Brad Verhulst

The heritability of alcohol use disorders: a meta-analysis of twin and adoption studies

BACKGROUND To clarify the role of genetic and environmental risk factors in alcohol use disorders (AUDs), we performed a meta-analysis of twin and adoption studies and explored the impact of sex, assessment method (interview v. hospital/population records), and study design (twin v. adoption study) on heritability estimates. METHOD The literature was searched for all unique twin and adoption studies of AUD and identified 12 twin and five adoption studies. The data were then reconstructed and analyzed using ordinal data full information maximum likelihood in the OpenMx program. Heterogeneity was tested with likelihood ratio tests by equating the parameters across studies. RESULTS There was no evidence for heterogeneity by study design, sex or assessment method. The best-fit estimate of the heritability of AUD was 0.49 [95% confidence interval (CI) 0.43-0.53], and the proportion of shared environmental variance was 0.10 (95% CI 0.03-0.16). Estimates of unique environmental proportions of variance differed significantly across studies. CONCLUSIONS AUD is approximately 50% heritable. The multiple genetically informative studies of this syndrome have produced consistent results that support the validity of this heritability estimate, especially given the different potential methodological weaknesses of twin and adoption designs, and of assessments of AUD based on personal interviews v. official records. We also found evidence for modest shared environmental effects suggesting that environmental factors also contribute to the familial aggregation of AUDs.

Integrating social science and genetics: news from the political front.

There has been growing interest in the use of genetic models to expand the understanding of political preferences, attitudes, and behaviors. Researchers in the social sciences have begun incorporating these models and have revealed that genetic differences account for individual differences in political beliefs, behaviors, and responses to the political environment. The first Integrating Genetics and the Social Sciences Conference, held at Boulder, Colorado in May of 2010, brought together these researchers. As a result, we jointly review the last 5 years of research in this area. In doing so, we explicate the methods, findings, and limitations of behavior genetic approaches, including twin designs, association studies, and genome-wide analyses, in their application toward exploring political preferences.

A Genetically Informed Study of the Longitudinal Relation Between Irritability and Anxious/Depressed Symptoms

OBJECTIVE Little is known about the longitudinal genetic and environmental association between juvenile irritability and symptoms of anxiety and depression. This studys goal was to assess the relationship between these constructs across a critical developmental period spanning childhood to young adulthood. METHOD Parents (n = 1,348 twin pairs) from the Swedish Twin Study of Child and Adolescent Development completed the Child/Adult Behavior Checklist (CBCL/ABCL) about their twin children. Data were collected during a prospective, 4-wave study starting in childhood (ages 8-9 years) and ending in young adulthood (ages 19-20 years). An irritability score and an anxious/depressed score were computed from CBCL/ABCL item endorsements. Genetically informative cross-lagged models were used to estimate the genetic and environmental relationship between these 2 constructs across time. RESULTS Our models suggested that irritability more strongly predicted anxious/depressed symptoms than vice versa, consistent with a causal role of irritability on anxiety/depression at older ages. This relationship was significant only in late childhood/early adolescence. Additive genetic and unique environmental factors were significant contributors to both irritability and anxious/depressed symptoms and were both specific to and shared between these 2 constructs. The same common environmental factors influenced both constructs, although these factors accounted for a smaller amount of variance than genetic or unique environmental factors. CONCLUSION This study adds to our understanding of the developmental relationship between irritability and anxious/depressed symptoms and the contribution of genes and environmental factors to their association across development. Findings suggest the need to monitor for emergence of internalizing symptoms in irritable children and their potential need for therapeutic intervention.

Political attitudes develop independently of personality traits.

The primary assumption within the recent personality and political orientations literature is that personality traits cause people to develop political attitudes. In contrast, research relying on traditional psychological and developmental theories suggests the relationship between most personality dimensions and political orientations are either not significant or weak. Research from behavioral genetics suggests the covariance between personality and political preferences is not causal, but due to a common, latent genetic factor that mutually influences both. The contradictory assumptions and findings from these research streams have yet to be resolved. This is in part due to the reliance on cross-sectional data and the lack of longitudinal genetically informative data. Here, using two independent longitudinal genetically informative samples, we examine the joint development of personality traits and attitude dimensions to explore the underlying causal mechanisms that drive the relationship between these features and provide a first step in resolving the causal question. We find change in personality over a ten-year period does not predict change in political attitudes, which does not support a causal relationship between personality traits and political attitudes as is frequently assumed. Rather, political attitudes are often more stable than the key personality traits assumed to be predicting them. Finally, the results from our genetic models find that no additional variance is accounted for by the causal pathway from personality traits to political attitudes. Our findings remain consistent with the original construction of the five-factor model of personality and developmental theories on attitude formation, but challenge recent work in this area.

Gene-Environment Interplay in Twin Models

In this article, we respond to Shultziner’s critique that argues that identical twins are more alike not because of genetic similarity, but because they select into more similar environments and respond to stimuli in comparable ways, and that these effects bias twin model estimates to such an extent that they are invalid. The essay further argues that the theory and methods that undergird twin models, as well as the empirical studies which rely upon them, are unaware of these potential biases. We correct this and other misunderstandings in the essay and find that gene-environment (GE) interplay is a well-articulated concept in behavior genetics and political science, operationalized as gene-environment correlation and gene-environment interaction. Both are incorporated into interpretations of the classical twin design (CTD) and estimated in numerous empirical studies through extensions of the CTD. We then conduct simulations to quantify the influence of GE interplay on estimates from the CTD. Due to the criticism’s mischaracterization of the CTD and GE interplay, combined with the absence of any empirical evidence to counter what is presented in the extant literature and this article, we conclude that the critique does not enhance our understanding of the processes that drive political traits, genetic or otherwise.

Using genetic information to test causal relationships in cross-sectional data

Cross-sectional data from twins contain information that can be used to derive a test of causality between traits. This test of directionality is based upon the fact that genetic relationships between family members conform to an established structural pattern. In this paper we examine several common methods for empirically testing causality as well as several genetic models that we build on for the Direction of Causation (DoC) model. We then discuss the mathematical components of the DoC model and highlight limitations of the model and potential solutions to these limitations. We conclude by presenting an example from the personality and politics literature that has begun to explore the question whether or not personality traits cause people to hold specific political attitudes.

A Power Calculator for the Classical Twin Design

Power is a ubiquitous, though often overlooked, component of any statistical analyses. Almost every funding agency and institutional review board requires that some sort of power analysis is conducted prior to data collection. While there are several excellent on line power calculators for independent observations, twin studies pose unique challenges that are not incorporated into these algorithms. The goal of the current manuscript is to outline a general method for calculating power in twin studies, and to provide functions to allow researchers to easily conduct power analyses for a range of common twin models. Several scenarios are discussed to demonstrate the importance of various factors that influence the power within the classical twin design and to serve as examples for the provided functions.

Genetic network properties of the human cortex based on regional thickness and surface area measures

We examined network properties of genetic covariance between average cortical thickness (CT) and surface area (SA) within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques—biometrical genetic modeling, cluster analysis, and graph theory—to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function.

Obsessive compulsive symptom dimensions and neuroticism: An examination of shared genetic and environmental risk

Individuals with obsessive compulsive disorder can display diverse and heterogeneous patterns of symptoms. Little is known about the relationship between obsessive‐compulsive symptom (OCS) dimensions and normal personality traits, particularly those that increase risk for other internalizing disorders. In this study of 1,382 individuals from female–female twin pairs, we examined the relationship between self‐report OCS dimensions derived from the Padua Inventory and Eysencks personality traits neuroticism and extraversion. We conducted factor analysis to determine their phenotypic structure followed by twin analyses to determine their genetic and environmental sources of covariation. A three‐factor solution, with dimensions corresponding to checking, aggressive obsessions, and contamination, was the best fit for the Padua OCS items. These dimensions were significantly and somewhat variably associated with neuroticism but negligibly associated with extraversion. The genetic correlations between neuroticism and these three OCS dimensions were moderate to high (0.66 with checking, 0.89 with aggressive obsessions, and 0.40 with contamination). However, the estimated genetic correlation between neuroticism and a unified latent OCS construct was smaller (0.32). Overall this study suggests that genetic, and to a smaller extent environmental, factors underlying neuroticism may act differentially as risk factors for OCS dimensions.

Integrating classical and contemporary explanations of political participation.

Traditional theories of political participation have emphasized its social and normative components; however, recent evidence suggests that political participation has a strong additive genetic component. Accordingly, it is necessary to reevaluate the traditional empirical findings and begin to integrate the two approaches. To do so, a variety of analyses were conducted that explore the modes of genetic and environmental transmission. I find that the empirical estimates of the relationships between the phenotypic level traits are highly consistent with what has been found in the traditional literature, the vast majority of the variance in political participation that is accounted for by the predictor variables is being accounted for at the genetic level, and not at the environmental level. Thus, the current findings suggest that the empirical results found in prior studies are quite likely very accurate. However, the interpretation of those empirical findings, as well as the subsequent theoretical implications, require serious revision.