Datasets comprising twins and their children can be a useful tool for those interested in understanding the nature of intergenerational associations between parent and offspring phenotypes. For example, by using such data it is possible to ask whether parent-child associations can be explained via genetic transmission, and/or whether associations remain significant after accounting for genetic relatedness between parent and child. By applying structural equation models (SEMs) to children-of-twins (CoT) data, it is possible to quantify the relative importance of genetic vs. non-genetic (social) pathways.
In the past, extensions of this model were presented which include bidirectional effects between parent and child phenotypes (i.e. parent-to-child vs. child-to-parent effects). This was accomplished by simultaneously modelling CoT data with children-as-twins-with parent data on the same phenotypes. This extended two-sample model (ECoT, Narusyte et al. 2008)) is an adaptation of the bidirectional models first suggested by Heath et al. (1993), and explored more recently by Olivares et al. (2016). The purpose is to use cross-sectional twin/family data to ask questions about the direction of causation between two phenotypes.
The ECoT model proved to have some shortcomings. In this talk I will explore the SEMs that have been used to analyse ECoT data, highlighting some of the limitations that these models have, and how they can, to a certain extent, be solved by using an extension including multiple offspring per parent in the CoT design. I will demonstrate the power and utility of these models using simulated data and real data from the Intergenerational Transmission of Risk Project (a subsample of the Norwegian Mother and Child Cohort Study).
References
Narusyte J., Neiderhiser J.M., D’Onofrio B.M., Reiss D., Spotts E.L., Ganiban J., & Lichtenstein P. (2008). Testing different types of genotype-environment correlation.. Developmental Psychology, 44, 1591–1603.
Heath A.C., Kessler R. C. , Neale M. C. , Hewitt J. K. , Eaves L. J. & Kendler K. S. (1993). Testing hypotheses about Direction of Causation.. Behavior Genetics, 23(1), 29-50.
Olivares E.L., Kendler K.S., Neale M.C., Gillespie N.A. (2016). The genetic and environmental association between parental monitoring and risk of cannabis.. Twin Research and Human Genetics, 19(4), 297–305.
Statistical Methods , Psychopathology (e.g., Internalizing, Externalizing, Psychosis)
