Developmental-genetic effects on level and change in childhood fears of twins during adolescence

The genetic and environmental structure of fear and anxiety in juvenile twins

Fear and anxiety are conceptualized as responses to acute or potential threat, respectively. Adult twin studies found substantial interplay between genetic and environmental factors influencing fear disorders (phobias) and anxiety disorders. Research in children, however, has largely examined these factors independently. Thus, there exists a substantial knowledge gap regarding the underlying etiologic structure of these closely-related constructs during development. Symptom counts for five fear (criticism, the unknown, death, animal, medical) and four anxiety (generalized, panic, separation, social) dimensions were obtained for 373 twin pairs ages 9-14. Multivariate twin modeling was performed to elucidate the genetic and environmental influences distributed amongst these dimensions. The best fitting model contained one genetic, two familial environmental, and two unique environmental factors shared between fear and anxiety symptoms plus dimension-specific genetic and unique environmental factors. Although several environmental factors were shared between fear and anxiety dimensions, one latent factor accounted for genetic influences across both domains. While adult studies find somewhat distinct etiological differences between anxiety and phobic disorders, the current results suggest that their relative genetic and environmental influences are not as clearly demarcated in children. These etiological distinctions are more nuanced, likely contributing to the highly diffuse symptom patterns seen during development.

Genetic and environmental influences on obsessive-compulsive behaviour across development: a longitudinal twin study

BACKGROUND

Little is known about the factors influencing the stability of obsessive-compulsive behaviour (OCB) from childhood to adolescence. The current study aimed to investigate: (1) the stability of paediatric OCB over a 12-year period; (2) the extent to which genetic and environmental factors influence stability; and (3) the extent to which these influences are stable or dynamic across development.

METHOD

The sample included 14 743 twins from a population-based study. Parental ratings of severity of OCB were collected at ages 4, 7, 9 and 16 years.

RESULTS

OCB was found to be moderately stable over time. The genetic influence on OCB at each age was moderate, with significant effects also of non-shared environment. Genetic factors exerted a substantial influence on OCB persistence, explaining 59-80% of the stability over time. The results indicated genetic continuity, whereby genetic influences at each age continue to affect the expression of OCB at subsequent ages. However, we also found evidence for genetic attenuation in that genetic influences at one age decline in their influence over time, and genetic innovation whereby new genes 'come on line' at each age. Non-shared environment influenced stability of OCB to a lesser extent and effects were largely unique to each age and displayed negligible influences on OCB at later time points.

CONCLUSIONS

OCB appears to be moderately stable across development, and stability is largely driven by genetic factors. However, the genetic effects are not entirely constant, but rather the genetic influence on OCB appears to be a developmentally dynamic process.

Stable genetic influence on anxiety-related behaviours across middle childhood

We examined the aetiology of anxiety symptoms in an unselected population at ages 7 and 9, a period during which anxiety disorders first begin to develop (mean age at onset is 11 years). Specifically, the aim of the study was to investigate genetic and environmental continuity and change in components of anxiety in middle childhood. Parents of over 3,500 twin pairs completed the Anxiety-Related Behaviours Questionnaire (ARBQ) when twins were 7 and 9 years old. Multivariate-longitudinal analyses were conducted to examine genetic and environmental influences on stability and change in four anxiety scales: Negative Cognition, Negative Affect, Fear and Social Anxiety. We found moderate temporal stability in all four scales from 7 to 9 years (correlations ranging from 0.45 to 0.54) and moderate heritability (average 54%). Both shared and non-shared environmental influences were modest (average 18%–28% respectively). Genetic factors (68%) explained most of the homotypic continuity in anxiety. We show that homotypic continuity of Anxiety-Related Behaviours (i.e. the continuation of one specific type of anxiety over time) was largely driven by genetic factors. In contrast, though more varied, heterotypic continuity between some traits (i.e. the change from one type of anxiety-related behaviour into another over time) was mainly due to shared-environmental factors.

Estimating fetal and maternal genetic contributions to premature birth from multiparous pregnancy histories of twins using MCMC and maximum-likelihood approaches

The analysis of genetic and environmental contributions to preterm birth is not straightforward in family studies, as etiology could involve both maternal and fetal genes. Markov Chain Monte Carlo (MCMC) methods are presented as a flexible approach for defining user-specified covariance structures to handle multiple random effects and hierarchical dependencies inherent in children of twin (COT) studies of pregnancy outcomes. The proposed method is easily modified to allow for the study of gestational age as a continuous trait and as a binary outcome reflecting the presence or absence of preterm birth. Estimation of fetal and maternal genetic factors and the effect of the environment are demonstrated using MCMC methods implemented in WinBUGS and maximum likelihood methods in a Virginia COT sample comprising 7,061 births. In summary, although the contribution of maternal and fetal genetic factors was supported using both outcomes, additional births and/or extended relationships are required to precisely estimate both genetic effects simultaneously. We anticipate the flexibility of MCMC methods to handle increasingly complex models to be of particular relevance for the study of birth outcomes.