Using adopted individuals to partition indirect maternal genetic effects into prenatal and postnatal effects on offspring phenotypes

Liang-Dar Hwang; Gunn-Helen Moen; David M Evans

doi:10.7554/eLife.73671

eLife (Jul 2022)

Using adopted individuals to partition indirect maternal genetic effects into prenatal and postnatal effects on offspring phenotypes

Liang-Dar Hwang,
Gunn-Helen Moen,
David M Evans

Affiliations

Liang-Dar Hwang: ORCiD; Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
Gunn-Helen Moen: Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia; The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia; Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
David M Evans: ORCiD; Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia; The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom

DOI: https://doi.org/10.7554/eLife.73671
Journal volume & issue: Vol. 11

Abstract

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Maternal genetic effects can be defined as the effect of a mother’s genotype on the phenotype of her offspring, independent of the offspring’s genotype. Maternal genetic effects can act via the intrauterine environment during pregnancy and/or via the postnatal environment. In this manuscript, we present a simple extension to the basic adoption design that uses structural equation modelling (SEM) to partition maternal genetic effects into prenatal and postnatal effects. We examine the power, utility and type I error rate of our model using simulations and asymptotic power calculations. We apply our model to polygenic scores of educational attainment and birth weight associated variants, in up to 5,178 adopted singletons, 943 trios, 2687 mother-offspring pairs, 712 father-offspring pairs and 347,980 singletons from the UK Biobank. Our results show the expected pattern of maternal genetic effects on offspring birth weight, but unexpectedly large prenatal maternal genetic effects on offspring educational attainment. Sensitivity and simulation analyses suggest this result may be at least partially due to adopted individuals in the UK Biobank being raised by their biological relatives. We show that accurate modelling of these sorts of cryptic relationships is sufficient to bring type I error rate under control and produce asymptotically unbiased estimates of prenatal and postnatal maternal genetic effects. We conclude that there would be considerable value in following up adopted individuals in the UK Biobank to determine whether they were raised by their biological relatives, and if so, to precisely ascertain the nature of these relationships. These adopted individuals could then be incorporated into informative statistical genetics models like the one described in our manuscript to further elucidate the genetic architecture of complex traits and diseases.

Published in eLife

ISSN: 2050-084X (Online)
Publisher: eLife Sciences Publications Ltd
Country of publisher: United Kingdom
LCC subjects: Medicine; Science: Biology (General)
Website: https://elifesciences.org

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