Inferring the direction of causation in cross-sectional twin data: theoretical and empirical considerations

Causal and common risk pathways linking childhood maltreatment to later intimate partner violence victimization

Childhood maltreatment and intimate partner violence (IPV) victimization are major psychiatric risk factors. Maltreatment substantially increases the likelihood of subsequent IPV victimization, but what drives this association is poorly understood. We analyzed retrospective self-reports of maltreatment and IPV victimization in 12,794 participants (58% women, 42% men) from the Twins Early Development Study at ages 21 and 26 using quantitative genetic methods. We estimated the etiological influences common to maltreatment and IPV, and the effect of maltreatment on IPV beyond such common influences. Participants who reported childhood maltreatment ( ~ 7% of the sample) were 3 times more likely than their peers to also report IPV victimization at age 21, 4 times more likely at 26. The association between maltreatment and IPV was mostly due to environmental influences shared by co-twins (42-43%) and genetic influences (30-33%), as well as nonshared environmental influences (25-27%). The association between maltreatment and IPV was similar for women and men, but its etiology partly differed by sex. Maltreatment had a moderate effect on IPV in phenotypic models (β = 0.25-0.30), decreasing to a small-to-moderate range in causally informative models accounting for their common etiology (β = 0.15-0.21). Risk factors common to maltreatment and IPV victimization are largely familial in origin, environmental and genetic. Even considering common risk factors, experiencing maltreatment may be causally related to subsequent IPV victimization. Interventions promoting safe intimate relationships among young adults exposed to maltreatment are warranted and should address family-level environmental risk and individual-level risk shaped by genetics.

Calculating Within-Pair Difference Scores in the Co-twin Control Design. Effects of Alternative Strategies

Co-twin studies are an elegant and powerful design that allows controlling for the effect of confounding variables, including genetic and a range of environmental factors. There are several approaches to carry out this design. One of the methods commonly used, when contrasting continuous variables, is to calculate difference scores between members of a twin pair on two associated variables, in order to analyse the covariation of such differences. However, information regarding whether and how the different ways of estimating within-pair difference scores may impact the results is scant. This study aimed to compare the results obtained by different methods of data transformation when performing a co-twin study and test how the magnitude of the association changes using each of those approaches. Data was simulated using a direction of causation model and by fixing the effect size of causal path to low, medium, and high values. Within-pair difference scores were calculated as relative scores for diverse within-pair ordering conditions or absolute scores. Pearson's correlations using relative difference scores vary across the established scenarios (how twins were ordered within pairs) and these discrepancies become larger as the within-twin correlation increases. Absolute difference scores tended to produce the lowest correlation in every condition. Our results show that both using absolute difference scores or ordering twins within pairs, may produce an artificial decrease in the magnitude of the studied association, obscuring the ability to detect patterns compatible with causation, which could lead to discrepancies across studies and erroneous conclusions.

Testing the causal impact of amyloidosis on total Tau using a genetically informative sample of adult male twins

INTRODUCTION

The amyloid cascade hypothesis predicts that amyloid-beta (Aβ) aggregation drives tau tangle accumulation. We tested competing causal and non-causal hypotheses regarding the direction of causation between Aβ40 and Aβ42 and total Tau (t-Tau) plasma biomarkers.

METHODS

Plasma Aβ40, Aβ42, t-Tau, and neurofilament light chain (NFL) were measured in 1,035 men (mean = 67.0 years) using Simoa immunoassays. Genetically informative twin modeling tested the direction of causation between Aβs and t-Tau.

RESULTS

No clear evidence that Aβ40 or Aβ42 directly causes changes in t-Tau was observed; the alternative causal hypotheses also fit the data well. In contrast, exploratory analyses suggested a causal impact of the Aβ biomarkers on NFL. Separately, reciprocal causation was observed between t-Tau and NFL.

DISCUSSION

Plasma Aβ40 or Aβ42 do not appear to have a direct causal impact on t-Tau. In contrast, Aβ aggregation may causally impact NFL in cognitively unimpaired men in their late 60s.

On the detection of population heterogeneity in causation between two variables: Finite mixture modeling of data collected from twin pairs

Causal inference is inherently complex, often dependent on key assumptions that are sometimes overlooked. One such assumption is the potential for unidirectional or bidirectional causality, while another is population homogeneity, which suggests that the causal direction between two variables remains consistent across the study sample. Discerning these processes requires meticulous data collection through an appropriate research design and the use of suitable software to define and fit alternative models. In psychiatry, the co-occurrence of different disorders is common and can stem from various origins. A patient diagnosed with two disorders might have one recognized as primary and the other as secondary, suggesting the existence of two types of comorbidity within the population. For example, in some individuals, depression might lead to substance use, while in others, substance use could lead to depression. Identifying the primary disorder is crucial for developing effective treatment plans. This article explores the use of finite mixture models to depict within-sample heterogeneity. We begin with the Direction of Causation (DoC) model for twin data and extend it to a mixture distribution model. This extension allows for the calculation of the likelihood of each individual's data for the two alternate causal directions. Given twin data, there are four possible pairwise combinations of causal direction. Through simulations, we investigate the Direction of Causation Twin Mixture (mixCLPM) model's potential to detect and model heterogeneity due to varying causal directions.

The relationship of school performance with self-control and grit is strongly genetic and weakly causal

The non-cognitive skills self-control and grit are often considered predictors of school performance, but whether this relationship is causal remains unclear. We investigated the causality of this association using a twin design. Specifically, we evaluated the direct impact of self-control and grit on school performance, while controlling for genetic or environmental influences common to all three traits (i.e., confounding). Teachers of 4891 Dutch 12-year-old twin pairs (of which 3837 were complete pairs) completed a survey about school performance (school grades), self-control (ASEBA self-control scale), and the perseverance aspect of grit. Our analysis aimed to determine the direct impact of self-control and grit on school performance, while simultaneously controlling for genetic or environmental confounding. Establishing the regression relationship corrected for confounding supports the interpretation of the regression relationship as causal. In all analyses, we corrected for sex, rater bias of the teachers, and parental socioeconomic status. Initially, in the standard regression, self-control, and grit explained 28.4% of the school performance variance. However, allowing for genetic confounding (due to genetic pleiotropy) revealed that most of this association could be attributed to genetic influences that the three traits share. In the presence of genetic pleiotropy, the phenotypic regression of school performance on self-control and grit accounted for only 4.4% (i.e., the effect size association with the causal hypothesis). In conclusion, self-control and grit predict school performance primarily due to genetic pleiotropy, with a much smaller causal effect (R2 = 4.4%). This suggests that interventions targeting self-control and grit alone may yield limited improvements in school performance.

Direction of dependence analysis for pre-post assessments using non-Gaussian methods: a tutorial

OBJECTIVE

We introduced methods for solving causal direction of dependence between variables observed in pre- and post-psychotherapy assessments, showing how to apply them and investigate their properties via simulations. In addition, we investigated whether changes in depressive symptoms drive changes in social and occupational functioning as suggested by the phase model of psychotherapy or vice versa, or neither.

METHOD

As a Gaussian (normal-distribution) model is unidentifiable here, we used an identifiable linear non-Gaussian structural vector autoregression model, conceptualizing instantaneous effects as during-psychotherapy causation and lagged effects as pre-treatment predictors of change. We tested six alternative estimators in six simulation settings that captured different real-world scenarios, and used real psychotherapy data from 1428 adult patients (Finnish Psychotherapy Quality Registry; assessments on Patient Health Questionnaire-9 and Social and Occupational Functioning Assessment Schedule).

RESULTS

The methodology was successful in identifying causal directions in simulated data. The real-data results provided no evidence for single direction of dependence, suggesting shared or reciprocal causation.

CONCLUSIONS

A powerful new tool was presented to investigate the process of psychotherapy using observational data. Application to patient data suggested that depression symptoms and functioning may reciprocate or reflect third variables instead of one predominantly driving the other during psychotherapy.

Power, measurement error, and pleiotropy robustness in twin-design extensions to Mendelian Randomization

Mendelian Randomization (MR) has become an important tool for causal inference in the health sciences. It takes advantage of the random segregation of alleles to control for background confounding factors. In brief, the method works by using genetic variants as instrumental variables, but it depends on the assumption of exclusion restriction, i.e., that the variants affect the outcome exclusively via the exposure variable. Equivalently, the assumption states that there is no horizontal pleiotropy from the variant to the outcome. This assumption is unlikely to hold in nature, so several extensions to MR have been developed to increase its robustness against horizontal pleiotropy, though not eliminating the problem entirely (Sanderson et al. 2022). The Direction of Causation (DoC) model, which affords information from the cross-twin cross-trait correlations to estimate causal paths, was extended with polygenic scores to explicitly model horizontal pleiotropy and a causal path (MR-DoC, Minică et al 2018). MR-DoC was further extended to accommodate bidirectional causation (MR-DoC2 ; Castro-de-Araujo et al. 2023). In the present paper, we compared the power of the DoC model, MR-DoC, and MR-DoC2. We investigated the effect of phenotypic measurement error and the effect of misspecification of unshared (individual-specific) environmental factors on the parameter estimates.

The Co-Twin Control Design: Implementation and Methodological Considerations

Establishing causal relationships in observational studies is an important step in research and policy decision making. The association between an exposure and an outcome can be confounded by multiple factors, often making it hard to draw causal conclusions. The co-twin control design (CTCD) is a powerful approach that allows for the investigation of causal effects while controlling for genetic and shared environmental confounding factors. This article introduces the CTCD and offers an overview of analysis methods for binary and continuous outcome and exposure variables. Tools for data simulation are provided, along with practical guidance and accompanying scripts for implementing the CTCD in R, SPSS, and Stata. While the CTCD offers valuable insights into causal inference, it depends on several assumptions that are important when interpreting CTCD results. By presenting a broad overview of the CTCD, this article aims to equip researchers with actionable recommendations and a comprehensive understanding of the design's strengths and limitations.

Literacy skills seem to fuel literacy enjoyment, rather than vice versa

Children who like to read and write tend to be better at it. This association is typically interpreted as enjoyment impacting engagement in literacy activities, which boosts literacy skills. We fitted direction-of-causation models to partial data of 3690 Finnish twins aged 12. Literacy skills were rated by the twins' teachers and literacy enjoyment by the twins themselves. A bivariate twin model showed substantial genetic influences on literacy skills (70%) and literacy enjoyment (35%). In both skills and enjoyment, shared-environmental influences explained about 20% in each. The best-fitting direction-of-causation model showed that skills impacted enjoyment, while the influence in the other direction was zero. The genetic influences on skills influenced enjoyment, likely via the skills→enjoyment path. This indicates an active gene-environment correlation: children with an aptitude for good literacy skills are more likely to enjoy reading and seek out literacy activities. To a lesser extent, it was also the shared-environmental influences on children's skills that propagated to influence children's literacy enjoyment. Environmental influences that foster children's literacy skills (e.g., families and schools), also foster children's love for reading and writing. These findings underline the importance of nurturing children's literacy skills. HIGHLIGHTS: It's known that how much children enjoy reading and writing and how good they are at it correlates ∼0.30, but causality remains unknown. We tested the direction of causation in 3690 twins aged 12. Literacy skills impacted literacy enjoyment, but not the other way around. Genetics influence children's literacy skills and how much they like and choose to read and write, indicating genetic niche picking.

MR-DoC2: Bidirectional Causal Modeling with Instrumental Variables and Data from Relatives

Establishing causality is an essential step towards developing interventions for psychiatric disorders, substance use and many other conditions. While randomized controlled trials (RCTs) are considered the gold standard for causal inference, they are unethical in many scenarios. Mendelian randomization (MR) can be used in such cases, but importantly both RCTs and MR assume unidirectional causality. In this paper, we developed a new model, MRDoC2, that can be used to identify bidirectional causation in the presence of confounding due to both familial and non-familial sources. Our model extends the MRDoC model (Minică et al. in Behav Genet 48:337-349,  https://doi.org/10.1007/s10519-018-9904-4 , 2018), by simultaneously including risk scores for each trait. Furthermore, the power to detect causal effects in MRDoC2 does not require the phenotypes to have different additive genetic or shared environmental sources of variance, as is the case in the direction of causation twin model (Heath et al. in Behav Genet 23:29-50,  https://doi.org/10.1007/BF01067552 , 1993).

Genetic factors explain a significant part of associations between adolescent well-being and the social environment

Socio-environmental factors play an important role in adolescent well-being, but potential genetic contributions to these associations are rarely assessed. To address this gap in the literature, associations between well-being and family conflict and functioning, number of friends, friendship importance and satisfaction, and leisure time variables were studied in N =  ~ 4700 twin pairs from the Netherlands Twin Register, us ing generalized estimating equations and twin-difference scores. When twin-difference scores indicated a role for genetic factors, we used bivariate genetic models to quantify genetic and environmental contributions to these associations. We identify significant associations between well-being and family functioning, family conflict, different leisure time activities, number of friends, and satisfaction with friendships. Additionally, we find evidence for large (73-91%) genetic influence on the associations between well-being and family conflict and functioning, leisure time sport/scouting clubs, and satisfaction with friendships. Finally, findings support the hypothesis of a causal association between well-being and family conflict and functioning. These findings have important implications for research into the social correlates of well-being in adolescence, as not taking genetic factors into account leads to overestimations of the influence of identified correlates and consequently to recommendations of these correlates as intervention targets.

Childhood maltreatment and disordered gambling in adulthood: disentangling causal and familial influences

BACKGROUND

Despite abundant research on the potential causal influence of childhood maltreatment (CM) on psychological maladaptation in adulthood, almost none has implemented the discordant twin design as a means of examining the role of such experiences in later disordered gambling (DG) while accounting for genetic and family environmental confounds. The present study implemented such an approach to disentangle the potential causal and familial factors that may account for the association between CM and DG.

METHODS

Participants were 3750 twins from the Australian Twin Registry [Mage = 37.60 (s.d. = 2.31); 58% female]. CM and DG were assessed separately via two semi-structured telephone interviews. Random-intercept generalized linear mixed models were fit to the data; zygosity, sex, educational attainment, childhood psychiatric disorder, adult antisocial behavior, and alcohol use disorder (AUD) were included as covariates.

RESULTS

Neither quasi-causal nor familial effects of CM predicted DG after adjusting for covariates. Educational attainment appeared to reduce the risk of DG while AUD appeared to increase risk; evidence also emerged for familial effects of antisocial behavior on DG. Post-hoc analyses revealed a familial effect of CM on antisocial behavior, indicating that the association between CM and DG identified in unadjusted models and in prior studies may be accounted for by genetic and shared family environmental effects of antisociality.

CONCLUSIONS

These findings add to the meager literature showing that CM does not exert a causal effect on DG, and present novel evidence that familial effects of antisocial behavior may account for the association between CM and DG identified in extant non-twin research.

Associations Between Traumatic Stress, Brain Volumes and Post-traumatic Stress Disorder Symptoms in Children: Data from the ABCD Study

Reduced volumes in brain regions of interest (ROIs), primarily from adult samples, are associated with posttraumatic stress disorder (PTSD). We extended this work to children using data from the Adolescent Brain Cognitive Development (ABCD) Study® (N = 11,848; Mage = 9.92). Structural equation modeling and an elastic-net (EN) machine-learning approach were used to identify potential effects of traumatic events (TEs) on PTSD symptoms (PTSDsx) directly, and indirectly via the volumes 300 subcortical and cortical ROIs. We then estimated the genetic and environmental variation in the phenotypes. TEs were directly associated with PTSDsx (r = 0.92) in children, but their indirect effects (r < 0.0004)-via the volumes of EN-identified subcortical and cortical ROIs-were negligible at this age. Additive genetic factors explained a modest proportion of the variance in TEs (23.4%) and PTSDsx (21.3%), and accounted for most of the variance of EN-identified volumes of four of the five subcortical (52.4-61.8%) three of the nine cortical ROIs (46.4-53.3%) and cerebral white matter in the left hemisphere (57.4%). Environmental factors explained most of the variance in TEs (C = 61.6%, E = 15.1%), PTSDsx (residual-C = 18.4%, residual-E = 21.8%), right lateral ventricle (C = 15.2%, E = 43.1%) and six of the nine EN-identified cortical ROIs (C = 4.0-13.6%, E = 56.7-74.8%). There is negligible evidence that the volumes of brain ROIs are associated with the indirect effects of TEs on PTSDsx at this age. Overall, environmental factors accounted for more of the variation in TEs and PTSDsx. Whereas additive genetic factors accounted for most of the variability in the volumes of a minority of cortical and in most of subcortical ROIs.

The Associations Between Leisure-Time Physical Activity and Academic Performance: A Twin Study

BACKGROUND

Both genetic and environmental influences have been shown to contribute to the association between physical activity and overall academic performance. The authors examined whether leisure-time physical activity (LTPA) shares genetic and environmental variances between spelling, essay writing, reading aloud, reading comprehension, and mathematics in early adolescence. Moreover, they investigated whether genetic polymorphisms associated with physical activity behavior affect these academic skills.

METHODS

Participants were 12-year-old Finnish twins (n = 4356-4370 twins/academic skill, 49% girls). Academic skills were assessed by teachers, and LTPA was self-reported. Polygenic scores for physical activity behavior were constructed from the UK Biobank. Quantitative genetic modeling and linear regression models were used to analyze the data.

RESULTS

The trait correlations between LTPA and academic skills were significant but weak (r = .05-.08). The highest trait correlation was found between LTPA and mathematics. A significant genetic correlation was revealed between LTPA and essay writing (rA = .14). Regarding polygenic scores of physical activity, the highest correlations were found with reading comprehension, spelling, and essay writing, but these results only approached statistical significance (P values = .09-.15).

CONCLUSIONS

The authors' results suggest that reading and writing are the academic skills that most likely share a common genetic background with LTPA.

Twins and Causal Inference: Leveraging Nature's Experiment

In this review, we discuss how samples comprising monozygotic and dizygotic twin pairs can be used for the purpose of strengthening causal inference by controlling for shared influences on exposure and outcome. We begin by briefly introducing how twin data can be used to inform the biometric decomposition of population variance into genetic, shared environmental, and nonshared environmental influences. We then discuss how extensions to this model can be used to explore whether associations between exposure and outcome survive correction for shared etiology (common causes). We review several analytical approaches that can be applied to twin data for this purpose. These include multivariate structural equation models, cotwin control methods, direction of causation models (cross-sectional and longitudinal), and extended family designs used to assess intergenerational associations. We conclude by highlighting some of the limitations and considerations that researchers should be aware of when using twin data for the purposes of interrogating causal hypotheses.

Relations between HEXACO personality and ideology variables are mostly genetic in nature

Existing work indicates that socio-political attitudes (or: ideology) are associated with personality, with Social Dominance Orientation and Right-Wing Authoritarianism relating most strongly to honesty-humility and openness to experience, the two value-related domains of the HEXACO framework. Using a sample of 7067 twins and siblings of twins (including 1376 complete twin pairs), we examined the degree to which these relations arise from common genetic and environmental sources. Heritability estimates for the HEXACO personality and ideology variables ranged from .34 to .58. Environmental factors shared by twins reared together showed negligible effects on individual differences in personality and ideology. At the phenotypic level, Social Dominance Orientation and Right-Wing Authoritarianism dimensions related most strongly to honesty-humility and openness to experience. These associations were mostly explained by genetic factors (48%–93%). Genetic correlations between openness to experience and the ideology scales ranged from –.29 to –.53; those between honesty-humility and the ideology scales ranged from –.31 to –.43. None of the environmental correlations exceeded | r| = .18. These results suggest that the relations between the two value-related domains of the HEXACO personality model and ideology are mostly genetic in nature, and that there is substantial overlap in the heritable components of personality and ideology.

Genetically Informed Regression Analysis: Application to Aggression Prediction by Inattention and Hyperactivity in Children and Adults

We present a procedure to simultaneously fit a genetic covariance structure model and a regression model to multivariate data from mono- and dizygotic twin pairs to test for the prediction of a dependent trait by multiple correlated predictors. We applied the model to aggressive behavior as an outcome trait and investigated the prediction of aggression from inattention (InA) and hyperactivity (HA) in two age groups. Predictions were examined in twins with an average age of 10 years (11,345 pairs), and in adult twins with an average age of 30 years (7433 pairs). All phenotypes were assessed by the same, but age-appropriate, instruments in children and adults. Because of the different genetic architecture of aggression, InA and HA, a model was fitted to these data that specified additive and non-additive genetic factors (A and D) plus common and unique environmental (C and E) influences. Given appropriate identifying constraints, this ADCE model is identified in trivariate data. We obtained different results for the prediction of aggression in children, where HA was the more important predictor, and in adults, where InA was the more important predictor. In children, about 36% of the total aggression variance was explained by the genetic and environmental components of HA and InA. Most of this was explained by the genetic components of HA and InA, i.e., 29.7%, with 22.6% due to the genetic component of HA. In adults, about 21% of the aggression variance was explained. Most was this was again explained by the genetic components of InA and HA (16.2%), with 8.6% due to the genetic component of InA.

Genetic evidence for a large overlap and potential bidirectional causal effects between resilience and well-being

Resilience and well-being are strongly related. People with higher levels of well-being are more resilient after stressful life events or trauma and vice versa. Less is known about the underlying sources of overlap and causality between the constructs. In a sample of 11.304 twins and 2.572 siblings from the Netherlands Twin Register, we investigated the overlap and possible direction of causation between resilience (i.e. the absence of psychiatric symptoms despite negative life events) and well-being (i.e. satisfaction with life) using polygenic score (PGS) prediction, twin-sibling modelling, and the Mendelian Randomization Direction of Causality (MR-DoC) model. Longitudinal twin-sibling models showed significant phenotypic correlations between resilience and well-being (.41/.51 at time 1 and 2). Well-being PGS were predictive for both well-being and resilience, indicating that genetic factors influencing well-being also predict resilience. Twin-sibling modeling confirmed this genetic correlation (0.71) and showed a strong environmental correlation (0.93). In line with causality, both genetic (51%) and environmental (49%) factors contributed significantly to the covariance between resilience and well-being. Furthermore, the results of within-subject and MZ twin differences analyses were in line with bidirectional causality. Additionally, we used the MR-DoC model combining both molecular and twin data to test causality, while correcting for pleiotropy. We confirmed the causal effect from well-being to resilience, with the direct effect of well-being explaining 11% (T1) and 20% (T2) of the variance in resilience. Data limitations prevented us to test the directional effect from resilience to well-being with the MR-DoC model. To conclude, we showed a strong relation between well-being and resilience. A first attempt to quantify the direction of this relationship points towards a bidirectional causal effect. If replicated, the potential mutual effects can have implications for interventions to lower psychopathology vulnerability, as resilience and well-being are both negatively related to psychopathology.

Integrating Family-Based and Mendelian Randomization Designs

Most Mendelian randomization (MR) studies published in the literature to date have involved analyses of unrelated, putatively independent sets of individuals. However, estimates obtained from these sorts of studies are subject to a range of biases including dynastic effects, assortative mating, residual population stratification, and horizontal pleiotropy. The inclusion of related individuals in MR studies can help control for and, in some cases, estimate the effect of these biases on causal parameters. In this review, we discuss these biases, how they can affect MR studies, and describe three sorts of family-based study designs that can be used to control for them. We conclude that including family information from related individuals is not only possible given the world's existing twin, birth, and large-scale population-based cohorts, but likely to reap rich rewards in understanding the etiology of complex traits and diseases in the near future.

Using Multimodel Inference/Model Averaging to Model Causes of Covariation Between Variables in Twins

OBJECTIVE

To explore and apply multimodel inference to test the relative contributions of latent genetic, environmental and direct causal factors to the covariation between two variables with data from the classical twin design by estimating model-averaged parameters.

METHODS

Behavior genetics is concerned with understanding the causes of variation in phenotypes and the causes of covariation between two or more phenotypes. Two variables may correlate as a result of genetic, shared environmental or unique environmental factors contributing to variation in both variables. Two variables may also correlate because one or both directly cause variation in the other. Furthermore, covariation may result from any combination of these sources, leading to 25 different identified structural equation models. OpenMx was used to fit all these models to account for covariation between two variables collected in twins. Multimodel inference and model averaging were used to summarize the key sources of covariation, and estimate the magnitude of these causes of covariance. Extensions of these models to test heterogeneity by sex are discussed.

RESULTS

We illustrate the application of multimodel inference by fitting a comprehensive set of bivariate models to twin data from the Virginia Twin Study of Psychiatric and Substance Use Disorders. Analyses of body mass index and tobacco consumption data show sufficient power to reject distinct models, and to estimate the contribution of each of the five potential sources of covariation, irrespective of selecting the best fitting model. Discrimination between models on sample size, type of variable (continuous versus binary or ordinal measures) and the effect size of sources of variance and covariance.

CONCLUSIONS

We introduce multimodel inference and model averaging approaches to the behavior genetics community, in the context of testing models for the causes of covariation between traits in term of genetic, environmental and causal explanations.

Punch-Drunk or Drunken Boxing? The Etiology of Alcohol-Related Physical Violence through Adolescence and Young Adulthood

BACKGROUND

Alcohol-related physical violence (ARPV) can be a causal consequence of alcohol consumption, but only for specific individuals (e.g., those predisposed to violence). Studies have not accounted for the shared etiology explaining comorbidity between alcohol use and violent behavior as a potential third-variable explanation of ARPV. The current study examined genetically-informed associations between ARPV, heavy alcohol use (HAU) and overall physical violence (OPV) in adolescence and young adulthood, by testing two proposed theories of ARPV processes (HAU causes ARPV, causal relationships depend upon OPV) and how overarching shared covariance may account for these associations.

METHODS

Using the twin and sibling subsample from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a series of biometric models tested hypotheses individually in adolescence and young adulthood. This included estimating bivariate Cholesky and direction-of-causality models, and trivariate Cholesky, independent pathway, and common pathway models.

RESULTS

HAU had a causal effect on ARPV in adolescence and young adulthood. This effect was not moderated by OPV at either developmental stage. A shared etiology or common latent factor did not explain associations between ARPV, OPV, and HAU, even though ARPV strongly covaried independently with HAU and with OPV. Finally, OPV also had a causal effect on ARPV in adolescence, and in young adulthood for adolescent-onset drinkers.

CONCLUSIONS

Causal theories of ARPV still hold when accounting for shared genetic and environmental variance. Further research on the exact role of violence (predispositions, environmental contexts) is required, as both phenotypes substantially (and separately) explain influences driving ARPV.

Supplemental data for this article is available online at https://doi.org/10.1080/10826084.2021.1887244.

Out of Control: Examining the Association Between Family Conflict and Self-Control in Adolescence in a Genetically Sensitive Design

OBJECTIVE

Family conflict is associated with low self-control in adolescence. Thus far research about the direction of this association is inconclusive. In this study, we sort out whether this association reflects a causal effect or whether it is explained by a common underlying cause, including genetic factors.

METHOD

In twin data, we fitted a series of causal models, and compared models for the association of family conflict and self-control including reciprocal causation, unidirectional causation from family conflict to low self-control, unidirectional causation from low self-control to family conflict, and common genetic susceptibility. We included data from a large sample of twins aged 14 years (N = 9,173), all enrolled in the Netherlands Twin Register.

RESULTS

The results suggested a unidirectional pathway model in which family conflict leads to low self-control in adolescence, with genetic factors also playing a role in explaining the association.

CONCLUSION

Adolescents experiencing family conflict are at risk for showing hampered self-control capacities, with family conflict being a robust predictor of low self-control through common genetic factors but also through direct causal influences.

Investigating the causal effect of cannabis use on cognitive function with a quasi-experimental co-twin design

BACKGROUND

It is unclear whether cannabis use causes cognitive decline; several studies show an association between cannabis use and cognitive decline, but quasi-experimental twin studies have found little support for a causal effect. Here, we evaluate the association of cannabis use with general cognitive ability and executive functions (EFs) while controlling for genetic and shared environmental confounds in a longitudinal twin study.

METHODS

We first examined the phenotypic associations between cannabis initiation, frequency, and use disorder with cognitive abilities, while also controlling for pre-use general cognitive ability and other substance involvement. We tested the concurrent association between the cannabis use variables and cognitive abilities in late adolescence and young adulthood and the longitudinal association between cannabis use variables during adolescence and young adulthood cognitive abilities. Next, we used multilevel models to test whether these relations reflect between- and/or within-twin pair associations.

RESULTS

Phenotypically, cannabis use was related to poorer cognitive functioning, although most associations were negligible after accounting for other substance use. Nevertheless, there were few significant within-family twin-specific associations, except that age 17 cannabis frequency was associated with worse age 23 Common EF and general cognitive ability.

CONCLUSIONS

We found little support for a potential causal effect of cannabis use on cognition, consistent with previous twin studies. Results suggest that cannabis use may not cause decline in cognitive ability among a normative sample of cannabis users.

Investigating the association between family connectedness and self-control in adolescence in a genetically sensitive design

Family connectedness is key for the development of self-control in early and middle childhood. But is family connectedness still important during the transitional phase of adolescence, when adolescents demand more independence from their parents and rely more on their peers? The aim of the present study was to investigate the association between family connectedness and self-control, and whether it still holds in adolescence using a genetically sensitive design. Data were used from a large sample of twins aged 14 (N = 11,260) and aged 16 (N = 8175), all enrolled in the Netherlands Twin Register. We applied bivariate twin models and monozygotic twin difference models to investigate the association between family connectedness and self-control and to unravel to what extent genetic and environmental factors explain this association. The results showed that more family connectedness is significantly related to better self-control in adolescence, albeit with a small effect size. Twin analyses revealed that this association was mainly explained by common genetic factors and that the effects of environmental factors were small. The current findings confirm the role of family connectedness in adolescent self-control. Importantly, however, the results demonstrate that phenomena we see within families seem the product of parent and children sharing the same genes rather than being exclusively attributable to environmental processes.

Unraveling the Relation Between Reading Comprehension and Print Exposure

The purpose of this study was to test the directionality of influence between reading comprehension (RC) and print exposure (PE), thereby estimating genetic and environmental effects of this relation. The sample consisted of 910 twins in fourth through ninth grades (M_age  = 12.33 years, SD = 1.41) from the Florida Twin Project on Reading, Behavior, and Environment. Using direction-of-causation model in a twin design, results supported a direction of influence running from RC to PE. This relation was underpinned by genetic and environmental factors of RC as well as PE. Implications for reading education are discussed.

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

Using genetic data to strengthen causal inference in observational research

Causal inference is essential across the biomedical, behavioural and social sciences.By progressing from confounded statistical associations to evidence of causal relationships, causal inference can reveal complex pathways underlying traits and diseases and help to prioritize targets for intervention. Recent progress in genetic epidemiology - including statistical innovation, massive genotyped data sets and novel computational tools for deep data mining - has fostered the intense development of methods exploiting genetic data and relatedness to strengthen causal inference in observational research. In this Review, we describe how such genetically informed methods differ in their rationale, applicability and inherent limitations and outline how they should be integrated in the future to offer a rich causal inference toolbox.

The causal influence of brain size on human intelligence: Evidence from within-family phenotypic associations and GWAS modeling

There exists a moderate correlation between MRI-measured brain size and the general factor of IQ performance (g), but the question of whether the association reflects a theoretically important causal relationship or spurious confounding remains somewhat open. Previous small studies (n < 100) looking for the persistence of this correlation within families failed to find a tendency for the sibling with the larger brain to obtain a higher test score. We studied the within-family relationship between brain volume and intelligence in the much larger sample provided by the Human Connectome Project (n = 1,022) and found a highly significant correlation (disattenuated ρ = 0.18, p < .001). We replicated this result in the Minnesota Center for Twin and Family Research (n = 2,698), finding a highly significant within-family correlation between head circumference and intelligence (disattenuated ρ = 0.19, p < .001). We also employed novel methods of causal inference relying on summary statistics from genome-wide association studies (GWAS) of head size (n ≈ 10,000) and measures of cognition (257,000 < n < 767,000). Using bivariate LD Score regression, we found a genetic correlation between intracranial volume (ICV) and years of education (EduYears) of 0.41 (p < .001). Using the Latent Causal Variable method, we found a genetic causality proportion of 0.72 (p < .001); thus the genetic correlation arises from an asymmetric pattern, extending to sub-significant loci, of genetic variants associated with ICV also being associated with EduYears but many genetic variants associated with EduYears not being associated with ICV. This is the pattern of genetic results expected from a causal effect of brain size on intelligence. These findings give reason to take up the hypothesis that the dramatic increase in brain volume over the course of human evolution has been the result of natural selection favoring general intelligence.

The analysis of causal relationships between blood lipid levels and BMD

Bone mineral density (BMD) and lipid levels are two of the most extensively studied risk factors for common diseases of aging, such as cardiovascular disease (CVD) and osteoporosis (OP). These two risk factors are also correlated with each other, but little is known about the molecular mechanisms behind this correlation. Recent studies revealed that circulating levels of several metabolites involved in the biosynthesis of androsterone correlate significantly with BMD and have the capacity to affect cholesterol and lipids levels. A main aim of the present study was to investigate the hypothesis that androsterone-related metabolites could provide a link between CVD and OP, as a common cause of lipid levels and BMD. The present study employed data from the NIHR BRC TwinsUK BioResource, comprising 1909 and 1994 monozygotic and dizygotic twin pairs, respectively, to address the causal relationships among BMD and lipids, and their associated metabolites, using reciprocal causation twin modelling, as well as Mendelian randomization (MR) using large publicly-available GWAS datasets on lipids and BMD, in conjunction with TwinsUK metabolite data. While results involving the twin modelling and MR analyses with metabolites were unable to establish a causal link between metabolite levels and either lipids or BMD, MR analyses of BMD and lipids suggest that lipid levels have a causal impact on BMD, which is consistent with findings from clinical trials of lipid-lowering drugs, which have also increased BMD.

Genetically Informative Mediation Modeling Applied to Stressors and Personality-Disorder Traits in Etiology of Alcohol Use Disorder

A statistical mediation model was developed within a twin design to investigate the etiology of alcohol use disorder (AUD). Unlike conventional statistical mediation models, this biometric mediation model can detect unobserved confounding. Using a sample of 1410 pairs of Norwegian twins, we investigated specific hypotheses that DSM-IV personality-disorder (PD) traits mediate effects of childhood stressful life events (SLEs) on AUD, and that adulthood SLEs mediate effects of PDs on AUD. Models including borderline PD traits indicated unobserved confounding in phenotypic path coefficients, whereas models including antisocial and impulsive traits did not. More than half of the observed effects of childhood SLEs on adulthood AUD were mediated by adulthood antisocial and impulsive traits. Effects of PD traits on AUD 5‒10 years later were direct rather than mediated by adulthood SLEs. The results and the general approach contribute to triangulation of developmental origins for complex behavioral disorders.

A Developmental Twin Study of Emotion Recognition and Its Negative Affective Clinical Correlates

OBJECTIVE

Youth with psychiatric disorders distinguished by irritability, including depression and associated trait neuroticism, show deficits in the ability to recognize facial expressions of emotion, particularly happiness. However, the contribution of genetic and environmental factors to this ability remains unknown. The present study examined this trait in twins to assess the genetic and environmental influences on face-emotion recognition abilities and their association with irritability, neuroticism, and depression.

METHOD

Child and adolescent twins (N = 957 from 496 families) 9 to 17 years old rated their irritability (on the Affective Reactivity Index), neuroticism (on the Junior Eysenck Personality Questionnaire), and depression (on the Short Mood and Feelings Questionnaire) and completed a face-emotion labeling task. Faces depicting anger, disgust, fear, happiness, sadness, and surprise were morphed with a neutral face, yielding 10 levels of increasing emotional expressivity. Biometrical twin analyses evaluated contributions of genetic and environmental factors to the etiology of face-emotion recognition and its association with irritability, neuroticism, and depression.

RESULTS

Recognition of each emotion was heritable; common and specific sets of genetic factors influenced all emotions and individual emotions, respectively. Irritability, neuroticism, and depression were modestly and negatively correlated with emotion recognition, particularly the recognition of happiness. For irritability and neuroticism, this correlation appeared largely due to genetic factors.

CONCLUSION

This study maps genetic and environmental contributions to face-emotion recognition and its association with irritability, neuroticism, and depression. Findings implicate common genetic factors in deficits regarding the recognition of happiness associated with irritability and neuroticism in childhood and adolescence.

Why do children read more? The influence of reading ability on voluntary reading practices

BACKGROUND

This study investigates the causal relationships between reading and print exposure and investigates whether the amount children read outside school determines how well they read, or vice versa. Previous findings from behavioural studies suggest that reading predicts print exposure. Here, we use twin-data and apply the behaviour-genetic approach of direction of causality modelling, suggested by Heath et al. (), to investigate the causal relationships between these two traits.

METHOD

Partial data were available for a large sample of twin children (N = 11,559) and 262 siblings, all enrolled in the Netherlands Twin Register. Children were assessed around 7.5 years of age. Mothers completed questionnaires reporting children's time spent on reading activities and reading ability. Additional information on reading ability was available through teacher ratings and performance on national reading tests. For siblings reading test, results were available.

RESULTS

The reading ability of the twins was comparable to that of the siblings and national norms, showing that twin findings can be generalized to the population. A measurement model was specified with two latent variables, Reading Ability and Print Exposure, which correlated .41. Heritability analyses showed that Reading Ability was highly heritable, while genetic and environmental influences were equally important for Print Exposure. We exploited the fact that the two constructs differ in genetic architecture and fitted direction of causality models. The results supported a causal relationship running from Reading Ability to Print Exposure.

CONCLUSIONS

How much and how well children read are moderately correlated. Individual differences in print exposure are less heritable than individual differences in reading ability. Importantly, the present results suggest that it is the children's reading ability that determines how much they choose to read, rather than vice versa.

The accuracy of LD Score regression as an estimator of confounding and genetic correlations in genome-wide association studies

To infer that a single-nucleotide polymorphism (SNP) either affects a phenotype or is linkage disequilibrium with a causal site, we must have some assurance that any SNP-phenotype correlation is not the result of confounding with environmental variables that also affect the trait. In this study, we study the properties of linkage disequilibrium (LD) Score regression, a recently developed method for using summary statistics from genome-wide association studies to ensure that confounding does not inflate the number of false positives. We do not treat the effects of genetic variation as a random variable and thus are able to obtain results about the unbiasedness of this method. We demonstrate that LD Score regression can produce estimates of confounding at null SNPs that are unbiased or conservative under fairly general conditions. This robustness holds in the case of the parent genotype affecting the offspring phenotype through some environmental mechanism, despite the resulting correlation over SNPs between LD Scores and the degree of confounding. Additionally, we demonstrate that LD Score regression can produce reasonably robust estimates of the genetic correlation, even when its estimates of the genetic covariance and the two univariate heritabilities are substantially biased.

Extending Causality Tests with Genetic Instruments: An Integration of Mendelian Randomization with the Classical Twin Design

Although experimental studies are regarded as the method of choice for determining causal influences, these are not always practical or ethical to answer vital questions in health and social research (e.g., one cannot assign individuals to a "childhood trauma condition" in studying the causal effects of childhood trauma on depression). Key to solving such questions are observational studies. Mendelian Randomization (MR) is an influential method to establish causality in observational studies. MR uses genetic variants to test causal relationships between exposures/risk factors and outcomes such as physical or mental health. Yet, individual genetic variants have small effects, and so, when used as instrumental variables, render MR liable to weak instrument bias. Polygenic scores have the advantage of larger effects, but may be characterized by horizontal pleiotropy, which violates a central assumption of MR. We developed the MR-DoC twin model by integrating MR with the Direction of Causation twin model. This model allows us to test pleiotropy directly. We considered the issue of parameter identification, and given identification, we conducted extensive power calculations. MR-DoC allows one to test causal hypotheses and to obtain unbiased estimates of the causal effect given pleiotropic instruments, while controlling for genetic and environmental influences common to the outcome and exposure. Furthermore, the approach allows one to employ strong instrumental variables in the form of polygenic scores, guarding against weak instrument bias, and increasing the power to detect causal effects of exposures on potential outcomes. Beside allowing to test pleiotropy directly, incorporating in MR data collected from relatives provide additional within-family data that resolve additional assumptions like random mating, the absence of the gene-environment interaction/covariance, no dyadic effects. Our approach will enhance and extend MR's range of applications, and increase the value of the large cohorts collected at twin/family registries as they correctly detect causation and estimate effect sizes even in the presence of pleiotropy.

Early maturation and substance use across adolescence and young adulthood: A longitudinal study of Finnish twins

Early maturation, indexed by pubertal development (PD), has been associated with earlier initiation and greater frequency of adolescent substance use, but this relationship may be biased by confounding factors and effects that change across development. Using a population-based Finnish twin sample (N = 3,632 individuals), we conducted twin modeling and multilevel structural equation modeling of the relationship between PD and substance use at ages 12-22. Shared environmental factors contributed to early PD and heavier substance use for females. Biological father absence was associated with early PD for boys but not girls, and did not account for the relationship between PD and substance use. The association between early PD and heavier substance use was partially due to between-family confounds, although early PD appeared to qualitatively alter long-term trajectories for some substances (nicotine), but not others (alcohol). Mediation by peer and parental factors did not explain this relationship within families. However, higher peer substance use and lower parental monitoring were themselves associated with heavier substance use, strengthening the existing evidence for these factors as targets for prevention/intervention efforts. Early maturation was not supported as a robust determinant of alcohol use trajectories in adolescence and young adulthood, but may require longer term follow-up. Subtle effects of early PD on nicotine and illicit drug use trajectories throughout adolescence and adulthood merit further investigation.

Attention Deficit Hyperactivity Disorder Symptoms and Low Educational Achievement: Evidence Supporting A Causal Hypothesis

Attention Deficit Hyperactivity Disorder (ADHD) and educational achievement are negatively associated in children. Here we test the hypothesis that there is a direct causal effect of ADHD on educational achievement. The causal effect is tested in a genetically sensitive design to exclude the possibility of confounding by a third factor (e.g. genetic pleiotropy) and by comparing educational achievement and secondary school career in children with ADHD who take or do not take methylphenidate. Data on ADHD symptoms, educational achievement and methylphenidate usage were available in a primary school sample of ~10,000 12-year-old twins from the Netherlands Twin Register. A substantial group also had longitudinal data at ages 7-12 years. ADHD symptoms were cross-sectionally and longitudinally, associated with lower educational achievement at age 12. More ADHD symptoms predicted a lower-level future secondary school career at age 14-16. In both the cross-sectional and longitudinal analyses, testing the direct causal effect of ADHD on educational achievement, while controlling for genetic and environmental factors, revealed an association between ADHD symptoms and educational achievement independent of genetic and environmental pleiotropy. These findings were confirmed in MZ twin intra-pair differences models, twins with more ADHD symptoms scored lower on educational achievement than their co-twins. Furthermore, children with ADHD medication, scored significantly higher on the educational achievement test than children with ADHD who did not use medication. Taken together, the results are consistent with a direct causal effect of ADHD on educational achievement.

Genetic and Environmental Contributions to the Association Between Cannabis Use and Psychotic-Like Experiences in Young Adult Twins

To investigate contributions of genetic and environmental risk factors and possible direction of causation for the relationship between symptoms of cannabis use disorders (CUD) and psychotic-like experiences (PLEs), a population-based sample of 2793 young adult twins (63.5% female, mean [range] age 28.2 [19-36] y) were assessed for symptoms of CUD and PLEs using the Composite International Diagnostic Interview. Latent risk of having symptoms of CUD or PLEs was modeled using Item Response Theory. Co-twin control analysis was performed to investigate effect of familiar confounding for the association between symptoms of CUD and PLEs. Biometric twin models were fitted to estimate the heritability, genetic and environmental correlations, and direction for the association. Lifetime use of cannabis was reported by 10.4 % of the twins, and prevalence of PLEs ranged from 0.1% to 2.2%. The incidence rate ratio of PLEs due to symptoms of CUD was 6.3 (95% CI, 3.9, 10.2) in the total sample and 3.5 (95% CI, 1.5, 8.2) within twin pairs. Heritability estimates for symptoms of CUD were 88% in men and women, and for PLEs 77% in men and 43% in women. The genetic and environmental correlations between symptoms of CUD and PLEs were 0.55 and 0.52, respectively. The model allowing symptoms of CUD to cause PLEs had a better fit than models specifying opposite or reciprocal directions of causation. The association between symptoms of CUD and PLEs is explained by shared genetic and environmental factors and direct effects from CUD to risk for PLEs.

The Genetic and Environmental Association Between Parental Monitoring and Risk of Cannabis, Stimulants, and Cocaine Initiation in a Sample of Male Twins: Does Parenting Matter?

Our aim was to test the direction of causation between self-report parental monitoring (PM) and the liability to illicit drug initiation (DI) as indicated by cannabis, cocaine, and stimulants. We fitted a multiple indicator model to test causal and non-causal models based on a large, genetically informative cross-sectional sample of male twins. The sample comprised 1,778 males aged 24-62 years from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. Data came from self-report measures of lifetime cannabis, stimulants, and cocaine initiation, and retrospective assessment of PM between ages 8-17 years. Multivariate modeling showed that familial aggregation in PM and DI were both explained by a combination of additive genetic and shared environmental effects. Moreover, the significant association between PM and DI was best explained by a correlated liability model versus causal models. PM has typically been assumed to be an environmental, causal risk factor for drug use and has been shown to be among the more salient environmental risk factors for illicit DI. Our data were not consistent with this causal hypothesis. Instead, a correlated liability model in which PM and risk of DI share common genetic and environmental risks provided a better fit to the data.

A test of the facultative calibration/reactive heritability model of extraversion

A model proposed by Lukaszewski and Roney (2011) suggests that each individual's level of extraversion is calibrated to other traits that predict the success of an extraverted behavioural strategy. Under 'facultative calibration', extraversion is not directly heritable, but rather exhibits heritability through its calibration to directly heritable traits ("reactive heritability"). The current study uses biometrical modelling of 1659 identical and non-identical twins and their siblings to assess whether the genetic variation in extraversion is calibrated to variation in facial attractiveness, intelligence, height in men and body mass index (BMI) in women. Extraversion was significantly positively correlated with facial attractiveness in both males (r=.11) and females (r=.18), but correlations between extraversion and the other variables were not consistent with predictions. Further, twin modelling revealed that the genetic variation in facial attractiveness did not account for a substantial proportion of the variation in extraversion in either males (2.4%) or females (0.5%).

Reciprocal causation models of cognitive vs volumetric cerebral intermediate phenotypes for schizophrenia in a pan-European twin cohort

In aetiologically complex illnesses such as schizophrenia, there is no direct link between genotype and phenotype. Intermediate phenotypes could help clarify the underlying biology and assist in the hunt for genetic vulnerability variants. We have previously shown that cognition shares substantial genetic variance with schizophrenia; however, it is unknown if this reflects pleiotropic effects, direct causality or some shared third factor that links both, for example, brain volume (BV) changes. We quantified the degree of net genetic overlap and tested the direction of causation between schizophrenia liability, brain structure and cognition in a pan-European schizophrenia twin cohort consisting of 1243 members from 626 pairs. Cognitive deficits lie upstream of the liability for schizophrenia with about a quarter of the variance in liability to schizophrenia explained by variation in cognitive function. BV changes lay downstream of schizophrenia liability, with 4% of BV variation explained directly by variation in liability. However, our power to determine the nature of the relationship between BV deviation and schizophrenia liability was more limited. Thus, while there was strong evidence that cognitive impairment is causal to schizophrenia liability, we are not in a position to make a similar statement about the relationship between liability and BV. This is the first study to demonstrate that schizophrenia liability is expressed partially through cognitive deficits. One prediction of the finding that BV changes lie downstream of the disease liability is that the risk loci that influence schizophrenia liability will thereafter influence BV and to a lesser extent. By way of contrast, cognitive function lies upstream of schizophrenia, thus the relevant loci will actually have a larger effect size on cognitive function than on schizophrenia. These are testable predictions.

Investigating cognitive transfer within the framework of music practice: genetic pleiotropy rather than causality

The idea of far transfer effects in the cognitive sciences has received much attention in recent years. One domain where far transfer effects have frequently been reported is music education, with the prevailing idea that music practice entails an increase in cognitive ability (IQ). While cross-sectional studies consistently find significant associations between music practice and IQ, randomized controlled trials, however, report mixed results. An alternative to the hypothesis of cognitive transfer effects is that some underlying factors, such as shared genes, influence practice behaviour and IQ causing associations on the phenotypic level. Here we explored the hypothesis of far transfer within the framework of music practice. A co-twin control design combined with classical twin-modelling based on a sample of more than 10,500 twins was used to explore causal associations between music practice and IQ as well as underlying genetic and environmental influences. As expected, phenotypic associations were moderate (r = 0.11 and r = 0.10 for males and females, respectively). However, the relationship disappeared when controlling for genetic and shared environmental influences using the co-twin control method, indicating that a highly practiced twin did not have higher IQ than the untrained co-twin. In line with that finding, the relationship between practice and IQ was mostly due to shared genetic influences. Findings strongly suggest that associations between music practice and IQ in the general population are non-causal in nature. The implications of the present findings for research on plasticity, modularity, and transfer are discussed.

Exploring the origins of asthma: Lessons from twin studies

This thesis explores the contribution of twin studies, particularly those studies originating from the Danish Twin Registry, to the understanding of the aetiology of asthma. First, it is explored how twin studies have established the contribution of genetic and environmental factors to the variation in the susceptibility to asthma, and to the variation in several aspects of the clinical expression of the disease such as its age at onset, its symptomatology, its intermediate phenotypes, and its relationship with other atopic diseases. Next, it is explored how twin studies have corroborated theories explaining asthma's recent increase in prevalence, and last, how these fit with the explanations of the epidemiological trends in other common chronic diseases of modernity.

Practice Does Not Make Perfect

The relative importance of nature and nurture for various forms of expertise has been intensely debated. Music proficiency is viewed as a general model for expertise, and associations between deliberate practice and music proficiency have been interpreted as supporting the prevailing idea that long-term deliberate practice inevitably results in increased music ability. Here, we examined the associations ( rs = .18–.36) between music practice and music ability (rhythm, melody, and pitch discrimination) in 10,500 Swedish twins. We found that music practice was substantially heritable (40%−70%). Associations between music practice and music ability were predominantly genetic, and, contrary to the causal hypothesis, nonshared environmental influences did not contribute. There was no difference in ability within monozygotic twin pairs differing in their amount of practice, so that when genetic predisposition was controlled for, more practice was no longer associated with better music skills. These findings suggest that music practice may not causally influence music ability and that genetic variation among individuals affects both ability and inclination to practice.

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.

Modeling the direction of causation between cross-sectional measures of disrupted sleep, anxiety and depression in a sample of male and female Australian twins

The direction of causation between measures of disrupted sleep, anxiety and depression is not well understood. Under certain conditions, cross-sectional analysis based on genetically informative data can provide important information about the direction of causation between variables. Two community-based samples of 7235 Australian twins aged 18-87 years were mailed an extensive questionnaire that covered a wide range of personality and behavioral measures. Included were self-report measures of disrupted sleep, as well as symptoms of anxiety and depression. Among all females, modeling the direction of causation did not support the hypothesis of sleep having a direct causal impact on risk of anxiety or depression. Among older females, we found evidence that both anxiety and depression interact reciprocally with disrupted sleep, whereas among younger women both anxiety and depression appear to have a causal impact on sleep. Results for males were equivocal. The nosological implications of our findings are discussed.

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.

Do shared etiological factors contribute to the relationship between sexual orientation and depression?

BACKGROUND

Gays, lesbians and bisexuals (i.e. non-heterosexuals) have been found to be at much greater risk for many psychiatric symptoms and disorders, including depression. This may be due in part to prejudice and discrimination experienced by non-heterosexuals, but studies controlling for minority stress, or performed in very socially liberal countries, suggest that other mechanisms must also play a role. Here we test the viability of common cause (shared genetic or environmental etiology) explanations of elevated depression rates in non-heterosexuals.

METHOD

A community-based sample of adult twins (n=9884 individuals) completed surveys investigating the genetics of psychiatric disorder, and were also asked about their sexual orientation. Large subsets of the sample were asked about adverse childhood experiences such as sexual abuse, physical abuse and risky family environment, and also about number of older brothers, paternal and maternal age, and number of close friends. Data were analyzed using the classical twin design.

RESULTS

Non-heterosexual males and females had higher rates of lifetime depression than their heterosexual counterparts. Genetic factors accounted for 31% and 44% of variation in sexual orientation and depression respectively. Bivariate analysis revealed that genetic factors accounted for a majority (60%) of the correlation between sexual orientation and depression. In addition, childhood sexual abuse and risky family environment were significant predictors of both sexual orientation and depression, further contributing to their correlation.

CONCLUSIONS

Non-heterosexual men and women had elevated rates of lifetime depression, partly due to shared etiological factors, although causality cannot be definitively resolved.

The Etiology of Mathematical and Reading (Dis)ability Covariation in a Sample of Dutch Twins

The genetic etiology of mathematical and reading (dis)ability has been studied in a number of distinct samples, but the true nature of the relationship between the two remains unclear. Data from the Netherlands Twin Register was used to determine the etiology of the relationship between mathematical and reading (dis)ability in adolescent twins. Ratings of mathematical and reading problems were obtained from parents of over 1500 twin pairs. Results of bivariate structural equation modeling showed a genetic correlation around .60, which explained over 90% of the phenotypic correlation between mathematical and reading ability. The genetic model was the same for males and females.

Correlation not causation: the relationship between personality traits and political ideologies

The assumption in the personality and politics literature is that a person's personality motivates them to develop certain political attitudes later in life. This assumption is founded on the simple correlation between the two constructs and the observation that personality traits are genetically influenced and develop in infancy, whereas political preferences develop later in life. Work in psychology, behavioral genetics, and recently political science, however, has demonstrated that political preferences also develop in childhood and are equally influenced by genetic factors. These findings cast doubt on the assumed causal relationship between personality and politics. Here we test the causal relationship between personality traits and political attitudes using a direction of causation structural model on a genetically informative sample. The results suggest that personality traits do not cause people to develop political attitudes; rather, the correlation between the two is a function of an innate common underlying genetic factor.