Twin-based Mendelian Randomization Analyses Highlight Smoking's Effects on Blood DNA Methylation, with Putative Reverse Causation.

Epigenome-wide association studies (EWAS) aim to identify differentially methylated loci associated with complex traits and disorders. EWAS of cigarette smoking shows some of the most widespread DNA methylation (DNAm) associations in blood. However, traditional EWAS cannot differentiate between causation and confounding, leading to ambiguity in etiological interpretations. Here, we apply an integrated approach combining Mendelian Randomization and twin-based Direction-of-Causation analyses (MR-DoC) to examine causality underlying smoking-associated blood DNAm changes in the Netherlands Twin Register (N=2577). Evidence across models suggests that current smoking's causal effects on DNAm likely drive many of the previous EWAS findings, implicating functional pathways relevant to several adverse health outcomes of smoking, including hemopoiesis, cell- and neuro-development, and immune regulation. Additionally, we find evidence of potential reverse causal influences at some DNAm sites, with 17 of these sites enriched for gene regulatory functional elements in the brain. The top three sites with evidence of DNAm's effects on smoking annotate to genes involved in G protein-coupled receptor signaling (GNG7, RGS3) and innate immune response (SLC15A4), elucidating potential biological risk factors for smoking. This study highlights the utility of integrating genotypic and DNAm measures in twin cohorts to clarify the causal relationships between health behaviors and blood DNAm.

Cohort Effects on Tobacco Consumption and its Genetic and Environmental Variance Among Finnish Adults born between 1880-1957.

INTRODUCTION: Population research indicates that smoking behaviors in Finland have varied over time by sex and birth cohort. Smoking behaviors are influenced by genes and the environment; like the behaviors themselves, these underlying influences are not necessarily stable over time and may be modifiable by national drug policy. METHODS: We utilized longitudinal mixed effects models and causal-common-contingent twin models to evaluate sex and cohort effects on tobacco consumption and the underlying genetic and environmental variance components in a birth cohort sample of same-sex twins born in Finland between 1880-1957, assessed in 1975, 1981, 1990, and 2011. RESULTS: We identified significant main effects of age, sex, and cohort on quantity of cigarette consumption, as well as significant age×cohort and sex×cohort interactions. We also identified sex and cohort effects on the liability to initiate regular smoking and the magnitude of variation underlying quantity of cigarette consumption. That said, heritability and environmental contributions to both traits were not different between the four sex×cohort groups. CONCLUSIONS: Our results indicate sex and cohort effects on the prevalence of smoking and its underlying variation. Our results on changing prevalence mirror existing population-level research in Finnish samples, but we did not identify differences in heritability found in other studies of cohort effects in tobacco use, potentially due to power issues. These results highlight the importance of considering age, cohort, and timing of policy changes when evaluating changes in substance consumption across time. IMPLICATIONS: This study identifies sex and cohort effects influencing tobacco consumption in a sample of Finnish adult twins born between 1880-1957. Our results are in line with other population level research in Finland and research on cohort effects influencing alcohol use in the same sample. Our results highlight the intertwining effects of age, cohort, sex, and substance policies on substance use.

Using Instrumental Variables to Measure Causation over Time in Cross-Lagged Panel Models.

Cross-lagged panel models (CLPMs) are commonly used to estimate causal influences between two variables with repeated assessments. The lagged effects in a CLPM depend on the time interval between assessments, eventually becoming undetectable at longer intervals. To address this limitation, we incorporate instrumental variables (IVs) into the CLPM with two study waves and two variables. Doing so enables estimation of both the lagged (i.e., "distal") effects and the bidirectional cross-sectional (i.e., "proximal") effects at each wave. The distal effects reflect Granger-causal influences across time, which decay with increasing time intervals. The proximal effects capture causal influences that accrue over time and can help infer causality when the distal effects become undetectable at longer intervals. Significant proximal effects, with a negligible distal effect, would imply that the time interval is too long to estimate a lagged effect at that time interval using the standard CLPM. Through simulations and an empirical application, we demonstrate the impact of time intervals on causal inference in the CLPM and present modeling strategies to detect causal influences regardless of the time interval in a study. Furthermore, to motivate empirical applications of the proposed model, we highlight the utility and limitations of using genetic variables as IVs in large-scale panel studies.

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, Minica 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 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 Cultural Transmission of Alcohol Use Disorder in Swedish Twin Pedigrees.

OBJECTIVE: Using Swedish nationwide registry data, we investigated the contribution of genetic and environmental risk factors to the etiology of alcohol use disorder (AUD) by extended twin pedigree modeling. METHOD: AUD was defined using public inpatient, outpatient, prescription, and criminal records. Three-generational pedigrees were selected for index individuals born between 1980 and 1990, obtained from the national twin and genealogical registers, whose parents were twins. Relatives of the twins included in the pedigrees were their parents, siblings, spouses, and children. Genetic structural equation modeling was applied to the population-based data on AUD, using OpenMx, with age used as a covariate. RESULTS: Analyses including up to 162,469 individuals in 18,971 pedigrees estimated AUD prevalence at 5%-12% in men and 2%-5% in women. Results indicated substantial heritability (about 50%-60%), of which a portion upwards of 5% was attributable to the consequences of assortative mating. Contributions of shared environmental factors to AUD, which represent a mix of within- and cross-generational effects, appeared to be moderate (about 10%-20%). Unique environment accounted for the remaining variance (about 20%-30%). Sex differences in the magnitude of the variance components suggested higher heritability in men and correspondingly higher shared environmental contributions in women. CONCLUSIONS: Using objective registry data, we found that AUD is highly heritable. Furthermore, shared environmental factors contributed significantly to the liability of AUD in both men and women.

Heritability of Childhood Music Engagement and Associations with Language and Executive Function: Insights from the Adolescent Brain Cognitive Development (ABCD) Study.

Music engagement is a powerful, influential experience that often begins early in life. Music engagement is moderately heritable in adults (~ 41-69%), but fewer studies have examined genetic influences on childhood music engagement, including their association with language and executive functions. Here we explored genetic and environmental influences on music listening and instrument playing (including singing) in the baseline assessment of the Adolescent Brain Cognitive Development study. Parents reported on their 9-10-year-old children's music experiences (N = 11,876 children; N = 1543 from twin pairs). Both music measures were explained primarily by shared environmental influences. Instrument exposure (but not frequency of instrument engagement) was associated with language skills (r = .27) and executive functions (r = .15-0.17), and these associations with instrument engagement were stronger than those for music listening, visual art, or soccer engagement. These findings highlight the role of shared environmental influences between early music experiences, language, and executive function, during a formative time in development.

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.

Exploring the relationships between adolescent alcohol misuse and later life health outcomes.

BACKGROUND: We sought to clarify the impact of adolescent alcohol misuse on adult physical health and subjective well-being. To do so, we investigated both the direct associations between adolescent alcohol misuse and early midlife physical health and life satisfaction and the indirect effects on these outcomes attributable to subsequent alcohol problems. METHOD: The sample included 2733 twin pairs (32% monozygotic; 52% female) from the FinnTwin16 study. Adolescent alcohol misuse was a composite of frequency of drunkenness, frequency of alcohol use, and alcohol problems at ages 16, 17, and 18.5. The early midlife outcomes included somatic symptoms, self-rated health, and life satisfaction at age 34. The mediators examined as part of the indirect effect analyses included alcohol problems from the Rutgers Alcohol Problem Index at ages 24 and 34. Serial mediation and co-twin comparison models were applied and included covariates from adolescence and early midlife. RESULTS: There were weak direct associations between adolescent alcohol misuse and early midlife physical health and life satisfaction. However, there was stronger evidence for indirect effects, whereby young adult and early midlife alcohol problems serially mediated the relationship between adolescent alcohol misuse and early midlife somatic symptoms (ß = 0.03, 95% CI [0.03, 0.04]), self-rated health (ß = -0.02, 95% CI [-0.03, -0.01]), and life satisfaction (ß = -0.03, CI [-0.04, -0.02]). These serial mediation effects were robust in co-twin comparison analyses. CONCLUSIONS: These results provide evidence that alcohol problems are a primary driver linking adolescent alcohol misuse and poor health outcomes across the lifespan.

Determining the stability of genome-wide factors in BMI between ages 40 to 69 years.

Genome-wide association studies (GWAS) have successfully identified common variants associated with BMI. However, the stability of aggregate genetic variation influencing BMI from midlife and beyond is unknown. By analysing 165,717 men and 193,073 women from the UKBiobank, we performed BMI GWAS on six independent five-year age intervals between 40 and 72 years. We then applied genomic structural equation modeling to test competing hypotheses regarding the stability of genetic effects for BMI. LDSR genetic correlations between BMI assessed between ages 40 to 73 were all very high and ranged 0.89 to 1.00. Genomic structural equation modeling revealed that molecular genetic variance in BMI at each age interval could not be explained by the accumulation of any age-specific genetic influences or autoregressive processes. Instead, a common set of stable genetic influences appears to underpin genome-wide variation in BMI from middle to early old age in men and women alike.

Smoking remains associated with education after controlling for social background and genetic factors in a study of 18 twin cohorts.

We tested the causality between education and smoking using the natural experiment of discordant twin pairs allowing to optimally control for background genetic and childhood social factors. Data from 18 cohorts including 10,527 monozygotic (MZ) and same-sex dizygotic (DZ) twin pairs discordant for education and smoking were analyzed by linear fixed effects regression models. Within twin pairs, education levels were lower among the currently smoking than among the never smoking co-twins and this education difference was larger within DZ than MZ pairs. Similarly, education levels were higher among former smoking than among currently smoking co-twins, and this difference was larger within DZ pairs. Our results support the hypothesis of a causal effect of education on both current smoking status and smoking cessation. However, the even greater intra-pair differences within DZ pairs, who share only 50% of their segregating genes, provide evidence that shared genetic factors also contribute to these associations.

Polygenic score for cigarette smoking is associated with ever electronic-cigarette use in a college-aged sample.

BACKGROUND AND AIMS: Electronic cigarette use has escalated rapidly in recent years, particularly among youth. Little is known about the genetic influences on e-cigarette use. This study aimed to determine whether genetic risk for regular use of combustible cigarettes or for number of cigarettes smoked per day confers risk for ever e-cigarette use or frequency of e-cigarette use. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: We used data from 9541 young adults from the Spit for Science longitudinal cohort study (2011-2019). Polygenic scores (PGS) of regular combustible cigarette use (PGS-RCU) and cigarettes per day (PGS-CPD) were constructed using summary statistics from the two largest available genome-wide association study (GWAS) meta-analysis of European ancestry and East Asian ancestry of combustible cigarette use and used to test whether the PGS of RCU or CPD predicted lifetime e-cigarette use and frequency of past 30-day e-cigarette use in a diverse sample of young adults of African (AFR), Admixed American (AMR), East Asian (EAS), European (EUR), and South Asian (SAS) ancestry. FINDINGS: The PGS-RCU was associated with lifetime e-cigarette use in the EUR sample (OR = 1.27, 95% CI = 1.19-1.36, P = 7.53 × 10-12 ), but not in the other subsamples (ps > 0.12). This association remained significant after excluding regular combustible cigarette smokers (OR = 1.21, 95% CI = 1.12-1.31, P = 3.36 × 10-6 ). There was no statistically significant association between PGS-CPD and lifetime e-cigarette use and neither the PGS-RCU nor the PGS-CPD were associated with frequency of e-cigarette use in the past 30 days in any of the subsamples. CONCLUSIONS: Genetic factors associated with regular combustible cigarette use appear to be associated with ever e-cigarette use in young adults. We did not find evidence for shared genetic factors influencing heaviness of use of combustible cigarettes and current e-cigarette use frequency.

Educational attainment of same-sex and opposite-sex dizygotic twins: An individual-level pooled study of 19 twin cohorts.

Comparing twins from same- and opposite-sex pairs can provide information on potential sex differences in a variety of outcomes, including socioeconomic-related outcomes such as educational attainment. It has been suggested that this design can be applied to examine the putative role of intrauterine exposure to testosterone for educational attainment, but the evidence is still disputed. Thus, we established an international database of twin data from 11 countries with 88,290 individual dizygotic twins born over 100 years and tested for differences between twins from same- and opposite-sex dizygotic pairs in educational attainment. Effect sizes with 95% confidence intervals (CI) were estimated by linear regression models after adjusting for birth year and twin study cohort. In contrast to the hypothesis, no difference was found in women (ß = -0.05 educational years, 95% CI -0.11, 0.02). However, men with a same-sex co-twin were slightly more educated than men having an opposite-sex co-twin (ß = 0.14 educational years, 95% CI 0.07, 0.21). No consistent differences in effect sizes were found between individual twin study cohorts representing Europe, the USA, and Australia or over the cohorts born during the 20th century, during which period the sex differences in education reversed favoring women in the latest birth cohorts. Further, no interaction was found with maternal or paternal education. Our results contradict the hypothesis that there would be differences in the intrauterine testosterone levels between same-sex and opposite-sex female twins affecting education. Our findings in men may point to social dynamics within same-sex twin pairs that may benefit men in their educational careers.

Mental health and music engagement: review, framework, and guidelines for future studies.

Is engaging with music good for your mental health? This question has long been the topic of empirical clinical and nonclinical investigations, with studies indicating positive associations between music engagement and quality of life, reduced depression or anxiety symptoms, and less frequent substance use. However, many earlier investigations were limited by small populations and methodological limitations, and it has also been suggested that aspects of music engagement may even be associated with worse mental health outcomes. The purpose of this scoping review is first to summarize the existing state of music engagement and mental health studies, identifying their strengths and weaknesses. We focus on broad domains of mental health diagnoses including internalizing psychopathology (e.g., depression and anxiety symptoms and diagnoses), externalizing psychopathology (e.g., substance use), and thought disorders (e.g., schizophrenia). Second, we propose a theoretical model to inform future work that describes the importance of simultaneously considering music-mental health associations at the levels of (1) correlated genetic and/or environmental influences vs. (bi)directional associations, (2) interactions with genetic risk factors, (3) treatment efficacy, and (4) mediation through brain structure and function. Finally, we describe how recent advances in large-scale data collection, including genetic, neuroimaging, and electronic health record studies, allow for a more rigorous examination of these associations that can also elucidate their neurobiological substrates.

Clarifying the Genetic Influences on Nicotine Dependence and Quantity of Use in Cigarette Smokers.

Nicotine dependence and smoking quantity are both robustly associated with the CHRNA5-A3-B4 gene cluster in the 15q25 region, and SNP rs16969968 in particular. The purpose of this paper is to use structural equation modeling techniques (SEM) to disentangle the complex pattern of relationships between rs16969968, nicotine quantity (as measured by the number of cigarettes an individual smokes per day; CPD) and nicotine dependence (as measured by the Fagerström Test for Nicotine Dependence; FTND). CPD is an indicator, but also a potential cause, of FTND, complicating the interpretation of associations between these constructs and requires a more detailed investigation than standard GWAS or general linear regression models can provide. FTND items and genotypes were collected in four samples, with a combined sample size of 5,373 respondents. A mega-analysis was conducted using a multiple group SEM approach to test competing hypotheses regarding the relationships between the SNP rs16969968, FTND and CPD. In the best fitting model, the FTND items loaded onto two correlated factors. The first, labeled "maintenance," assesses the motivation to maintain constant levels of nicotine through out the day. The second was labeled "urgency" as its items concern the urgency to restore nicotine levels after abstinence. We focus our attention on the "maintenance" factor, of which CPD was an indicator. The best fitting model included a negative feedback loop between the Maintenance factor and CPD. Accordingly, the motivation to maintain higher levels of nicotine increased the quantity of nicotine consumed, which subsequently decreases the maintenance motivation. The fact that the Maintenance-CPD feedback model fits the data best implies that there are at least two biological pathways that lead from rs16969968 to smoking behaviors. The model is consistent with a supply and demand system, which allows individuals to achieve a homeostatic equilibrium for their nicotine concentration.

Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being.

The distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin models in a large sample of adolescent twins, to disentangle the association between well-being (WB) and four complex traits (optimism, anxious-depressed symptoms (AD), aggressive behaviour (AGG), and educational achievement (EA)). Optimism and AD showed respectively a strong positive and negative phenotypic correlation with WB, the negative correlation of WB and AGG is lower and the correlation with EA is nearly zero. All four traits showed a large genetic contribution to the covariance with well-being. The genetic correlations of well-being with optimism and AD are strong and smaller for AGG and EA. We used the results of the models to explain what information is retrieved based on the bivariate heritability versus the genetic correlations and the (clinical) implications.

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.

The Genetic and Environmental Influences Contributing to the Association between Electronic and Conventional Cigarette Initiation.

INTRODUCTION: As the use of electronic cigarette (EC) continues to rise in the United States, especially among adolescents and young adults, it is necessary to better understand the factors associated with EC initiation. Specifically, it is unclear how genetic and environmental contributions influence the initiation of EC. Furthermore, the degree to which genetic and environmental influences are shared between EC initiation and conventional cigarette (CC) initiation is unknown. METHODS: A sample of young adult twins ages 15-20 (N = 858 individuals; 421 complete twin pairs) was used to estimate the genetic and environmental influences on the liability of initiation unique to EC and CC as well as the degree to which these factors are shared between the two. Approximately 24% of participants initiated the use of EC, 19% initiated the use of CC, and 11% initiated the dual use. RESULTS: Combined contributions of additive genetic and shared environmental influences were significant for CC (ACC = 0.19 [95% confidence interval {CI} = 0-0.79], p = 0.57; CCC = 0.42 [95% CI = 0-0.70], p = 0.13) and EC (AEC = 0.25 [95% CI = 0-0.83, p = 0.44; CEC = 0.42 [95% CI = 0-0.73], p = 0.12), whereas unique environmental influences were significant (ECC = 0.39 [95% CI = 0.18-0.57], p < 0.001; EEC = 0.32 [95% CI = 0.14-0.56], p < 0.001). Results also demonstrated a significant overlap of the unique environmental (rE = 0.87, p < 0.001) and familial influences contributing to correlation between the two phenotypes in the bivariate analysis. CONCLUSIONS: These preliminary results suggest that both genes and environmental influences are potential drivers of EC initiation among adolescents and young adults. IMPLICATIONS: This article is the first to use a sample of twin to estimate the contributions of genetic and environmental influences toward EC initiation and estimate the potential for overlapping influences with CC initiation. This study has implications for future debate about the etiology of EC and CC use with respect to potential overlapping genetic and environmental influences.

Common Liabilities in Internalizing Symptoms and Cigarette Use in Adolescence.

INTRODUCTION: Substance use and mood disorders account for about 10% of the global burden of disease and, among adolescents, are a significant source of disability. The present study examined whether additive genetic or shared environmental factors influenced the covariance of internalizing symptoms and cigarette use during adolescence when both of these problems begin to increase. AIMS AND METHODS: We used data (n = 1230 pairs of twins) from the Virginia Twin Study of Adolescent Behavioral Development (mean age = 15.3) to decompose the variance of internalizing symptoms, cigarette initiation, and quantity of cigarettes smoked in a variance decomposition model that included a beta coefficient to allow for estimates of cigarette initiation to influence quantity of cigarettes smoked. RESULTS: In biometric models we were able to equate all parameter estimates by sex. After identifying the best fitting model, parameter estimates were calculated and the significance of overlapping paths between internalizing symptoms and cigarette initiation were tested. After accounting for the genetic architecture of cigarette initiation and quantity smoked, the covariance between internalizing symptoms and cigarette use was accounted for by sex-specific shared and unique environmental factors. CONCLUSIONS: Among adolescents, the overlap in risk factors between internalizing symptoms and cigarette use is because of non-genetic, environmental factors. Further exploration of the environmental sources of variance involved in the onset of adolescents internalizing symptoms and cigarette use is warranted. IMPLICATIONS: We find that during adolescence common environmental factors influence the association between internalizing symptoms and cigarette use. Correlated vulnerabilities because of environmental sources between internalizing and cigarette use may be open to intervention and likely will influence the progression of internalizing and cigarette use.

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.