Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts

Silventoinen, Karri; Jelenkovic, Aline; Sund, Reijo; Latvala, Antti; Honda, Chika; Inui, Fujio; Tomizawa, Rie; Watanabe, Mikio; Sakai, Norio; Rebato, Esther; Busjahn, Andreas; Tyler, Jessica; Hopper, John L.; Ordoñana, Juan R.; Sánchez-Romera, Juan F.; Colodro‐Conde, Lucía; Calais-Ferreira, Lucas; Oliveira, Vinícius Cunha; Ferreira, Paulo H.; Medda, Emanuela; Nisticò, Lorenza; Toccaceli, Virgilia; Derom, Cathérine; Vlietinck, Robert; Loos, Ruth J.F.; Siribaddana, Sisira; Hotopf, Matthew; Sumathipala, Athula; Rijsdijk, Frühling; Duncan, Glen E.; Buchwald, Dedra; Tynelius, Per; Rasmussen, Finn; Tan, Qihua; Zhang, Dongfeng; Pang, Zengchang; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Aslan, Anna K. Dahl; Hwang, Amie E.; Mack, Thomas M.; Krueger, Robert F.; McGue, Matt; Pahlen, Shandell; Brandt, Ingunn; Nilsen, Thomas Sevenius; Harris, Jennifer R.; Martin, Nicholas G.; Medland, Sarah E.; Montgomery, Grant W.; Willemsen, Gonneke; Bartels, Meike; Beijsterveldt, Catharina E. M. van; Franz, Carol E.; Kremen, William S.; Lyons, Michael J.; Silberg, Judy L.; Maes, Hermine H.; Kandler, Christian; Nelson, Tracy L.; Whitfield, Keith E.; Corley, Robin P.; Huibregtse, Brooke M.; Gatz, Margaret; Butler, David A.; Tárnoki, Ádám Domonkos; Tárnoki, Dávid László; Park, Hang A; Lee, Joo-Yeon; Lee, Soo Ji; Sung, Joohon; Yokoyama, Yoshie; Sørensen, Thorkild I A; Boomsma, Dorret I.; Kaprio, Jaakko

doi:10.1038/s41598-020-69526-6

Cited by 97 publications

(90 citation statements)

References 38 publications

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“…For direct genetic effects, estimates for educational achievement were significantly larger than attainment. This finding agrees with previous twin evidence, which suggested ~60% heritability for educational achievement measured in childhood and adolescence (Rimfeld et al, 2018) and ~40% for educational attainment measured in adulthood (Branigan, McCallum, & Freese, 2013; Silventoinen et al, 2020). Some plausible explanations of such higher heritability/direct genetic effects for educational achievement are discussed in the supplement (section 7.5).…”

Section: Discussionsupporting

confidence: 93%

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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Section: Discussionsupporting

confidence: 93%

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

Wang

2021

Preprint

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“…Overestimating heritability would lead to overestimating genetic confounding and thus underestimating the residual association between exposure and outcome. For example, a recent study of 193,518 twins across 16 countries has showed that educational attainment is 43% heritable [24]. As can be seen in Figure 1, this lower estimate would lead to a substantially larger adjusted association.…”

Section: Discussionmentioning

confidence: 99%

Genetic sensitivity analysis: adjusting for genetic confounding in epidemiological associations

Pingault

Rijsdijk

Schoeler

et al. 2019

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Objective. Countless associations between risk factors and outcomes are reported in epidemiological research, but often without estimating the contribution from genetics. However most outcomes and risk factors are substantially heritable, and genetic influences can confound these associations. Here we propose a two-stage approach for evaluating the role of shared genetic effects in explaining these observed associations.Method. Genotyped unrelated participants from the Twins Early Development Study are included (N from 3,663 to 4,693 depending on the outcome) in our analyses. As an example for our proposed approach, we focus on maternal educational attainment, a risk factor known to associate with a variety of offspring social and health outcomes, including child educational achievement, Body Mass Index, and Attention Deficit Hyperactivity Disorders (ADHD). In the first stage of our approach we estimate how much of the phenotypic associations between maternal education and child outcomes can be attributed to shared genetic effects via regressions controlling for increasingly powerful polygenic scores. In the second stage, we estimate shared genetic effects using heritability estimates and genetic correlations equal to those derived in both SNP-based and twin-based studies. Finally, evidence from the two stages are evaluated in conjunction to provide an overall assessment of the likelihood that the association is explained by genetics.Results. Associations between maternal education and the three developmental outcomes are highly significant. The magnitude of these associations decrease when using polygenic scores to account for shared genetic effects, explaining between 14.3% and 24.3% of the original associations. For the three outcomes, the magnitude of these associations further decrease under a SNP-based heritability scenario and are almost entirely or entirely explained by genetics under a twin-based heritability scenario. Conclusions. Observed association between maternal education and child educational attainment, BMIand ADHD symptoms may be largely explained by genetics. To the extent that available estimates of SNP-based and twin-based heritabilities are accurate, the present findings represent a call for caution Genetic confounding 3 when interpreting non-genetically informed epidemiology studies of the role of maternal education or other 'environmental' risk factors. The two-stage approach that we propose adds a new tool to probe the robustness of findings regarding the role of a range of risk factors. Our approach, akin to a genetically informed sensitivity analysis, only requires a genotyped cohort with adequate phenotypic measurements, and has the potential to be widely applied across the life and social sciences.Genetic confounding 4

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“…This indicates that observed shrinkage is likely to be largely driven by assortative mating or indirect genetic effects since both of these tend to influence associations proportional to the direct effect (whereas population stratification is likely to have larger effects on ancestrally informative markers). The common environment terms from classical twin studies suggest that there are likely to be indirect genetic effects on educational attainment [41], cognitive ability [42] and smoking [43], but suggest that the observed shrinkage for height is likely to be a consequence of assortative mating [10, 43, 44].…”

Section: Discussionmentioning

confidence: 99%

Within-sibship GWAS improve estimates of direct genetic effects

Howe¹,

Nivard²,

Morris³

et al. 2021

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Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.

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Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts

Cited by 97 publications

References 38 publications

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

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

Genetic sensitivity analysis: adjusting for genetic confounding in epidemiological associations

Within-sibship GWAS improve estimates of direct genetic effects

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