You are misunderstanding what 'variance explained' means. It means 'variance', as in, average differences between individuals; nothing to do with the average ef

You are misunderstanding what 'variance explained' means. It means 'variance', as in, average differences between individuals; nothing to do with the average effect size or possible maxima or anything like that. It refers only to predicting the net effect after, being distributed at population frequencies, most of those hundred variants have canceled each other out. In editing, the population frequencies & distribution don't matter, only the summed effect size of all the variants flipped. Confusing one for the other is like confusing waves on a beach with a tsunami: https://www.gwern.net/Embryo-selection#limits-to-iterated-selection-the-paradox-of-polygenicity https://www.gwern.net/Embryo-selection#limits-to-iterated-se... Since they have an average effect size of ~0.05-0.1 IQ points or so, a few hundred of those would in fact be many SDs. You can download the PGS, grab the top few hundred or thousand betas, and sum them if you don't believe me. (I show this with Benyamin et al 2014 in that section above, but no reason one couldn't redo it with a better PGS; the results won't change much.) And yes, Hsu really does believe this, he is quite explicit in that 2014 paper that that is how it would work (in addition to countless places on his blog & Twitter) and I've discussed it with him in the past. (As other comments point out, the real problem with this logic is that the hits are usually not causal but tag the causal variant, even if you had some magic CRISPR which could make hundreds of arbitrary edits. That's soluble, but not easily. It is, however, not a problem for selection procedures.)