The Causes of Individual Differences in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is characterized by various symptoms including impaired social interactions, unusually repetitive behaviors, and highly restricted interests etc. People with ASD differ significantly on their clinical profiles and the causes of such individual differences are not yet fully understood. The present paper provides an overview of the causes of individual differences in ASD from three different perspectives: genetic, environmental, and neurobiological perspectives. The present paper also describes one study design in detail within each perspective (i.e., classical twin design, epidemiological case-control design, and magnetic resonance imaging), and explains how each study design is informative about the causes of ASD.

Trait-specific testing of the equal environment assumption: The case of school grades and upper secondary school attendance

Objective: This paper tests the equal environment assumption for school grades and upper secondary school attendance and describes the conditions under which violations are problematic. Background: A growing number of sociologists use twin-based research designs, particularly the Classical Twin Design (CTD), to differentiate between genetic and social causes of social inequalities. One key assumption of CTD is that environmental influences are shared by monozygotic and dizygotic twins to the same extent; called the equal environment assumption (EEA). This assumption is frequently contested and the target of concern, because violation can result in an overestimation of heritability and an underestimation of the role of the social environment. Method: Using data from the first wave of the German TwinLife study, the paper illustrates two approaches to test EEA for school grades and enrolment in upper secondary school (Gymnasium). The analysis is based on a sample of twins (N = 1,576) aged ten to twelve years. Results: The results show that the approaches are able to detect violations of EEA (though in different ways), depending on the environmental variables that might causally be involved in trait variance. Only in one case was a violation was observed; it had no effect on heritability estimates. Conclusion: While EEA holds for school grades, violations do not automatically invalidate CTD in case of upper secondary school attendance.

Estimating heritability of psychological traits using the classical twin design; a gentle introduction to concepts and assumptions

Heritability is a concept that is often misunderstood. The term is used somewhat differently by researchers from how it is used in common parlance. This paper is a gentle introduction to the scientific concept of heritability, and to how it can be estimated for psychological traits in humans through analyses of data from monozygotic and dizygotic pairs of twins. The paper then explores some of the assumptions of the classical twin design, and presents calculations of the consequences of breaking these assumptions. Lastly, the paper introduces multivariate twin modeling, with a focus on how heritability of traits can be impacted by causal effects from other traits, and how twin designs can be informative when making causal inferences.

Birmingham and Beyond

Nick Martin was a doctoral student of mine at the University of Birmingham in the mid 1970s. In this review, I discuss two of Nick’s earliest and most seminal contributions to the field of behavior genetics. First, Martin and Eaves’ (1977) extension of the model-fitting approach to multivariate data, which laid the theoretical groundwork for a generation of multivariate behavior genetic studies. Second, the Martin et al.’s (1978) manuscript on the power of the classical twin design, which showed that thousands of twin pairs would be required in order to reliably estimate components of variance, and has served as impetus for the formation of large-scale twin registries across the world. I discuss these contributions against the historical backdrop of a time when we and others were struggling with the challenge of figuring out how to incorporate gene-by-environment interaction, gene–environment correlation, mate selection and cultural transmission into more complex genetic models of human behavior.

Musings on Visscher et al. (2006)

The classical twin design relies on a number of strong number of assumptions in order to yield unbiased estimates of heritability. This includes the equal environments assumption — that monozygotic and dizygotic twins experience similar degrees of environmental similarity — an assumption that is likely to be violated in practice for many traits of interest. An alternative method of estimating heritability that does not suffer from many of these limitations is to model trait similarity between sibling pairs as a function of their empirical genome-wide identity by descent sharing, estimated from genetic markers. In this review, I recount the story behind Nick Martin’s and my development of this method, our first attempts at applying it in a human population and more recent studies using the original and related methods to estimate trait heritability.

Statistical Power and the Classical Twin Design

Dr Nick Martin has made enormous contributions to the field of behavior genetics over the past 50 years. Of his many seminal papers that have had a profound impact, we focus on his early work on the power of twin studies. He was among the first to recognize the importance of sample size calculation before conducting a study to ensure sufficient power to detect the effects of interest. The elegant approach he developed, based on the noncentral chi-squared distribution, has been adopted by subsequent researchers for other genetic study designs, and today remains a standard tool for power calculations in structural equation modeling and other areas of statistical analysis. The present brief article discusses the main aspects of his seminal paper, and how it led to subsequent developments, by him and others, as the field of behavior genetics evolved into the present era.

Heritability in friendship networks

Friendship networks account for a large part of an individual’s economic success or failure in life. Using data from the German TwinLife study, we explore, within a classical twin design, to which extent friendship networks are related to genes. We find a substantial heritability component in twins’ network sizes and network homophily, but not in twins’ network closeness. Addressing indirect ways in which genes could influence network characteristics, we do not find evidence that shared hobbies affects networks.