Phantom genetic nurture: assortative mating accounts for most of the apparent association between parental genotypes and childhood cognitive performance

Authors

Malawsky, D. S., Hegemann, L., Wootton, O., Havdahl, A. K., Sunde, H. F., Martin, H. C.

Abstract

Parental genotypes may influence offspring outcomes through the environments parents provide, a process known as genetic nurture, but estimating such effects from polygenic scores is complicated jointly by measurement error, unobserved genetic variation, and assortative mating. Here, we introduce RAVEL, a structural equation modeling framework that uses two independently constructed polygenic scores for the same trait to estimate latent genetic liability associations in parent-offspring trios and to distinguish direct and non-transmitted genetic associations. Through analytic derivations and simulations, we show that naive trio regressions can produce spurious non-zero parental coefficients, attenuate genuine genetic nurture effects, and obscure asymmetric parental effects, whereas RAVEL recovers unbiased estimates of the underlying coefficients when the assortative mating history and the extent of unobserved genetic variation are correctly specified. Applying RAVEL to national test scores in the Norwegian Mother, Father and Child Cohort Study using polygenic scores for educational attainment, we find that parental genetic liabilities explain less than 0.5% as much variance in childhood cognitive performance as the child's own genetic liability (substantially lower than the 10% observed with naive trio regressions) once assortative mating is modeled, with only a small paternal association significantly surviving the correction. In contrast, we find a maternal-specific non-transmitted association with offspring premature birth. RAVEL provides a general framework for interpreting trio polygenic score analyses of direct and non-transmitted genetic effects, clarifying the contribution of parental genetic liabilities to offspring traits.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 07 Sep 2026.

Stats

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.