CD/CV and Goldstein

Everyone seems to be talking about this NY Times interview with David B. Goldstein (Gene Sherpas, biomarker-driven mental health, Adaptive Complexity, John Hawks …)

In the proud tradition of blogging, I will add my voice to the noise.

The common disease / common variant hypothesis

The arguments concern association mapping and the so-called Common Disease / Common Variant (CD/CV) hypothesis.  The CD/CV goes like this: a lot of common diseases are late-onset, so we do not expect selection to be strong against the genetic factors underlying them. This, combined with the recent expansion in the human population leads us to expect that a lot of common diseases to be caused by relatively common variants.

If the hypothesis is true, then we should be able to locate these common variants since we can tag all common variants in the genome with relatively few markers, and we can type these using SNP chips.

If the hypothesis is false, then we are screwed. We probably need complete re-sequencing and some heavy duty statistics to get anywhere.

Out of convenience more than anything, people chose to believe the CD/CV to be true, and started projects such as HapMap to map the common variation in the genome.  Based on this map, companies developed chips to tag all variation genome wide, and disease studies used these chips to do genome wide scans.

Goldstein argues:

It takes large, expensive trials with hundreds of patients in different countries to find even common variants behind a disease. Rare variants lie beyond present reach. “It’s an astounding thing,” Dr. Goldstein said, “that we have cracked open the human genome and can look at the entire complement of common genetic variants, and what do we find? Almost nothing. That is absolutely beyond belief.”

If rare variants account for most of the genetic burden of disease, then the idea of decoding everyone’s genome to see to what diseases they are vulnerable to will not work, at least not in the form envisaged. “I don’t believe we should do more and more genomewide association studies for common diseases,” Dr. Goldstein said. Instead, he suggested, the “missing heritability” might be tracked by thoroughly studying the genome of specific patients.

I would say the jury is still out on this one, but it is clear that the CD/CV isn’t as common as it was hyped to be.  We can only explain a small percentage of the heritability of diseases with the variants found so far.  Still, we have discovered more variants that we can replicate within the last year or two than in all the time up to genome wide scans, so writing off genome wide association studies completely is a bit extreme, in my view.

No, CD/CV is not the full story, but some common variants exist, cause we have found them!

The real question is, of course, how much heritability is explained by common variants and how much by rare variants.  Right now, we simply do not know.  The power to detect even common variants is limited, so there might be more out there to find.  On the other hand, it is hard to believe that the vast majority of the heritability is caused by common variants since we still can only explain very little of it, so some rare variants must be involved.

In the coming few years we will probably figure this out, and that is exciting indeed.

Common disease and selection

Now as for variants behind common diseases being selectively (near) neutral — part of why they can be common in the first place — that is an interesting question.

I personally think that selection is playing a larger part in the story of common diseases than we think, and I look forward to learning this story.

Are we seeing common variants because bottlenecks have reduced selection strength so rare variants — otherwise selected against —  have managed to increase in frequency by drift? Are we seeing common variants because they are selected for by some balancing selection? Are they hitch-hiking  on beneficial variants?

We are already hearing about interesting findings in here (Helgason et al. 2007, Blekhman et al. 2008) and we will learn much more in the future.

We live in interesting times indeed, and now is not the time to abandon genome wide association studies.