Intermediate confounding in trio relationships: The importance of complete data in effect size estimation

Tubbs, Justin D.; Zhang, Yan Dora; Sham, Pak C.

doi:10.1002/gepi.22294

Cited by 16 publications

(16 citation statements)

References 14 publications

(18 reference statements)

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“…Second, the magnitude of genetic nurture effects was slightly smaller in the virtual parent design versus the statistical control approach. A recent study has shown the importance of using complete trio data, as missing the genotype of one parent can bias direct genetic effects and genetic nurture effects (Tubbs, Zhang, & Sham, 2020). Evidence from one of the included studies (T. Morris et al, 2020) using both partial and full statistical control approach echoed this view.…”

Section: Discussionmentioning

confidence: 99%

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: Discussionmentioning

confidence: 99%

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

Wang

2021

Preprint

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“…Due to the correlation between parental and offspring genotypes, GWAS captures both the direct and indirect genetic effects in its estimates, which further complicates the interpretation of GWAS results (13). If the genetic nurture effect (i.e., parental genotypes affecting offspring phenotype) is present for a given trait, downstream analyses based on GWAS associations could be biased and misleading (6,8,27).…”

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confidence: 99%

Estimating genetic nurture with summary statistics of multigenerational genome-wide association studies

Zhong

Lin

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Marginal effect estimates in genome-wide association studies (GWAS) are mixtures of direct and indirect genetic effects. Existing methods to dissect these effects require family-based, individual-level genetic, and phenotypic data with large samples, which is difficult to obtain in practice. Here, we propose a statistical framework to estimate direct and indirect genetic effects using summary statistics from GWAS conducted on own and offspring phenotypes. Applied to birth weight, our method showed nearly identical results with those obtained using individual-level data. We also decomposed direct and indirect genetic effects of educational attainment (EA), which showed distinct patterns of genetic correlations with 45 complex traits. The known genetic correlations between EA and higher height, lower body mass index, less-active smoking behavior, and better health outcomes were mostly explained by the indirect genetic component of EA. In contrast, the consistently identified genetic correlation of autism spectrum disorder (ASD) with higher EA resides in the direct genetic component. A polygenic transmission disequilibrium test showed a significant overtransmission of the direct component of EA from healthy parents to ASD probands. Taken together, we demonstrate that traditional GWAS approaches, in conjunction with offspring phenotypic data collection in existing cohorts, could greatly benefit studies on genetic nurture and shed important light on the interpretation of genetic associations for human complex traits.

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“…For example, bias amplification has already been recognized in the propensity score literature [12, 13], where the inclusion of instrumental variables (Z) in a propensity score in the presence of unmeasured confounding leads to bias amplification (sometimes referred to as Z-bias [15, 20]). Furthermore, bias amplification is the same phenomenon that leads to bias in within-family/trio mendelian randomization when one parent’s genotypes are omitted [26]. It is also bias amplification that gives rise to inflation of non-shared confounding in sibling analyses [16, 27].…”

Section: Discussionmentioning

confidence: 99%

Bias amplification of unobserved confounding in pharmacoepidemiological studies using indication-based sampling: there is no free lunch in restricting the sample to those with a particular drug-indication

Ahlqvist

Madley‐Dowd

et al. 2022

Preprint

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Estimating causal effects in observational pharmacoepidemiology is a challenging task, as it is often plagued by confounding by indication. Restricting the sample to those with an indication for drug use is a commonly performed procedure; indication-based sampling ensures that the exposed and unexposed are exchangeable on the indication - limiting the potential for confounding by indication. However, indication-based sampling has received little scrutiny, despite the hazards of exposure-related covariate control. Using causal diagrams, simulations, and empirical examples, we demonstrate that indication-based sampling in the presence of unobserved confounding can give rise to bias amplification, a self-inflicted phenomenon where one inflates pre-existing bias through inappropriate covariate control. Additionally, we show that indication-based sampling generally leads to a greater net bias than alternative approaches, such as regression adjustment. Finally, we expand on how bias amplification should be reasoned about when distinct clinically relevant effects on the outcome among those with an indication (effect-heterogeneity) exist. We conclude that studies using indication-based sampling should have robust justification - and that it should by no means be considered a 'free lunch' to adopt such approaches. As such, we suggest that future observational studies stay wary of bias amplification when considering drug indications.

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Intermediate confounding in trio relationships: The importance of complete data in effect size estimation

Cited by 16 publications

References 14 publications

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

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

Estimating genetic nurture with summary statistics of multigenerational genome-wide association studies

Bias amplification of unobserved confounding in pharmacoepidemiological studies using indication-based sampling: there is no free lunch in restricting the sample to those with a particular drug-indication

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