I’m a software developer by training with an interest in genetics. I currently run a startup working on multiplex gene editing technology.
GeneSmith
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Yes, you definitely should! Storing sperm is cheap. The procedure to freeze it is usually around $1000 and it’s typically $100-$200/year to store. I still haven’t picked a company to do it myself, but I think they’re all generally pretty good. Vitrification seems to work a bit better than conventional storage.
Yeah, this is fair. My personal take is that polygenic embryo selection changes the calculus a fair bit. A good third of my friends are now having children via IVF just to get access to embryo selection. If you’re going to do that anyways, then freezing eggs at a younger age starts to become a bit of a no-brainer.
The language on Joh Hopkins website is being deliberately conservative. The reality is we have almost no data on eggs that have been frozen longer than 10 years, so they say 10 years becuase we don’t have direct evidence for them being viable longer. What data we do have on eggs that have been frozen and then used after 4-8 years indicates time frozen has no effect on survival rates or fertilization rates. It would be very surprising to me if there’s no impact on survival after 8 years, but at 10 years they suddenly start to degrade.
You can look a little further afield for more direct evidence of the long-term efficacy of freezing for fertility preservation. There are some neat animal studies in which sperm frozen for 50 years was used to create sheep, with the authors noting that the pregnancy rate of the frozen semen was identical to the pregnancy rate for the fresh semen.
My best guess is you’d see essentially zero degradation from longer freezing periods.
The optimal age to freeze eggs is 19
Flag proposal:
Reasons why I think this is a good flag:
It’s simple
It communicates the message
People will be reminded of it every time they see a stop sign, which is a lot
I think perhaps part of the reason this post didn’t get reviewed is because it’s kind of a compressed version of a post I wrote later which can be seen here: https://www.lesswrong.com/posts/DfrSZaf3JC8vJdbZL/how-to-make-superbabies
Maybe worth reviewing this one independently. But both posts more or less came from the same talk at LessOnline 2024.
This was perhaps an understandable viewpoint to hold in June when the best publicly available IQ predictor from the EA4 study only correlated with actual IQ at .3 in the general population (and less within family, which is what matters for embryo selection).
I happened to have spoken with some of the people from Herasight at the time and knew they had a predictor that performed quite a bit better than what was publicly available, which is where my optimism was coming from.
In October they finally published their validation white paper so now I can point to something other than private conversations to show you really can get as big of a boost as claimed.
Some people are still skeptical. Sasha Gusev for example has claimed that Herasight applied a “fudge factor” to get to 20% of variance explained by adjusting adjusting for the noisiness of the UKBB and ABCD cohorts. This is based on the fact that their raw predictor explained 13.7% of the within-family variance, and they applied an “adjustment factor” to that based on the fact that the test they validated on only has a test-retest correlation of .61.
I don’t find the critique all that convincing, though my knowledge in the reliability of different psychometric methods is still pretty limited so take my opinion with a grain of salt. It’s well known that UKBB’s fluid intelligence test is pretty noisy, and the method they used to correct for that (disattenuation) seems pretty bog-standard.
They also published a follow-up in which they used another method, latent variable modeling, which produced similar results.All that being said, it would be better if there were third-party benchmarks like we have in the AI field to evaluate the relative strength of all these different predictors.
I think it’s probably about time to create or fund an org to do this kind of thing. We need something like METR or MLPerf for genetic predictors. No such benchmarks exist right now.
This is actually a real problem. No dataset exists right now that we can guarantee hasn’t been used in the training of these models. And while I basically believe that most of these companies have done their evaluations honestly (with the possible exception of Nucleus), relying on companies honestly reporting predictor performance when they have an economic incentive to exaggerate or cheat is not ideal.I think you could actuallly start out with an incredibly small dataset. Even just 100 samples would be enough to make a binary “bullshit” or “plausible” validation set on continuous value predictors like height or IQ.
Yes, please DM!
I’m thinking about writing a practical guide to having polygenically screened children (AKA superbabies) in 2025. You can now increase your kids IQ by about 4-10 points and/or decrease their risk of some pretty serious diseases by doing IVF and picking an embryo with better genetic predispositions.
There’s a bunch of little shit almost no one knows that can have a pretty significant impact on the success rates of the process like how to find a good clinic, what kinds of questions to ask your physician, how to get meds cheaply, how to get the most euploid embryos per dollar, which polygenic embryo selection company to pick etc.
Would anyone find this useful?
Do you think head transplants on to repeatedly cloned bodies could work as life extension? Even without genetic improvements to increase longevity, I can imagine switching bodies every 20-50 years becoming mundane with nearly modern surgical techniques provided we can reconnect the nervous system.
Yes, I think head transplants could extend lifespan pretty significantly if you can do them safely (they’re currently super dangerous), but I don’t think it would extend lifespan indefinitely. The brain itself ages, so unless you have a means of gradually replacing brain tissue a la Jean Hebert, you’re not going to get to indefinite lifespan extension.
Related to this, do you think parabiosis would work without all the body switching?
I mean… would you WANT your circulatory system hooked up to that of someone else? Sounds gross, weird and extremely inconvenient to me, even if you’re the one benefitting.
I can see blood transfusions if you can make artificial blood. But I can’t see parabiosis ever being a thing unless it’s in some exceptional circumstances.
There’s another interesting question related to this one which has to do with creating a gene edited clone of yourself.
If we can make an embryo from one of your stem cells, we could potentially do substantial editing of it to enhance it in various ways (perhaps to reduce disease risk or increase intelligence).
How many edits would one need to make before it is no longer really a clone of you?
What if instead we grew a genetically enhanced replacement body for you with no knee issues and better cardiovascular performance? Are you still you with a new body?
There are all kinds of interesting questions that arise with sufficiently powerful biotech. Most people don’t spend much time thining about them because the tech to make them relevant is a ways off.
I’d appreciate if you could provide links to “clear evidence of its writing style across all of these surfaces, and the entire.. vibe of the campaign feels like it was completely synthesized by 4o”
I understand it may be hard to definitively show this but anything you can show would be helpful.
It’s fine, I wouldn’t expect you to read all the comment.
There are only a few hundred IQ-related genes, and they’re found through a correlation in over 240k people, so it’s not necessary that you can just edit all these genes to set them on a “more IQ” version in a specific genome, and get maximum IQ. www.southampton.ac.uk/news/2018/03/genes-intelligence.page
There have been quite a few more genetic variants linked to IQ since this study was published in 2018. Herasight has the best IQ predictor I know of, which can explain over twice as much variance as the best predictors we had in 2018.
Of course it’s correct that in most cases we aren’t highly certain which one of a cluster of variants is actually causing the effect we observe.
But we don’t need to know. We just need reasonably good odds. Then we can edit variants with the highest combined probability of causality * effect size. That’s how we came up with the graph in the post: we didn’t falsely assume we know which of the variants are causal.
By editing more nucleotide sequences, you will only increase the risks of breaking the genome’s reading, replication, expression and other mechanisms, killing the cell. DNA isn’t merely a line of text that encodes proteins, it’s full of commands for enzymes to work with it. As a tip of the iceberg: there are 20k genes that encode 100-1000k proteins in human body, because 1 gene contains several exons (and introns), which, during transcription, are combined in different ways to encode several proteins.
Yes, that’s true if you’re doing single shot editing, which is one of the limitations for the kind of germline engineering we’re currently pursuing. But the more advanced editing protocols don’t rely on single shot editing. They use iterated CRISPR, as explained in the post, and that in turn uses multiple rounds of editing. In each round, you’re selecting cells that not only received many edits, but didn’t contain any deal-breaker mutations.
So at least in theory, there is no reason why adding more edits would break essential genomic functions.
In practice, there are a lot of headaches here: base editors result in bystander edits, prime editors result in indels, and each cell division carries a certain risk of copying errors and chromosomal abnormalities. None of these are insurmountable, but overcoming them will require a decent bit of engineering.
Do you have a link to the Habr article? I’m curious to read what people are saying.
Subtle dig at Balaji from Bannon? Interesting.
Anyone have insights into whether this is a genuine offer that could be taken up by members of the administration if they have the right attitude vs a simple power play by China to try to get more support from potential allies?
Trying to gauge how cynical to be here.
As someone who works in genetics and has been told for years he is a “eugenicist” who doesn’t care about minorities, I understand your pain.
It’s just part of the tax we have to pay for doing something that isn’t the same as everyone else.
If you continue down this path, it will get easier to deal with these sorts of criticisms over time. You’ll develop little mental techniques that make these interactions less painful. You’ll find friends who go through the same thing. And the sheer repetitiveness will make these criticisms less emotionally difficult.
And I hope you do continue because the work you’re doing is very important. When new technology causes some kind of change, people look around for the nearest narrative that suits their biases. The narratives in leftist spaces right now are insane. AI is not a concern because it uses too much water. It’s not a concern because it is biased against minorities (if anything it is a little biased in favor of them!)
There is one narrative that I think would play well in leftist spaces which comes pretty close to the truth, and isn’t yet popular:
AI companies are risking all of our lives in a race for profits
Simply getting this idea out there and more broadly known in leftist spaces is incredibly valuable work.
So I hope you keep going.
On the topic of predictability and engineering – sure, we can influence predispositions, but the point I was trying to make is epistemological: the level of uncertainty and interdependence in human development makes the engineering metaphor fragile. Medicine, to your point, does aim to “figure out” complex systems – but it’s also deeply aware of its limitations, unintended consequences, and historical hubris. That humility didn’t come through strongly in your piece, at least to me.
Perhaps so. But the default assumption, seemingly made by just about everyone, is that there is nothing we can do about any of this stuff.
And that’s just wrong. The human genome is not a hopeless complex web of entangled interactions. Most of the variance in common traits is linear in nature, meaning we can come up with reasonably accurate predictions of traits by simply adding up the effects of all the genes involved. And thus by extension, if we could flip enough of these genes, we could actually change people’s genetic predisposition.
Furthermore, nature has given us the best dataset ever in genetics, which is billions of siblings that act as literal randomized control trials for the effect of genes on life outcomes.
If I felt that the world was suffering from excess genetic engineering hubris, then I might be more cautious in my language. But that is not in fact what is happening! What is happening is humanity is being far too cautious, mostly because they hold a lot of false assumptions about how complex the genome is.
We have this insane situation in reproductive genetics right now where tens of thousands of children are being born every year with much higher genetic predispositions towards disease than they should have because doctors don’t understand polygenic risk scores and would rather implant embryos that look nice under a microscope.
do we really know enough about gene–environment interactions to be confident in the long-term effects of shifting polygenic profiles at scale?
It depends what your standard is: if the bar we need to meet is “we can’t make any changes that might result in unpredictable effects”, then of course we can’t be confident.
But if the bar is “we know enough to say with high confidence improve the life of the child”, then we are already there for small changes, and can get there relatively soon for much larger ones.
Hi Nabokos,
I appreciate the comment. I think many academically inclined follks probably have similar views to yours. Let me explain my thinking here:
What troubles me most is how little attention is paid to emotional attachment, which is arguably the cornerstone of healthy development. This reads more like a plan for growing babies in vitro than raising actual children.
If I were to go into the ins and outs of emotional attachment, this already long post would have been at least twice the length. And seeing as I am not an expert in the area, I hardly think it would have been useful to the average reader.
Of course emotional attachment is important. It’s one of the most important things for happy, healthy childhood development.
But there are many good books on that topic and I don’t think everyone who writes about any aspect of childhood or babies needs to include a section on the topic. If you think there are good resources people here should read, please post them!
You can’t predict or engineer how a baby will turn out.
It’s certainly true you can’t predict EXACTLY how a baby will turn out, but you CAN influence predispositions. In fact, most of parenting is about exactly this! How to change your child’s environment to influence the kinds of things they do and the sort of person they become.
Honest question: do you have kids?
Sadly I do not have kids yet! I hope to have them in the next few years.
Also, much of the terminology you use feels superficial or misapplied. Science and education aren’t just about memorizing buzzwords – they require deep understanding, and that takes time, context, and mentorship.
I don’t see how this is at odds with genetic engineering.
I’m a medical doctor, and what strikes me again and again is how people assume that complex systems – like human beings – can be “figured out” with enough reading or clever design
I think it’s fair to say that the entire field of medicine is one big attempt to do exactly this. I don’t see how gene editing differs from what we try to do with drugs.
(e.g. hypertension isn’t caused by a single gene)
Where exactly did I say this?
But did it ever occur to you that these ‘optimized’ new people might come with new problems and diseases? Biology tends to work like that: you push on one part, something else breaks.
Yes, I have in fact considered this. There are several different ways to assess how big of a problem this could be:
You can look at genetic correlations between different diseases to see if there’s some kind of tradeoff. When we do this we see that the correlations are generally (though not universally) weak, and when they do exist, they actually tend to work in your favor, meaning decreasing the risk of one disease is more likely than not to result in a tiny reduction of others.
You can just look directly at people who have low genetic predispositions to various diseases and see if they have any issues at different rates from the general population. And the answer here again is generally “no”.
Together these imply that it should in fact be possible to significantly improve health, intelligence, and other aspects of what makes life good without necessarily making that many difficult tradeoffs.
Also, just based on what we know about evolution it shouldn’t actually surprise us that much that we can increase overall performance, especially when there has been as big of a shift in the environment as what we’ve experienced in the last few hundred years.
It would be nice if your critique actually addressed some specific concrete issues you have with the post or its ideas. The one specific example you gave (me thinking hypertension is caused by one gene) isn’t even something I said. I’m not even sure where you’re getting that idea from.
I think you make a reasonably compelling case, but when I think about the practicality of this in my own life it’s pretty hard to imagine not spending any time talking to chatbots. ChatGPT, Claude and others are extremely useful.
Inducing psychosis in your users seems like a bad business strategy, so I view the current cases as accidental collateral damage, mostly borne of the tendency of some users to end up going down weird self-reinforcing rabbit holes. I haven’t had any such experiences because this is not the way I use chatbots, but I guess I can see perhaps some extra caution warranted for safety researchers if these bots get more powerful and are actually adversarial to them?
I think this threat model is only applicable in a pretty narrow set of scenarios: one where powerful AI is agentic enough to decide to induce psychosis if you’re chatting with it, but not agentic enough to make this happen on its own despite likely being given ample opportunities to do so outside of contexts in which you’re chatting with it. And also one where it actually views safety researchers as pertinent to its safety rather than as irrelevant.
I guess I could see that happening but it doesn’t seem like such circumstances would last long.
I’m sorry to hear it man. The good news is you actually still have a chance for a child even if you wait another decade. It will become harder (for multiple reasons, not just sperm quality), but you still have a chance.
I wish you the best of luck in finding a job. That will probably help you have kids much more than sperm freezing.