Genetically informed analyses of childhood individual differences

This dissertation aimed to explore the origins of individual differences in childhood traits such as height, self-control, grit, and school performance, using various analytical models. In Chapter 2, the role of geographical location was examined as a third-level variable in a twin study design, with child-level as the first level and family-level as the second level. A 3-level multilevel model was employed to analyze twin data and investigate regional clustering of children's height in the Netherlands. Our research revealed that ~2% of the phenotypic variance in children's height can be attributed to regional clustering, which accounts for 7% of the variance explained by common environmental components between families. Children in the North of the Netherlands tended to be taller than those in the South, with boys generally being taller than girls. I also examined the potential effect of genetic ancestry on regional clustering by assessing the impact of genetic principal components in a subset of participants with genome-wide single nucleotide polymorphism (SNP) data. Principal component analysis of the covariance matrix of the SNP data allows us to identify genetic principal components, which reflect allele frequency gradients. Our results indicated that, after accounting for genetic factors, region no longer had a significant effect on height variation. These findings suggest that the phenotypic variance explained by regional clustering are attributable to ancestry effects on height. Chapter 3 demonstrated the power of multi-study collaboration and Bayesian evidence synthesis. The study used this approach to quantify and compare support for competing hypotheses regarding multi-informant scores on the ASEBA Self Control Scale (ASCS) in four Dutch cohorts. As the set of available reporters on children’s self-control varied across the cohorts (e.g., parents, teachers, self-reports), each cohort evaluated different aspects of the overall competing hypotheses. Our findings consistently provided evidence for the partial hypothesis that parents reported more self-control issues than teachers. The aggregated results showed most support for the hypothesis that children report the highest number of self-control problems, followed by their mothers and fathers, while teachers report the fewest problems. However, there were inconsistencies in the ordering of self-reported self-control problems. This chapter illustrated the importance of taking the informant into account, and the potential of combining results from different studies with Bayesian evidence synthesis. In Chapter 4, genetic covariance structure modeling and regression were combined to predict school performance using self-control and grit. The study revealed that 28.4% of individual differences in school performance could be explained by self-control, grit, and their covariance. Genetic components of self-control and grit were the primary contributors to explained variance in school performance, with environmental factors playing a minor role after controlling for socio-economic status, sex, and rater (teacher) effects. The study addressed data issues related to censoring and rater variance estimation. Chapter 5 delved into the potential causal relationship between self-control, grit, and school performance. A causal model was applied to examine the phenotypic regression of school performance on self-control and grit, considering potential confounding factors. The results showed that most of the relationship between self-control, grit, and school performance was due to genetic confounding, which is likely to reflect genetic pleiotropy: i.e., the genes that explained individual differences in self-control and grit also explained individual differences in school performance. Direct effects of self-control and grit on school performance were observed but accounted for only 4.4% of the variation, while 12.4% was attributed to pleiotropy. In summary, this dissertation employed various analytical approaches to investigate the factors contributing to individual differences in childhood traits. The findings shed light on the complex interplay of genetic and environmental factors in shaping these traits.