%, respectively. Additive genetic factors explained half of the variance in NSSH (55%) and SSH (50%), with the rest explained by non-shared environmental factors. Phenotypically, NSSH and SSH were strongly correlated (r = 0.87) with their correlation explained by genetic (57%) and non-shared environmental (43%) factors. We found no evidence that NSSH and SSH differed in their phenotypic and aetiological relationships with mental health measures. CONCLUSION: Our findings suggest no aetiological difference between NSSH and SSH. NSSH and SSH should be regarded as two different ends of a continuum, rather than as two distinct categories

Weak associations between pubertal development and psychiatric and behavioral problems

Pubertal development has been associated with adverse outcomes throughout adolescence and adulthood. However, much of the previous literature has categorized outcome variables and pubertal timing measures for ease of mean difference or odds ratio interpretation. We use a UK-representative sample of over 5000 individuals drawn from the Twins Early Development Study to extend this literature by adopting an individual differences approach and emphasizing effect sizes. We investigate a variety of psychiatric and behavioral measures collected longitudinally at ages 11, 14 and 16, for multiple raters and for males and females separately. In addition, we use two measures of pubertal development: the Pubertal Development Scale at each age, as well as the age of menarche for girls. We found that pubertal development, however assessed, was linearly associated with a range of psychiatric and behavioral outcomes; however, the effect sizes of these associations were modest for both males and females with most correlations between −0.10 and 0.10. Our systematic analysis of associations between pubertal development, and psychiatric and behavioral problems is the most comprehensive to date. The results showing linearity of the effects of pubertal development support an individual differences approach, treating both pubertal development and associated outcomes as continuous rather than categorical variables. We conclude that pubertal development explains little variance in psychiatric and behavioral outcomes (<1% on average). The small effect sizes indicate that the associations are weak and should not warrant major concern at least in non-clinical populations

The p factor: genetic analyses support a general dimension of psychopathology in childhood and adolescence

Background: Diverse behaviour problems in childhood correlate phenotypically, suggesting a general dimension of psychopathology that has been called the p factor. The shared genetic architecture between childhood psychopathology traits also supports a genetic p. This study systematically investigates the manifestation of this common dimension across self‐, parent‐ and teacher‐rated measures in childhood and adolescence. / Methods: The sample included 7,026 twin pairs from the Twins Early Development Study (TEDS). First, we employed multivariate twin models to estimate common genetic and environmental influences on p based on diverse measures of behaviour problems rated by children, parents and teachers at ages 7, 9, 12 and 16 (depressive traits, emotional problems, peer problems, autism traits, hyperactivity, antisocial behaviour, conduct problems and psychopathic tendencies). Second, to assess the stability of genetic and environmental influences on p across time, we conducted longitudinal twin modelling of the first phenotypic principal components of childhood psychopathological measures across each of the four ages. Third, we created a genetic p factor in 7,026 unrelated genotyped individuals based on eight polygenic scores for psychiatric disorders to estimate how a general polygenic predisposition to mostly adult psychiatric disorders relates to childhood p. / Results: Behaviour problems were consistently correlated phenotypically and genetically across ages and raters. The p factor is substantially heritable (50%–60%) and manifests consistently across diverse ages and raters. However, residual variation in the common factor models indicates unique contributions as well. Genetic correlations of p components across childhood and adolescence suggest stability over time (49%–78%). A polygenic general psychopathology factor derived from studies of psychiatric disorders consistently predicted a general phenotypic p factor across development (0.3%–0.9%). / Conclusions: Diverse forms of psychopathology generally load on a common p factor, which is highly heritable. There are substantial genetic influences on the stability of p across childhood. Our analyses indicate genetic overlap between general risk for psychiatric disorders in adulthood and p in childhood, even as young as age 7. The p factor has far‐reaching implications for genomic research and, eventually, for diagnosis and treatment of behaviour problems.

Genotype-Environment Interaction in ADHD:Genetic Predisposition Determines the Extent to Which Environmental Influences Explain Variability in the Symptom Dimensions Hyperactivity and Inattention

Although earlier research has shown that individual differences on the spectrum of attention deficit hyperactivity disorder (ADHD) are highly heritable, emerging evidence suggests that symptoms are associated with complex interactions between genes and environmental influences. This study investigated whether a genetic predisposition [Note that the term ‘genetic predisposition’ was used in this manuscript to refer to an estimate based on twin modeling (an individual’s score on the latent trait that resembles additive genetic influences) in the particular population being examined.] for the symptom dimensions hyperactivity and inattention determines the extent to which unique-environmental influences explain variability in these symptoms. To this purpose, we analysed a sample drawn from the Twins Early Development Study (TEDS) that consisted of item-level scores of 2168 16-year-old twin pairs who completed both the Strengths and Difficulties Questionnaire (SDQ; Goodman, in J Child Psychol Psychiatry 38:581–586, 1997) and the Strength and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN; Swanson, in Paper presented at the meeting of the American Psychological Association, Los Angeles, 1981) questionnaire. To maximize the psychometric information to measure ADHD symptoms, psychometric analyses were performed to investigate whether the items from the two questionnaires could be combined to form two longer subscales. In the estimation of genotype-environment interaction, we corrected for error variance heterogeneity in the measurement of ADHD symptoms through the application of item response theory (IRT) measurement models. A positive interaction was found for both hyperactivity (e.g., β1 = 2.20 with 95% highest posterior density interval equal to [1.79;2.65] and effect size equal to 3.00) and inattention (e.g., β1 = 2.16 with 95% highest posterior density interval equal to [1.56;2.79] and effect size equal to 3.07). These results indicate that unique-environmental influences were more important in creating individual differences in both hyperactivity and inattention for twins with a genetic predisposition for these symptoms than for twins without such a predisposition.</p

The genetics of specific cognitive abilities

Most research on individual differences in performance on tests of cognitive ability focuses on general cognitive ability (g), the highest level in the three-level Cattell-Horn-Carroll (CHC) hierarchical model of intelligence. About 50% of the variance of g is due to inherited DNA differences (heritability) which increases across development. Much less is known about the genetics of the middle level of the CHC model, which includes 16 broad factors such as fluid reasoning, processing speed, and quantitative knowledge. We provide a meta-analytic review of 863,041 monozygotic-dizygotic twin comparisons from 80 publications for these middle-level factors, which we refer to as specific cognitive abilities (SCA). Twin comparisons were available for 11 of the 16 CHC domains. The average heritability across all SCA is 55%, similar to the heritability of g. However, there is substantial differential heritability and the SCA do not show the dramatic developmental increase in heritability seen for g. We also investigated SCA independent of g (g-corrected SCA, which we refer to as SCA.g). A surprising finding is that SCA.g remain substantially heritable (53% on average), even though 25% of the variance of SCA that covaries with g has been removed. Our review frames expectations for genomic research that will use polygenic scores to predict SCA and SCA.g. Genome-wide association studies of SCA.g are needed to create polygenic scores that can predict SCA profiles of cognitive abilities and disabilities independent of g. These could be used to foster children’s cognitive strengths and minimise their weaknesses