Hermine Maes

Recent advances in the genetic epidemiology and molecular genetics of substance use disorders

This article reviews current advances in the genetics of substance use disorders (SUDs). Both genetic and environmental sources of risk are required to develop a complete picture of SUD etiology. Genetic sources of risk for SUDs are not highly substance specific in their effects. Genetic and environmental risks for SUDs typically do not only add together but also interact with each other over development. Risk gene identification for SUDs has been difficult, with one recent success in identifying nicotinic receptor variants that affect risk for nicotine dependence. The impact of genetic variants on SUD risk will individually be small. Although genetic epidemiologic methods are giving us an increasingly accurate map of broad causal pathways to SUDs, gene discovery will be needed to identify the specific biological systems. Identifying these risk genes and understanding their action will require large clinical samples, and interaction between these studies and work in model organisms.

An evaluation of different approaches for behavior genetic analyses with psychiatric symptom scores.

We used a simulation study to evaluate six approaches for behavior genetic analyses of psychiatric symptom scores. For the selection of the correct model, the best results were obtained with approaches using transformed scores in combination with a procedure involving p-values. With normalizing transformations, the χ2 test statistic gave a reasonable impression of the overall fit of the model but was less accurate when used as a difference test. The asymptotic distribution free estimation methods yielded χ2s that were much too large. All data analysis techniques yielded substantially biased parameter estimates. The most biased results were obtained with normalizing transformations. The least biased results were obtained with tobit correlations, but because of its large standard errors the most precise estimates were obtained with polychoric correlations and optimal scale scores. An empirical study showed that a recognition of the role of methodological factors was helpful to understand part of the differences between assessment instruments, raters, and data analysis techniques that were found in the real data.

Multivariate genetic analysis of twin-family data on fears: Mx models

We describe the implementation of multivariate models of familial resemblance with the Mx package. The structural equation models allow for the effects of assortative mating, additive and dominant genes, common and specific environment, and both genetic and cultural transmission between generations. Two approaches are compared: a correlational one based on Fulker and a factor model described by Phillips and Fulker. Both are illustrated by application to published data on social fears and fear of leadership measured in monozygotic and dizygotic twins and their parents. In the example data, genetic dominance yields a more parsimonious explanation of the data than does cultural transmission, although neither is needed to obtain a good fit to the data. A model of reduced genetic correlation between generations also fits the data but has inherent limitations in this sample. Extensions to sex-limitation and more complex models are discussed.

Genetic Innovation and Stability in Externalizing Problem Behavior Across Development: A Multi-Informant Twin Study

The use of cross-informant ratings in previous longitudinal studies on externalizing behavior may have obscured the presence of continuity of genetic risk. The current study included latent factors representing the latent estimates of externalizing behavior based on both parent and self-report which eliminated rater-specific effects from these latent estimates. Symptoms of externalizing behavior of 1,480 Swedish twin pairs were obtained at ages 8–9, 13–14, 16–17 and 19–20 both by parent and self-report. Mx modeling was used to estimate additive genetic, shared and specific environmental influences. Genetic continuity was found over the entire developmental period as well as additional sources of genetic influence emerging around early and late adolescence. New unique environmental effects (E) on externalizing behavior arose early in adolescence. The results support both the presence of genetic continuity and change in externalizing behavior during adolescence due to newly emerging genetic and environmental risk factors.