On non-genic disease polymorphism
Daniel MacArthur discusses genome-wide association studies which has so far mainly found disease associated polymorphisms outside of genes.
The claim in question is that the tendency of GWAS to find disease associations outside of protein-coding genes is somehow a problem; but, as p-ter notes, there’s perfectly plausible reasons for disease risk variants to be found in non-coding regions.
Indeed, I think most of us working in genomics have seen the proliferation of non-coding hits in GWAS studies as a positive, in that it seems to be teaching us something new and unexpected about the underlying biology of human variation.
There is a problem with polymorphisms outside of genes. We generally have no idea how they functionally affect us to increase or decrease the disease risk. If we have no idea what a given polymorphism means in terms of function, it is harder to work out; we don’t really know where to start with figuring it out.
As far as I can see, though, that is the only problem with that.
That’s it, though, as far as I can see. If the polymorphism is statistically significant associated with the disease, and we can replicate this in independent data, then that is what the data is saying. It might be inconvenient, but tough luck! No one promised us that this would be easy.
Quoting from Gene Expression:
Their answer to this rhetorical question is that common SNPs (used on current genotyping platforms) are generally nonfunctional. The alternative, the evidence for which I’ll present here, is that our ability to predict functional SNPs is poor. In the phrase “no known function”, the emphasis should be on the word “known”.
GWA studies have been a great success in locating polymorphisms associated with disease, that we can actually replicate.
Sure, we are working with very large data sets here, and false positives is a major problem (see e.g. here and here), but this is a problem we can handle.
And sure, GWA lets us find only the CD/CV type of disease associations and not all diseases will follow this pattern, but with the success of GWA studies so far, I think it is fair to say that there are enough to be found here to make it worthwhile!