The latent causal variable (LCV) model is based on a latent variable L that mediates the genetic correlation between the two traits (Figure 1a). Under the LCV model, trait 1 is fully genetically causal for trait 2 if it is perfectly genetically correlated with L; ``fully" means that the entire genetic component of trait 1 is causal for trait 2 (Figure 1b). More generally, trait 1 is partially genetically causal for trait 2 if the latent variable has a stronger genetic correlation with trait 1 than with trait 2; ``partially" means that part of the genetic component of trait 1 is causal for trait 2. In order to quantify partial causality, we define the genetic causality proportion (gcp) of trait 1 on trait 2. The gcp ranges between 0 (no partial genetic causality) and 1 (full genetic causality). A high value of gcp (even if it is not exactly 1) implies that interventions targeting trait 1 are likely to affect trait 2. An intermediate value implies that some interventions targeting trait 1 may affect trait 2. (However, we caution that
