This study has two important limitations (additional limitations are discussed in the Supplementary Note). First, the LCV model includes only a single intermediary and can be confounded in the presence of multiple intermediaries. However, the 30 trait pairs with gcp^ > 0.6 are unlikely to be false positives (see Supplementary Note and Supplementary Figure 2). Second, because LCV models only two traits at a time, it cannot be used to identify conditional effects given observed confounders[4,60]. This approach was used, for example, to show that triglycerides affect coronary artery disease risk conditional on LDL[4]. However, it is less essential for LCV to model observed genetic confounders, since LCV explicitly models a latent genetic confounder.
