Perhaps We Have a Use for These GWAS, Afterall

In my last post, I briefly critiqued this study absurdly correlating genetics to income and offered a challenge to the authors. My opinion of GWAS is obvious to anyone who skims through this blog, but it occurs to me that perhaps we might have a use for GWAS, afterall, as I recently tweeted:

Here’s a different take: The extent to which you can correlate genes to income in a society, is a direct measure of the unfairness and class stratification of that society. 

If we assume, as I do, that most genetic correlations in the behavioral genetics realm are due to population stratification, then we know that any genetic correlations would demonstrate ways in which the society is stratified. This could be in obvious ways such as racial delineations, but might also include more subtle classist issues (He/She is not from the right family...) and would be an even better way to measure more covert discrimination. By the way, I think this is provable in the sense that other societies will have entirely different loci correlated to income, a fact that will cause a lot of mental gymnastics to explain away.
If we can't prove the causality of the genes flagged in such studies, shouldn't we assume that they are an indication, of an unfair stratification of the society? If we could rid ourselves of all such genetic commonalities, wouldn't that lead us to a true meritocracy? Therefore, wouldn't it make sense and be more fair to give job and college admission preferences to those with the LOWEST polygenic scores for income? As the very "not racist" individuals who embraced this study and took me to task on Twitter pointed out, shouldn't we pursue the truth wherever it happens to lead?

Cross Ancestry Study of Schizophrenia puts out its best face (only)

I wanted to make a few quick points about this study:

Comparative genetic architectures of schizophrenia in East Asian and European populations

I tried to ask a few questions to one of the authors promoting it on Twitter, but he did not respond, so if I am incorrect about any fact, leave a comment here and I will update. Let's start with the Abstract, which is below in full:

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide-significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (genetic correlation = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations.

The reason I am showing the entire abstract is to point out what it doesn't say: That the study apparently failed to replicate any of the previous significant loci for schizophrenia (as far as I can tell). The authors simply ignore this, almost as if it is expected, yet expend a lot of time trying to make lemonade out of a lemon without telling us it was a lemon, trying to justify why schizophrenia would present in the same way in different cultures, when it is presumably due to entirely different gene sets.
In my view, you would not expect any of the loci to match between the two studies because the loci are generally false positives, probably enhanced by population stratification issues that are going to be different in these two different populations. Let me go over some of the findings and why I believe they are consistent with pop/strat, false positives after the fold:

PTSD and the GWAS Hype Machine

A new PTSD GWAS makes a few bold claims.  I think it's a good example of the kind of hype that these studies, which show next to nothing, crank out to hype their results. In this puff piece related to the study, they start with:

Large study reveals PTSD has strong genetic component like other psychiatric disorders

Which 1. It does not and 2. Is not really shown to be true of other psychiatric disorders, either, except in the same hyped fashion as this study. Now let's look at this from the same puff piece:

The study team also reports that, like other psychiatric disorders and many other human traits, PTSD is highly polygenic, meaning it is associated with thousands of genetic variants throughout the genome, each making a small contribution to the disorder. Six genomic regions called loci harbor variants that were strongly associated with disease risk, providing some clues about the biological pathways involved in PTSD.

 If it is highly polygenic, on what basis are they saying this if only 6 loci were strongly associated with disease risk (this is not even accurate, as I'll discuss in moment)? "Genome-wide, a substantial number of variants had some level of association with PTSD, showing the disorder to be highly polygenic," What this is saying is that there are other loci (presumed genetic variants) that did not reach significance, but they include through the subterfuge of "polygenic scores." There is no basis, other than the hopefulness of those doing these studies, that these below significant findings are anything more than non-significant findings. I'll  also note that none of these 6 loci were found in previous studies. Thus, this is an entirely unreplicated study. Now, let's take a look at the loci they did claim to find:

More pop/strat discussion related to polygenic scores

This article in Quanta magazine highlights a couple of recent studies in which population stratification issues are giving artificially inflated polygenic score results that don't subsequently have validity when looking at even a relatively similar population, much less diverse populations.  These were for height, which seems like the most obvious candidate for a genetic trait for which one could get a valid polygenic score, but they had to walk back previous claims.  If they can't get if for height, one should immediately ask why anyone would take such a score seriously for say, depression, or "educational attainment." They are putting a lot of time and effort into these studies and the best they can say to date is that maybe some of the correlations are valid, but pop/strat has not been ruled out as the exclusive cause of all their SNP correlations and subsequent polygenic scores.

The UK BioBank: The Beast of Pop/Strat

Here is yet another study looking at population stratification issues related to GWAS studies and polygenic score results: Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis.
They looked at geographic structure and found that the UK Biobank is subject to a lot of stratification in that regard. They looked at BMI (body mass index), household income, and educational attainment and found all of them to be subject to geographic population stratification, even with principle component analysis.  First they looked at a smaller subset of genetic data from a previous study (ALSPAC)

...we anticipate that the educational attainment of people who migrate for economic reasons differs from people who do not. Educational attainment is therefore aligned to subtle genetic differences even in this apparently geographically and ethnically homogenous population and this is co-incident with axes of ancestry.

They move on to the beast, the UK Biobank:

Polygenic Scores are the New Black?

When I was criticizing genetic linkage studies in the early 2000's,  genome-wide association studies (GWAS) were all the rage.  These appeared to FINALLY be falling out of favor, due to their propensity to generate false positives.  Good riddance...  Unfortunately, like a hydra, They return with a vengeance, and with a second head:  Genome-wide Polygenic Scores.  The idea here is that one can take  thousands of genetic markers from a GWAS and find common matches for individuals sharing a particular trait.  I can see where this idea is going to appeal to a younger set of scientist brought up in the age of artificial intelligence, but I believe that we are again looking at a clever way to suggest that traits have genetic linkages, when in fact this type of analysis, at least on my first glance, appears to do nothing of the kind.