Estimation of Direct and Indirect Polygenic Effects and Gene-Environment Interactions using Polygenic Scores in Case-Parent Trio Studies

Music City Center 

Family-based studies provide a unique opportunity to characterize genetic risks of diseases in the presence of population structure, assortative mating, and indirect genetic effects. We propose a likelihood-based method, PGS-TRI, for the analysis of polygenic scores (PGS) in case-parent trio studies for estimation of the risk of an index condition associated with direct effects of inherited PGS, indirect effects of parental PGS, and gene-environment interactions. We assume the disease risk follows a log-linear model and PGS follows a normal distribution, allowing for family-specific effects in both components to account for arbitrary population structures. We show that likelihood calculations can be simplified into a parental PGS component and a transmission-based likelihood, from which genetic effect estimates can be derived in closed forms. Extensive simulation studies demonstrate the robustness of PGS-TRI in the presence of complex population structure and assortative mating compared to alternative methods. We apply PGS-TRI to multi-ancestry trio studies of autism spectrum disorders and orofacial clefts to establish the first transmission-based estimates of risk associated with pre-defined PGS for these conditions and other related traits. For both conditions, we further explored offspring risk associated with polygenic gene-environment interactions, and direct and indirect effects of genetically predicted levels of gene expression and metabolite traits.