Evidence-based psychiatric genetics, AKA the false dichotomy between common and rare variant hypotheses
Someone on the BGAnet Facebook group posted about this paper (I can't find a full online copy, the link is just to the abstract.)
Peter Visscher and colleagues make the point that old-fashioned genetics language borrowed from Mendelizing rare gene disorders doesn't do a good job describing the genetics of more complex disorders like schizophrenia and depression, and of course they are right. Penetration, hetergoeneity, phenocopy make sense for disorders caused by a single gene or a countable handful of genes, but not for the kinds of complex, mega-polygenic disorders and normal traits that psychiatric geneticists study today.
But I don't think they take the argument far enough. They wind up optimistic about the genetics of schizophrenia and depression. Not optimistic that they are heritable-- there is no controversy about that-- but optimistic that studying the genetics of depression via GWAS will sooner or later produce something that looks like the biology of depression. I doubt it. The obstacle, as Visscher et al show, is that right now the SNPs for schizophrenia with the biggest effect sizes account for much less than a percent in the variance of liability, depression even less. Even if you add up all the SNPs that have been reliably associated with schizophrenia you get only about a percent. So Visscher et al draw a comparison with height, which five years ago was at about the same place SNP-explanation-wise, and now, thanks to some truly enormous samples, is all the way up to 10%.
But so what? What is to be learned by examining associations between phenotypes and individual SNPs that account for miniscule percentages of the variance. OK, if you have half a million participants they are statistically significant, but where is the evidence that over the long run finding more and more tinier and tinier statistically significant SNPs is going to add up to a theory of anything? Maybe at some point something points to some kind of biological pathway which can then be studied using other methods. If so, fine, but I can't get over the impression that the primary motivation for all of the GWAS is to re-document the by now obvious fact that one way or another all these things are heritable, that SOMEHOW all that genetic variation produces a correlation in schizophrenia liability of .7 in identical twins. But we already knew that.
One piece of old-fashioned genetic language that Visscher et al don't give up is "causal variant." SNPs work because they are in linkage disequilibrium with the "causal variants" that actually cause height and schizophrenia. In some very literal sense that has to be true, if all the word causal means is, "is associated with." What if there is a variant that predisposes young children to interact less successfully with their mothers, which causes them to get less food, which causes them to be a little shorter. Is that a "causal variant" for height? The real conclusion about massively polygenic developmental systems is that the idea of causal variants doesn't really apply. Genes are inputs into complex developmental systems, out of which phenotypes emerge on the other end. In an absolute sense, there are no "genes for" anything, and no genes that qualify as "causes" for anything.
One quick test I apply to all bio-genetic accounts of complex behavioral phenotypes. Every time Visscher et al refer to schizophrenia or depression, substitute "marital status." It is heritable, about as heritable as depression. Do you doubt that a GWAS with half a million participants would find a few significant associations? How could it be otherwise? But is there any sense to be found in talk about "causal variants" for divorce? Are there human traits to which this whole line of genetic explanation does not apply? If so, how do we know the difference? Once upon a time, everyone thought quantitative genetics would do it.... some things would turn out to be really genetic, others, well, whatever the opposite of genetic was supposed to be. It didn't work, and it isn't working now.