That matrix goes a long way in showing that there isn’t much correlation between diseases in the natural distribution. What is the reason to believe those correlations will remain low when you are making edits resulting in an extremely unlikely genome?
We’d edit the SNPs which have been found to causally influence the trait of interest in an additive manner. The genome would only become “extremely unlikely” if we made enough edits to push the predicted trait value to an extreme value—which you probably wouldn’t want to do for decreasing disease risk. E.g. if someone has +2 SD risk of developing Alzheimer’s, you might want to make enough edits to shift them to −2 SD, which isn’t particularly extreme.
You’re right that this is a risk with ambitious intelligence enhancement, where we’re actually interested in pushing somewhat outside the current human range (especially since we’d probably need to push the predicted trait value even further in order to get a particular effect size in adults) -- the simple additive model will break down at some point.
Also, due to linkage disequilibrium, there are things that could go wrong with creating “unnatural genomes” even within the current human range. E.g. if you have an SNP with alleles A and B, and there are mutations at nearby loci which are neutral conditional on having allele A and deleterious conditional on having allele B, those mutations will tend to accumulate in genomes which have allele A (due to linkage disequilibrium), while being purged from genomes with allele B. If allele B is better for the trait in question, we might choose it as an edit site in a person with allele A, which could be highly deleterious due to the linked mutations. (That said, I don’t think this situation of large-conditional-effect mutations is particularly likely a priori.)
That matrix goes a long way in showing that there isn’t much correlation between diseases in the natural distribution. What is the reason to believe those correlations will remain low when you are making edits resulting in an extremely unlikely genome?
We’d edit the SNPs which have been found to causally influence the trait of interest in an additive manner. The genome would only become “extremely unlikely” if we made enough edits to push the predicted trait value to an extreme value—which you probably wouldn’t want to do for decreasing disease risk. E.g. if someone has +2 SD risk of developing Alzheimer’s, you might want to make enough edits to shift them to −2 SD, which isn’t particularly extreme.
You’re right that this is a risk with ambitious intelligence enhancement, where we’re actually interested in pushing somewhat outside the current human range (especially since we’d probably need to push the predicted trait value even further in order to get a particular effect size in adults) -- the simple additive model will break down at some point.
Also, due to linkage disequilibrium, there are things that could go wrong with creating “unnatural genomes” even within the current human range. E.g. if you have an SNP with alleles A and B, and there are mutations at nearby loci which are neutral conditional on having allele A and deleterious conditional on having allele B, those mutations will tend to accumulate in genomes which have allele A (due to linkage disequilibrium), while being purged from genomes with allele B. If allele B is better for the trait in question, we might choose it as an edit site in a person with allele A, which could be highly deleterious due to the linked mutations. (That said, I don’t think this situation of large-conditional-effect mutations is particularly likely a priori.)