On the sources of the height–intelligence correlation: New insights from a bivariate ACE model with assortative mating

A robust positive correlation between height and intelligence, as measured by IQ tests, has been established in the literature. This paper makes several contributions toward establishing the causes of this association. First, we extend the standard bivariate ACE model to account for assortative mating. The more general theoretical framework provides several key insights, including formulas to decompose a cross-trait genetic correlation into components attributable to assortative mating and pleiotropy and to decompose a cross-trait within-family correlation. Second, we use a large dataset of male twins drawn from Swedish conscription records and examine how well genetic and environmental factors explain the association between (i) height and intelligence and (ii) height and military aptitude, a professional psychogologist’s assessment of a conscript’s ability to deal with wartime stress. For both traits, we find suggestive evidence of a shared genetic architecture with height, but we demonstrate that point estimates are very sensitive to assumed degrees of assortative mating. Third, we report a significant within-family correlation between height and intelligence \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(\hat{\rho}=0.10),$$\end{document} suggesting that pleiotropy might be at play

Genetic analyses of maternal and teacher ratings on attention problems in 7-year-old Dutch twins

The goal of the present study is to examine genetic and environmental influences on maternal and teacher ratings of Attention Problems (AP) in 7-year-old children. Teachers completed the Teacher Report Form (N=2259 pairs), and mothers the Child Behavior Checklist (N=2057 pairs). Higher correlations were found in twins rated by the same teacher than in twins rated by different teachers. This can be explained by rater bias or by a greater environmental sharing in twins, who are in the same classroom. We further found that 41% of the variation in maternal and teacher ratings is explained by a common factor. The heritability of this common factor is 78%. The heritabilities of the rater specific factors of mothers and teachers are 76% and 39%, respectively. Because Attention Problems that are persistent over situations may indicate more serious behavior problems than context dependent Attention Problems, we believe that gene finding strategies should focus on this common phenotype

Linkage analysis of longitudinal data and design consideration

BACKGROUND: Statistical methods have been proposed recently to analyze longitudinal data in genetic studies. So far, little attention has been paid to examine the relationship among key factors in genetic longitudinal studies including power, the number of families or sibships, and the number of repeated measures per individual subjects. RESULTS: We proposed a variance component model that extends classic variance component models for a single quantitative trait to mapping longitudinal traits. Our model includes covariate effects and allows genetic effects to vary over time. Using our proposed model, we examined the power, pedigree structures, and sample size through simulation experiments. CONCLUSION: Our simulation results provide useful insights into the study design for genetic, longitudinal studies. For example, collecting a small number of large sibships is much more powerful than collecting a large number of small sibships or increasing the number of repeated measures, when the total number of measurements is comparable

Can programme theory be used as a 'translational tool’ to optimise health service delivery in a national early years’ initiative in Scotland: a case study

Background Theory-based evaluation (TBE) approaches are heralded as supporting formative evaluation by facilitating increased use of evaluative findings to guide programme improvement. It is essential that learning from programme implementation is better used to improve delivery and to inform other initiatives, if interventions are to be as effective as they have the potential to be. Nonetheless, few studies describe formative feedback methods, or report direct instrumental use of findings resulting from TBE. This paper uses the case of Scotland’s, National Health Service, early years’, oral health improvement initiative (Childsmile) to describe the use of TBE as a framework for providing feedback on delivery to programme staff and to assess its impact on programmatic action.<p></p> Methods In-depth, semi-structured interviews and focus groups with key stakeholders explored perceived deviations between the Childsmile programme 'as delivered’ and its Programme Theory (PT). The data was thematically analysed using constant comparative methods. Findings were shared with key programme stakeholders and discussions around likely impact and necessary actions were facilitated by the authors. Documentary review and ongoing observations of programme meetings were undertaken to assess the extent to which learning was acted upon.<p></p> Results On the whole, the activities documented in Childsmile’s PT were implemented as intended. This paper purposefully focuses on those activities where variation in delivery was evident. Differences resulted from the stage of roll-out reached and the flexibility given to individual NHS boards to tailor local implementation. Some adaptations were thought to have diverged from the central features of Childsmile’s PT, to the extent that there was a risk to achieving outcomes. The methods employed prompted national service improvement action, and proposals for local action by individual NHS boards to address this.<p></p> Conclusions The TBE approach provided a platform, to direct attention to areas of risk within a national health initiative, and to agree which intervention components were 'core’ to its hypothesised success. The study demonstrates that PT can be used as a 'translational tool’ to facilitate instrumental use of evaluative findings to optimise implementation within a complex health improvement programme.<p></p&gt

Sex Differences in Genetic Architecture of Complex Phenotypes?

We examined sex differences in familial resemblance for a broad range of behavioral, psychiatric and health related phenotypes (122 complex traits) in children and adults. There is a renewed interest in the importance of genotype by sex interaction in, for example, genome-wide association (GWA) studies of complex phenotypes. If different genes play a role across sex, GWA studies should consider the effect of genetic variants separately in men and women, which affects statistical power. Twin and family studies offer an opportunity to compare resemblance between opposite-sex family members to the resemblance between same-sex relatives, thereby presenting a test of quantitative and qualitative sex differences in the genetic architecture of complex traits. We analyzed data on lifestyle, personality, psychiatric disorder, health, growth, development and metabolic traits in dizygotic (DZ) same-sex and opposite-sex twins, as these siblings are perfectly matched for age and prenatal exposures. Sample size varied from slightly over 300 subjects for measures of brain function such as EEG power to over 30,000 subjects for childhood psychopathology and birth weight. For most phenotypes, sample sizes were large, with an average sample size of 9027 individuals. By testing whether the resemblance in DZ opposite-sex pairs is the same as in DZ same-sex pairs, we obtain evidence for genetic qualitative sex-differences in the genetic architecture of complex traits for 4% of phenotypes. We conclude that for most traits that were examined, the current evidence is that same the genes are operating in men and women

Genetic and environmental influences on the relation between attention problems and Attention Deficit Hyperactivity Disorder.

Objective: The assessment of symptoms of ADHD in children is usually based on a clinical interview or a behavior checklist. The aim of the present study is to investigate the extent to which these instruments measure an underlying construct and to estimate the genetic and environmental influences on individual differences in ADHD. Methods: Maternal ratings were collected on 10,916 twins from 5,458 families. Child Behavior Checklist (CBCL) ratings were available for 10,018, 6,565, and 5,780 twins at the ages 7, 10, and 12, respectively. The Conners Rating Scale (4,887 twins) and the DSM interview (1,006 twins) were completed at age 12. The magnitude of genetic and environmental influences on the variance of the three measures of ADHD and the covariance among the three measures of ADHD was obtained. Results: Phenotypic correlations range between .45 and .77. Variances and covariances of the measurements were explained mainly by genetic influences. The model that provided the best account of the data included an independent pathway for additive and dominant genetic effects. The genetic correlations among the measures collected at age 12 varied between .63 and 1.00. Conclusions: The genetic overlap between questionnaire ratings and the DSM-IV diagnosis of ADHD is high. Clinical and research implications of these findings are presented