Can GE-Covariance Originating in Phenotype to Environment Transmission Account for the Flynn Effect?

How nonshared environmental factors come to correlate with heredity

Conventional longitudinal behavioral genetic models estimate the relative contribution of genetic and environmental factors to stability and change of traits and behaviors. Longitudinal models rarely explain the processes that generate observed differences between genetically and socially related individuals. We propose that exchanges between individuals and their environments (i.e., phenotype-environment effects) can explain the emergence of observed differences over time. Phenotype-environment models, however, would require violation of the independence assumption of standard behavioral genetic models; that is, uncorrelated genetic and environmental factors. We review how specification of phenotype-environment effects contributes to understanding observed changes in genetic variability over time and longitudinal correlations among nonshared environmental factors. We then provide an example using 30 days of positive and negative affect scores from an all-female sample of twins. Results demonstrate that the phenotype-environment effects explain how heritability estimates fluctuate as well as how nonshared environmental factors persist over time. We discuss possible mechanisms underlying change in gene-environment correlation over time, the advantages and challenges of including gene-environment correlation in longitudinal twin models, and recommendations for future research.

Cross-Lagged Analysis of Interplay Between Differential Traits in Sibling Pairs: Validation and Application to Parenting Behavior and ADHD Symptomatology

Understanding the factors that contribute to behavioral traits is a complex task, and partitioning variance into latent genetic and environmental components is a useful beginning, but it should not also be the end. Many constructs are influenced by their contextual milieu, and accounting for background effects (such as gene-environment correlation) is necessary to avoid bias. This study introduces a method for examining the interplay between traits, in a longitudinal design using differential items in sibling pairs. The model is validated via simulation and power analysis, and we conclude with an application to paternal praise and ADHD symptoms in a twin sample. The model can help identify what type of genetic and environmental interplay may contribute to the dynamic relationship between traits using a cross-lagged panel framework. Overall, it presents a way to estimate and explicate the developmental interplay between a set of traits, free from many common sources of bias.

Widowhood and the Stability of Late Life Depressive Symptomatology in the Swedish Adoption Twin Study of Aging

Although the Swedish Adoption Twin of Aging (SATSA) has been used to investigate phenotypic stability of late life depressive symptoms, the biometric processes underlying this stability have not been studied. Under a reciprocal effects modeling framework, we used SATSA twins' Center for Epidemiologic Studies Depression (CES-D) Scale data across 5 waves (from 1987-2007) to test whether the reciprocal exchange between twins within a family and their nonshared environments (P<=>E) promote the accumulation of gene-environment correlation (rGE) over time. The model generates increasing rGE that produces subsequent stable environmental differences between twins within a family-a process hypothesized to explain stability in chronic late life depressive symptoms. Widowhood is included as a stressful life experience that may introduce an additional nonshared source of variability in CES-D scores. Genetic effects and nonshared environmental effects are primary sources of stability of late life depressive symptoms without evidence of underlying rGE processes. Additionally, widowhood explained stable differences in CES-D scores between twins within a family up to 3 years after spousal loss.

Twin Differentiation of Cognitive Ability Through Phenotype to Environment Transmission: The Louisville Twin Study

The Louisville Twin Study is one of the most intensive twin studies of cognitive ability. The repeated measurements of the twins are ideal for testing developmental twin models that allow for the accumulation of gene-environment correlation via a (P⇒E) transmission process to explain twins' divergence in mean ability level over time. Using full-scale IQ scores from 566 pairs of twins (MZ = 278; DZ = 288), we tested whether a P⇒E transmission model provided better representation of actual developmental processes than a genetic simplex model. We also addressed whether the induced gene-environment correlation alters the meaning of the latent nonshared environmental factors with a simple numerical method for interpreting nonshared environmental factors in the context of P⇒E transmission. The results suggest that a P⇒E model provided better fit to twins' FSIQ data than a genetic simplex model and the meaning of the nonshared environment was preserved in the context of P⇒E.

Genetic and Environmental Stability of Intelligence in Childhood and Adolescence

The present study examined the genetic and environmental contributions to the temporal stability of verbal, non-verbal and general intelligence across a developmental period spanning childhood and adolescence (5–18 years). Longitudinal twin data collected in four different studies on a total of 1,748 twins, comprising 4,641 measurement points in total, were analyzed using genetic adaptations of the simplex model. The heterogeneity in the type of instrument used to assess psychometric intelligence across the different subsamples and ages allowed us to address the auxiliary question of how to optimally utilize the existing longitudinal data in the context of gene-finding studies. The results were consistent across domains (verbal, non-verbal and general intelligence), and indicated that phenotypic stability was driven primarily by the high stability of additive genetic factors, that the stability of common environment was moderate, and that the unique environment contributed primarily to change. The cross-subscale stability was consistently low, indicating a small overlap between different domains of intelligence over time. The high stability of additive genetic factors justifies the use of a linear combination of scores across the different ages in the context of gene-finding studies.

GE covariance through phenotype to environment transmission: an assessment in longitudinal twin data and application to childhood anxiety

We considered identification of phenotype (at occasion t) to environment (at occasion t + 1) transmission in longitudinal model comprising genetic, common and unique environmental simplex models (autoregressions). This type of transmission, which gives rise to genotype-environment covariance, is considered to be important in developmental psychology. Having established identifying constraints, we addressed the issue of statistical power to detect such transmission given a limited set of parameter values. The power is very poor in the ACE simplex, but is good in the AE model. We investigated misspecification, and found that fitting the standard ACE simplex to covariance matrices generated by an AE simplex with phenotype to E transmission produces the particular result of a rank 1 C (common environment) covariance matrix with positive transmission, and a rank 1 D (dominance) matrix given negative transmission. We applied the models to mother ratings of anxiety in female twins (aged 3, 7, 10, and 12 years), and obtained support for the positive effect of one twin's phenotype on the other twin's environment.