Thursday, May 9, 2019

Conjuring some within-family pop strat

Are you ready to hear something? I want you to see if this sounds familiar: any time you try a decent crime, you got fifty ways you're gonna f**k up. If you think of twenty-five of them, then you're a genius... and you ain't no genius. 
-Mickey Rourke to William Hurt in Body Heat

In a recent Twitter discussion, wherein I suggested that "Educational Attainment" GWAS/PGS are largely bogus, bolstered by population stratification and assortative mating, someone noted:  "Sooo, you'll bet against EA3 explaining even 1% in any new European sample within families?" The implication here is that, despite the many studies coming out lately suggesting the extent to which polygenic scores are subject to stratification issues, if even 1% is explained in a "within family" PGS, then at least something is genetic. This is quite a lowering of the bar from the supposed 13% from EA3 (the third large educational attainment GWAS study), which I assume from some of the recent studies (here and here), they see dwindling away. Anyway, something is better than nothing, so this is a way to suggest "something" is there. Certainly, when looking at "in family" GWAS/PGS, you are going to expect significantly less population stratification, since you are looking at individuals that share the same parents, upbringing and DNA.  For example, a recent study showed significant attenuation when looking at "in family" (which surprisingly, considering the authors, they attributed to socioeconomic confounders). Nevertheless,  even a smaller percentage is still something and now they might claim, at the cost of a predictive dilution, that they eliminated all stratification issues by using "within-family" analysis. Well, I'm not so sure about that, as I will discuss below the fold.

Wednesday, May 8, 2019

Another study questions polygenic scores

This new study:

Variable prediction accuracy of polygenic scores within an ancestry group



is yet another in the long line of studies showing that polygenic scores are replete with problems like population stratification and assortative mating. It buries the lede a bit, in that it takes another swing at the so-called "educational attainment" genetics, probably because I sense the authors don't want to completely give up the ship, but let me make a few points about the study.

The Depression Gene that Wouldn't die

This is a good piece about a gene variant that was presumed for a couple of decades to be related to depression, with hundreds of studies surrounding it, leading to more and more theories of how it effects depression. The gene was 5-HTTLPR which is presumably related to serotonin and gave everyone the feels, because it validated the use of Prozac and similar serotonin based drugs. Then it turned out to be bogus. I believe I was asked specifically about this gene in my psychiatry board exam. Another take home message from this is that if you are jumping on some new study purporting to find a gene or genetic variants for a mental disorder, put it in a drawer for a few years and see if it holds up. They never do, but they are never wrong.

Sunday, May 5, 2019

Hoping for a House of Cards

I've already done a review of Robert Plomin's "Blueprint," but I take it a step further in this piece in Logos, pondering whether this is really all they've got and, if so, where that leaves the field of psychiatry,  were the whole GWAS/Polygenic Score research behemoth, which has hogged so much of the mental and material resources for furthering the field, finally hits its dead end? You might call it a fantasy piece.

Wednesday, May 1, 2019

Is This a Successful Study for Bipolar Genetics? That's how they are billing it.

A "new" GWAS came out for Bipolar Disorder. As yet, I have only seen the abstract, but I wonder whether I need to see more? Let me comment on a few things:
"Eight of the 19 variants that were genome-wide significant (P < 5 × 10−8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity."
Is that really what it's consistent with? If you have variants that were found to be significant in previous studies and you include the data from those studies in your current study, even if the effect size was small (and, the power now increased), you should expect most of them to retain significance, even if they weren't significant in the new data set independently. The fact that half of them have lost significance is a good indication that most or all of them were false positives to begin with. Moreover, once again, why not do an independent GWAS (I'm assuming they did not) of the new data and compare it to the old data?
Now let's look at the very next sentence: