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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).

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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.

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