In summary, modeling the first PC of measured confounders as a covariate recovers the PRS effect size estimate under reasonable assumptions about the proportion of the confounding data that is measured and the correlation structure of the confounding data. These assumptions are complementary, such that meeting one assumption more robustly relaxes the other assumption. Required assumptions become stricter as rGE (and the magnitude of bias) increases.
