28 research outputs found

    Sub-types of insomnia in adolescents: insights from a quantitative/ molecular twin study

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    Background: Insomnia with short sleep duration has been postulated as more severe than that accompanied by normal/long sleep length. While the short duration subtype is considered to have greater genetic influence than the other subtype, no studies have addressed this question. This study aimed to compare these subtypes in terms of: 1) the heritability of insomnia symptoms; 2) polygenic scores (PGS) for insomnia symptoms and sleep duration; 3) the associations between insomnia symptoms and a wide variety of traits/disorders. Methods: The sample comprised 4,000 pairs of twins aged 16 from the Twins Early Development Study. Twin models were fitted to estimate the heritability of insomnia in both groups. PGS were calculated for self-reported insomnia and sleep duration and compared among participants with short and normal/long sleep duration. Results: Heritability was not significantly different in the short sleep duration group (A=0.13 [95%CI=0.01, 0.32]) and the normal/long sleep duration group (A=0.35 [95%CI=0.29, 0.40]). Shared environmental factors accounted for a substantial proportion of the variance in the short sleep duration group (C=0.19 [95%CI= 0.05, 0.32]) but not in the normal/long sleep duration group (C=0.00 [95%CI=0.00, 0.04]). PGS did not differ significantly between groups although results were in the direction expected by the theory. Our results also showed that insomnia with short (as compared to normal/long) sleep duration had a stronger association with anxiety and depression (p<.05) - although not once adjusting for multiple testing. Conclusions: We found mixed results in relation to the expected differences between the insomnia subtypes in adolescents. Future research needs to further establish cut-offs for ‘short’ sleep at different developmental stages and employ objective measures of sleep

    Rotation is visualisation, 3D is 2D: using a novel measure to investigate the genetics of spatial ability.

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    Spatial abilities–defined broadly as the capacity to manipulate mental representations of objects and the relations between them–have been studied widely, but with little agreement reached concerning their nature or structure. Two major putative spatial abilities are “mental rotation” (rotating mental models) and “visualisation” (complex manipulations, such as identifying objects from incomplete information), but inconsistent findings have been presented regarding their relationship to one another. Similarly inconsistent findings have been reported for the relationship between two- and three-dimensional stimuli. Behavioural genetic methods offer a largely untapped means to investigate such relationships. 1,265 twin pairs from the Twins Early Development Study completed the novel “Bricks” test battery, designed to tap these abilities in isolation. The results suggest substantial genetic influence unique to spatial ability as a whole, but indicate that dissociations between the more specific constructs (rotation and visualisation, in 2D and 3D) disappear when tested under identical conditions: they are highly correlated phenotypically, perfectly correlated genetically (indicating that the same genetic influences underpin performance), and are related similarly to other abilities. This has important implications for the structure of spatial ability, suggesting that the proliferation of apparent subdomains may sometimes reflect idiosyncratic tasks rather than meaningful dissociations

    Multivariable G-E interplay in the prediction of educational achievement

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    Polygenic scores are increasingly powerful predictors of educational achievement. It is unclear, however, how sets of polygenic scores, which partly capture environmental effects, perform jointly with sets of environmental measures, which are themselves heritable, in prediction models of educational achievement. Here, for the first time, we systematically investigate gene-environment correlation (rGE) and interaction (GxE) in the joint analysis of multiple genome-wide polygenic scores (GPS) and multiple environmental measures as they predict tested educational achievement (EA). We predict EA in a representative sample of 7,026 16-year-olds, with 20 GPS for psychiatric, cognitive and anthropometric traits, and 13 environments (including life events, home environment, and SES) measured earlier in life. Environmental and GPS predictors were modelled, separately and jointly, in penalized regression models with out-of-sample comparisons of prediction accuracy, considering the implications that their interplay had on model performance. Jointly modelling multiple GPS and environmental factors significantly improved prediction of EA, with cognitive-related GPS adding unique independent information beyond SES, home environment and life events. We found evidence for rGE underlying variation in EA (rGE =.38; 95% CIs =.30,.45). We estimated that 40% (95% CIs = 31%, 50%) of the polygenic scores effects on EA were mediated by environmental effects, and in turn that 18% (95% CIs = 12%, 25%) of environmental effects were accounted for by the polygenic model, indicating genetic confounding. Lastly, we did not find evidence that GxE effects significantly contributed to multivariable prediction. Our multivariable polygenic and environmental prediction model suggests widespread rGE and unsystematic GxE contributions to EA in adolescence

    Phenotypic and genetic evidence for a unifactorial structure of spatial abilities

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    Spatial abilities encompass several skills differentiable from general cognitive ability (g). Importantly, spatial abilities have been shown to be significant predictors of many life outcomes, even after controlling for g. To date, no studies have analyzed the genetic architecture of diverse spatial abilities using a multivariate approach. We developed “gamified” measures of diverse putative spatial abilities. The battery of 10 tests was administered online to 1,367 twin pairs (age 19–21) from the UK-representative Twins Early Development Study (TEDS). We show that spatial abilities constitute a single factor, both phenotypically and genetically, even after controlling for g. This spatial ability factor is highly heritable (69%). We draw three conclusions: (i) The high heritability of spatial ability makes it a good target for gene-hunting research; (ii) some genes will be specific to spatial ability, independent of g; and (iii) these genes will be associated with all components of spatial ability

    Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits

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    The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located nearNEDD4LandSLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (R(g)ranging from 0.11 to 0.76, P-values Author summary Although twin studies have shown that body mass index (BMI) is highly heritable, many common genetic variants involved in the development of BMI have not yet been identified, especially in children. We studied associations of more than 40 million genetic variants with childhood BMI in 61,111 children aged between 2 and 10 years. We identified 25 genetic variants that were associated with childhood BMI. Two of these have not been implicated for BMI previously, located close to the genesNEDD4LandSLC45A3. We also show that the genetic background of childhood BMI overlaps with that of birth weight, adult BMI, waist-to-hip-ratio, diastolic blood pressure, type 2 diabetes, and age at menarche. Our results suggest that the biological processes underlying childhood BMI largely overlap with those underlying adult BMI. However, the overlap is not complete. Additionally, the genetic backgrounds of childhood BMI and other cardio-metabolic phenotypes are overlapping. This may mean that the associations of childhood BMI and later cardio-metabolic outcomes are partially explained by shared genetics, but it could also be explained by the strong association of childhood BMI with adult BMI.Peer reviewe

    The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia:design, results and future prospects

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    The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

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    The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.Peer reviewe
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