[timy2shoes]

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).

[carbocation]

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).

[nextos]

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

[dumb1224]

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.

[sjducb]

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.