Yes, but it's not dramatically different from what is out there already.

There is a concerning gap between prediction and causality. In problems, like this one, where lots of variables are highly correlated, prediction methods that only have an implicit notion of causality don't perform well.

Right now, SOTA seems to use huge population data to infer causality within each linkage block of interest in the genome. These types of methods are quite close to Pearl's notion of causal graphs.