This has been done. Not to 1cm but ~3cm, and it has been reproduced by many labs all over the world
That said, most genetic prediction aren't targeting exact vales, but avoiding the worst outcomes, which is a lot easier.
Instead of saying this embryo will go grow to X cm, the claim is this embryo is 90% likely to grow to be taller than average.
Same for IQ. They don't predict the IQ, but decrease poor outcomes and increase high ones. Hell, we have had rough monogenic screening for IQ since the 1960s
Particulary the legend for figure 5:
> Activated SNPs are distributed roughly uniformly throughout the genome.
If the authors were actually identifying a genetic component to a heritable trait, I'd expect them to observe some linkage disequilibrium. And without any analysis of the SNPs (are they coding/noncoding? which genes are they associated with?) it's hard to believe that they're uncovering actual biology and not just chance correlates with external/socioeconomic factors.
I also find it difficult to trust studies when the lead author fails to disclose a conflict of interest. [2]
[1] https://academic.oup.com/genetics/article/210/2/477/5931053
[2] https://academic.oup.com/genetics/article/214/1/231/5930514
This is routinely validated on siblings. If the polygenic scores are as accurate in predicting differences between siblings (who, presumably, share substantially same environment) as they are between unrelated people, it means that they detect real, biological things, instead of just some kind of population stratification. The linked abstract, of course, mentions this, and you'd have known this if you had read the article.
Also, your assumption that socioeconomic factors are independent of genomes (that they are just "chance correlates) is also substantially wrong. Genes correlate with socioeconomic factors, because they often cause socioeconomic factors. People are not born into socioeconomic conditions randomly, they are born into socioeconomic conditions of people who share half of their genome with them.
Do you think no biological basis exists? Either way, they are still correlates, even if some aren't causative.
These models are still predictive when tested against control groups outside the training population.
Understanding whether the model is capturing biology is critical when thinking about applying it to IVF. If the model is primarily capturing socioeconomic correlates, those factors will (in most cases) be fixed for all embryos from a given pair of parents. The PRS needs to be weighting _biological_ risk conditioned on a fixed environment if its to be used ethically in this context.
In what case are you expecting the purchasers to be harmed? It seems reasonable to screen for the other factors as well if a correlation exists.
An example of Nature would be comparing well fed children of basket ball players vs children of horse jockeys.
I don't know why that would be the standard, since the amount of variation in height that's attributable to environmental factors might make that fundamentally impossible. But we can get quite close to that standard nonetheless.
And even if it's not possible yet, do you think that in 20 years we'll have no ability to predict height or intelligence from a genome? It seems very plausible to me, especially with how cheap genome sequencing is now.
Yes, that is my point.
Both intelligence and attractiveness have a significant amount of variation attributable to environmental or other external factors, and have the additional complication that they cannot be measured by a single objective unit (like height can).
> do you think that in 20 years we'll have no ability to predict height or intelligence from a genome
The quantification of intelligence is notoriously confounded by socioeconomic factors. I do not think talking about predicting a feature makes sense while we are currently unable to describe it well.
IMO dedicating funding to improving child care, healthcare+diet, and k-12 education will have a much greater impact on increasing a society's measures of intelligence and educational attainment. There's much stronger evidence that these factors are associated with improved outcomes. But, the work isn't "sexy" and doesn't come with a sci-fi flair.
Kind of like ignoring climate work in favor of Mars colonization. There seems to be a cultural bias in tech towards moonshot panaceas vs doing the unglamorous grind. It makes me think of the Bill Gates quote that "a lazy person will find an easy way to do a hard job," and while that's valuable in some contexts I don't think it's universally applicable.
If we are doing this selection of IVF embryos it is feasible to control for these confounding factors.
> IMO dedicating funding to improving child care, healthcare+diet, and k-12 education will have a much greater impact on increasing a society's measures of intelligence and educational attainment. There's much stronger evidence that these factors are associated with improved outcomes. But, the work isn't "sexy" and doesn't come with a sci-fi flair.
Source? Isn't intelligence in adulthood more correlated with your parents than any of these environmental factors? That was at least what I had recalled from twin adoption studies.
Maybe if you do it in North Korea, but US/Europe are already pretty much "maxed out" here. You can always improve things on the margin, but you're not going to see substantial gains of even d = 0.5 magnitude.
https://www.ilsna.net/resources/schoolnutrition/historyschoo....
Personally, I think this interpretation of polygenic risk scoring is a crock of irreproducible shite. I don’t think it’s your fault, I think a lot of people in the field are shilling something they don’t have for grant money, and they’ve created an exciting sci-fi yarn that’s easy for people outside the field to digest.
Height is a univariate trait that does not change after the age of ~20. If you show me someone who can take a genome and predict adult height within a centimeter, then I’ll believe they have a snowball’s chance of predicting something as nuanced and varied as “attractiveness” or “intelligence”.
I think there’s promise in applying PRS to assessing risk for non-Mendelian disease, but there’s far too many social and environmental variables at play to reliably predict these softer features. Like other people have joked, if you want a single number that best predicts educational attainment, use a zip code.