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Although stress is frequently considered an environmental factor, dependent stressful life events (SLEs) -- stressors that result from one’s actions or behaviors -- may in fact be evoked by a genetic liability. It has been suggested that dependent SLEs may be partially caused by poor executive function (EFs), higher-level cognitive abilities that enable individuals to implement goal-directed behavior. We investigated the possibility of genetic and environmental overlap between SLEs and EFs in a longitudinal twin study. We found high genetic stability in the number of dependent SLEs from age 23 to age 29, suggesting that the number of dependent stressors show persistence across time due to their genetic etiology. In addition, there was a nominally significant negative genetic correlation between a Common EF latent factor and dependent SLEs at age 23. The genetic stability of dependent SLEs and association with Common EF provides insight into how some behaviors may lead to persistent stress.

Lower self-control is a significant correlate or predictor of a wide range of adult outcomes, and this association may be due to more general tendencies toward childhood externalizing problems. The present study examined the association between toddlerhood self-control expressed within a “don’t” compliance task (at 14 to 36 months) and later externalizing problems (parent-reported externalizing problems from age 4 to 12 years, teacher-reported externalizing problems from age 7 to 12 years, and self-reported conduct disorder symptoms at age 17 years) in a longitudinal, genetically informative study. The slope of self-control, but not its intercept, predicted later teacher-reported, but not parent- or self-reported, externalizing problems. That is, increase in self-control during toddlerhood was associated with lower levels of later teacher-reported externalizing problems. The slope of self-control was no longer a significant predictor of teacher-reported externalizing problems after controlling for observed disregard for others, a robust predictor of externalizing problems. Thus, the hypothesis that self-control is the primary predictor of externalizing problems was not supported. Results from genetic analyses suggested that the covariance between the slope of self-control and teacher-reported externalizing problems is due to both genetic and shared environmental influences.

© 2015, Springer Science+Business Media New York. Behavioral disinhibition (BD) is a quantitative measure designed to capture the heritable variation encompassing risky and impulsive behaviors. As a result, BD represents an ideal target for discovering genetic loci that predispose individuals to a wide range of antisocial behaviors and substance misuse that together represent a large cost to society as a whole. Published genome-wide association studies (GWAS) have examined specific phenotypes that fall under the umbrella of BD (e.g. alcohol dependence, conduct disorder); however no GWAS has specifically examined the overall BD construct. We conducted a GWAS of BD using a sample of 1,901 adolescents over-selected for characteristics that define high BD, such as substance and antisocial behavior problems, finding no individual locus that surpassed genome-wide significance. Although no single SNP was significantly associated with BD, restricted maximum likelihood analysis estimated that 49.3 % of the variance in BD within the Caucasian sub-sample was accounted for by the genotyped SNPs (p = 0.06). Gene-based tests identified seven genes associated with BD (p ≤ 2.0 × 10−6). Although the current study was unable to identify specific SNPs or pathways with replicable effects on BD, the substantial sample variance that could be explained by all genotyped SNPs suggests that larger studies could successfully identify common variants associated with BD.

The present study examined the influence of maternal and child characteristics on parenting behaviors in a genetically informative study. The participants were 976 twins and their mothers from the Colorado Longitudinal Twin Study and the Twin Infant Project. Indicators of positive parenting were coded during parent–child interactions when twins were 7–36 months old. Child cognitive abilities and affection were independent correlates of positive parenting. There were significant gender differences in the magnitude of genetic and environmental influences on positive parenting, with shared environmental influences on parenting of girls and additive genetic influences on parenting of boys. Girls received significantly more positive parenting than boys. Differences in etiology of positive parenting may be explained by developmental gender differences in child cognitive abilities and affection, such that girls may have more rewarding interactions with parents, evoking more positive parenting.

The present study assessed the factor structure and etiology of traditional perseverative and nonperseverative errors, and six narrowly defined errors that occur during the Wisconsin Card Sorting Task (WCST). A computer-administered version of the WCST, designed to maximize the variance in a nonclinical sample, was used. Phenotypic factor analysis and twin models were used to examine the structure and genetic and environmental etiology in 191 monozygotic and 165 dizygotic adolescent twin pairs. Factor analysis did not support the traditional division of errors into perseverative and nonperseverative errors. Heritability of individual indices was small to moderate (a(2) = 0.10 - 0.42), with varying significance. Estimates of shared environment (c(2) = 0.00 - 0.14) were not significant. The best fitting multivariate genetic model had one genetic factor, with specific variance and covariance due to nonshared environmental influences. These results suggest that there are common underlying genetic influences on WCST indices, along with index-specific environmental variance that does not correspond to the traditional division between perseverative and nonperseverative errors.

Klein and Riso proposed several alternative models explaining the causes of comorbidity between two disorders (KR models). For each comorbidity model, they also presented a set of predictions for comparing the prevalence of disorder A-only, disorder B-only, and disorder AB (i.e., both disorders) among the relatives of probands with A-only, B-only, AB and controls (i.e., the KR predictions). Neale and Kendler provided the quantitative expectations for these prevalences (i.e., the NK models) and suggested biometric model fitting as an alternative way of testing comorbidity models. Neale and Kendler also suggested that the KR predictions have limited use because variations in the model parameters may lead to different predictions. We tested the KR predictions on two sets of data simulated under the assumptions of the KR/NK models. The results predicted by Klein and Riso and the results derived from the simulated datasets matched in most cases, but there were several notable discrepancies between the two sets of results. First, these discrepancies may be due to variations in the model parameters although the KR predictions are valid tests of the model for some model parameter sets. Second, several KR predictions may not be valid because they do not consider the necessary conditions for the diagnosis of A-only and B-only or alternative routes to comorbidity that are not hypothesized in their comorbidity model, including the fact that some comorbid cases will result by chance in all comorbidity models.

Behavioral inhibition is a temperamental trait that refers to slow approach to novel items, shyness towards new people, and fearfulness in new situations, and individuals may develop inhibited response styles by as early as two years of age. There are important methodological considerations in the assessment of early temperament, with parental report and observational measures providing both corroborative and unique data. The present study examined behavioral inhibition measured by parental report and observational measures in a genetically informative sample to delineate the agreement between the methods and the uniqueness of each method, and to estimate the magnitude of genetic and environmental influences on the common and unique variance. The biometric, psychometric, and rater bias models were conducted to study the covariance between measurement modalities. Overall, the results suggested a common phenotype was assessed by both parents and observers. The latent phenotype underlying parental and observational measures of behavioral inhibition was moderately to substantially heritable.

Studies have demonstrated little to no heritability for adolescent religiosity but moderate genetic, shared environmental, and nonshared environmental influences on adult religiosity. Only one longitudinal study of religiosity in female twins has been conducted (Koenig et al., Dev Psychol 44:532–543, 2008), and reported that persistence from mid to late adolescence is due to shared environmental factors, but persistence from late adolescence to early adulthood was due to genetic and shared environmental factors. We examined the etiology of stability and change in religious values and religious attendance in males and females during adolescence and early adulthood. The heritability of both religious values and religious attendance increased from adolescence to early adulthood, although the increase was greater for religious attendance. Both genetic and shared environmental influences contributed to the stability of religious values and religious attendance across adolescence and young adulthood. Change in religious values was due to both genetic and nonshared environmental influences specific to early adulthood, whereas change in religious attendance was due in similar proportions to genetic, shared environmental, and non-shared environmental influences.

It is often assumed that childhood maltreatment causes conduct problems via an environmentally mediated process. However, the association may be due alternatively to either a nonpassive gene-environment correlation, in which parents react to children’s genetically-influenced conduct problems by maltreating them, or a passive gene-environment correlation, in which parents’ tendency to engage in maltreatment and children’s conduct problems are both influenced by a hereditary vulnerability to antisocial behavior (i.e. genetic mediation). The present study estimated the contribution of these processes to the association between maltreatment and conduct problems. Bivariate behavior genetic analyses were conducted on approximately 1,650 twin and sibling pairs drawn from a large longitudinal study of adolescent health (Add Health). The correlation between maltreatment and conduct problems was small; much of the association between maltreatment and conduct problems was due to a nonpassive gene-environment correlation. Results were more consistent with the hypothesis that parents respond to children’s genetically-influenced conduct problems by maltreating them than the hypothesis that maltreatment causes conduct problems.

Theory and empirical evidence suggest that children’s genetically influenced characteristics help to shape the environments they experience, including the parenting they ‘receive’. The extent of these genetically-mediated child effects on childhood maltreatment is not well known. The present study estimates the magnitude of genetically mediated child effects on maltreatment in 3,297 twins and siblings who were part of a large nationally representative sample of adolescents (ADD health). Participants in early adulthood retrospectively reported their experiences of physical and sexual maltreatment and neglect. Results are consistent with small genetically-mediated child effects on physical maltreatment and neglect, and none on sexual maltreatment, and all three forms of maltreatment are influenced mainly by idiosyncratic individual circumstances.

Are genetic and environmental risks for adolescent substance use specific to individual substances or general across substance classes? We examined this question in 645 monozygotic twin pairs, 702 dizygotic twin pairs, 429 biological sibling pairs, and 96 adoptive (biologically unrelated) sibling pairs ascertained from community-based samples, and ranging in age from 12 to 18 years. Substance use patterns and symptoms were assessed using structured psychiatric interviews. Biometrical model fitting was carried out using age- and sex-specific thresholds for (a) repeated use and (b) problem use, defined as one or more DSM-IV symptoms of abuse or dependence. We hypothesized that problem use would be more heritable than use in adolescence, and that both genetic and environmental risks underlying tobacco, alcohol, and marijuana use and problem use would be significantly correlated. Results of univariate analyses suggested significant heritable factors for use and problem use for all substances with the exception of alcohol use. Shared environmental factors were important in all cases and special twin environmental factors were significant for tobacco use, tobacco problem use, and alcohol use. Multivariate analyses yielded significant genetic correlations between each of the substances (for both levels studied), and significant shared environmental correlations among use variables only. Our results suggest that tobacco, alcohol, and marijuana problem use are mediated by common genetic influences, but shared environmental influences may be more substance-specific for problem use.

Neale and Kendler (1995, Am J Hum Genet 57:935–953) described 13 comorbidity models, providing the most comprehensive set of alternative hypotheses regarding the possible causes of comorbidity to date. This research note describes an extension of the Neale and Kendler model fitting approach that permits the inclusion of measured covariates. An example of 13 models examining the comorbidity between alcohol dependence and illicit drug dependence is presented.

Given that knowledge regarding the etiology of comorbidity between disorders can have a significant impact on research regarding the classification, treatment, and etiology of the disorders, the ability to reject incorrect hypotheses regarding the causes of comorbidity is very important. A simulation study was conducted to assess the validity of the Neale and Kendler (1995) model-fitting approach in examining the etiology of comorbidity between two disorders. First, data were simulated under the assumptions of the 13 alternative comorbidity models described by Neale and Kendler. Second, model-fitting analyses testing the comorbidity models were conducted on the simulated datasets. Thirteen sets of data with varying model parameters were simulated to test Neale and Kendler's assertion that their model-fitting approach is appropriate across a range of potential prevalences and degrees of familiality. The validity of the model-fitting approach in examining unselected twin data and a combination of selected family data and unselected family data was explored. The model-fitting approach successfully discriminated several classes of comorbidity models, although discrimination between models within classes of related models was less accurate. Results suggest that the model-fitting approach can be a useful tool in examining the etiology of the comorbidity between disorders if the caveats of the present study's results are considered carefully. As predicted by Neale and Kendler, variations in the disorder prevalences and familial correlations did not affect the validity of their model-fitting approach, but affected the power to discriminate the correct model. As suggested by Neale and Kendler, the model-fitting approach can be applied to both unselected and selected data and to both twin and family data.

Klein and Riso proposed several alternative models explaining the causes of comorbidity between two disorders (KR models). For each comorbidity model, they also presented a set of predictions for comparing the prevalence of disorder A-only, disorder B-only, and disorder AB (i.e., both disorders) among the relatives of probands with A-only, B-only, AB and controls (i.e., the KR predictions). Neale and Kendler provided the quantitative expectations for these prevalences (i.e., the NK models) and suggested biometric model fitting as an alternative way of testing comorbidity models. Neale and Kendler also suggested that the KR predictions have limited use because variations in the model parameters may lead to different predictions. We tested the KR predictions on two sets of data simulated under the assumptions of the KR/NK models. The results predicted by Klein and Riso and the results derived from the simulated datasets matched in most cases, but there were several notable discrepancies between the two sets of results. First, these discrepancies may be due to variations in the model parameters although the KR predictions are valid tests of the model for some model parameter sets. Second, several KR predictions may not be valid because they do not consider the necessary conditions for the diagnosis of A-only and B-only or alternative routes to comorbidity that are not hypothesized in their comorbidity model, including the fact that some comorbid cases will result by chance in all comorbidity models.