The Indirect Genetic Effect Interaction Coefficient ψ: Theoretically Essential and Empirically Neglected

The interaction effect coefficient psi has been a much-discussed, fundamental parameter of indirect genetic effect (IGE) models since its formal mathematical description in 1997. The coefficient simultaneously describes the form of changes in trait expression caused by genes in the social environment and predicts the evolutionary consequences of those IGEs. Here, we report a striking mismatch between theoretical emphasis on psi and its usage in empirical studies. Surveying all IGE research, we find that the coefficient psi has not been equivalently conceptualized across studies. Several issues related to its proper empirical measurement have recently been raised, and these may severely distort interpretations about the evolutionary consequences of IGEs. We provide practical advice on avoiding such pitfalls. The majority of empirical IGE studies use an alternative variance-partitioning approach rooted in well-established statistical quantitative genetics, but several hundred estimates of psi (from 15 studies) have been published. A significant majority are positive. In addition, IGEs with feedback, that is, involving the same trait in both interacting partners, are far more likely to be positive and of greater magnitude. Although potentially challenging to measure without bias, psi has critically-developed theoretical underpinnings that provide unique advantages for empirical work. We advocate for a shift in perspective for empirical work, from psi as a description of IGEs, to psi as a robust predictor of evolutionary change. Approaches that run evolution forward can take advantage of psi to provide falsifiable predictions about specific trait interactions, providing much-needed insight into the evolutionary consequences of IGEs.

Automated summary

This article highlights the mismatch between the theoretical emphasis and empirical usage of the interaction effect coefficient psi in indirect genetic effect (IGE) models. It discusses the conceptualization and empirical measurement issues related to psi, and advocates for a shift in perspective to view psi as a robust predictor of evolutionary change. The article also emphasizes the potential of psi to provide insight into the evolutionary consequences of IGEs through falsifiable predictions.