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Noncognitive skills such as motivation and self-regulation, predict academic achievement beyond cognitive skills. However, the role of genetic and environmental factors and of their interplay in these developmental associations remains unclear. We provide a comprehensive account of how cognitive and noncognitive skills contribute to academic achievement from ages 7 to 16 in a sample of >10,000 children from England and Wales. Results indicated that noncognitive skills become increasingly predictive of academic achievement across development. Triangulating genetic methods, including twin analyses and polygenic scores (PGS), we found that the contribution of noncognitive genetics to academic achievement becomes stronger over development. The PGS for noncognitive skills predicted academic achievement developmentally, with prediction nearly doubling by age 16, pointing to gene-environment correlation (rGE). Within-family analyses indicated both passive and active/evocative rGE processes driven by noncognitive genetics. By studying genetic effects through a developmental lens, we provide novel insights into the role of noncognitive skills in academic development.

The intergenerational transmission of educational attainment from parents to their children is one of the most important and studied relationships in social science. Longitudinal studies have found strong associations between parents’ and their children’s educational outcomes, which could be due to the effects of parents. Here we provide new evidence about whether parents’ educational attainment affects their parenting behaviours and children’s early educational outcomes using within-family Mendelian randomization and data from 40,907 genotyped parent-child trios from the Norwegian Mother, Father and Child Cohort (MoBa) study. We found evidence suggesting that parents’ educational attainment affects their children’s educational outcomes from age 5 to 14. More studies are needed to provide more samples of parent-child trios and assess the potential consequences of selection bias and grandparental effects.

Background A joint, hierarchical structure of psychopathology and personality has been reported in adults but should also be investigated at earlier ages, as psychopathology often develops before adulthood. Here, we investigate the joint factor structure of psychopathology and personality in eight-year-old children, estimate factor heritability and explore external validity through associations with established developmental risk factors. Methods Phenotypic and biometric exploratory factor analyses with bifactor rotation on genetically informative data from the Norwegian Mother, Father, and Child Cohort (MoBa) study. The analytic sub-sample comprised 10 739 children (49% girls). Mothers reported their children's symptoms of depression (Short Moods and Feelings Questionnaire), anxiety (Screen for Anxiety Related Disorders), attention-deficit/hyperactivity disorder inattention and hyperactivity, oppositional-defiant disorder, conduct disorder (Parent/Teacher Rating Scale for Disruptive Behavior Disorders), and Big Five personality (short Hierarchical Personality Inventory for Children). Developmental risk factors (early gestational age and being small for gestational age) were collected from the Medical Birth Registry. Results Goodness-of-fit indices favored a p factor model with three residual latent factors interpreted as negative affectivity, positive affectivity, and antagonism, whereas psychometric indices favored a one-factor model. ADE solutions fitted best, and regression analyses indicated a negative association between gestational age and the p factor, for both the one- and four-factor solutions. Conclusion Correlations between normative and pathological traits in middle childhood mostly reflect one heritable and psychometrically interpretable p factor, although optimal fit to data required less interpretable residual latent factors. The association between the p factor and low gestational age warrants further study of early developmental mechanisms.

This study investigates associations between personality traits at age eight and academic performance between ages 10 to 14, controlling for family confounds. Sibling data from the Norwegian Mother and Child Cohort Study (MoBa) were used (n = 9,701). First, we estimated overall associations between Big Five personality traits and academic performance, including literacy, numeracy, and foreign language. Second, we added sibling fixed effects to remove unmeasured confounders shared by siblings as well as rating bias. Openness to Experience (between-person β=0.22 [95% CI 0.21 - 0.24]) and Conscientiousness (between-person β=0.18 [95% CI 0.16 - 0.20]) were most strongly related to educational performance. Agreeableness (between-person β=0.06 [95% CI -0.08 - 0.04]) and Extraversion (between-person β=0.02 [95% CI 0.00 - 0.04]) showed small associations with educational performance. Neuroticism had a moderate negative association (between-person beta=-0.14 [95% CI -0.15 - 0.11]). All associations between personality and performance were robust to confounding: the within-family estimates from sibling fixed effects models overlapped with the between-person effects. Finally, childhood personality was equally predictive of educational performance across ages and genders. Although family background is influential for academic achievement, it does not confound associations with personality. Childhood personality traits reflect unbiased and consistent individual differences in educational potential.

Distinguishing between the effects of nature and nurture constitutes a major research goal for those interested in understanding human development. It is known, for example, that many parent traits predict mental health outcomes in children, but the causal processes underlying such associations are often unclear. Family-based quasi-experimental designs such as sibling comparison, adoption and extended family studies have been used for decades to distinguish the genetic transmission of risk from the environmental effects family members potentially have on one another. Recently, these designs have been combined with genomic data, and this combination is fuelling a range of exciting methodological advances. In this review we explore these advances - highlighting the ways in which they have been applied to date and considering what they are likely to teach us in the coming years about the aetiology and intergenerational transmission of psychopathology.

A child’s environment is thought to be composed of different levels that interact with individual genetic propensities, with less advantaged environments suppressing genetic effects on achievement. However, studies have not tested this theory comprehensively across multiple environmental levels. Here, we quantify the contributions of child, parent, school, neighbourhood, district, and municipality factors to achievement, and investigate interactions between polygenic scores for educational attainment (EA-PGS) and environmental levels. We link population-wide administrative data on children’s standardised test results, schools and residential identifiers to the Norwegian Mother, Father and Child Cohort Study (MoBa), which includes >23,000 genotyped parent-child trios. We test for gene-environment interactions using multilevel models with interactions between EA-PGS and random effects for school and residential environments (thus remaining agnostic to specific features of environments) and use parent EA-PGS to control for gene-environment correlation. Our within-family results suggest that students’ EA-PGS interact with schools but not residential environments (neighbourhoods, districts, and municipalities), which explain negligible variance. Students’ EA-PGS explain four times the variance in achievement in the 2.5% of schools where EA-PGS associations are strongest as in the 2.5% where effects are weakest. Contrary to theory, PGS effects are stronger in less advantaged environments (lower-performing schools). None of the school sociodemographic measures we tested could explain the interaction. Schools make a greater difference to the achievements of students with lower EA-PGS, explaining 4% of the variance for students 2SD below the mean PGS, but 2% for students 2SD above the mean. Policy to reduce social inequality in achievement in Norway should focus on tackling unequal support across schools for children with difficulties, and not on differences between residential areas.

Background Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of methods that use large samples of (unrelated or related) genotyped individuals. Methods Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability, i.e. the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals [linkage disequilibrium score regression, genomic relatedness restricted maximum-likelihood (GREML) estimation] and family-based genomic designs (sibling regression, GREML-kinship, trio-genome-wide complex trait analysis, maternal-genome-wide complex trait analysis, relatedness disequilibrium regression). Results We describe how heritability is estimated for each method and the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared with samples of related individuals. Conclusions Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why.

Background: Theoretical models of the development of childhood externalizing disorders emphasize the role of parents. Empirical studies have not been able to identify specific aspects of parental behaviors explaining a considerable proportion of the observed individual differences in externalizing problems. The problem is complicated by the contribution of genetic factors to externalizing problems, as parents provide both genes and environments to their children. We studied the joint contributions of direct genetic effects of children and the indirect genetic effects of parents through the environment on externalizing problems. Methods: The study used genome-wide single nucleotide polymorphism data from 9,675 parent–offspring trios participating in the Norwegian Mother Father and child cohort study. Based on genomic relatedness matrices, we estimated the contribution of direct genetic effects and indirect maternal and paternal genetic effects on ADHD, conduct and disruptive behaviors at 8 years of age. Results: Models including indirect parental genetic effects were preferred for the ADHD symptoms of inattention and hyperactivity, and conduct problems, but not oppositional defiant behaviors. Direct genetic effects accounted for 11% to 24% of the variance, whereas indirect parental genetic effects accounted for 0% to 16% in ADHD symptoms and conduct problems. The correlation between direct and indirect genetic effects, or gene–environment correlations, decreased the variance with 16% and 13% for conduct and inattention problems, and increased the variance with 6% for hyperactivity problems. Conclusions: This study provides empirical support to the notion that parents have a significant role in the development of childhood externalizing behaviors. The parental contribution to decrease in variation of inattention and conduct problems by gene–environment correlations would limit the number of children reaching clinical ranges in symptoms. Not accounting for indirect parental genetic effects can lead to both positive and negative bias when identifying genetic variants for childhood externalizing behaviors. publishedVersion