> 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”.
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
I haven't previously read the Lello paper [1] that review is citing, but a quick skim makes me skeptical.
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]
> it's hard to believe that they're uncovering actual biology and not just chance correlates with external/socioeconomic factors.
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.
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.
Nature can still be important for even highly heritable traits. For example, the size of a person's vocabulary is highly heritable, but a feral human will have very limited vocabulary. Such traits still have a very strong biological basis.
The control on those are in places that have relatively standard nutritional distribution. The environment obviously plays a strong role, just look at the height difference in populations between north and South Korea.
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
https://arxiv.org/pdf/2101.05870.pdf