On these genetics blogs I am constantly hearing this mealy-mouthed blather about how complex human genetics is and that no individual genes are important. You sound like agnostics lecturing atheists. I can just imagine you lecturing doctors for prescribing drugs that target neurotransmitters. If a gene cannot have an important effect on a behavior, then why should a single type of molecule have an important effect on a behavior? You are all pointing to these pointless GWAS that focus entirely on SNPs, neglecting gene expression despite the ironic title of the blog. When a study attacked the depression gene, your blog attacked candidate gene research. When that study was disproved, your blog was silent. Candidate gene research gives us a small amount of immediately useful information. GWAS research gives us hope that someday, hopefully, we shall know a lot more about a more significant genetic contribution to behavior. Great, but that is not low-hanging fruit. This wouldn’t bother me if there was some attention being paid in the serious genetics blogosphere to candidate gene research. Blogs like Gene Expression used to do that. Now you have become Apostles for Ignorance.

The problems that are often touted about GWAS (lack of replication, lack of results) can be at least partially attributable to the following: (1) poor choice of cases (ie: for diseases with too loose a definition/characterization), (2) much too low a sample size (really, for low effect sizes, the power to detect effects is quite low at the typical 2000-5000 sample size level…the real sample sizes for direct effects should be a MINIMUM of ~10,000, and for epistasis, you need at least double that if not 5X that number of samples), (3) population effects. I’m not saying that you cannot detect anything from GWAS with low sample sizes…just look at the cannonical GWAS on AMD by Klein et al. But the cases must be very carefully chosen and the contribution from any single gene detected must be at least moderate for such a study design to work.

It’s a shame to see articles written and theories espoused as though there can only really be one approach to understanding genetic variation and architecture. I propose that we’re likely to find that many Mendelian diseases have some lower level of contribution from other genes (“modifier genes” or small epistatic interaction effects that contribute to severity and penetrance, or age of onset, that kind of thing); complex diseases have some combination of effects from relatively common polymorphisms of small effect, rare mutations, epistasis, epigenetics and gene-by-environment interactions. In short, there is a continuum of genetic architecture and few diseases will fit entirely within the paradigm of “common disease common variant” or “classic Mendelian trait”.

To get more to the point of this particular post, I also find that the economic implications of the work into different populations will be intriguing. However, trying to tie everything to genetic causes without considering environment would be a very large mistake, particularly when it comes to economic behavior (call it “development” or whatever…it comes down to behavior). At the point where such studies could actually be useful, I think we’ll see a confluence of collaborative studies between geneticists, economists, and either cultural anthropologists or sociologists. Let’s just hope that people keep their conclusions on the conservative side of data interpretation.

This quote assumes much more than is warranted. Even if we do get large numbers of fully sequenced DNA samples, what would it mean? We know just about nothing about how DNA affects the behavior. In fact, we know very little about how DNA affects disease.

They under-sample rare variants and DNA regions translated into non-coding RNA, which seems to orchestrate most organic development in vertebrates. Or it may be that thousands of small mutations disrupt body and brain in different ways in different populations. At worst, each human trait may depend on hundreds of thousands of genetic variants that add up through gene-expression patterns of mind-numbing complexity.

Epicycles and more epicycles.