I'm a software developer by training with an interest in genetics. I currently run a startup working on multiplex gene editing technology.
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I'll give a quick TL;DR here since I know the post is long.
There's about 20,000 genes that affect intelligence. We can identify maybe 500 of them right now. With more data (which we could get from government biobanks or consumer genomics companies), we could identify far more.
If you could edit a significant number of iq-decreasing genetic variants to their iq-increasing counterpart, it would have a large impact on intelligence. We know this to be the case for embryos, but it is also probably the case (to a lesser extent) for adults.
So the idea is you inject trillions of these editing proteins into the bloodstream, encapsulated in a delivery capsule like a lipid nanoparticle or adeno-associated virus, they make their way into the brain, then the brain cells, and the make a large number of edits in each one.
This might sound impossible, but in fact we've done something a bit like this in mice already. In this paper, the authors used an adenovirus to deliver an editor to the brain. They were able to make the targeted edit in about 60% of the neurons in the mouse's brain.
There are two gene editing tools created in the last 7 years which are very good candidates for our task, with a low chance of resulting in off-target edits or other errors. Those two tools are called base editors and prime editors. Both are based on CRISPR.
If you could do this, and give the average brain cell 50% of the desired edits, you could probably increase IQ by somewhere between 20 and 100 points.
What makes this difficult
There are two tricky parts of this proposal: getting high editing efficiency, and getting the editors into the brain.
The first (editing efficiency) is what I plan to focus on if I can get a grant. The main issue is getting enough editors inside the cell and ensuring that they have high efficiency at relatively low doses. You can only put so many proteins inside a cell before it starts hurting the cell, so we have to make a large number of edits (at least a few hundred) with a fixed number of editor proteins.
The second challenge (delivery efficiency) is being worked on by several companies right now because they are trying to make effective therapies for monogenic brain diseases. If you plan to go through the bloodstream (likely the best approach), the three best candidates are lipid nanoparticles, engineered virus-like particles and adeno-associated viruses.
There are additional considerations like how to prevent a dangerous immune response, how to avoid off-target edits, how to ensure the gene we're targeting is actually the right one, how to get this past the regulators, how to make sure the genes we target actually do something in adult brains, and others which I address in the post.
What I plan to do
I'm trying to get a grant to do research on multiplex editing. If I can we will try to increase the number of edits that can be done at the same time in cell culture while minimizing off-targets, cytotoxicity, immune response, and other side-effects.
If that works, I'll probably try to start a company to treat polygenic brain disorders like Alzheimers. If we make it through safety trials for such a condition, we can probably start a trial for intelligence enhancement.
If you know someone that might be interested in funding this work, or a biologist with CRISPR editor expertise, please send me a message!
It's probably worth noting that there's enough additive genetic variance in the human gene pool RIGHT NOW to create a person with a predicted IQ of around 1700.
You're not going to be able to do that in one shot due to safety concerns, but based on how much we've been able to influence traits in animals through simple selective breeding, we ought to be able to get pretty damn far if we are willing to do this over a few generations. Chickens are literally 40 standard deviations heavier than their wild-type ancestors, and other types of animals are tens of standard deviations away from THEIR wild-type ancestors in other ways. A human 40 standard deviations away from natural human IQ would have an IQ of 600.
Even with the data we have TODAY we could almost certainly make someone in the high 100s to low 200s just with gene editing an a subset of the not-all-that-great IQ test data we've already collected:
If one of the big government biobanks just allows the data that has ALREADY BEEN COLLECTED to be used to create an IQ predictor, we could nearly double the expected gain (in fact, we would more than double it for higher numbers of edits)
All we need is time. In my view it's completely insane that we're rolling the dice on continued human existence like this when we will literally have human supergeniuses walking around in a few decades.
The biggest bottleneck for this field is a reliably technique to convert a stem cell to an embryo. There's a very promising project that might yield a workable technique to do that and the guy who wants to run it can't because he doesn't have $4 million to do primate testing (despite the early signs showing it will pretty plausibly work).
If we have time, human genetic engineering literally is the solution to the alignment problem. We are maybe 5-8 years out from being able to make above-average altruism, happy, healthy supergeniuses and instead of waiting a few more decades for those kids to grow up, we've collectively decided to roll the dice on making a machine god.
We have this incredible situation right now where the US government is spending tens of billions of dollars on infrastructure designed to make all of its citizens obsolete, powerless and possibly dead, yet won't even spend a few million on research to make humans better.
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1EDIT: The full post is now up
Oh boy do I have a response for you.
I think it may be possible to significantly enhance adult intelligence through gene editing.
The basic idea goes something like this:
- There are about 20,000 genetic variants that influence fluid intelligence
- Most of the variance among humans is determined by the number of IQ-decreasing minor alleles someone has.
- If you can flip a significant portion of those IQ-decreasing alleles to their IQ increasing counterparts, you can likely significantly increase someone's intelligence
- The effect size is going to be smaller than it would be if you made those same edits in an embryo because some of the genes you're targeting are only active during development. But my best guess at the moment is that we would still expect a gain of several standard deviations. However I am not very certain about this because I have not yet gotten access to SOTA genetic predictors of intelligence.
There are a million little details to get into, especially those related to the delivery of an editing vector, avoiding a negative immune response and avoiding off-target edits. But after researching this with a couple of collaborators for the last month and a half, I am starting to think this is going to be possible.
What's more, there are already several clinical trails underway right now that plan to use the same gene editing delivery platform that I have in mind for this kind of adult intelligence enhancement.
IF one could get this protocol to work, the actual experience of the procedure would be kind of magical: you'd literally get an intravenous injection (and possibly some medication to temporarily suppress your immune system) and your fluid intelligence would improve by a couple of standard deviations within about a week. I suspect it would take further months to years for the full benefits of the change to become clear, since crystallized intelligence is what really determines outcomes.
It's difficult to predict how long it will take to roll out something like this in an actual human trial, but I think it's plausible we could have something working within 5 years, which might be soon enough to significantly impact the trajectory of AI.
I'm working on a longer post about this, so I'll ping you when it goes up.
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1One data point that's highly relevant to this conversation is that, at least in Europe, intelligence has undergone quite significant selection in just the last 9000 years. As measured in a modern environment, average IQ went from ~70 to ~100 over that time period (the Y axis here is standard deviations on a polygenic score for IQ)
The above graph is from David Reich's paper
I don't have time to read the book "Innate", so please let me know if there are compelling arguments I am missing, but based on what I know the "IQ-increasing variants have been exhausted" hypothesis seems pretty unlikely to be true.
There's well over a thousand IQ points worth of variants in the human gene pool, which is not what you would expect to see if nature had exhaustively selected for all IQ increasing variants.
Unlike traits that haven't been heavily optimized (like resistance to modern diseases)
Wait, resistance to modern diseases is actually the single most heavily selected for thing in the last ten thousand years. There is very strong evidence of recent selection for immune system function in humans, particularly in the period following domestication of animals.
Like there has been so much selection for human immune function that you literally see higher read errors in genetic sequencing readouts in regions like the major histocompatibility complex (there's literally that much diversity!)
but suggests the challenge may be greater than statistical models indicate, and might require understanding developmental pathways at a deeper level than just identifying associated variants.
If I have one takeaway from the last ten years of deep learning, it's that you don't have to have a mechanistic understanding of how your model is solving a problem to be able to improve performance. This notion that you need a deep mechanical understanding of how genetic circuits operate or something is just not true.
What you actually need to do genetic engineering is a giant dataset and a means of editing.
Statistical methods like finemapping and adjusting for population level linkage disequilibrium help, but they're just making your gene editing more efficient by doing a better job of identifying causal variants. They don't take it from "not working" to "working".
Also if we look at things like horizontal gene transfer & shifting balance theory we can see these as general ways to discover hidden genetic variants in optimisation and this just feels highly non-trivial to me? Like competing against evolution for optimal information encoding just seems really difficult apriori? (Not a geneticist so I might be completely wrong here!)
Horizontal gene transfer doesn't happen in humans. That's mostly something bacteria do.
There IS weird stuff in humans like viral DNA getting incorporated into the genome, (I've seen estimates that about 10% of the human genome is composed of this stuff!) but this isn't particularly common and the viruses often accrue mutations over time that prevents them from activating or doing anything besides just acting like junk DNA.
Occasionally these viral genes become useful and get selected on (I think the most famous example of this is some ancient viral genes that play a role in placental development), but this is just a weird quirk of our history. It's not like we're prevented from figuring out the role of these genes in future outcomes just because they came from bacteria.
11It's a good question. The remarkable thing about human genetics is that most of the variants ARE additive.
This sounds overly simplistic, like it couldn't possible work, but it's one of the most widely replicated results in the field.
There ARE some exceptions. Personality traits seem to be mostly the result of gene-gene interactions, which is one reason why SNP heritability (additive variance explained by common variants) is so low.
But for nearly all diseases and for many other traits like height and intelligence, ~80% of variance is additive. somewhere between 50 and 80% of the heritable variance is additive. And basically ALL of the variance we can identify with current genetic predictors is additive.
This might seem like a weird coincidence. After all, we know there is a lot of non-linearity in actual gene regulatory networks. So how could it be that all the common variants simply add together?
There's a pretty clear reason from an evolutionary point of view: evolution is able to operate on genes with additive effects much more easily than on those with non-additive effects.
The set of genetic variants inherited is scrambled every generation during the sperm and egg formation process. Those that need other common variants present to work their effects just have a much harder time spreading among the population because their benefits are inconsistent across generations.
So over time the genome ends up being enriched for additivity.
There IS lots of non-additivity happening in genes which are universal among the human population. If you were to modify two highly conserved regions, the effects of both edits could end up being much greater or much less than the sum of the effects of the two individual variants. But that's also not that surprising; evolution has had a lot of time to build dependencies on these regions, so we should expect modifying them to have effects that are hard to predict.
You also had a second question embedded within your first, which is about second order effects from editing, like increased IQ resulting in more mental instability or something.
You can just look at people who naturally have high IQ to see whether this is a concern. What we see is that, with the exception of aspbergers, higher IQ actually tends to be associated with LOWER rates of mental illness.
Also you can see from my chart looking at genetic correlations between diseases that, with a few exceptions, there just isn't that much correlation between diseases. The set of variants that affects two different diseases are mostly disjoint sets.
2OpenAI's continued practice of publishing the blueprints allowing others to create more powerful models seems to undermine their claims that they are worried about "bad actors getting there first".
If you were a scientist working on the Manhattan project because you were worried about Hitler getting the atomic bomb first, you wouldn't send your research on centrifuge design to german research scientists. Yet every company that claims they are more likely than other groups to create safe AGI continues to publish the blueprints for creating AGI to the open web.
Is there any actual justification for this other than "The prestige of getting published in top journals makes us look impressive?"
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
"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.
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.
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Medication is taken stimulating egg production
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Eggs are extracted
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Eggs are frozen and unfrozen at a later date (optional but necessary for polygenic screening)
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Eggs are fertilized, turning them into embryos
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Embryos grow to day 5 blastocysts, at which point they are biopsied
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Day 5 blastocysts are biopsied for polygenic screening (and to see if they're chromosomally normal)
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The euploiod embryo with the highest polygenic score is implanted.
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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.
Billionaires read LessWrong. I have personally had two reach out to me after a viral blog post I made back in December of last year.
The way this works is almost always that someone the billionaire knows will send them an interesting post and they will read it.
Several of the people I've mentioned this to seemed surprised by it, so I thought it might be valuable information for others.
I've started a gene therapy company, raised money, opened a lab, hired the inventor of one of the best multiplex gene editing techniques to be our chief scientific officer, and am currently working on cell culture experiments with the help of a small team.
I may write a post about what's happened at some point. But things are moving.