Comparing findings from the random-intercept cross-lagged panel model and the monozygotic twin difference cross-lagged panel model: Maladaptive parenting and offspring emotional and behavioural problems.

Background: In this study we compare results obtained when applying the monozygotic twin difference cross-lagged panel model (MZD-CLPM) and a random intercept cross-lagged panel model (RI-CLPM) to the same data. Each of these models is designed to strengthen researchers' ability to draw causal inference from cross-lagged associations. We explore differences and similarities in how each model does this, and in the results each model produces. Specifically, we examine associations between maladaptive parenting and child emotional and behavioural problems in identical twins aged 9, 12 and 16. Method: Child reports of 5698 identical twins from the Twins Early Development Study (TEDS) were analysed. We ran a regular CLPM to anchor our findings within the current literature, then applied the MZD-CLPM and the RI-CLPM. Results: The RI-CLPM and MZD-CLPM each enable researchers to evaluate the direction of effects between correlated variables, after accounting for unmeasured sources of potential confounding. Our interpretation of these models therefore focusses primarily on the magnitude and significance of cross-lagged associations. In both the MZD-CLPM and the RI-CLPM behavioural problems at age 9 resulted in higher levels of maladaptive parenting at age 12. Other effects were not consistently significant across the two models, although the majority of estimates pointed in the same direction. Conclusion: In light of the triangulated methods, differences in the results obtained using the MZD-CLPM and the RI-CLPM underline the importance of careful consideration of what sources of unmeasured confounding different models control for and that nuance is required when interpreting findings using such models. We provide an overview of what the CLPM, RI-CLPM and MZD-CLPM can and cannot control for in this respect and the conclusions that can be drawn from each model.

Socioeconomic status and risk for child psychopathology: exploring gene-environment interaction in the presence of gene-environment correlation using extended families in the Norwegian Mother, Father and Child Birth Cohort Study.

BACKGROUND: Low socioeconomic status (SES) is associated with increased risk for emotional and behavioural problems among children. Evidence from twin studies has shown that family SES moderates genetic and environmental influences on child mental health. However, it is also known that SES is itself under genetic influence and previous gene-environment interaction (G×E) studies have not incorporated the potential genetic overlap between child mental health and family SES into G×E analyses. We applied a novel approach using extended family data to investigate the moderation of aetiological influences on child emotional and behavioural problems by parental socioeconomic status in the presence of modelled gene-environment correlation. METHODS: The sample comprised >28,100 children in extended-family units drawn from the Norwegian Mother, Father and Child Cohort Study (MoBa). Mothers reported children's emotional and behavioural symptoms. Parents' income and educational attainment were obtained through linkage to administrative register data. Bivariate moderation Multiple-Children-of-Twins-and-Siblings (MCoTS) models were used to analyse relationships between offspring outcomes (emotional and behavioural symptom scores) and parental socioeconomic moderators (income rank and educational attainment). RESULTS: The aetiology of child emotional symptoms was moderated by maternal and paternal educational attainment. Shared environmental influences on child emotional symptoms were greater at lower levels of parents' education. The aetiology of child behavioural symptoms was moderated by maternal, but not paternal, socioeconomic factors. Genetic factors shared between maternal income and child behavioural symptoms were greater in families with lower levels maternal income. Nonshared environmental influences on child behavioural symptoms were greater in families with higher maternal income and education. CONCLUSIONS: Parental socioeconomic indicators moderated familial influences and nonshared environmental influences on child emotional and behavioural outcomes. Maternal SES and child mental health share aetiological overlap such that shared genetic influence was greater at the lower end of the socioeconomic distribution. Our findings collectively highlight the role that family socioeconomic factors play in shaping the origins of child emotional and behavioural problems.

Assessing aetiological overlap between child and adult attention-deficit hyperactivity disorder symptoms in an extended family design.

BACKGROUND: Several longitudinal studies have cast doubt on the aetiological overlap between child and adult attention-deficit hyperactivity disorder (ADHD). However, a lack of genetically sensitive data following children across adulthood precludes direct evaluation of aetiological overlap between child and adult ADHD. AIMS: We circumvent the existing gap in longitudinal data by exploring genetic overlap between maternal (adult) and offspring (child) ADHD and comorbid symptoms in an extended family cohort. METHOD: Data were drawn from the Norwegian Mother, Father and Child Cohort Study, a Norwegian birth registry cohort of 114 500 children and their parents. Medical Birth Registry of Norway data were used to link extended families. Mothers self-reported their own ADHD symptoms when children were aged 3 years; reported children's ADHD symptoms at age 5 years; and children's ADHD, oppositional defiant disorder (ODD), conduct disorder, anxiety and depression symptoms at age 8 years. Genetic correlations were derived from Multiple-Children-of-Twins-and-Siblings and extended bivariate twin models. RESULTS: Phenotypic correlations between adult ADHD symptoms and child ADHD, ODD, conduct disorder, anxiety and depression symptoms at age 8 years were underpinned by medium-to-large genetic correlations (child ADHD: rG = 0.55, 95% CI 0.43-0.93; ODD: rG = 0.80, 95% CI 0.46-1; conduct disorder: rG = 0.44, 95% CI 0.28-1; anxiety: rG = 0.72, 95% CI 0.48-1; depression: rG = 1, 95% CI 0.66-1). These cross-generational adult-child genetic correlations were of a comparable magnitude to equivalent child-child genetic correlations with ADHD symptoms at age 5 years. CONCLUSIONS: Our findings provide genetically sensitive evidence that ADHD symptoms in adulthood share a common genetic architecture with symptoms of ADHD and four comorbid disorders at age 8 years. These findings suggest that in the majority of cases, ADHD symptoms in adulthood are not aetiologically distinct from in childhood.