Is there a plausible path towards gene therapies that edit dozens, hundreds, or thousands of different genes like this? I thought people were worried about off-target errors, etc? (Or at least problems like “you’ll have to take 1000 different customized doses of CRISPR therapy, which will be expensive”.) So my impression is that this kind of GWAS-inspired medicine would be most impactful with whole-genome synthesis? (Currently super-expensive?)
To be clear I agree with the main point this post is making about how we don’t need animal models, etc, to do medicine if we have something that we know works!
Yes, there is. I’ve been working on a post about this for the last few months and hope to post something much more comprehensive soon.
Off-targets are a potential issue though they’re less of an issue if you target non-coding regions that aren’t directly translated into proteins. The editing tools have also improved a lot since the original CRISPR publications back in 2012. Base editors and prime editors have indel rates like 50-300x lower than original CRISPR.
(Or at least problems like “you’ll have to take 1000 different customized doses of CRISPR therapy, which will be expensive”.)
Base editors and prime editors can do simultaneous edits in the same cell. I’ve read a paper where the authors did 50 concurrent base edits (though it was in a cell type that is easier than average to edit). Scaling concurrent editing capabilities is the very first thing I want to focus on.
Also, if your delivery vector doesn’t trigger an adaptive immune response (or end up being toxic for some other reason), you can redose someone a few times and make new edits with each round. If we can solve delivery issues, the dosing would be as simple as giving someone an IV injection.
I’m not saying these are simple problems. Solving all of them is going to be hard. But many of the steps have already been done independently in one research paper or another.
So my impression is that this kind of GWAS-inspired medicine would be most impactful with whole-genome synthesis?
No. You don’t need to be able to synthesize a genome to make any of this work. You can edit the genome of a living person.
Thanks, this is exciting and inspiring stuff to learn about!
I guess another thing I’m wondering about, is how we could tell apart genes that impact a trait via their ongoing metabolic activities (maybe metabolic is not the right term… what I mean is that the gene is being expressed, creating proteins, etc, on an ongoing basis), versus genes that impact a trait via being important for early embryonic / childhood development, but which aren’t very relevant in adulthood. Genes related to intelligence, for instance, seem like they might show up with positive scores in a GWAS, but their function is confined to helping unfold the proper neuron connection structures during fetal development, and then they turn off, so editing them now won’t do anything. Versus other genes that affect, say, what kinds of cholesterol the body produces, seem more likely to have direct impact via their day-to-day operation (which could be changed using a CRISPR-like tool).
Do we have any way of distinguishing the one type of genes from the other? (Maybe we can just look at living tissue and examine what genes are expressed vs turned off? This sounds hard to do for the entire genome...) Or perhaps we have reason to believe something like “only 20% of genes are related to early development, 80% handle ongoing metabolism, so the GWAS --> gene therapy pipeline won’t be affected too badly by the dilution of editing useless early-development genes”?
I guess another thing I’m wondering about, is how we could tell apart genes that impact a trait via their ongoing metabolic activities (maybe metabolic is not the right term… what I mean is that the gene is being expressed, creating proteins, etc, on an ongoing basis), versus genes that impact a trait via being important for early embryonic / childhood development, but which aren’t very relevant in adulthood.
Yes, this is an excellent question. And I think it’s likely we could (at least for the brain) thanks to some data from this study that took brain biopsies from individuals of varying stages of life and looked at the transcriptome of cells from different parts of the brain.
My basic prior is that the effect of editing is likely to be close to the same as if you edited the same gene in an embryo iff the peak protein expression occurs in adulthood. Though there aren’t really any animal experiments that I know of yet which look at how the distribution of effect sizes vary by trait and organ.
Is there a plausible path towards gene therapies that edit dozens, hundreds, or thousands of different genes like this? I thought people were worried about off-target errors, etc? (Or at least problems like “you’ll have to take 1000 different customized doses of CRISPR therapy, which will be expensive”.) So my impression is that this kind of GWAS-inspired medicine would be most impactful with whole-genome synthesis? (Currently super-expensive?)
To be clear I agree with the main point this post is making about how we don’t need animal models, etc, to do medicine if we have something that we know works!
Yes, there is. I’ve been working on a post about this for the last few months and hope to post something much more comprehensive soon.
Off-targets are a potential issue though they’re less of an issue if you target non-coding regions that aren’t directly translated into proteins. The editing tools have also improved a lot since the original CRISPR publications back in 2012. Base editors and prime editors have indel rates like 50-300x lower than original CRISPR.
Base editors and prime editors can do simultaneous edits in the same cell. I’ve read a paper where the authors did 50 concurrent base edits (though it was in a cell type that is easier than average to edit). Scaling concurrent editing capabilities is the very first thing I want to focus on.
Also, if your delivery vector doesn’t trigger an adaptive immune response (or end up being toxic for some other reason), you can redose someone a few times and make new edits with each round. If we can solve delivery issues, the dosing would be as simple as giving someone an IV injection.
I’m not saying these are simple problems. Solving all of them is going to be hard. But many of the steps have already been done independently in one research paper or another.
No. You don’t need to be able to synthesize a genome to make any of this work. You can edit the genome of a living person.
Thanks, this is exciting and inspiring stuff to learn about!
I guess another thing I’m wondering about, is how we could tell apart genes that impact a trait via their ongoing metabolic activities (maybe metabolic is not the right term… what I mean is that the gene is being expressed, creating proteins, etc, on an ongoing basis), versus genes that impact a trait via being important for early embryonic / childhood development, but which aren’t very relevant in adulthood. Genes related to intelligence, for instance, seem like they might show up with positive scores in a GWAS, but their function is confined to helping unfold the proper neuron connection structures during fetal development, and then they turn off, so editing them now won’t do anything. Versus other genes that affect, say, what kinds of cholesterol the body produces, seem more likely to have direct impact via their day-to-day operation (which could be changed using a CRISPR-like tool).
Do we have any way of distinguishing the one type of genes from the other? (Maybe we can just look at living tissue and examine what genes are expressed vs turned off? This sounds hard to do for the entire genome...) Or perhaps we have reason to believe something like “only 20% of genes are related to early development, 80% handle ongoing metabolism, so the GWAS --> gene therapy pipeline won’t be affected too badly by the dilution of editing useless early-development genes”?
Yes, this is an excellent question. And I think it’s likely we could (at least for the brain) thanks to some data from this study that took brain biopsies from individuals of varying stages of life and looked at the transcriptome of cells from different parts of the brain.
My basic prior is that the effect of editing is likely to be close to the same as if you edited the same gene in an embryo iff the peak protein expression occurs in adulthood. Though there aren’t really any animal experiments that I know of yet which look at how the distribution of effect sizes vary by trait and organ.