Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores

Trejo, Sam; Domingue, Benjamin W.

doi:10.1101/524850

Cited by 20 publications

(18 citation statements)

References 49 publications

(55 reference statements)

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“…For example, prediction of trait differences between embryos relies on genetic variation within a family, where only direct genetic effects are relevant. If direct genetic effects are not highly correlated with population effect estimates, then embryo selection based on population effect estimates will perform poorly relative to using direct effects 24 . Other implications may depend upon the source of the bias in population effect estimates.…”

Section: Discussionmentioning

confidence: 99%

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Mendelian imputation of parental genotypes for genome-wide estimation of direct and indirect genetic effects

Young

Nehzati

Lee

et al. 2020

Preprint

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AbstractAssociations between genotype and phenotype derive from four sources: direct genetic effects, indirect genetic effects from relatives, population stratification, and correlations with other variants affecting the phenotype through assortative mating. Genome-wide association studies (GWAS) of unrelated individuals have limited ability to distinguish the different sources of genotype-phenotype association, confusing interpretation of results and potentially leading to bias when those results are applied – in genetic prediction of traits, for example. With genetic data on families, the randomisation of genetic material during meiosis can be used to distinguish direct genetic effects from other sources of genotype-phenotype association. Genetic data on siblings is the most common form of genetic data on close relatives. We develop a method that takes advantage of identity-by-descent sharing between siblings to impute missing parental genotypes. Compared to no imputation, this increases the effective sample size for estimation of direct genetic effects and indirect parental effects by up to one third and one half respectively. We develop a related method for imputing missing parental genotypes when a parent-offspring pair is observed. We provide the imputation methods in a software package, SNIPar (single nucleotide imputation of parents), that also estimates genome-wide direct and indirect effects of SNPs. We apply this to a sample of 45,826 White British individuals in the UK Biobank who have at least one genotyped first degree relative. We estimate direct and indirect genetic effects for ∼5 million genome-wide SNPs for five traits. We estimate the correlation between direct genetic effects and effects estimated by standard GWAS to be 0.61 (S.E. 0.09) for years of education, 0.68 (S.E. 0.10) for neuroticism, 0.72 (S.E. 0.09) for smoking initiation, 0.87 (S.E. 0.04) for BMI, and 0.96 (S.E. 0.01) for height. These results suggest that GWAS based on unrelated individuals provides an inaccurate picture of direct genetic effects for certain human traits.

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Section: Discussionmentioning

confidence: 99%

“…In expectation, this should give the same estimated parental effects as using observed parental genotypes (Supplementary Note). The correlation between direct and population effects, 24 , is equal to…”

Section: Simulations In Uk Biobankmentioning

confidence: 99%

Mendelian imputation of parental genotypes for genome-wide estimation of direct and indirect genetic effects

Young

Nehzati

Lee

et al. 2020

Preprint

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“…Indeed, a more recent study found that using the latest GPS for educational attainment, there was an attenuation of ∼55% in the prediction of years of schooling within families in comparison to between-family estimates. 29 …”

Section: Introductionmentioning

confidence: 99%

Comparing Within- and Between-Family Polygenic Score Prediction

Selzam

Ritchie

Pingault

et al. 2019

The American Journal of Human Genetics

222

238

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Polygenic scores are a popular tool for prediction of complex traits. However, prediction estimates in samples of unrelated participants can include effects of population stratification, assortative mating, and environmentally mediated parental genetic effects, a form of genotype-environment correlation (rGE). Comparing genome-wide polygenic score (GPS) predictions in unrelated individuals with predictions between siblings in a within-family design is a powerful approach to identify these different sources of prediction. Here, we compared within-to between-family GPS predictions of eight outcomes (anthropometric, cognitive, personality, and health) for eight corresponding GPSs. The outcomes were assessed in up to 2,366 dizygotic (DZ) twin pairs from the Twins Early Development Study from age 12 to age 21. To account for family clustering, we used mixed-effects modeling, simultaneously estimating within-and between-family effects for target-and cross-trait GPS prediction of the outcomes. There were three main findings: (1) DZ twin GPS differences predicted DZ differences in height, BMI, intelligence, educational achievement, and ADHD symptoms; (2) target and cross-trait analyses indicated that GPS prediction estimates for cognitive traits (intelligence and educational achievement) were on average 60% greater between families than within families, but this was not the case for non-cognitive traits; and (3) much of this within-and between-family difference for cognitive traits disappeared after controlling for family socioeconomic status (SES), suggesting that SES is a major source of between-family prediction through rGE mechanisms. These results provide insights into the patterns by which rGE contributes to GPS prediction, while ruling out confounding due to population stratification and assortative mating.

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“…Although we used appropriate statistical methods and conducted the analyses across multiple independent cohorts, findings related to genetic data associated with these phenotypes need to be interpreted cautiously. 58 , 60 The results of our current analysis are also limited by the statistical power of the PTSD GWAS data sets, which may have limited our ability to observe the reverse association of PTSD with EA. However, we used multiple methods that showed significant associations when applied to similarly powered GWAS data sets.…”

Section: Discussionmentioning

confidence: 94%

“…Additionally, income may reflect indirect effects, such as those induced by genetic nurture on EA. 57 , 58 Socioeconomic factors might also be associated with the outcome of PTSD, given that individuals with poorer outcomes are more likely to be included in studies of prevalent cases.…”

Section: Discussionmentioning

confidence: 99%

Association of Economic Status and Educational Attainment With Posttraumatic Stress Disorder

et al. 2019

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IMPORTANCE There is a well-established negative association of educational attainment (EA) and other traits related to cognitive ability with posttraumatic stress disorder (PTSD), but the underlying mechanisms are poorly understood. OBJECTIVES To investigate the association of PTSD with traits related to EA. DESIGN, SETTING, AND PARTICIPANTS Genetic correlation, polygenic risk scoring, and mendelian randomization (MR) were conducted including 23 185 individuals with PTSD and 151 309 control participants from the Psychiatric Genomics Consortium for PTSD and up to 1 131 881 individuals assessed for EA and related traits from UK Biobank, 23andMe, and the Social Science Genetic Association Consortium. Data were analyzed from July 3 through November 19, 2018. MAIN OUTCOMES AND MEASURES Genetic correlation obtained from linkage disequilibrium score regression, phenotypic variance explained by polygenic risk scores, and association estimates from MR. RESULTS Summary association data from multiple genome-wide association studies were available for a total of 1 180 352 participants (634 391 [53.7%] women). Posttraumatic stress disorder showed negative genetic correlations with EA (r g = −0.26; SE = 0.05; P = 4.60 × 10 −8). Mendelian randomization analysis, conducting considering a random-effects inverse-variance weighted method, indicated that EA has a negative association with PTSD (β = −0.23; 95% CI, −0.07 to −0.39; P = .004). Investigating potential mediators of the EA-PTSD association, propensity for trauma exposure and risk-taking behaviors were observed as risk factors for PTSD independent of EA

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Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores

Cited by 20 publications

References 49 publications

Mendelian imputation of parental genotypes for genome-wide estimation of direct and indirect genetic effects

Mendelian imputation of parental genotypes for genome-wide estimation of direct and indirect genetic effects

Comparing Within- and Between-Family Polygenic Score Prediction

Association of Economic Status and Educational Attainment With Posttraumatic Stress Disorder

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