A general test for gene-environment interaction in sib pair-based association analysis of quantitative traits

The Concept of Resistance to Substance Use and a Research Approach: The Resist! Project

Illicit substance use is dangerous in both acute and chronic forms, frequently resulting in lethal poisoning, addiction, and other negative consequences. Similar to research in other psychiatric conditions, whose ultimate goal is to enable effective prevention and treatment, studies in substance use are focused on factors elevating the risk for the disorder. The rapid growth of the substance use problem despite the effort invested in fighting it, however, suggests the need in changing the research approach. Instead of attempting to identify risk factors, whose neutralization is often infeasible if not impossible, it may be more promising to systematically reverse the perspective to the factors enhancing the aspect of liability to disorder that shares the same dimension but is opposite to risk, that is, resistance to substance use. Resistance factors, which enable the majority of the population to remain unaffected despite the ubiquity of psychoactive substances, may be more amenable to translation. While the resistance aspect of liability is symmetric to risk, the resistance approach requires substantial changes in sampling (high-resistance rather than high-risk) and using quantitative indices of liability. This article provides an overview and a practical approach to research in resistance to substance use/addiction, currently implemented in a NIH-funded project. The project benefits from unique opportunities afforded by the data originating from two longitudinal twin studies, the Virginia Twin Study of Adolescent and Behavioral Development and the Minnesota Twin Family Study. The methodology described is also applicable to other psychiatric disorders.

Genetic and Environmental Variation in Continuous Phenotypes in the ABCD Study®

Twin studies yield valuable insights into the sources of variation, covariation and causation in human traits. The ABCD Study® (abcdstudy.org) was designed to take advantage of four universities known for their twin research, neuroimaging, population-based sampling, and expertise in genetic epidemiology so that representative twin studies could be performed. In this paper we use the twin data to: (i) provide initial estimates of heritability for the wide range of phenotypes assessed in the ABCD Study using a consistent direct variance estimation approach, assuring that both data and methodology are sound; and (ii) provide an online resource for researchers that can serve as a reference point for future behavior genetic studies of this publicly available dataset. Data were analyzed from 772 pairs of twins aged 9-10 years at study inception, with zygosity determined using genotypic data, recruited and assessed at four twin hub sites. The online tool provides twin correlations and both standardized and unstandardized estimates of additive genetic, and environmental variation for 14,500 continuously distributed phenotypic features, including: structural and functional neuroimaging, neurocognition, personality, psychopathology, substance use propensity, physical, and environmental trait variables. The estimates were obtained using an unconstrained variance approach, so they can be incorporated directly into meta-analyses without upwardly biasing aggregate estimates. The results indicated broad consistency with prior literature where available and provided novel estimates for phenotypes without prior twin studies or those assessed at different ages. Effects of site, self-identified race/ethnicity, age and sex were statistically controlled. Results from genetic modeling of all 53,172 continuous variables, including 38,672 functional MRI variables, will be accessible via the user-friendly open-access web interface we have established, and will be updated as new data are released from the ABCD Study. This paper provides an overview of the initial results from the twin study embedded within the ABCD Study, an introduction to the primary research domains in the ABCD study and twin methodology, and an evaluation of the initial findings with a focus on data quality and suitability for future behavior genetic studies using the ABCD dataset. The broad introductory material is provided in recognition of the multidisciplinary appeal of the ABCD Study. While this paper focuses on univariate analyses, we emphasize the opportunities for multivariate, developmental and causal analyses, as well as those evaluating heterogeneity by key moderators such as sex, demographic factors and genetic background.

Financial strain moderates genetic influences on self-rated health: support for diathesis-stress model of gene-environment interplay

Data from the Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium were used to examine predictions of different models of gene-by-environment interaction to understand how genetic variance in self-rated health (SRH) varies at different levels of financial strain. A total of 11,359 individuals from 10 twin studies in Australia, Sweden, and the United States contributed relevant data, including 2,074 monozygotic and 2,623 dizygotic twin pairs. Age ranged from 22 to 98 years, with a mean age of 61.05 (SD = 13.24). A factor model was used to create a harmonized measure of financial strain across studies and items. Twin analyses of genetic and environmental variance for SRH incorporating age, age², sex, and financial strain moderators indicated significant financial strain moderation of genetic influences on self-rated health. Moderation results did not differ across sex or country. Genetic variance for SRH increased as financial strain increased, matching the predictions of the diathesis-stress and social comparison models for components of variance. Under these models, environmental improvements would be expected to reduce genetically based health disparities.

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.

IGEMS: The Consortium on Interplay of Genes and Environment Across Multiple Studies - An Update

The Interplay of Genes and Environment across Multiple Studies (IGEMS) is a consortium of 18 twin studies from 5 different countries (Sweden, Denmark, Finland, United States, and Australia) established to explore the nature of gene-environment (GE) interplay in functioning across the adult lifespan. Fifteen of the studies are longitudinal, with follow-up as long as 59 years after baseline. The combined data from over 76,000 participants aged 14-103 at intake (including over 10,000 monozygotic and over 17,000 dizygotic twin pairs) support two primary research emphases: (1) investigation of models of GE interplay of early life adversity, and social factors at micro and macro environmental levels and with diverse outcomes, including mortality, physical functioning and psychological functioning; and (2) improved understanding of risk and protective factors for dementia by incorporating unmeasured and measured genetic factors with a wide range of exposures measured in young adulthood, midlife and later life.

Early life socioeconomic status moderates associations between objective sleep and weight-related indicators in middle childhood

OBJECTIVES

This study tested whether early socioeconomic status moderated links between objective and subjective sleep and weight indicators during middle childhood.

DESIGN

The study design was cross-sectional but included data from earlier assessment points in the study.

SETTING

Data were collected from families across the state of Arizona.

PARTICIPANTS

Participants were 382 children recruited from birth records (49.5% female; M_age = 8.47 years; 56.5% European American; 25.1% Latino; 25% living at or below the poverty line).

MEASUREMENTS

Assessments included socioeconomic status at 12 months of age, and sleep and weight indicators at 8 years.

RESULTS

Longer sleep durations predicted lower body mass index and decreased odds of being overweight/obese across all children, regardless of socioeconomic background. For children from low socioeconomic backgrounds, longer sleep duration predicted lower percent body fat, greater efficiency predicted lower percent body fat and body mass index and smaller waist circumference, and more sleep problems predicted larger waist circumference. For children from low socioeconomic backgrounds, greater sleep duration and efficiency also predicted the lowest odds of being overweight/obese, and more sleep problems predicted the greatest odds of being overweight/obese.

CONCLUSIONS

Early life may be a sensitive period that sets the stage for stronger links between sleep and weight indicators in middle childhood. Findings offer important information regarding the protective role of sleep in the promotion of health, as well as the negative consequences that may be stronger for children who experienced low early-life socioeconomic status.

Complex effects of dyslexia risk factors account for ADHD traits: evidence from two independent samples

BACKGROUND

Developmental dyslexia (DD) and attention deficit/hyperactivity disorder (ADHD) are among the most common neurodevelopmental disorders, whose etiology involves multiple risk factors. DD and ADHD co-occur in the same individuals much more often than would be expected by chance. Several studies have found significant bivariate heritability, and specific genes associated with either DD or ADHD have been investigated for association in the other disorder. Moreover, there are likely to be gene-by-gene and gene-by-environment interaction effects (G × G and G × E, respectively) underlying the comorbidity between DD and ADHD. We investigated the pleiotropic effects of 19 SNPs spanning five DD genes (DYX1C1, DCDC2, KIAA0319, ROBO1, and GRIN2B) and seven DD environmental factors (smoke, miscarriage, birth weight, breastfeeding, parental age, socioeconomic status, and parental education) for main, either (a) genetic or (b) environmental, (c) G × G, and (d) G × E upon inattention and hyperactivity/impulsivity. We then attempted replication of these findings in an independent twin cohort.

METHODS

Marker-trait association was analyzed by implementing the Quantitative Transmission Disequilibrium Test (QTDT). Environmental associations were tested by partial correlations. G × G were investigated by a general linear model equation and a family-based association test. G × E were analyzed through a general test for G × E in sib pair-based association analysis of quantitative traits.

RESULTS

DCDC2-rs793862 was associated with hyperactivity/impulsivity via G × G (KIAA0319) and G × E (miscarriage). Smoke was significantly correlated with hyperactivity/impulsivity. We replicated the DCDC2 × KIAA0319 interaction upon hyperactivity/impulsivity in the twin cohort.

CONCLUSIONS

DD genetic (DCDC2) and environmental factors (smoke and miscarriage) underlie ADHD traits supporting a potential pleiotropic effect.

Gender Differences in Marital Status Moderation of Genetic and Environmental Influences on Subjective Health

From the IGEMS Consortium, data were available from 26,579 individuals aged 23 to 102 years on 3 subjective health items: self-rated health (SRH), health compared to others (COMP), and impact of health on activities (ACT). Marital status was a marker of environmental resources that may moderate genetic and environmental influences on subjective health. Results differed for the 3 subjective health items, indicating that they do not tap the same construct. Although there was little impact of marital status on variance components for women, marital status was a significant modifier of variance in all 3 subjective health measures for men. For both SRH and ACT, single men demonstrated greater shared and nonshared environmental variance than married men. For the COMP variable, genetic variance was greater for single men vs. married men. Results suggest gender differences in the role of marriage as a source of resources that are associated with subjective health.

Genotype by environment interactions in cognitive ability: a survey of 14 studies from four countries covering four age groups

A large part of the variation in cognitive ability is known to be due to genetic factors. Researchers have tried to identify modifiers that influence the heritability of cognitive ability, indicating a genotype by environment interaction (G×E). To date, such modifiers include measured variables like income and socioeconomic status. The present paper focuses on G×E in cognitive ability where the environmental variable is an unmeasured environmental factor that is uncorrelated in family members. We examined this type of G×E in the GHCA-database (Haworth et al., Behav Genet 39:359-370, 2009), which comprises data of 14 different cognition studies from four different countries including participants of different ages. Results indicate that for younger participants (4-13 years), the strength of E decreases across the additive genetic factor A, but that this effect reverts for older participants (17-34 years). However, a clear and general conclusion about the presence of a genuine G×E is hampered by differences between the individual studies with respect to environmental and genetic influences on cognitive ability.

Challenges and opportunities in genome-wide environmental interaction (GWEI) studies

The interest in performing gene-environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene-environment interaction studies and the technical challenges related to these studies-when the number of environmental or genetic risk factors is relatively small-has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze genome-wide environmental interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for genome-wide association gene-gene interaction studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to "joining" two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes.

Detecting specific genotype by environment interactions using marginal maximum likelihood estimation in the classical twin design

Considerable effort has been devoted to the analysis of genotype by environment (G × E) interactions in various phenotypic domains, such as cognitive abilities and personality. In many studies, environmental variables were observed (measured) variables. In case of an unmeasured environment, van der Sluis et al. (2006) proposed to study heteroscedasticity in the factor model using only MZ twin data. This method is closely related to the Jinks and Fulker (1970) test for G × E, but slightly more powerful. In this paper, we identify four challenges to the investigation of G × E in general, and specifically to the heteroscedasticity approaches of Jinks and Fulker and van der Sluis et al. We propose extensions of these approaches purported to solve these problems. These extensions comprise: (1) including DZ twin data, (2) modeling both A × E and A × C interactions; and (3) extending the univariate approach to a multivariate approach. By means of simulations, we study the power of the univariate method to detect the different G × E interactions in varying situations. In addition, we study how well we could distinguish between A × E, A × C, and C × E. We apply a multivariate version of the extended model to an empirical data set on cognitive abilities.

Alcohol and aggressive behavior in men--moderating effects of oxytocin receptor gene (OXTR) polymorphisms

We explored if the disposition to react with aggression while alcohol intoxicated was moderated by polymorphic variants of the oxytocin receptor gene (OXTR). Twelve OXTR polymorphisms were genotyped in 116 Finnish men [aged 18-30, M = 22.7, standard deviation (SD) = 2.4] who were randomly assigned to an alcohol condition in which they received an alcohol dose of 0.7 g pure ethanol/kg body weight or a placebo condition. Aggressive behavior was measured using a laboratory paradigm in which it was operationalized as the level of aversive noise administered to a fictive opponent. No main effects of the polymorphisms on aggressive behavior were found after controlling for multiple testing. The interactive effects between alcohol and two of the OXTR polymorphisms (rs4564970 and rs1488467) on aggressive behavior were nominally significant and remained significant for the rs4564970 when controlled for multiple tests. To the best of our knowledge, this is the first experimental study suggesting interactive effects of specific genetic variants and alcohol on aggressive behavior in humans.

Causes and consequences of obesity: the contribution of recent twin studies

Obesity is a genetically complex disorder that produces a myriad of health problems. Most of the recognized complications of obesity are not only strongly influenced by lifestyle factors, but also present with independent genetic predispositions that are notoriously difficult to disentangle in humans. Most studies on the causes and consequences of acquired obesity are encumbered by the incomplete ability to control for genetic influences. However, utilizing a unique experiment of nature, namely monozygotic twins (MZ) discordant for obesity as 'clonal controls' of obese and non-obese individuals has enabled the fine characterization of the effects and possible antecedents of acquired obesity while controlling for the genetic background, as well as pointed to novel obesity predisposing candidate genes. This review is a distillation of the findings from more than 10 years of research done in an exceptionally well-characterized collection of MZ and dizygotic (DZ) twins, based on the Finnish Twin Cohorts. Topics covered include the nature of development of obesity from the childhood onwards, the role of exercise in modifying the genetic susceptibility, the resulting inflammatory, prediabetic and preatherosclerotic changes in whole body and adipose tissue physiology, as well as the newest insights provided by the omics revolution.

A note on false positives and power in G × E modelling of twin data

The variance components models for gene–environment interaction proposed by Purcell in 2002 are widely used. In both the bivariate and the univariate parameterization of these models, the variance decomposition of trait T is a function of moderator M. We show that if M and T are correlated, and moderator M is correlated between twins as well, the univariate parameterization produces a considerable increase in false positive moderation effects. A simple extension of this univariate moderation model prevents this elevation of the false positive rate provided the covariance between M and T is itself not also subject to moderation. If the covariance between M and T varies as a function of M, then moderation effects observed in the univariate setting should be interpreted with care as these can have their origin in either moderation of the covariance between M and T or in moderation of the unique paths of T. We conclude that researchers should use the full bivariate moderation model to study the presence of moderation on the covariance between M and T. If such moderation can be ruled out, subsequent use of the extended univariate moderation model, as proposed in this paper, is recommended as this model is more powerful than the full bivariate moderation model.

Genetic effects on anger control and their interaction with alcohol intoxication: a self-report study

Individual differences in anger control are important to consider when trying to understand intoxicated aggression (Parrott and Giancola, 2004). We explored, first, genetic and environmental effects on anger control both in self-reported sober and alcohol intoxicated states, and whether the same genetic and environmental effects influence it in both these states, and second, a possible interaction between genetic effects and alcohol in the control of anger. In the population based sample (N=8964) of Finnish twins (18-33 years) and their siblings (18 years or older), genetic effects on anger control were found both for the self-reported sober (27% for men, 34% for women) and alcohol intoxicated states (29% for men, 37% for women), with high genetic correlations (from .77 to .85) between these states. Genetic effects (26% for men, 29% for women) were also found for the difference in anger control between the self-reported sober and alcohol intoxicated states, suggesting the effect of alcohol on anger control depends on the genotype of the individual.