Another Genetics and Intelligence GWAS/Meta-Analysis

I have been hoping to look at more studies based on intelligence and genetics, and tried to reach out to scientists and authors touting genetic evidence for intelligence to cite specific studies that they find convincing.  I have received no reply to my request, so for now I will pick and choose as I see fit.  I take, and prefer, requests, however.

This critique is for the following study:

A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence (Hill et al., 2017)

It is another GWAS/meta-analysis study.  Anyone who is following my critiques on this blog will probably assume, correctly, that I am going to harp on the lack of a random control.  I'll get to that, but wanted to make a few comments, first.

Another Depression GWA/Meta-Analysis claims 44 risk variants for Major Depressive Disorder

This is a critique of this study, titled:   

Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depressive disorder

After only a couple of weeks and, now, my 6th critique of a genetic study, I once again have the same issue before I even get started on the study:  There is no randomized control.

The Pittelli Test for Non-Randomness in a GWAS

I have been making a suggestion for how Genome-wide Association Tests could be checked upfront to determine the likelihood that their alleged genetic correlations are not simply random false positives.  As I've pointed out previously, when you look at hundreds of thousands of loci or SNP's with potentially millions of study participants, it is very likely that some (if not all) of your "significant" p values were only random, false positives.  I want to formalize my suggestion (and, for the fun of it, name it after myself).
Here is my proposal:

Educational Attainment genes or a whole lot of nothing

I took a look at this study, because I was told that there are some really fantastic studies related to genetics and intelligence/educational attainment that have come out since 2015.  This one is from 2016.  I am very unimpressed:

Genome-wide association study identifies 74 loci associated with educational attainment

Each of the studies I've looked at so far involving GWAS have a fundamental problem right up front and this one is not an exception.

Depression GWAS Study, 2018

This will be my first critique of a depression GWAS study (Link Here):

Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathway (Howard, et al.)

Let me start by discussing the first sentence of this study:

"Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies."

"Replication" Is Not a Malleable Standard

As I start reading over these Genome-wide Association Studies, I am seeing a lot of attempts to "replicate" their findings within their study.  This is something I assume is being done in order to dispense with the annoying problem of putting out studies that are never replicated.  "How do they do this"?, you might ask.   And this is quite interesting.  They use meta-analysis.  They take old studies that actually had negative results, combine them and compare the meta-analysis results to the alleged positive findings.  (Addendum:  I now will refer to these attempts at replication as "Hindsight Replication").  "Do they have to match the findings of the study, with statistically significant results"?, you might ask. 

Risky Business: Making your own diagnoses, backed by hundreds of false positives.

For the same reasons that I am hesitant to waste time on silly studies, I think it is worthwhile to not let these things go unchecked, and I'm not seeing anyone else trying to debunk this foolishness, so in addition to more traditional studies, I will take what I think is a much needed critical eye to a study  like this one:

Genome-wide study identifies 611 loci associated with risk tolerance and risky behaviors

ADHD and Genetic Testing

Advertisement for a quick-dissolve, long-acting amphetamine from a psychiatry trade journal:  

Ah yes, "Designed With Patients in Mind."

I understand the difficulty that comes with a child that meets the criteria of ADHD and I don't want to dismiss out of hand, the pharmaceutical "solution" in such cases, but I think it's a good diagnosis to discuss in regards to genetic correlation tests, to address some of the larger implications.  The fact that we are talking about children makes it all the more important to get it right.

GWAS/Meta-Analysis 78,308 (Sniekers): A critique of this study claiming numerous genetic correlations to intelligence

Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence

 I had someone cite this study as strong evidence for specific genetic linkages to intelligence.  I'm getting a lot of, "A lot has changed in the field lately," types of comments, which are maybe a bit condescending, but not entirely off base.  To be honest, I'm surprised at how little change there has been since I was critiquing these studies 15 to 20 years ago.  They still jump to the same conclusions.  They still have no sense that their studies are producing false positives.  Some of the terminology has changed and, really, they are a bit overly technical and harder to read (or I'm just getting older).  Despite the fact that I disagree with the conclusions of this study, as I will lay out shortly, there is something to be said for dumbing down your points a bit, unless your goal is a bit of technical obfuscation (not accusing, just saying...).

Publishing Bias, but look a little closer

Over the past few decades, hundreds of "genetic links" have been "found", largely through genome-wide association studies, in which the researchers look at hundreds of different genetic loci to find 1 or 2 that are more highly correlated in their study group vs. their control group, whether this be for intelligence, schizophrenia, "novelty-seeking", etc.  As I've already mentioned, these studies tend to crank out a lot of false positives, which even the scientific community is coming to terms with, as can be seen here.  So, since almost all of the hundreds of alleged genetic linkages have not been replicated, we might expect to see a lot of studies in the literature that give negative results, refuting the previous positive results.   In actuality, although we occasionally do see that, it is the exception rather than the rule.

Bipolar Disorder. What are we really talking about?

As a clinical psychiatrist, I have a lot of thoughts about studies, genetic or otherwise, of the various mental disorders.  Before we even look at the merits of a genetic association study for a particular mental disorder, I think it's worth looking at a few diagnoses and some of the possible pitfalls of doing a study specific to a diagnosis.  Some diagnoses might have a more "organic" flavor to them (Schizophrenia, Schizoaffective Disorder, Bipolar Disorder) and one might assume that they would lend themselves better to genetic association study.  So I'll start with one of those: Bipolar Disorder.

The Mechanism: Dead Genes or Fast Moving Enzymes?

In my last post, I discussed the mathematical unlikelihood of polygenic contributions to a heritable trait or disorder.  Let's say you simply refuse to give up the ship.  You just want to believe that there is a magical cascade of interactions between tens of thousands of genes that confer the phenotype you are looking for.  Shortly, I will have a question for you...

The Contradiction Between "Polygenic" Traits and High Heritablity

When I was critiquing genetic linkage studies back in the day, almost all of the studies would include something in the abstract about the trait they were looking at (intelligence, schizophrenia, depression, etc.) being “highly heritable,” as if this somehow lent credence to the results of the study.  After repeated failures to replicate, a new view of the genetic bases of of these disorders began to emerge and is now quite popular and accepted as a given by most scientists in the field, as far as I can tell.  I think it is best exemplified by a quote from this piece:

“Complex traits are just that—complex. Most traits are incredibly polygenic, likely involving tens of thousands of loci. These loci will act via a vast number of pathways”.

Meta-Analysis: Making your bad results good for fun and profit.

As mentioned in my last post, genome-wide association studies generated many positive "correlations" for genetic loci related to a particular disorder, that could not be consistently replicated.  This should have tipped them off that they were dealing with false positives.  It didn't, though.  They were determined to turn their lemons into lemonade.  They often did this by using meta-analysis.  The idea behind meta-analysis is that you combine the results of numerous studies, effectively increasing your sample size to give you a more accurate big picture of all the results.  I won't say that this approach is never useful in science, but in these instances, it was nothing more than an attempt to get a positive result.  There are two common approaches to using meta-analysis to bolster your negative results.  The first is focusing on a single genetic polymorphism.  Those performing the meta-analysis would focus their attention on a particular genetic locus for a particular disorder using all the published studies (worth noting that there may have been other studies, more likely with a negative result, that didn't get published).  Here is why you are going to create a false positive result:

Genome-wide Association Studies and why they are so prone to false positives

I thought that Genome-wide Association Studies (GWAS) were going out of favor, but it looks like they are most of what genetic researchers are cranking out, which is puzzling.  I was always surprised that they were given any credence at all as anything other than a screening study.  It always seemed likely to me that they were only producing false positives and it was frustrating when I wrote letters to journals and the authors would respond in a way that made it clear they did not understand basic concepts of statistics (when I get a chance, I'll try to round up all my previous letters to the editor that survived the peri-internet age of the early 2000's).  Let me explain why they produced so many false positives:

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.

Redemption Is an Infinite Loop of Despair.

In the early 2000's, I was writing letters to various psychiatry journals to debunk studies being done alleging to show genetic loci correlated to specific mental illnesses, personality traits, intelligence, etc. .  It was clear to me that these studies were nothing but false positives.  See an example I wrote to the British Journal of Psychiatry here.  I was largely disregarded and even mocked.  In one instance, I was told that they wouldn't print my letter unless I got two other psychiatrists to vouch for my character.  I kid you not.  I told them to pound salt.  I believe that at least one of my supervisors prevented me from getting a supervisor position based on these letters.  I got frustrated with the whole thing, decided to focus on my career, and stopped paying attention, so I never noticed this article, lovingly titled, "Most Reported Genetic Associations with General Intelligence Are Probably False Positives," essentially making the same point 10 years later. 
Really, this opens up an old wound.  I don't feel redemption.  In fact, as I dip my toe back in this pond, I can already see that I will receive the same reception or worse.  I am retired now, so I don't really give a crap.  It will take me awhile to catch up to the current lingo, but I'm already seeing the same basic flaws I saw at that time and I am going to take it down.  They can write another paper about why it was all wrong in 2028 but, by that time, they will all be onto the next great thing.

The "Merit" Genes

This paper, entitled "Genetic influence on social outcomes during and after the Soviet era in Estonia,"  purports to show that, after the fall of communism in Estonia, genetically superior individuals were able to rise to the top, because the new capitalistic society was based more on merit (meritocracy).