TL:DR: If you’re female you should consider freezing your eggs and if you’re male with a female partner you should consider talking to them about freezing their eggs. You should probably do this regardless of whether you want to wait for the technology to improve. The process will cost about $40k-50k for the first kid with today’s prices, and probably $10k/kid after that. The benefit will be at least a year or so of increased life expectancy per kid, a decrease of heart disease, diabetes, and various cancers on the order of 10%-40%, and possibly increased IQ of somewhere between 0 and 10 points even if you don’t directly select for it (due to positive pleiotropy).
Here are some more details:
A BASIC PRIMER
So right now we have a bunch of Genome Wide Associate Studies (GWAS) that look at single letters in the genome and how strongly changes in those letters are associated with some trait of interest. These GWAS can usually explain 10-15% of the variance in a given trait, with some notable exceptions such as height, where we can explain >40% of the variance.
I think the two potential benefit of waiting to have kids would be seeing an improvement in the percentage of variance explainable by polygenic scores and having a broader set of traits from which to choose.
WHAT IS AVAILABLE NOW
The only company I know of actually offering polygenic screening available to the general public is Genomic Prediction. Their trait panel is entirely focused on common diseases like heart disease, cancer, diabetes and a couple of others. Let me first give a summary of the cost-effectiveness of this type of “disease reduction” screening.
The implied “variance explained” by the reductions shown in their genomic index is actually quite impressive for some of these diseases. Let’s use their original preprint from here: https://www.mdpi.com/2073-4425/11/6/648/htm
I used Carmi et al’s code from “Utility of polygenic embryo screening for disease depends on the selection strategy” to estimate the implied variance explained given those reductions and come up with predictors able to explain about 40-50% of variance for Type 2 Diabetes, Heart Attack and Coronary Artery Disease, and slightly lower for Hypertension and the others.
Those are very impressive numbers. Most stand-alone predictors explain less than 15% of variance. This implies that either Genomic Prediction’s numbers are wrong, or there’s something really amazing going on in genomic indexing: somehow selecting against multiple diseases is straight up better than selecting for a single disease, even if you only care about a single disease.
Part of this might just be a result of sample size: when your coronary artery disease predictor is trained on one population and your hypertension predictor is trained on another, there’s probably some kind of pooling effect going on. But given that most of the data for these predictors seems to come from UK Biobank, there’s also a more profound implication to the reductions shown in their panel: it seems likely that most of these clinically distinct disease are all manifestations of some underlying “health factor”, and that health factor has a strong genetic basis. Some genetic variants increase your risk of many many diseases. If that was not true, you would not see simultaneous reductions of this size across so many diseases. And my bet is there are reductions to diseases not even shown on the panel. What a crazy thing to discover while researching a LessWrong post reply. This is probably worth a whole post.
“For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait.”
This is actually incredible. My interpretation is that there’s not only a general factor g for intelligence across cognitive tasks, but also an h factor for health across multiple diseasees
Anyways, the implication for you question here is that current DISEASE predictors are already very very strong. Explaining 40-50% of variance from a predictor is incredible. That’s probably getting close to the limit of heritability for some of these. So for heart disease, diabetes, and some types of cancer, we’re probably nearing the limit of what polygenic predictors can explain and there is not much point waiting for them to get better. Right now you could probably simultaneously decrease the risk of many of these diseases by 70-80% by selecting among 10 embryos.
WHAT ARE THE BENEFITS OF WAITING?
Disease predictors are not nearly as good for non-European populations. I believe they the second best predictors are for South Asian, followed by east asian and then African. If you or your spouse trace your primary ancestor to one or multiple of those groups, it makes more sense to wait. Predictors for those of African ancestry in particular have substantial room for improvement.
The second caveat is about selecting for non-disease traits. This community has expressed particular interest in selecting for intelligence, though there are obviously other non-disease traits such as conscientiousness or mental energy that are also important.
There is substantial room for improvement in our intelligence predictors. Right now you could likely pay a PHD student <$10,000 to construct an intelligence predictor for you based on the Education Attainment Study #3 that would probably explain about 20% of variance in intelligence. If you had 14 euploid embryos to choose from and 70% of those implant, you would expect your first child to have an IQ about 4-5 points higher than the average of you and your spouse/partner.
Steve Hsu, one of the leading researchers in this field, has estimated that we would be able to explain 50-60% 30-40% of the variance in cognitive ability if the UK biobank simply offered their existing intelligence test to the 90% of BioBank participants who haven’t taken it. That would raise the expected IQ gain from selection among 14 embryos to ~9.5 points, which would perhaps be worth waiting for, though it’s not clear when or even if UK Biobank will do that. And since most of the biobank participants are European, the benefit might be somewhat smaller for other ethnicities.
So if you and your spouse are both European, you used normal IVF with multiple rounds of egg extractions and improved predictors would be a gain of about 13 IQ points. And since you probably wouldn’t select exclusively for IQ (disease are important too), I’d guess a more realistic gain would be about 10 points.
Also paying that PHD student to make the intelligence predictor might get all research into the genetic roots of intelligence banned, so consider that a major possible downside. Though if it wasn’t banned you could distribute it to anyone who wanted it and everyone doing IVF could have children 3-10 IQ points above their parents.
Then there’s the question of all these other important traits that we don’t even have predictors for, like conscientiousness, mental energy, performance while sleep-deprived and whatever else you value. I haven’t researched these other traits in depth too much, but it seems like there’s a lot of other important stuff that fall into this bucket.
Funny anecdote from the study: the associated genes were found to modulate behavioral response to cocaine. The authors don’t say what percentage of variance is explained by those 190 genes, but my guess is it’s in the neighborhood of 5%. So if you waited 5 years to have kids, these predictors of personality traits would almost certainly improve, probably to somewhere between 15% and 40%.
I can’t find a single GWAS on mental energy. Why has no one looked into that yet?
A similar improvement is likely to happen for many of the other predictors, particularly those for which people have already done GWAS.
Of course there’s one more question you’d have to answer even if you did have great predictors: which of these personality traits should be selected for and how strongly? All else held equal, more intelligence seems to pretty much always be better, and high disease risk seems to pretty much always be worse. Of course you can’t necessarily hold all else equal when selecting a for a finite set of traits, but most of the literature I’ve read about plieotropy suggests that unless you have extremely powerful selection techniques (i.e. iterated embryo selection, gene editing or whole genome synthesis), these are unlikely to be a concern.
But with personality traits I don’t yet have a clear mental model of which traits should be selected for and how strongly. I think most parents mostly want to give their child a happy productive life more than anything else, and besides the no-brainers like reducing predisposition to depression and anxiety, it’s not entirely clear how to do that.
WHAT SHOULD I DO?
If you would be willing to pay ~$40k to substantially decrease your child’s risk of common diseases and increase their lifespan by ~1 year, you should consider doing freezing eggs and doing IVF. And if you’re not ready to have kids yet or you want to wait for polygenic predictors to improve, you should freeze your eggs (or talk with your partner about freezing their eggs).
Why freeze eggs? Well unfortunately a woman’s production of chromosomally normal eggs gets substantially lower with age. The percentage of eggs that will be “euploid” (chromosomally normal) first increases in the late teens and early 20′s before reaching its max around 25. It then slowly declines starting around 30 and really accelerating after age 35. By the early 40′s, 80%+ of eggs produced will be aneuploid. The more euploid eggs available for freezing, the bigger a gain you’ll get from polygenic screening.
A woman’s capacity to actually carry a pregnancy to term on the other hand, lasts well into the post-menopausal period. The oldest mother to giver birth via donor eggs was 74! So by freezing eggs, you can preserve fertility for as much as 40 years.
If you’re single and a guy, then there are not really many action items for you. Sperm quality doesn’t really seem to decline until about 40, at which point it drops off slowly. The only direct option here would be to get eggs from a donor bank, but if you do that you’d likely have to face the challenges of single parenting. Plus donor eggs cost a few tens of thousands, so it would be quite a bit more expensive.
HOW DO I ACTUALLY DO THIS?
If you’re seriously considering doing IVF for polygenic screening, the first step is comparing IVF clinics. Some IVF clinics are 3x the cost of others for essentially the same service. Some IVF clinics have poor implantation cryopreservation and low implantation success rates. So choosing the right clinic will have a big effect on your cost/benefit analysis. Egg retrieval usually takes 3-6 visits from what I’ve heard, so it may actually be worth flying to another state (or perhaps even another country) to lower the price.
You then have to consider the IVF funnel to figure out how much it’s going to cost to achieve a certain reduction in disease risk/increase in healthspan. I really wish there was a tool for this because a lot of factors can substantially affect loss rates. But the basic gist is this: at each step in the IVF process, fewer eggs/embryos come out than go in. The three most important factors affecting the number of embryos you have to choose from are the IVF clinic, the genetic testing company, and the age of the mother.
Here are all the steps that have to be done.
Medication is taken stimulating egg production
Eggs are extracted
Eggs are frozen and unfrozen at a later date (optional but necessary for polygenic screening)
Eggs are fertilized, turning them into embryos
Embryos grow to day 5 blastocysts, at which point they are biopsied
Day 5 blastocysts are biopsied for polygenic screening (and to see if they’re chromosomally normal)
The euploiod embryo with the highest polygenic score is implanted.
A baby is born
At every single one of these steps, fewer eggs/embryos come out than went in.
If you’re 23-28 you’ll probably get around 15 eggs per cycle of IVF. According to some random news articles I looked up, 40%-50% of those will grow to day 5 blastocysts (this might be higher if you go to a good clinic and/or don’t have fertility issues)
If you’re 23-28, about 80% of the embryos that reach this stage will be euploid, meaning they have the potential to implant and turn into a healthy child. The others will either result in miscarriage or have a condition like Down Syndrome if implanted.
When you choose an embryo to implant, there’s a roughly 70% chance it will lead to a live birth (lower if you have fertility issues).
So roughly 30% of eggs extracted will lead to a live birth (though it should be noted that the above numbers may not be accurate since my numbers might be wrong a bunch of factors influence the percentage).
That means you need 3-4x as many eggs extracted as you want to select from. At 15 eggs per IVF cycle in good conditions, that’s 2-3 rounds of egg extraction if you want 10 embryos to choose from (taking implantation rates into account).
I think egg freezing is about $6k/cycle with genetic testing included. So for 3 cycles, that’s about $20k. Then IVF itself is I think like $15k. So maybe $35k-45k all-in cost not including the cost of childbirth, which is stupidly exensive but usually covered by insurance.
It should be noted that there’s actually a pretty big gain from selecting from just 2 embryos. Going up to 10 increases the benefit by about 80%, but the gains are still pretty noticable from any selection at all.
Anyways, I hope this was helpful. Let me know if you want me to write a more in-depth post about how to do IVF for polygenic selection.
I wonder if (or how likely) you can sale the other embryos, and for how much.
I wonder if you want, say, 4 children, whether there are economies of scale (say: will the top 4 embryo out of 30 embryos be better than the top 2 embryos out of 15?).
I’m very interested in this space. You seem to have identify an important need: reviewing IVF clinics. I haven’t researched whether that need is already fulfilled or not, but if not, I’d be interested in thinking of a potential business model to respond to this need (and if not, doing it non-for-profit).
There are also related questions I’d like to research, such as tips on how to choose an independent sperm donor; how much regression to the mean is there (ie. to know when marginal returns becomes too low to be worth it); survey on fraction of people that would donate gamete if asked to by a friend; polygenic screening aside, is there still an economic case for freezing eggs early, etc.. All this could be documented on a specific website.
Anyway, I don’t want to scope creep this project. I’d love if you wrote a more in-depth post about how to do IVF for polygenic selection for LessWrong. Ex.: I’d like to know how egg qualities decrease with age to know when it becomes more important, and what the health risks are.
But if anyone is interested in either a) contributing to those projects, or b) consuming the value of those projects, then I invite you to reach out to me at mathieu.roy.37@gmail.com.
I wonder if you want, say, 4 children, whether there are economies of scale (say: will the top 4 embryo out of 30 embryos be better than the top 2 embryos out of 15?).
I assume you are imagining a comparison like a one-step procedure where you implant 4 out of a batch of 30, vs a two-step procedure where you must implant 2 out of a batch of 15 each step while discarding the previous batch. The answer turns out to be yes, in this case, but not because of economies of scale (I haven’t seen anyone actually quote discounts for biopsying & genotyping large batches), but option value (and mumble mumble Jensen’s inequality mumble convexity).
The expected ranks are the same because they are i.i.d., so it doesn’t matter on average if you pick 2-of-15 twice or 4-of-30 once. But that’s just the starting point: you have a lossy pipeline to feed them into before you get 4 children out the other end, and a lot of embryos will never implant or yield a live birth. So, in the two-step scenario, when you lose your top candidate and have to pick from the small within-step pool, you get forced back to the mean more than if you had pooled them all in a single step and could retry with the next-best globally. This makes it worse. (Imagine a more extreme scenario where you are picking 1-of-2 100 times vs picking 100-of-200 once. When you lose an embryo in a 1-of-2 step, your backup embryo is at −0.56SD, because just as the expected gain from max(2) is 0.56, the expected gain from the symmetrical min(2) is −0.56SD, and with only 2 candidates, if you lose the max, all you have left is the min. Whereas if you had pooled them, then when you lose your first embryo in 100-of-200, the expected rank of fallback candidate #101 is ~0SD, just like #100 was ~0SD.) The more finegrained irreversible decisions must be, the worse the ‘ratchet’ of losses is. (This is because there are only bad surprises; if there were good surprises, the logic works the other direction, which is why the value of a bunch of separate options > the value of the mean of those options.)
Considering the unpleasantness and difficulty of egg harvesting, and the ease of storage, it doesn’t make much sense to try to do things in many stages.
how much regression to the mean is there (ie. to know when marginal returns becomes too low to be worth it)
Regression to a (population) mean is not relevant because you are comparing sibling embryos which are distributed around the parental mean by construction.
For many traits, returns are pretty linear. Like IQ points, it doesn’t much matter where you are, the value of another point is pretty constant. So you can just ignore that entirely and operate on marginal gains. (eg if the parents are both 130 IQ and you calculate a marginal gain of +1 IQ point from selection & that makes it profitable, maybe their genotypic mean is actually 115 IQ, but it doesn’t matter, because the marginal gain will still be +1 IQ point over the batch mean and will still be profitable).
For binary traits, you can have diminishing returns based on where the trait value is. As I note in my other comment, if a family is at very high risk for a trait like schizophrenia, then selection can be extremely valuable beyond what the average PGS % would imply; the flip side of this is that then there must be families who have below-average risk and benefit a below-average amount. However, these diminishing returns are automatically incorporated in any index score (which is how one should be selecting). If the polygenic score for SCZ is already very low, then the index component for embryos which move the SCZ score even lower will be very small, because it reduces a tiny absolute risk by a tiny absolute amount, which has a tiny expected value, and the index will prefer embryos which move more important traits.
If you want to model such scenarios to imagine conditioning on a specific example/family history, it’s easy to just switch out the population fraction for the implied fraction of the ‘parental population’ in your liability-threshold code, and everything works as before. But I generally use the average because the average is the average.
I find the mostly linear relationship between IQ and income to be surprising. If we use the odds of winning a Nobel as a proxy for “ability to make an important scientific discovery”, doesn’t the lack of average-IQ winners imply some kind of exponential relationship between IQ and scientific productivity?
If both the linear income relationship and the one described above are true, it implies an exponentially decreasing ability of high IQ people to capture the value they create.
doesn’t the lack of average-IQ winners imply some kind of exponential relationship between IQ and scientific productivity?
Something like that. A straight line on log odds charts in SMPY, IIRC.
it implies an exponentially decreasing ability of high IQ people to capture the value they create.
Oh definitely. This is a point Gensowski and others make: part of the reason that the income relationship does bend is that it’s hard to capture all your positive externalities even though the patenting rate etc increases. You can invent the transistor or antibiotics, but you won’t capture anywhere remotely close to 1% of the total surplus. Also part of the country-level story for why IQ looks so powerful: individuals don’t capture anything remotely approaching their full contributions (in the same way that people on the other end of the spectrum do not internalize anything remotely like the harm they do to everyone else), so the country-level correlations can be much stronger than individual-level ones.
TL:DR: If you’re female you should consider freezing your eggs and if you’re male with a female partner you should consider talking to them about freezing their eggs. You should probably do this regardless of whether you want to wait for the technology to improve. The process will cost about $40k-50k for the first kid with today’s prices, and probably $10k/kid after that. The benefit will be at least a year or so of increased life expectancy per kid, a decrease of heart disease, diabetes, and various cancers on the order of 10%-40%, and possibly increased IQ of somewhere between 0 and 10 points even if you don’t directly select for it (due to positive pleiotropy).
Here are some more details:
A BASIC PRIMER
So right now we have a bunch of Genome Wide Associate Studies (GWAS) that look at single letters in the genome and how strongly changes in those letters are associated with some trait of interest. These GWAS can usually explain 10-15% of the variance in a given trait, with some notable exceptions such as height, where we can explain >40% of the variance.
I think the two potential benefit of waiting to have kids would be seeing an improvement in the percentage of variance explainable by polygenic scores and having a broader set of traits from which to choose.
WHAT IS AVAILABLE NOW
The only company I know of actually offering polygenic screening available to the general public is Genomic Prediction. Their trait panel is entirely focused on common diseases like heart disease, cancer, diabetes and a couple of others. Let me first give a summary of the cost-effectiveness of this type of “disease reduction” screening.
The implied “variance explained” by the reductions shown in their genomic index is actually quite impressive for some of these diseases. Let’s use their original preprint from here: https://www.mdpi.com/2073-4425/11/6/648/htm
I used Carmi et al’s code from “Utility of polygenic embryo screening for disease depends on the selection strategy” to estimate the implied variance explained given those reductions and come up with predictors able to explain about 40-50% of variance for Type 2 Diabetes, Heart Attack and Coronary Artery Disease, and slightly lower for Hypertension and the others.
Those are very impressive numbers. Most stand-alone predictors explain less than 15% of variance. This implies that either Genomic Prediction’s numbers are wrong, or there’s something really amazing going on in genomic indexing: somehow selecting against multiple diseases is straight up better than selecting for a single disease, even if you only care about a single disease.
Part of this might just be a result of sample size: when your coronary artery disease predictor is trained on one population and your hypertension predictor is trained on another, there’s probably some kind of pooling effect going on. But given that most of the data for these predictors seems to come from UK Biobank, there’s also a more profound implication to the reductions shown in their panel: it seems likely that most of these clinically distinct disease are all manifestations of some underlying “health factor”, and that health factor has a strong genetic basis. Some genetic variants increase your risk of many many diseases. If that was not true, you would not see simultaneous reductions of this size across so many diseases. And my bet is there are reductions to diseases not even shown on the panel. What a crazy thing to discover while researching a LessWrong post reply. This is probably worth a whole post.
EDIT: I found a study that replicated the strong positive pleiotropy effect shown in Genomic Prediction’s index: https://www.researchgate.net/publication/323614487_Improving_genetic_prediction_by_leveraging_genetic_correlations_among_human_diseases_and_traits
This is actually incredible. My interpretation is that there’s not only a general factor g for intelligence across cognitive tasks, but also an h factor for health across multiple diseasees
Anyways, the implication for you question here is that current DISEASE predictors are already very very strong. Explaining 40-50% of variance from a predictor is incredible. That’s probably getting close to the limit of heritability for some of these. So for heart disease, diabetes, and some types of cancer, we’re probably nearing the limit of what polygenic predictors can explain and there is not much point waiting for them to get better. Right now you could probably simultaneously decrease the risk of many of these diseases by 70-80% by selecting among 10 embryos.
WHAT ARE THE BENEFITS OF WAITING?
Disease predictors are not nearly as good for non-European populations. I believe they the second best predictors are for South Asian, followed by east asian and then African. If you or your spouse trace your primary ancestor to one or multiple of those groups, it makes more sense to wait. Predictors for those of African ancestry in particular have substantial room for improvement.
The second caveat is about selecting for non-disease traits. This community has expressed particular interest in selecting for intelligence, though there are obviously other non-disease traits such as conscientiousness or mental energy that are also important.
There is substantial room for improvement in our intelligence predictors. Right now you could likely pay a PHD student <$10,000 to construct an intelligence predictor for you based on the Education Attainment Study #3 that would probably explain about 20% of variance in intelligence. If you had 14 euploid embryos to choose from and 70% of those implant, you would expect your first child to have an IQ about 4-5 points higher than the average of you and your spouse/partner.
Steve Hsu, one of the leading researchers in this field, has estimated that we would be able to explain
50-60%30-40% of the variance in cognitive ability if the UK biobank simply offered their existing intelligence test to the 90% of BioBank participants who haven’t taken it. That would raise the expected IQ gain from selection among 14 embryos to ~9.5 points, which would perhaps be worth waiting for, though it’s not clear when or even if UK Biobank will do that. And since most of the biobank participants are European, the benefit might be somewhat smaller for other ethnicities.So if you and your spouse are both European, you used normal IVF with multiple rounds of egg extractions and improved predictors would be a gain of about 13 IQ points. And since you probably wouldn’t select exclusively for IQ (disease are important too), I’d guess a more realistic gain would be about 10 points.
Also paying that PHD student to make the intelligence predictor might get all research into the genetic roots of intelligence banned, so consider that a major possible downside. Though if it wasn’t banned you could distribute it to anyone who wanted it and everyone doing IVF could have children 3-10 IQ points above their parents.
Then there’s the question of all these other important traits that we don’t even have predictors for, like conscientiousness, mental energy, performance while sleep-deprived and whatever else you value. I haven’t researched these other traits in depth too much, but it seems like there’s a lot of other important stuff that fall into this bucket.
Here’s a GWAS looking at neuroticism that found 190 genes associated with the trait at 2.5*10^-5. https://www.nature.com/articles/s41598-021-82123-5#Sec2
Funny anecdote from the study: the associated genes were found to modulate behavioral response to cocaine. The authors don’t say what percentage of variance is explained by those 190 genes, but my guess is it’s in the neighborhood of 5%. So if you waited 5 years to have kids, these predictors of personality traits would almost certainly improve, probably to somewhere between 15% and 40%.
I can’t find a single GWAS on mental energy. Why has no one looked into that yet?
A similar improvement is likely to happen for many of the other predictors, particularly those for which people have already done GWAS.
Of course there’s one more question you’d have to answer even if you did have great predictors: which of these personality traits should be selected for and how strongly? All else held equal, more intelligence seems to pretty much always be better, and high disease risk seems to pretty much always be worse. Of course you can’t necessarily hold all else equal when selecting a for a finite set of traits, but most of the literature I’ve read about plieotropy suggests that unless you have extremely powerful selection techniques (i.e. iterated embryo selection, gene editing or whole genome synthesis), these are unlikely to be a concern.
But with personality traits I don’t yet have a clear mental model of which traits should be selected for and how strongly. I think most parents mostly want to give their child a happy productive life more than anything else, and besides the no-brainers like reducing predisposition to depression and anxiety, it’s not entirely clear how to do that.
WHAT SHOULD I DO?
If you would be willing to pay ~$40k to substantially decrease your child’s risk of common diseases and increase their lifespan by ~1 year, you should consider doing freezing eggs and doing IVF. And if you’re not ready to have kids yet or you want to wait for polygenic predictors to improve, you should freeze your eggs (or talk with your partner about freezing their eggs).
Why freeze eggs? Well unfortunately a woman’s production of chromosomally normal eggs gets substantially lower with age. The percentage of eggs that will be “euploid” (chromosomally normal) first increases in the late teens and early 20′s before reaching its max around 25. It then slowly declines starting around 30 and really accelerating after age 35. By the early 40′s, 80%+ of eggs produced will be aneuploid. The more euploid eggs available for freezing, the bigger a gain you’ll get from polygenic screening.
A woman’s capacity to actually carry a pregnancy to term on the other hand, lasts well into the post-menopausal period. The oldest mother to giver birth via donor eggs was 74! So by freezing eggs, you can preserve fertility for as much as 40 years.
If you’re single and a guy, then there are not really many action items for you. Sperm quality doesn’t really seem to decline until about 40, at which point it drops off slowly. The only direct option here would be to get eggs from a donor bank, but if you do that you’d likely have to face the challenges of single parenting. Plus donor eggs cost a few tens of thousands, so it would be quite a bit more expensive.
HOW DO I ACTUALLY DO THIS?
If you’re seriously considering doing IVF for polygenic screening, the first step is comparing IVF clinics. Some IVF clinics are 3x the cost of others for essentially the same service. Some IVF clinics have poor implantation cryopreservation and low implantation success rates. So choosing the right clinic will have a big effect on your cost/benefit analysis. Egg retrieval usually takes 3-6 visits from what I’ve heard, so it may actually be worth flying to another state (or perhaps even another country) to lower the price.
You then have to consider the IVF funnel to figure out how much it’s going to cost to achieve a certain reduction in disease risk/increase in healthspan. I really wish there was a tool for this because a lot of factors can substantially affect loss rates. But the basic gist is this: at each step in the IVF process, fewer eggs/embryos come out than go in. The three most important factors affecting the number of embryos you have to choose from are the IVF clinic, the genetic testing company, and the age of the mother.
Here are all the steps that have to be done.
Medication is taken stimulating egg production
Eggs are extracted
Eggs are frozen and unfrozen at a later date (optional but necessary for polygenic screening)
Eggs are fertilized, turning them into embryos
Embryos grow to day 5 blastocysts, at which point they are biopsied
Day 5 blastocysts are biopsied for polygenic screening (and to see if they’re chromosomally normal)
The euploiod embryo with the highest polygenic score is implanted.
A baby is born
At every single one of these steps, fewer eggs/embryos come out than went in.
If you’re 23-28 you’ll probably get around 15 eggs per cycle of IVF. According to some random news articles I looked up, 40%-50% of those will grow to day 5 blastocysts (this might be higher if you go to a good clinic and/or don’t have fertility issues)
If you’re 23-28, about 80% of the embryos that reach this stage will be euploid, meaning they have the potential to implant and turn into a healthy child. The others will either result in miscarriage or have a condition like Down Syndrome if implanted.
When you choose an embryo to implant, there’s a roughly 70% chance it will lead to a live birth (lower if you have fertility issues).
So roughly 30% of eggs extracted will lead to a live birth (though it should be noted that the above numbers may not be accurate since my numbers might be wrong a bunch of factors influence the percentage).
That means you need 3-4x as many eggs extracted as you want to select from. At 15 eggs per IVF cycle in good conditions, that’s 2-3 rounds of egg extraction if you want 10 embryos to choose from (taking implantation rates into account).
I think egg freezing is about $6k/cycle with genetic testing included. So for 3 cycles, that’s about $20k. Then IVF itself is I think like $15k. So maybe $35k-45k all-in cost not including the cost of childbirth, which is stupidly exensive but usually covered by insurance.
It should be noted that there’s actually a pretty big gain from selecting from just 2 embryos. Going up to 10 increases the benefit by about 80%, but the gains are still pretty noticable from any selection at all.
Anyways, I hope this was helpful. Let me know if you want me to write a more in-depth post about how to do IVF for polygenic selection.
There’s also Orchid (https://www.orchidhealth.com/). (And Genomic Prediction is now LifeView, https://www.lifeview.com/.)
So far as I know Orchid hasn’t actually brought a product to market yet, though they’re working on one
I wonder if (or how likely) you can sale the other embryos, and for how much.
I wonder if you want, say, 4 children, whether there are economies of scale (say: will the top 4 embryo out of 30 embryos be better than the top 2 embryos out of 15?).
I’m very interested in this space. You seem to have identify an important need: reviewing IVF clinics. I haven’t researched whether that need is already fulfilled or not, but if not, I’d be interested in thinking of a potential business model to respond to this need (and if not, doing it non-for-profit).
There are also related questions I’d like to research, such as tips on how to choose an independent sperm donor; how much regression to the mean is there (ie. to know when marginal returns becomes too low to be worth it); survey on fraction of people that would donate gamete if asked to by a friend; polygenic screening aside, is there still an economic case for freezing eggs early, etc.. All this could be documented on a specific website.
Anyway, I don’t want to scope creep this project. I’d love if you wrote a more in-depth post about how to do IVF for polygenic selection for LessWrong. Ex.: I’d like to know how egg qualities decrease with age to know when it becomes more important, and what the health risks are.
But if anyone is interested in either a) contributing to those projects, or b) consuming the value of those projects, then I invite you to reach out to me at mathieu.roy.37@gmail.com.
This is not just an intellectual curiosity.
I assume you are imagining a comparison like a one-step procedure where you implant 4 out of a batch of 30, vs a two-step procedure where you must implant 2 out of a batch of 15 each step while discarding the previous batch. The answer turns out to be yes, in this case, but not because of economies of scale (I haven’t seen anyone actually quote discounts for biopsying & genotyping large batches), but option value (and mumble mumble Jensen’s inequality mumble convexity).
The expected ranks are the same because they are i.i.d., so it doesn’t matter on average if you pick 2-of-15 twice or 4-of-30 once. But that’s just the starting point: you have a lossy pipeline to feed them into before you get 4 children out the other end, and a lot of embryos will never implant or yield a live birth. So, in the two-step scenario, when you lose your top candidate and have to pick from the small within-step pool, you get forced back to the mean more than if you had pooled them all in a single step and could retry with the next-best globally. This makes it worse. (Imagine a more extreme scenario where you are picking 1-of-2 100 times vs picking 100-of-200 once. When you lose an embryo in a 1-of-2 step, your backup embryo is at −0.56SD, because just as the expected gain from max(2) is 0.56, the expected gain from the symmetrical min(2) is −0.56SD, and with only 2 candidates, if you lose the max, all you have left is the min. Whereas if you had pooled them, then when you lose your first embryo in 100-of-200, the expected rank of fallback candidate #101 is ~0SD, just like #100 was ~0SD.) The more finegrained irreversible decisions must be, the worse the ‘ratchet’ of losses is. (This is because there are only bad surprises; if there were good surprises, the logic works the other direction, which is why the value of a bunch of separate options > the value of the mean of those options.)
Considering the unpleasantness and difficulty of egg harvesting, and the ease of storage, it doesn’t make much sense to try to do things in many stages.
Regression to a (population) mean is not relevant because you are comparing sibling embryos which are distributed around the parental mean by construction.
For many traits, returns are pretty linear. Like IQ points, it doesn’t much matter where you are, the value of another point is pretty constant. So you can just ignore that entirely and operate on marginal gains. (eg if the parents are both 130 IQ and you calculate a marginal gain of +1 IQ point from selection & that makes it profitable, maybe their genotypic mean is actually 115 IQ, but it doesn’t matter, because the marginal gain will still be +1 IQ point over the batch mean and will still be profitable).
For binary traits, you can have diminishing returns based on where the trait value is. As I note in my other comment, if a family is at very high risk for a trait like schizophrenia, then selection can be extremely valuable beyond what the average PGS % would imply; the flip side of this is that then there must be families who have below-average risk and benefit a below-average amount. However, these diminishing returns are automatically incorporated in any index score (which is how one should be selecting). If the polygenic score for SCZ is already very low, then the index component for embryos which move the SCZ score even lower will be very small, because it reduces a tiny absolute risk by a tiny absolute amount, which has a tiny expected value, and the index will prefer embryos which move more important traits.
If you want to model such scenarios to imagine conditioning on a specific example/family history, it’s easy to just switch out the population fraction for the implied fraction of the ‘parental population’ in your liability-threshold code, and everything works as before. But I generally use the average because the average is the average.
I guess I was using “economies of scale” very loosely; that’s kind of what I had in mind, but thank you for the details and explanations!
I find the mostly linear relationship between IQ and income to be surprising. If we use the odds of winning a Nobel as a proxy for “ability to make an important scientific discovery”, doesn’t the lack of average-IQ winners imply some kind of exponential relationship between IQ and scientific productivity?
If both the linear income relationship and the one described above are true, it implies an exponentially decreasing ability of high IQ people to capture the value they create.
Something like that. A straight line on log odds charts in SMPY, IIRC.
Oh definitely. This is a point Gensowski and others make: part of the reason that the income relationship does bend is that it’s hard to capture all your positive externalities even though the patenting rate etc increases. You can invent the transistor or antibiotics, but you won’t capture anywhere remotely close to 1% of the total surplus. Also part of the country-level story for why IQ looks so powerful: individuals don’t capture anything remotely approaching their full contributions (in the same way that people on the other end of the spectrum do not internalize anything remotely like the harm they do to everyone else), so the country-level correlations can be much stronger than individual-level ones.
Thanks for writing this up. I’d be interested in the more in-depth post.