There's a classic blues song Georgia on My Mind that is ironically appropriate. The current Nature has two reports of mapping studies of autism traits (and there is reference to a third study published elsewhere). The study gained a lot of attention (or was given a lot of hype, depending on your view of these things). It isn't the first such story to get attention. These studies are treated as if they are major findings, and tend to reinforce the idea that GWAS are a powerful approach to understanding the genetics of complex disease. Despite the evidence, we can't seem to get GWAS off our mind.
Of course 'major' is a subjective judgment but after filtering the rhetoric in the media, and looking at what the actual papers and authors say, it turns out that, as before, these new findings account for less than 1% of autism cases (and such estimates are often upwardly biased for various statistical reasons). And the genes were known before as potentially relevant. And the different studies did not find the same genes.
This is par for the course, unfortunately, because autism is a sadly damaging disease both to the persons affected and those who care about them. One doesn't want to dismiss any findings that might materially help. But as even the authors of one of the studies pointed out in comments to the media (e.g., here), this is further evidence that GWAS are a fading tool, though that is not how the news media portrayed the result.
The sad fact is that in autism, as in many other diseases, there is plenty of generic evidence for genetic risk factors playing some role (because the disorder seems to cluster somewhat in families), yet the prevalence has grown rapidly only in a recent few decades. Yes, there is the lingering question of whether prevalence has actually risen, or just the probability that a child will be diagnosed with one of a broadened spectrum of disorders, but prevalence has continued to rise rapidly even in the last few years, while the definition of the spectrum has been the same, which makes it seem less likely that rates are simply reflecting increased or altered diagnosis. This shows that even if there are gene-environment interactions, the trait is preponderantly due to environmental factors--unfortunately, despite all sorts of guesses and wild guess, the factors are not yet known.
GWAS and other mapping approaches held out hope to many, and even to some extent to skeptics, that diseases like autism for which there was no good physiological understanding could reveal genes, and hence mechanisms that would lead both to understanding and eventually to treatment. But this hope really hasn't been borne out.
The current typical response (and that of the authors of these studies) is that we need larger studies of various genetic sorts. As we've said a few times in this blog, and as even some GWAS proponents believe, that is most likely to mean much more work to find much less, and unlikely to really crack the problem. Larger studies will in principle find rarer things, but that only works if the increase in study size isn't accompanied by even greater risk heterogeneity (an improved signal to noise ratio). Even complete DNA sequence can't automatically pull the rabbit out of the hat, because the more DNA examined the more variable sites one will find.
Since it is likely that much of what we're looking for is regulatory, and we don't yet know very well how to identify such sequences, we'll be awash in DNA data with no clearer biological picture. There are some subtle points afoot here. They have to do with the statistical nature of these studies. It's possible in principle that even with densely-marked GWAS no marker will have detectably strong association with the true causal site (or, worse, sites) in a chromosome region. Full DNA sequence would in principle include the site(s) directly, but the plethora of data may well obscure it. Generally, if individual signal is strong enough to be breakthrough-generating, we should have seen it by now.
So, each new study like these recent ones presses home the dual points: large association studies simply do not seem to be the way to understand these complex traits, and instead we need some clever person to show us a better way.
We need to get GWAS off our mind (though it doesn't seem likely to happen any time soon). Being negative about GWAS may seem unseemly. But it is an attempt to be constructive. These problems are so worth studying that they are worth studying right rather than just studying again and again in the same unsatisfactory way.