Estimating effects of parents’ cognitive and non-cognitive skills on offspring education using polygenic scores

Demange, Perline; Hottenga, Jouke Jan; Abdellaoui, Abdel; Eilertsen, Espen Moen; Malanchini, Margherita; Domingue, Benjamin W.; Zeeuw, Eveline L. de; Rimfeld, Kaili; Eley, Thalia C.; Boomsma, Dorret I.; Bergen, Elsje van; Breen, Gerome; Nivard, Michel G.; Cheesman, Rosa

doi:10.1101/2020.09.15.296236

Cited by 23 publications

(22 citation statements)

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“…To quantify the variance explained by passive geneenvironment correlation and by active and reactive gene-environment correlation combined, we simul taneously investigated betweensibling and betweenfamily effects of PGS (base sample GWAS childhoodmaltreatment ) 58,59 in a holdout sample of 12 855 individuals from the UK Biobank (including 2849 sibling pairs, target sample; appendix pp 15-19), using a mixedeffects regression model with the following equation:…”

Section: Contribution Of Different Mechanisms To Childhood Maltreatmentmentioning

confidence: 99%

Gene–environment correlations and causal effects of childhood maltreatment on physical and mental health: a genetically informed approach

Warrier

Kwong

Luo

et al. 2021

The Lancet Psychiatry

129

140

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Background Childhood maltreatment is associated with poor mental and physical health. However, the mechanisms of gene-environment correlations and the potential causal effects of childhood maltreatment on health are unknown. Using genetics, we aimed to delineate the sources of gene-environment correlation for childhood maltreatment and the causal relationship between childhood maltreatment and health. MethodsWe did a genome-wide association study meta-analysis of childhood maltreatment using data from the UK Biobank (n=143 473), Psychiatric Genomics Consortium (n=26 290), Avon Longitudinal Study of Parents and Children (n=8346), Adolescent Brain Cognitive Development Study (n=5400), and Generation R (n=1905). We included individuals who had phenotypic and genetic data available. We investigated single nucleotide polymorphism heritability and genetic correlations among different subtypes, operationalisations, and reports of childhood maltreatment. Family-based and population-based polygenic score analyses were done to elucidate gene-environment correlation mechanisms. We used genetic correlation and Mendelian randomisation analyses to identify shared genetics and test causal relationships between childhood maltreatment and mental and physical health conditions.Findings Our meta-analysis of genome-wide association studies (N=185 414) identified 14 independent loci associated with childhood maltreatment (13 novel). We identified high genetic overlap (genetic correlations 0•24-1•00) among different maltreatment operationalisations, subtypes, and reporting methods. Within-family analyses provided some support for active and reactive gene-environment correlation but did not show the absence of passive geneenvironment correlation. Robust Mendelian randomisation suggested a potential causal role of childhood maltreatment in depression (unidirectional), as well as both schizophrenia and ADHD (bidirectional), but not in physical health conditions (coronary artery disease, type 2 diabetes) or inflammation (C-reactive protein concentration).Interpretation Childhood maltreatment has a heritable component, with substantial genetic correlations among different operationalisations, subtypes, and retrospective and prospective reports of childhood maltreatment. Familybased analyses point to a role of active and reactive gene-environment correlation, with equivocal support for passive correlation. Mendelian randomisation supports a (primarily bidirectional) causal role of childhood maltreatment on mental health, but not on physical health conditions. Our study identifies research avenues to inform the prevention of childhood maltreatment and its long-term effects.

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Section: Contribution Of Different Mechanisms To Childhood Maltreatmentmentioning

confidence: 99%

Gene–environment correlations and causal effects of childhood maltreatment on physical and mental health: a genetically informed approach

Warrier

Kwong

Luo

et al. 2021

The Lancet Psychiatry

129

140

View full text Add to dashboard Cite

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“…Population stratification was controlled for by using principal component analysis in most studies included in the meta-analysis but residual population stratification may still exist. Emerging methods should, in future, better account for remaining biases for example by capitalizing further on family-based designs (Balbona, Kim, & Keller, 2020; Demange et al, 2020; Young et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Conversely, the nurturing behaviours from parents may impact offspring more at earlier ages, as they spend more time at home rather than school, spend more time with their parents rather than peers, which might lead to genetic nurture effects decreasing with age. Moreover, genetic nurture may act distinctively over time through different pathways as suggested by a recent study showing parent non-cognitive but not cognitive related characteristics were more important for educational achievement at age 16 than age 12 (Demange et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

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Genetic nurture effects on education: a systematic review and meta-analysis

Wang

2021

Preprint

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Child educational development is associated with major psychological, social, economic and health milestones throughout the life course. Understanding the early origins of educational inequalities and their reproduction across generations is therefore crucial. Recent genomic studies provide novel insights in this regard, uncovering “genetic nurture” effects, whereby parental genotypes influence offspring’s educational development via environmental pathways rather than genetic transmission. These findings have yet to be systematically appraised. We conducted the first systematic review and meta-analysis to quantify genetic nurture effects on educational outcomes and investigate key moderators. Twelve studies comprising 38,654 distinct parent(s)-offspring pairs or trios from eight cohorts were included, from which we derived 22 estimates of genetic nurture effects. Multilevel random effects models showed that the effect of genetic nurture on offspring’s educational outcomes (βgenetic nurture = 0.08, 95% CI [0.07, 0.09]) was about half the size of direct genetic effects (βdirect genetic = 0.17, 95% CI [0.13, 0.20]). Maternal and paternal genetic nurture effects were similar in magnitude, suggesting comparable roles of mothers and fathers in determining their children’s educational outcomes. Genetic nurture effects were largely explained by parental educational level and family socioeconomic status, suggesting that genetically influenced environments play an important role in shaping child educational outcomes. Even after accounting for genetic transmission, we provide evidence that environmentally mediated parental genetic influences contribute to the intergenerational transmission of educational outcomes. Further exploring these downstream environmental pathways may inform educational policies aiming to break the intergenerational cycle of educational underachievement and foster social mobility.Public Significance StatementThis meta-analysis demonstrates that parents’ genetics influence their children’s educational outcomes through the rearing environments that parents provide. This “genetic nurture” effect is largely explained by family socioeconomic status and parental education level, is similar for mothers and fathers (suggesting that both parents equally shape their children’s educational outcomes) and is about half the size of direct genetic effects on children’s educational outcomes. Interventions targeting such environmental pathways could help to break the intergenerational cycle of educational underachievement and foster social mobility.

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“…inattention (InA) and hyperactivity (HA). These types of questions of a best genetic predictor of an outcome trait or disease may come up in multiple contexts, such as the prediction of educational attainment by cognitive ability and non-cognitive skills (Demange et al 2020 ) or hypertension and cardiovascular outcomes by multiple correlated factors (Lucaroni et al 2019 ).…”

Section: Discussionmentioning

confidence: 99%

Genetically Informed Regression Analysis: Application to Aggression Prediction by Inattention and Hyperactivity in Children and Adults

et al. 2020

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We present a procedure to simultaneously fit a genetic covariance structure model and a regression model to multivariate data from mono- and dizygotic twin pairs to test for the prediction of a dependent trait by multiple correlated predictors. We applied the model to aggressive behavior as an outcome trait and investigated the prediction of aggression from inattention (InA) and hyperactivity (HA) in two age groups. Predictions were examined in twins with an average age of 10 years (11,345 pairs), and in adult twins with an average age of 30 years (7433 pairs). All phenotypes were assessed by the same, but age-appropriate, instruments in children and adults. Because of the different genetic architecture of aggression, InA and HA, a model was fitted to these data that specified additive and non-additive genetic factors (A and D) plus common and unique environmental (C and E) influences. Given appropriate identifying constraints, this ADCE model is identified in trivariate data. We obtained different results for the prediction of aggression in children, where HA was the more important predictor, and in adults, where InA was the more important predictor. In children, about 36% of the total aggression variance was explained by the genetic and environmental components of HA and InA. Most of this was explained by the genetic components of HA and InA, i.e., 29.7%, with 22.6% due to the genetic component of HA. In adults, about 21% of the aggression variance was explained. Most was this was again explained by the genetic components of InA and HA (16.2%), with 8.6% due to the genetic component of InA.

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Estimating effects of parents’ cognitive and non-cognitive skills on offspring education using polygenic scores

Cited by 23 publications

References 71 publications

Gene–environment correlations and causal effects of childhood maltreatment on physical and mental health: a genetically informed approach

Gene–environment correlations and causal effects of childhood maltreatment on physical and mental health: a genetically informed approach

Genetic nurture effects on education: a systematic review and meta-analysis

Genetically Informed Regression Analysis: Application to Aggression Prediction by Inattention and Hyperactivity in Children and Adults

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