Like any new (medical) technology, I think that it’s important to consider the ethical implications. This doesn’t mean that we shouldn’t do it or allow it, but just that we should be thoughtful about it.
As for clinic success rates, I didn’t mean to imply that “they don’t mean anything”. It’s just that prospective patients should be aware that they can’t always be taken at face value. Clinic populations may differ significantly and the data can be manipulated to some extent. The good news though is that as long as a clinic does a significant volume of IVF cycles per year and reports decent success rates, it’s probably fine.
I agree that increasing insurance coverage for infertility services would help improve access and reduce disparities.
RE IVG, I see your point. I guess germline/embryo gene-editing (if it were proven safe, efficient, and efficacious) would have greater utility than PGT-P (preimplantation genetic testing for polygenic risk).
The paper you linked outlining the limitations of polygenic embryo screening mostly rests its conclusions on the supposed impossibility of showing that embryo screening actually works.
Again, I refer back to tests of polygenic risk scores in siblings. If predictors work in that population, they should be considered clinically validated. This kind of validation is standard practice in other areas of data science. I’d appreciate it if you or someone else questioning PGT-P could outline exactly why they believe sibling validation of polygenic scores is insufficient evidence to justify its clinical use. It is literally a randomized control trial for genes.
My response to other criticisms in the paper:
“Furthermore, statistical manipulation of genetic data may limit the detection of rare pathogenic gene variants”
De novo mutations are exceedingly rare. The average person has about 70. The expected effect from missing these mutations is so low that it’s barely worth considering, especially compared to the expected benefits of simply improving predictors and adding more traits to the selection index used in PGT-P.
not only is it difficult to assess the clinical validity of PRS-ES in terms of the outcomes in question, it is also possible that clinical validity would be limited by the different effects of future environment on gene expression, compared to the past.
Yes, I agree that this is a fair critique of embryo selection, particularly for the diseases of old age. But the obvious solution here is just to apply some time discount factor; weight traits like depressive tendency, obesity, and intelligence more heavily than prostate cancer and heart disease, since the former will have an impact much sooner.
Mathematical modelling of PRS-ES has been attempted and indicated extremely limited utility in terms of non-pathological trait selection (Karavani et al., 2019), such as height and intelligence quotient (IQ).
The Karavani study used predictors that were already outdated by two years when the study was published. They are even more outdated today. Today you could expect +6 IQ points and +3.7 cm using state of the art predictors and the same assumptions made in the Karavani study.
Furthermore the overall expected gain increases as you add traits to your index.
Most of the conditions which can be assessed using PRS have a significant gender association.
Yes, this is why Genomic Prediction adjusts for sex in their index. I assume Orchid does the same thing though I know less about their selection methodology.
As elegantly described by Turley et al. (2021), the purported benefit of PRS-ES is commonly calculated and presented as a difference not between two average embryos, but rather a difference between the highest and the lowest possible risk embryos, thus maximizing the theoretical benefit of the test.
I’ve looked at the Genomic Prediction report and this is NOT how the results are presented. The expected reductions are calculated using actual siblings, and a baseline is an average person, not between the highest and lowest risk embryo.
I have asked and risk has NEVER been reported in the way described. It’s amazing how even in otherwise reputable journals these easily falsifiable rumors are allowed to spread.
It is also important to note that all embryos produced by a couple are genetically related and share on average 50% of SNPs. One must conclude that owing to inherent limitations of the PRS-ES models and limited variation in the genetic makeup of embryos produced by a couple, the clinical utility of PRS-ES is almost certainly diminutively small (Karavani et al., 2019).
Wrong. sibling variation is 1/sqrt(2) times that of the regular population, which is plenty for selection to result in substantial disease risk reduction or trait improvements. See Lello et al for more details
I could go on about this paper, but over and over again I see the authors making unsubstantiated claims contradicted by the evidence. There ARE a few legitimate issues with embryo selection, but the paper focuses most of its energy on non-issues.
I pretty much agree with the rest of your comment, though I think the situation for patients is better than you think. I’ve spoken with the genetic counselors at both Orchid and Genomic Prediction and found them to be very straightforward about the expected benefits and risks. The real issue with Genomic Prediction is they seem to have taken down their page showing the expected disease reductions from polygenic embryo screening. I don’t know why.
Thanks for the response.
I thought the following article does a good job of outlining some of the limitations of PRS for embryo selection:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9527452/
Like any new (medical) technology, I think that it’s important to consider the ethical implications. This doesn’t mean that we shouldn’t do it or allow it, but just that we should be thoughtful about it.
As for clinic success rates, I didn’t mean to imply that “they don’t mean anything”. It’s just that prospective patients should be aware that they can’t always be taken at face value. Clinic populations may differ significantly and the data can be manipulated to some extent. The good news though is that as long as a clinic does a significant volume of IVF cycles per year and reports decent success rates, it’s probably fine.
I agree that increasing insurance coverage for infertility services would help improve access and reduce disparities.
RE IVG, I see your point. I guess germline/embryo gene-editing (if it were proven safe, efficient, and efficacious) would have greater utility than PGT-P (preimplantation genetic testing for polygenic risk).
The paper you linked outlining the limitations of polygenic embryo screening mostly rests its conclusions on the supposed impossibility of showing that embryo screening actually works.
Again, I refer back to tests of polygenic risk scores in siblings. If predictors work in that population, they should be considered clinically validated. This kind of validation is standard practice in other areas of data science. I’d appreciate it if you or someone else questioning PGT-P could outline exactly why they believe sibling validation of polygenic scores is insufficient evidence to justify its clinical use. It is literally a randomized control trial for genes.
My response to other criticisms in the paper:
“Furthermore, statistical manipulation of genetic data may limit the detection of rare pathogenic gene variants”
De novo mutations are exceedingly rare. The average person has about 70. The expected effect from missing these mutations is so low that it’s barely worth considering, especially compared to the expected benefits of simply improving predictors and adding more traits to the selection index used in PGT-P.
not only is it difficult to assess the clinical validity of PRS-ES in terms of the outcomes in question, it is also possible that clinical validity would be limited by the different effects of future environment on gene expression, compared to the past.
Yes, I agree that this is a fair critique of embryo selection, particularly for the diseases of old age. But the obvious solution here is just to apply some time discount factor; weight traits like depressive tendency, obesity, and intelligence more heavily than prostate cancer and heart disease, since the former will have an impact much sooner.
Mathematical modelling of PRS-ES has been attempted and indicated extremely limited utility in terms of non-pathological trait selection (Karavani et al., 2019), such as height and intelligence quotient (IQ).
The Karavani study used predictors that were already outdated by two years when the study was published. They are even more outdated today. Today you could expect +6 IQ points and +3.7 cm using state of the art predictors and the same assumptions made in the Karavani study.
Furthermore the overall expected gain increases as you add traits to your index.
Most of the conditions which can be assessed using PRS have a significant gender association.
Yes, this is why Genomic Prediction adjusts for sex in their index. I assume Orchid does the same thing though I know less about their selection methodology.
As elegantly described by Turley et al. (2021), the purported benefit of PRS-ES is commonly calculated and presented as a difference not between two average embryos, but rather a difference between the highest and the lowest possible risk embryos, thus maximizing the theoretical benefit of the test.
I’ve looked at the Genomic Prediction report and this is NOT how the results are presented. The expected reductions are calculated using actual siblings, and a baseline is an average person, not between the highest and lowest risk embryo.
I have asked and risk has NEVER been reported in the way described. It’s amazing how even in otherwise reputable journals these easily falsifiable rumors are allowed to spread.
It is also important to note that all embryos produced by a couple are genetically related and share on average 50% of SNPs. One must conclude that owing to inherent limitations of the PRS-ES models and limited variation in the genetic makeup of embryos produced by a couple, the clinical utility of PRS-ES is almost certainly diminutively small (Karavani et al., 2019).
Wrong. sibling variation is 1/sqrt(2) times that of the regular population, which is plenty for selection to result in substantial disease risk reduction or trait improvements. See Lello et al for more details
I could go on about this paper, but over and over again I see the authors making unsubstantiated claims contradicted by the evidence. There ARE a few legitimate issues with embryo selection, but the paper focuses most of its energy on non-issues.
I pretty much agree with the rest of your comment, though I think the situation for patients is better than you think. I’ve spoken with the genetic counselors at both Orchid and Genomic Prediction and found them to be very straightforward about the expected benefits and risks. The real issue with Genomic Prediction is they seem to have taken down their page showing the expected disease reductions from polygenic embryo screening. I don’t know why.