A model of developmental change in hierarchical phenotypes with application to specific cognitive abilities

Notes on Three Decades of Methodology Workshops

Since 1987, a group of behavior geneticists have been teaching an annual methodology workshop on how to use state-of-the-art methods to analyze genetically informative data. In the early years, the focus was on analyzing twin and family data, using information of their known genetic relatedness to infer the role of genetic and environmental factors on phenotypic variation. With the rapid evolution of genotyping and sequencing technology and availability of measured genetic data, new methods to detect genetic variants associated with human traits were developed and became the focus of workshop teaching in alternate years. Over the years, many of the methodological advances in the field of statistical genetics have been direct outgrowths of the workshop, as evidence by the software and methodological publications authored by workshop faculty. We provide data and demographics of workshop attendees and evaluate the impact of the methodology workshops on scientific output in the field by evaluating the number of papers applying specific statistical genetic methodologies authored by individuals who have attended workshops.

Stability of Genetic and Environmental In‘uences on Reading Performance at 7 and 12 Years of Age in the Colorado Adoption Project

Results obtained from longitudinal studies suggest that individual differences in reading performance are relatively stable over time. However, the aetiology of this stability has not been previously explored. In the current study, the aetiology of longitudinal stability of reading performance between 7 and 12 years of age was assessed using data from adoptive (97 unrelated sibling pairs at age 7 and 73 pairs at age 12) and nonadoptive (106 related pairs at age 7 and 75 pairs at age 12) children tested in the Colorado Adoption Project. Results of a bivariate behavioural genetic analysis confirmed earlier findings of moderate genetic influence on individual differences in reading performance at both 7 and 12 years of age ( h2 = .49 and .37, respectively). Moreover, about 70% of the observed stability ( r = .61) between the two ages was due to common genetic influences. Of special interest, no new heritable or shared environmental variation was manifested at age 12, suggesting that the same genetic and shared environmental influences were operating at both ages. In contrast, nonshared environmental influences (e.g. instructional methods, teachers, peers, etc.) were responsible for change between 7 and 12 years of age, indicating the salience of such factors for the development of reading performance between middle childhood and adolescence.

Computation of individual latent variable scores from data with multiple missingness patterns

Latent variable models are used in biological and social sciences to investigate characteristics that are not directly measurable. The generation of individual scores of latent variables can simplify subsequent analyses. However, missing measurements in real data complicate the calculation of scores. Missing observations also result in different latent variable scores having different degrees of accuracy which should be taken into account in subsequent analyses. This manuscript presents a publicly available software tool that addresses both these problems, using as an example a dataset consisting of multiple ratings for ADHD symptomatology in children. The program computes latent variable scores with accompanying accuracy indices, under a 'user-specified' structural equation model, in data with missing data patterns. Since structural equation models encompass factor models, it can also be used for calculating factor scores. The program, documentation and a tutorial, containing worked examples and specimen input and output files, is available at http://statgen.iop.kcl.ac.uk/lsc .

Extracting meaning from comorbidity: genetic analyses that make sense

As behavioral genetic strategies have become part of the arsenal of research in developmental psychopathology, a wide variety of genetic analyses are being applied to child psychiatric data. Multivariate genetic techniques have been used to explore comorbidity among traits or disorders and the main analysis undertaken has been to examine whether comorbidity is due to shared genetic and/or environmental factors. However, this model ignores other possible causes of comorbidity, which are reviewed. In particular, genetic analyses of comorbidity have only infrequently considered the model of phenotypic causality (one disorder directly influencing another), which provides an important alternative with potentially different implications for intervention strategies. Data from a recently published article by Wamboldt, Schmitz, and Mrazek (1998) are used to illustrate the potential difficulties of distinguishing between models of shared genetic/environmental risk and phenotypic causality. Given that the sample sizes required to distinguish between these models are often large, and frequently greater than those of the datasets available, it is argued that researchers should select the models that they test based on other lines of evidence that these models are plausible. Where convincing evidence does not exist, researchers should explore alternative models and determine their power to discriminate between these models.

Intellektuelle Entwicklung über die Lebensspanne: Überblick und ausgewählte Forschungsbrennpunkte

Zusammenfassung. Aus der Perspektive des Zweikomponentenmodells der Kognitionsontogenese, das der biologischen Mechanik die kulturell geformte Pragmatik gegenüberstellt, wird die intellektuelle Entwicklung über die Lebensspanne nachgezeichnet. Besonders berücksichtigt werden folgende Gegenstände: (a) Formen der Abhängigkeit zwischen mechanischer und pragmatischer Entwicklung; (b) ontogenetische Veränderungen in relativer Stabilität, Heritabilität und Differenzierung intellektueller Fähigkeiten; (c) historische und ontogenetische Plastizität des Leistungsniveaus; (d) die Purifizierung der Messung von Altersunterschieden in der Mechanik; und (e) die Suche nach basalen Determinanten der mechanischen Entwicklung. Plädiert wird für eine Konzeptualisierung intellektueller Entwicklung, die bereichsspezifische und übergreifende Aspekte gleichermaßen berücksichtigt.

The independent prediction of general intelligence by elementary cognitive tasks: genetic and environmental influences

Current theories of intelligence have, in some cases, begun to include elementary cognitive tasks. Behavioral genetic studies of intelligence have not taken these theories into account. The current study includes 135 MZ and 128 DZ twin pairs from the Western Reserve Twin Project. The 11 WISC-R subtests as well as 6 elementary cognitive tasks were employed. Using a Schmid-Leiman (1957) transformation, analyses indicate a four-group factor model, supported by a second-order general factor at both phenotypic and biometric levels. Results indicate that the general factor, group factors, and specific residuals are necessary when examining additive genetic variance. Common environmental variance can be collapsed into a single general factor.