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My suspicion has always been that this sort of data–common SNPs from all comers and no specific phenotype collection–is not very useful for any sort of drug design. And if it is, publicly available data will be just as good as 23andMe's larger amount.

It was a bet worth trying, IMHO, but always a risky bet. And with bio, you don't find out if your bets work for a decade or more, because the iteration cycle is 10x slower than software for businesses/consumers.

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My suspicion has been that SNP array data is not that useful for drug discovery. They’re targeting the most common/variable SNPs, which I suspect don’t have a large health effect (except for maybe late in life, otherwise how would they get passed down). I would suspect the more valuable targets would be rarer, or arise de novo (as is common in cancer, eg driver mutations).

The effect size of common SNPs is not informative about the effect of drugging their related genes. For example, the common variants near HMG-CoA reductase have very small but significant (confidently nonzero) effects. Yet drugging HMG-CoA reductase can reduce LDL cholesterol by ~40-50% (statins).

deCODE Genetics, whose history is very interesting and worth reading [1], was bought by Amgen based on this premise.

Note, however, that SNPs like the one you pointed out are relatively infrequent. Amgen was expecting a two digit % improvement in their pharma pipeline by using GWAS insights.

[1] https://en.wikipedia.org/wiki/DeCODE_genetics

> Note, however, that SNPs like the one you pointed out are relatively infrequent.

If you mean that SNPs with small effect sizes don't always point to useful drug targets with big druggable effects, that is possible, but this remains an open question and is the subject of intensive research right now.

Yes, I agree. The trick is probably to find cell-specific SNPs located in regulatory regions so that there are no off-target effects. Massive screens using single-cell perturbations will help to gain some insights.

You’re right that rarer SNPs have big effect sizes. However the problem is that they’re rare so you don’t make much money treating ppl with rare diseases.

There are SNPs that have significant clinical impact and alter the downstream translation and associated with poor outcome.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129253/

They could help in stratifying patients and strategically targeted therapy. They can't be easily targeted (drugged) drirectly but they could lead to therapeutics if I understand correctly.

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