Daniel MacArthur points me to a Newsweek article on the bankruptcy of Decode Genetics. The author describes (one of) Decode’s problems like this:
The genetics of illness turned out to be more complex than researchers expected. At deCODE and elsewhere, the new genes linked to common diseases turned out to be rare or to have only small effects on individual risk. That killed any prospect of using deCODE’s discoveries to make blockbuster drugs.
The leap–that small genetic effect sizes means no prospects of drug discovery–sounds reasonable, but is actually wrong. Here’s an example of why:
Consider a trait like, say, cholesterol levels. Massive genome-wide association studies have been performed on this trait, identifying a large number of loci of small effect. One of these loci is HMGCR, coding for HMG-CoA reductase, an important molecule in cholesterol synthesis. The allele identified increases cholesterol levels by 0.1 standard deviations, meaning a genetic test would have essentially no ability to predict cholesterol levels. By the logic of the Newsweek piece, any drug targeted at HMGCR would have no chance of becoming a blockbuster.
Any doctor knows where I’m going with this: one of the best-selling groups of drugs in the world currently are statins, which inhibit the activity of (the gene product of) HMGCR. Of course, statins have already been invented, so this is something of a cherry-picked example, but my guess is that there are tens of additional examples like this waiting to be discovered in the wealth of genome-wide association study data. Figuring out which GWAS hits are promising drug targets will take time, effort, and a good deal of luck; in my opinion, this is the major lesson from Decode (which is not all that surprising a lesson)–drug development is really hard.
