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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Graph The Reverend Dr. Lindon John Eaves was an eminent professor in behavior genetics, with an international reputation as an exceptional scientist. Dr. Eaves was also highly influential in his supervision of graduate and post-doctoral students at the University of Birmingham, the University of Oxford, and subsequently VCU, of whom many have very distinguished careers of their own. Professor Eaves was a distinguished professor, scholar, mentor and friend, but foremost a genuine human being. [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]

Purpose: Resilience to stressful life events (SLEs), which increase risk of psychopathology, is influenced by genetic factors. The purpose of this paper was to map the overlap of etiologic risk factors for resilience onto the broad psychopathological map. Resilience was defined as the difference between the twins' total score on a broad measure of internalizing symptoms and their predicted score based on their cumulative exposure to SLEs.Methods: Cholesky decompositions were performed with OpenMx to quantify the overlap in genetic and environmental risk factors between resilience and four phenotypes [major depression (MD), generalized anxiety disorder (GAD), alcohol abuse or dependence (AAD), and antisocial personality disorder (ASPD)].Results: The genetic factors that influence resilience account for 42 and 61 % of the heritability of MD and GAD, respectively, and 20 and 18 % for AAD and ASPD, respectively. The latent genetic contribution to MD was shared 47 % with resilience, and for AAD, this estimate was lower (23 %). The shared environmental covariance was nominal.Conclusions: Genetic influences on resilience contribute to internalizing phenotypes to a higher degree than to externalizing phenotypes. Environmental influences can also have an enduring effect on resilience. However, virtually all of the covariance between resilience and the phenotypes was genetic. [ABSTRACT FROM AUTHOR]

Twin and family studies have provided overwhelming evidence for the genetic basis of individual differences in tobacco initiation (TI), regular smoking (RS) and nicotine dependence (ND). However, only a few genes have been reliably associated with ND. We used a finite mixture distribution model to examine the significance and effect size of the association of previously identified and replicated specific variants in the CHRNA5 and CHRNA3 receptor genes with ND, against the background of genetic and environmental risk factors for ND. We hypothesize that additional phenotypic information in relatives who have not been genotyped can be used to increase the power of detecting the genetic variant. The nicotine measures were assessed by personal interview in female, male and opposite sex twin pairs ( N = 4,153) from the population-based Virginia Twin Registry. Three SNPs in the CHRNA5 and CHRNA3 receptor genes, previously shown to be significantly associated with ND in this sample, were replicated in the augmented analyses; they accounted for less than one percent of the genetic variance in liability to ND, which is estimated to be over 50% of the phenotypic variance. The significance of these effects was increased by adding twins with phenotype but without genotype data, but gains are limited and variable. The SNPs associated with ND did not show a significant association with either TI or RS and appear to be specific to the addictive stage of ND, characterized by current smoking and smoking a large amount of cigarettes per day. Furthermore, these SNPs did not appear to be associated with the remaining items comprising the FTND scale. This study confirmed a significant contribution of the CHRNA receptor on different forms of tobacco dependence. However, the genetic variant only accounted for little of the total genetic variance for liability to ND. Including phenotypic data on ungenotyped relatives can improve the statistical power to detect the effects of genetic variants when they contribute to individual differences in the phenotype. [ABSTRACT FROM AUTHOR]

To determine the relationship between the genetic and environmental risk factors for common internalizing psychopathology (IP) and mental well-being (MWB), we examined detailed measures of emotional, social and psychological well-being, and a history of major depression (MD), generalized anxiety disorder (GAD) and panic attacks in the last year, in 1,386 twins from same-sex pairs from the MIDUS national USA sample assessed in 1995 and then again in 2005. Statistical analyses were performed with the Mx program. In the 1995 data, the best fit model contained one substantially heritable common factor for MD, GAD and panic attacks, and one strongly heritable common factor for the three well-being measures. Genetic and environmental risk factors for IP accounted for, respectively, 50 and 5%, of the genetic and environmental influences on MWB. We then constructed, using 1995 and 2005 data, two common factors that reflected temporally stable influences on (i) MD and GAD, and (ii) on emotional and psychological well-being. Genetic and environmental risk factors for the stable liability to IP accounted for 41 and 29% of the stable genetic and environmental influences, respectively, on MWB. This study suggests that genetic risk factors for IP make up 41-50% of the genetic influences on MWB. The overlap of environmental risk factors is more modest. Although low levels of IP on average reflect a high genetic propensity for MWB, other independent genetic influences play an important role in producing good mental health. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) of body mass index (BMI) using large samples have yielded approximately a dozen robustly associated variants and implicated additional loci. Individually these variants have small effects and in aggregate explain a small proportion of the variance. As a result, replication attempts have limited power to achieve genome-wide significance, even with several thousand subjects. Since there is strong prior evidence for genetic influence on BMI for specific variants, alternative approaches to replication can be applied. Instead of testing individual loci sequentially, a genetic risk sum score (GRSS) summarizing the total number of risk alleles can be tested. In the current study, GRSS comprising 56 top variants catalogued from two large meta-analyses was tested for association with BMI in the Molecular Genetics of Schizophrenia controls (2,653 European-Americans, 973 African-Americans). After accounting for covariates known to influence BMI (ancestry, sex, age), GRSS was highly associated with BMI ( p value = 3.19E−06) although explained a limited amount of the variance (0.66%). However, area under receiver operator criteria curve (AUC) estimates indicated that the GRSS and covariates significantly predicted overweight and obesity classification with maximum discriminative ability for predicting class III obesity (AUC = 0.697). The relative contributions of the individual loci to GRSS were examined post hoc and the results were not due to a few highly significant variants, but rather the result of numerous variants of small effect. This study provides evidence of the utility of a GRSS as an alternative approach to replication of common polygenic variation in complex traits. [ABSTRACT FROM AUTHOR]

Considerable evidence from twin and adoption studies indicates that genetic and shared environmental factors play a significant role in the initiation of smoking behavior. Although twin and adoption designs are powerful to detect genetic and environmental influences, they do not provide information on the processes of assortative mating and parent–offspring transmission and their contribution to the variability explained by genetic and/or environmental factors. We examined the role of genetic and environmental factors for smoking initiation using an extended kinship design. This design allows the simultaneous testing of additive and non-additive genetic, shared and individual-specific environmental factors, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission. A dichotomous lifetime smoking measure was obtained from twins and relatives in the Virginia 30,000 sample. Results demonstrate that both genetic and environmental factors play a significant role in the liability to smoking initiation. Major influences on individual differences appeared to be additive genetic and unique environmental effects, with smaller contributions from assortative mating, shared sibling environment, twin environment, cultural transmission and resulting genotype–environment covariance. The finding of negative cultural transmission without dominance led us to investigate more closely two possible mechanisms for the lower parent–offspring correlations compared to the sibling and DZ twin correlations in subsets of the data: (i) age × gene interaction, and (ii) social homogamy. Neither mechanism provided a significantly better explanation of the data, although age regression was significant. This study showed significant heritability, partly due to assortment, and significant effects of primarily non-parental shared environment on smoking initiation. [ABSTRACT FROM AUTHOR]

Twin data can provide valuable insight into the relationship between the stages of phenomena such as disease or substance abuse. Initiation of substance use may be caused by factors that are the same as, partially shared with, or completely independent of those that cause progression from use to abuse. Comparison of rates of progression among the cotwins of twins who do vs. do not initiate provides indirect information about the relationship between initiation and progression. Existing models for this relationship have been difficult to extend because they are usually expressed in terms of explicit integrals. In this paper, the problem is overcome by regarding the analysis of twin data on initiation and progression as a special case of missing data, in which individuals who do not initiate are regarded as having missing data on progression measures. Using the general framework for the analysis of ordinal data with missing values available in Mx makes extensions that include other variables much easier. The effects of continuous covariates such as age on initiation and progression becomes simple. Also facilitated are the examination of initiation and progression in two or more substances, and transition models with two or more steps. The methods are illustrated with data on the effects of cohort on liability to cannabis use and abuse, bivariate analysis of tobacco use and dependence and cannabis use and abuse, and the relationships between initiation of smoking, regular smoking and nicotine dependence. Other suitable applications include the relationship between symptoms and diagnosis, such as fears and the progression to phobia. [ABSTRACT FROM AUTHOR]

Several “genetic” item-response theory (IRT) models are fitted to the responses of 1086 adolescent female twins to the 33 multi-category item Mood and Feeling Questionnaire relating to depressive symptomatology in adolescence. A Markov-chain Monte Carlo (MCMC) algorithm is used within a Bayesian framework for inference using Gibbs sampling, implemented in the program WinBUGS 1.4. The final model incorporated separate genetic and non-shared environmental traits (“A and E”) and item-specific genetic effects. Simpler models gave markedly poorer fit to the observations judged by the deviance information criterion (DIC). The common genetic factor showed major loadings on melancholic items, while the environmental factor loaded most highly on items relating to self-deprecation. The MCMC approach provides a convenient and flexible alternative to Maximum Likelihood for estimating the parameters of IRT models for relatively large numbers of items in a genetic context. Additional benefits of the IRT approach are discussed including the estimation of latent trait scores, including genetic factor scores, and their sampling errors. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether the observed phenotypic stability in explosive strength during adolescence, as measured by inter-age correlations in vertical jump (VTJ), is mainly caused by genetic and/or environmental factors. Methods: Subjects are from the Leuven Longitudinal Twin Study (LLTS) ( n = 105 pairs, equally divided over five zygosity groups). VTJ data were aligned on age at peak height velocity (APHV) to attenuate the temporal fluctuations in inter-age correlations caused by differences in timing of the adolescent growth spurt. Simplex models were fitted using structural equation modelling. Results: After aligning the data on APHV, the annual inter-age correlations show a clear simplex structure over a 4 year interval. The best fitting models included additive genetic and unique environmental sources of variation. Heritability estimates ranged between 60.8% (CI 37.7%–77.2%) and 87.3% (CI 74.2%–94.0%) for boys and between 76.5% (CI 56.7%–89.0%) and 88.6% (CI 77.8%–94.1%) for girls. Up to 56.4% and 62.8% of the total variation at the last measurement occasion is explained by additive genetic factors that already explained a significant amount of variation at previous measurement occasions in boys and girls respectively. It thus can be concluded that the observed stability of explosive strength during adolescence is mainly caused by a stable genetic influence in boys and girls. Conclusions: Additive genetic factors seem to be the main cause of the observed phenotypic stability in VTJ performance in boys and girls during adolescence. [ABSTRACT FROM AUTHOR]

This study explores the associations between polymorphisms in two candidate genes-myostatin gene (MSTN or GDF8) and angiotensin-converting enzyme (ACE) gene-with interindividual differences in human muscle mass and strength responses to strength training. The MSTN AluI A55T (exon 1), BanII K153R, TaqI E164 K and BstNI P198A (all in exon 2) markers and the ACE insertion (I)/deletion (D) polymorphism were typed in 57 males [22.4 (3.7) years] who participated in a 10-week, high-resistance training program for the elbow flexors. Maximal strength, and maximal isometric and concentric elbow flexor torques were measured at baseline and after training. Information on muscle cross-sectional area of the upper arm was obtained by computer tomography scans. Only one individual was heterozygous for the MSTN BanII K153R variant. No allelic variant was detected at the other MSTN sites in this population. For the ACE I/D polymorphism, no evidence was found for an association of the D or I allele with baseline strength, isometric and concentric torque or arm muscle cross-sectional area [analysis of covariance (ANCOVA) 0.25< P<0.97]. Responses to the strength-training program were not associated with the ACE I/D genotype (ANCOVA 0.057< P<0.70). Borderline significance was found for larger strength gains in dynamic flexion torques for I/I genotypes. This study therefore does not support the hypothesis that an increased muscle fiber hypertrophic effect of strength training is present in D-allele carriers. [ABSTRACT FROM AUTHOR]

Univariate and multivariate analyses of the genetic and environmental contributions to variance in adipose tissue and adipose tissue distribution were carried out in early adolescents. Stature, weight, body mass index (BMI), and five subcutaneous skinfolds were measured at half-yearly intervals in 105 MZ and DZ twin pairs from 10 to 14 years. The most parsimonious model, which provided an adequate explanation for variation in the BMI, five skinfolds, and the T/E ratio, included additive genetic and specific environmental factors. Multivariate analyses of the genetic architecture of subcutaneous fat indicated a general skinfold genetic factor, an extremity skinfold genetic factor, and skinfold specific genetic factors. This implies that all skinfolds are under control of the same set of genes, that a different set of genes partly controls extremity skinfolds, and that other genes have a small skinfold specific impact. Environmental contributions included a general skinfold environmental factor and skinfold specific environmental factors. BMI is under control of the same set of genes as skinfolds and shows high genetic correlations with trunk skinfolds, which implies that nearly the same genes may influence trunk skinfolds and the BMI. All models were fairly consistent across the age range. [ABSTRACT FROM AUTHOR]

The magnitude of genetic and environmental factors and the influence of contrast effects on attention-deficit hyperactivity disorder (ADHD) symptomatology were examined on a sample of 900 twin pairs, aged 7–13, participating in the Virginia Twin Study of Adolescent Behavioral Development (VTSABD). In addition, the genetic and environmental correlations between ADHD and oppositional-defiant disorder/conduct disorder (ODD/CD) symptomatology were estimated. A series of structural models was applied to maternal ratings from a telephone survey, designed to screen for the three dimensions of ADHD symptomatology (hyperactivity, impulsivity, and inattention) and ODD/CD symptomatology. Model-fitting results suggested that ADHD symptomatology is highly heritable and influenced mostly by additive genetic, specific environmental, and contrast effects. However, this analysis could not exclude with statistical significance additional effects from dominance. The results of the best-fitting bivariate model suggested that the genetic correlation between the two traits is 50% and replicated previous findings of a common genetic factor influencing the comorbidity of ADHD and ODD/CD symptomatologies. [ABSTRACT FROM AUTHOR]