4 ms·

polygenic risk scores are composed of massive number of loci, so direct gene editing (ala crispr) is not feasible.

by aydyn 4y ago

gwern 4y ago
More specifically: polygenic scores work and are additive, while epistasis and dominance are trivial (contra the furious FUDing upthread by someone determinedly ignoring the fact that, no matter how many cute restaurant analogies you use, we have lots of phenome-wide data from UKBB and elsewhere showing additive variance is larger than epistatic variance and dominance is so irrelevant it's hard to distinguish from 0%, not that that's relevant in the first place), because they use SNPs to tag blocks or stretches of the genome which carry the causal variants, the SNPs aren't themselves usually causal. So if you directly edited all of the SNPs with nontrivial posterior probability of the effect you want, you would get much smaller effects than you expect (as much as 90% smaller). But if you operate on the blocks (haplotypes), the SNPs continue to serve their existing role as markers, and you can optimize by selecting for all of the useful blocks and dropping the rest. (This is how IES would work, especially if it could run for many generations/cycles; operating on just the SNP level is only what people who haven't thought about it think it would do.) A lot of problems go away when you are doing selection, preserving all the existing causal relationships (like the extensive positive correlation among health traits which means that you won't get any net 'backfire effects'), instead of causal interventions like editing.
- dekhn 4y ago
  This doesn't make any sense to me. I tried to parse it several times (I'm a PhD computational biologist but no expert in this area) Thinking in snps and haplotypes has been tripping up geneticists for years. Everything in genomics is highly nonlinear, not additive, and with massive amounts of long range interactions, feedback, and state. Also organismal phenotypes are very different from molecular phenotypes- often organismal phenotypes are actually several underlying things grouped with a common label simply because they have similar features.

polygenic risk scores are composed of massive number of loci, so direct gene editing (ala crispr) is not feasible.

by aydyn 4y ago

polygenic risk scores are composed of massive number of loci, so direct gene editing (ala crispr) is not feasible.

More specifically: polygenic scores work and are additive, while epistasis and dominance are trivial (contra the furious FUDing upthread by someone determinedly ignoring the fact that, no matter how many cute restaurant analogies you use, we have lots of phenome-wide data from UKBB and elsewhere showing additive variance is larger than epistatic variance and dominance is so irrelevant it's hard to distinguish from 0%, not that that's relevant in the first place), because they use SNPs to tag blocks or stretches of the genome which carry the causal variants, the SNPs aren't themselves usually causal. So if you directly edited all of the SNPs with nontrivial posterior probability of the effect you want, you would get much smaller effects than you expect (as much as 90% smaller). But if you operate on the blocks (haplotypes), the SNPs continue to serve their existing role as markers, and you can optimize by selecting for all of the useful blocks and dropping the rest. (This is how IES would work, especially if it could run for many generations/cycles; operating on just the SNP level is only what people who haven't thought about it think it would do.) A lot of problems go away when you are doing selection, preserving all the existing causal relationships (like the extensive positive correlation among health traits which means that you won't get any net 'backfire effects'), instead of causal interventions like editing.

dekhn 4y ago
This doesn't make any sense to me. I tried to parse it several times (I'm a PhD computational biologist but no expert in this area) Thinking in snps and haplotypes has been tripping up geneticists for years. Everything in genomics is highly nonlinear, not additive, and with massive amounts of long range interactions, feedback, and state. Also organismal phenotypes are very different from molecular phenotypes- often organismal phenotypes are actually several underlying things grouped with a common label simply because they have similar features.