IQ and longevity claim takes a hit

This paper  calls the lie on this paper:

Arden et al.  The association between intelligence and lifespan is mostly genetic Int J Epidemiology

The claim was not only that IQ was associated with a longer lifespan, but that "genes for IQ" (a fantasy of the IQ people) were directly correlated with longevity.  Great read.  It's all starting to collapse.

Blueprint?

My review of Robert Plomin's, "Blueprint:  How DNA Makes Us What We Are".
(If you are on a tablet or phone, it's easier to read the PDF format)

Yet More Evidence that PRS is Largely a Measure of Population Stratification

Here is another study pointing to the lack of validity of polygenic risk scores.  This one was for height:

We find that the signals of selection using UKB effect-size estimates for height are strongly attenuated or absent. We also provide evidence that previous analyses were confounded by population stratification Therefore, the conclusion of strong polygenic adaptation now lacks support. 

If you aren't able to control for population stratification for something as straight-forward and quantifiable as height, then certainly you won't be able to do better with "Educational Attainment" or really any more complex psychiatric trait or mental construct.  The null here, is that polygenic scores largely measure population stratification and I would be interested in what could be demonstrated that would lead one to reject the null.  Moreover, the failure of PRS also brings into question the polygenic (and, presumably omnigenic) models for phenotypes. 

Stratification and PRS Difficulties

It is becoming clear that population stratification is  a big issue in when assessing polygenic scores.  This study demonstrates:

 Our results emphasize that we have limited understanding of the interplay between our current PS and genetic population structure even within one of the most thoroughly studied populations in human genetics. Therefore, we recommend refraining from using the current PS to argue for significant polygenic basis for geographic phenotype differences until we understand better the source and extent of the geographic bias in the current PS.

Much of the work on this study involved height, so drawing conclusions about more complex mental traits would be even more confounding.  (Would be useful to have a better understanding of the differences in population between Eastern and Western Finland). 

McCRISPR and the Collective Sanctimony of the Scientists Who Made it Happen

I don't want to add too much to the obvious ethical lapse of the recent CRISPR human guinea pig experiment by Chinese genetic scientist, He Jiankui, as there is an endless stream of outraged scientists, exemplified by this article in Nature: CRISPR-baby scientist fails to satisfy critics. I would, however, like to make a point about the collective scientific outrage, exemplified by a few quotes in the article linked above:

“I’m happy he came, but I was really horrified and stunned when he described the process he used,” says Jennifer Doudna, a biochemist at the University of California, Berkeley, and a pioneer of the CRISPR–Cas-9 gene-editing technique that He used. “It was so inappropriate on so many levels.”

So, it was "the process he used" rather than what he did.  If only he had used a more appropriate process.  Let's look at another quote:

Eugenics in Action

Now they have a company that will scan embryos for IQ related genes from GWAS studies.  The fact that the studies are trash hardly seems to matter.  They can always say that they are improving with each new study and never have any accountability.  You can never prove them wrong.  Scientists doing these studies: You are the new eugenicists and I suspect history won't treat you kindly. 

Longevity "genetics" appears to be strongly inflated due to assortative mating

This study just came out which used the Ancestry database to assess the genetic heritability of longevity, which has been previously formulated as upwards of 15 to 30%.  They found that, in fact, taking away assortative mating it is below 10%.  They used pedigrees and compared the in-law siblings.
A GWAS in such a scenario, then, would pick up a lot of extraneous, noncausal genetic associations that were really just related to commonalities from assortative mating, leading one to believe that these genes had some specific role for longevity and possibly wasting a researcher's time.
I would be interested in seeing a similar study on educational attainment, as I think it might very well show the same thing.  I have, in fact, postulated just this in previous posts on here.

A Recent Critique of PRS

This preprint (updated) does some mathematical modeling and shows that PRS, even with h2 = 1, is not as useful as previously thought.  I'll spare you the math (which I'm still trying to wrap my head around) and leave you with their conclusion:

"In summary, our investigation clears up some misconceptions on PRS and demonstrates that PRS is not as useful as its name suggests, and as powerful as the genetics community expects neither for predicting polygenic traits. We hope this research will serve as a wake up call to the genetics community in appreciating more about the challenges in studying complex polygenic traits. As such, more resources and efforts can be devoted in performing better experiments and developing better statistical methods." 

Learning about the elitist opinions of a study's authors through their dubious study

This preprint of an alleged "study, " "GENETIC CONSEQUENCES OF SOCIAL STRATIFICATION IN GREAT BRITAIN", is the kind of filth that has only been suggested in previous studies, but apparently they are feeling puffed up enough to just go full-on eugenic.  I realize that they believe that what they are saying is backed up by genetic evidence, but that's what the phrenologists thought, as well.  Realistically, I can't fully dispute all of the claims, as I am not familiar enough with the geography of England and the socio-economic aspects of their society.  Nonetheless, it's not hard to see what is happening here, if one really wanted to see it, which is that their beliefs about the genetics of superior sorts (i.e.,  people more like them) are causing them to miss the forest through the trees in terms of stratification of a society.  I am quite confident that I can tell you the authors' politics, socioeconomic and geographic backgrounds and opinions about various mental illnesses, without having met any of them.  It is an elitist view of the world, written by elitists, for the pleasure of other elitists.  They should be ashamed.  So, let's go through this, shall we:

More on the idea of "Yoking Stratification"

I posted previously about the idea of "Yoking Stratification," and that post can be viewed here.  In short, the idea is that, GWAS results can be skewed, because individuals with a particular trait often marry/mate with individuals with that same trait. The term for this is assortative mating: i.e., Tall people tend to marry tall people, people with a high BMI, tend to marry other people with a high BMI, and as one study showed, people with a mental illness tend to more frequently marry others with that same mental illness or, to a lesser extent, other mental illnesses.   This is a potential source of population stratification and I think is difficult to control for to any extent.   As I noted in the previous blog post linked above, this could therefore artificially inflate the number of SNP's found to be "significant" for the trait and the polygenic score might just be a reflection of the common genetic markers due to this selective trait mating pattern, but unrelated to the trait itself, in the same way that Ancestry.com determines your racial background via genetic markers that likely have nothing to do with being "Irish" or "Chinese."
This point was driven home recently, when a study came out  with N = 360,000 that failed to find SNP's for "left-handedness." 

"Minimal Phenotyping" to crank up your GWAS hits creates more problems

This study points out that minimal phenotyping (dumping anyone into your GWAS with a 1 or 2 question screening rather than meeting full diagnostic criteria) for major depression is getting hits that are then tied to CNS enrichment (genes found more commonly in the central nervous system, implying some brain mechanism), but the ones that were "enriched" were actually the extra ones picked up by minimal phenotyping.  This is a problem, because CNS enrichment would be expected to be more prominent for those who met the full criteria for MDD, rather than just answering a couple of questions about depression.  This implies that there are likely false positives, or at the very least, non-specific positives, unrelated to major depression.  Thus, when you try to isolate functional neurological aspects of the disorder, either to understand cause or pursue pharmaceutical options, etc., you are likely barking up the wrong tree.  CNS enrichment is also used as a backdoor method to imply the validity of the genetic variants found in particular GWAS studies related to mental disorders.
So, adding to the fact that there have been no independently replicated, significant genetic variants found for depression, to date, even with minimal phenotyping, we also cannot confirm that these genes have any relation to depression by assessing CNS enrichment.

New Depression Study Finding 102 Variants. What is Replication?

A new Depression study claiming 102 genetic variants has just come out (pre-publish).  I don't want to do an extended critique, so I will stick to a few main points:

The Good News Bible of Educational Attainment

In an effort to keep the "Educational Attainment" study relevant, we get yet more mileage from this polygenic risk score in another study.  It's a Plomin study, so you know where it's going, of course.  What strikes me most about this study is the absolute optimism and failure to consider than any of the findings can be anything other than proof of the genetics of "educational attainment," an absurd notion if you really turn off your filters for a second.  So let's go through it, a bit, shall we? 
Let's start with the opening sentence, which I think sets the scene for all of the rest that follows:

Ever increasing sample sizes and methodological advances in polygenic methods have made it possible to powerfully predict complex traits such as cognitive abilities without knowing anything about the causal chain between genes and behaviour. 

The question, of course, here, is what you are actually predicting? 

More Risk-Taking genetics

I will make a quick point related to this study:
Genetics of self-reported risk-taking behaviour, trans-ethnic consistency and relevance to brain gene expression (Strawbridge, et al.).

The study notes 8 novel loci for this so-called "risk-taking behavior" (diagnosed by asking people one question: “Would you describe yourself as someone who takes risks?”), as well as noting "...two replicated previous findings."  My quick point is that the 2 "replicated" SNP's were from a previous study by the same author using the same UK Biobank dataset (which has expanded since the last study from a few months ago).  Obviously, you would expect some "replication" when using overlapping datasets.

In short, no independently replicated SNP's from previous studies of this ilk, and some of the SNP's, even bolstered by using some of the same data, were not replicated.  Moreover, no independent analysis of the new data, which was simply folded into the old study in a meta-analysis type of format.  Again, in an attempt to bolster N, the study did not look at the new data independently.  

I might add to this critique when I've had more time to examine it in detail. 

It's Already Eugenics.

Over the past several years, I have spent  time taking on studies related to the genetics of mental illness, IQ, personality traits, etc.  I have done so for a few reasons, but largely to counter what I think is, effectively, a reductionist mindset that pervades the scientific community and, by extension, society at large, leading to a kind of eugenic attitude towards society's problems.  I believe that this is quite harmful.  My general approach has been to attack the studies directly, which have historically been relatively easy to pick apart, even for someone who does not work directly in such research.   It was my view, and still is, that the "findings" in these studies are not what is generally being suggested (genes for the traits noted above). 
Up until recently, these studies repeatedly failed to replicate at all, and the mantra from scientists was that they just needed bigger databases.  I had hoped this would not be the case, but I can see now that as the databases are getting into the millions, it appears that they are starting to get some associations that are relatively consistent (at least within specific groups). (Update: Please see Addendum 2 below.  it is still unclear to me to what extent there is replication).
What these associations mean,  of course, is open for debate and speculation.  I am of the view that they don't really have anything to do with the actual traits and are probably some form of population stratification, but even if that is the case, it does allow for a bit of statistical predictive capability.  In my opinion, this  minor predictive success will soon become asymptotic, but that alone is enough to fuel years of these studies, striving for better and better predictability.   Nevertheless, this puts me in a rather difficult position.

Progressives should not "Embrace the Genetics of Education." Nor should anyone else.

A new study (which I hope to critique in the next week or so), has all the usual suspects excited and touting it as some conclusive proof of their genetic assumptions.  I would like to specifically address this NY Times Op-Ed from Paige Harden, PhD.  I'm sure she feels that it is well-intentioned and focused on the best interests of society, but that is exactly the problem.  What is really happening in this piece is the use of genetic assumptions to justify a world view.  Let's start with the title:

Why Progressives Should Embrace the Genetics of Education

Before we even start, think about that for just a moment. "The genetics of education." 

"Yoking" Stratification. A working theory.

Recently, I've been trying to get a better handle on population stratification.  Some of this has to do with what I believe are erroneous "correlations" made by the use of polygenic risk scores.  I am under the assumption that these so-called correlations for various traits are due more to stratification issues.  Recently, there have been a few studies proposing stratification issues for apparent genetic associations that did not replicate.  I discussed this paper related to genetics and height in my previous post.
In a discussion on the intellectual bastion known as Twitter, someone sent me a link to a study discussing the issues of stratification and polygenic risk related to schizophrenia (hat tip to @Race_Realist) and it occurred to me that there might be at least a partial explanation for some of this "hidden" stratification.  Let me start by looking at this paper.

Are Polygenic Risk Scores Just a Measure of Population Stratification?

This preprint article  came out recently regarding GWAS results for height.  It created a bit of a stir amongst scientists involved in this kind of research, as it questioned the validity of previous, significant genetic associations for height.  This got me to thinking about the current Holy Grail of  GWAS researchers: The polygenic risk score.  I believe that their conclusion throws the whole concept into question.  Let me explain...

Genes for loneliness, health club attendance, bar hopping and churchgoing, all in one study!

I am attempting to critique this study:

Elucidating the genetic basis of social interaction and isolation (Day et al.)

There are many directions I can go with such a critique.  The most appealing and easiest, would be to mock it with a couple of quick quotes and be done with it.  Then, I think to myself, are there people out there that take a study like this seriously?  And, of course there are a lot of people who take a study like this seriously.  

I'm hoping, though, that there are a few scientists who have been holding onto these GWAS studies as some sort of proof of all kinds of mental constructs, who might have a bit of a crisis of confidence when reading something like this.  Perhaps they would like to dismiss this as an outlier, or misguided in some way.

Here's where they have a problem.  Because, this study was done by the book.  It has all the elements used to prove that there are genetic associations for these traits, just as studies are done to find associations for IQ, mental disorders, and personality traits.  So if you are touting GWAS studies related to any of these traits, you need to explain why your study is good and this one is ridiculous, or you need to embrace this ridiculous study.  There is no in between.

With that in mind, I will go through how this study follows the same formula as your cherished studies and you can decide which side of the health club attendance gene fence you sit on.

More Evidence That No One Knows What Is Going On.

This piece: 

"Theory Suggests That All Genes Affect Every Complex Trait," shows how little has been gleaned from all of these GWAS studies.  They simply have no idea what or how genes affect complex traits.  They have no way of explaining high heritability through this mechanism, either.  Here's an excerpt from the title:

The more closely geneticists look at complex traits and diseases, the harder it gets to find active genes that don’t influence them.

Another way of saying this is that they are all false positives.  The most ridiculous part of this is that they advocate for even larger GWAS studies to figure this all out.  C'mon.  Admit it's a failure.  Move on...

The Bell Tolls for Thee, GWAS

It appears from this paper, that a new wave of skepticism is starting related to GWAS studies.  The fact that the studies are largely false positives is not stated overtly, but you can feel some doubt from the believers.

Some excerpts:

GWAS are fast expanding to encompass hundreds of thousands, even millions, of patients (see 'The genome-wide tide'). But biologists are likely to find that larger studies turn up more and more genetic variants — or 'hits' — that have minuscule influences on disease, says Jonathan Pritchard, a geneticist at Stanford University in California. It seems likely, he argues, that common illnesses could be linked by GWAS to hundreds of thousands of DNA variants: potentially, to every single DNA region that happens to be active in a tissue involved in a disease.

Can you almost hear them saying "false positives"?

Here's another interesting excerpt:

Are you Hangry?...

I hesitate to go after studies that have a ridiculous enough premise to start with, but after critiquing GWAS studies, they are all starting to sound a bit ridiculous and I think we have a bit of a slippery slope, where there is this idea that a gene can be found for just about anything you can conceive of.  Do you like raisins?  Maybe there's a gene for that.  Do you think elephants are simply beautiful?  Perhaps it's a gene that makes you think that...
So here is a real study that was done to determine whether there is a gene for getting "hangry."  What is hangry, you might ask?  Well, of course it is the propensity to get angry when you get hungry.  Get it?  Hangry...   Here is a link to it so that you don't think I'm making it up
In any case, I'll take it on...

Another GWAS meta-analysis that suggests replications when the opposite is the case

"Since the discovery of general cognitive ability (or ‘g’) in 1904..."  (When I read a sentence like this, I am already a bit leery of what will come next.)

This critique is for the following study: 

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.  Gail Davies, et al.

This study is a meta-analysis of several studies I have already critiqued, here, here and here, as well as some new cohorts.  If I understand correctly, the new ones are the CHARGE and COGENT cohorts, but  in any case, it does not appear that any of the new datasets were ever studied independently related to cognitive ability and were simply added to the N of the meta-analyis.  I have a problem with this, which hopefully will become obvious as you read this critique. 

GWAS Catalog For Life!

Steve Pittelli <stevepittelli@gmail.com>	6:51 PM (19 hours ago)
to gwas-info

Hello there,
I was wondering what your policy is, regarding GWAS associations that are not subsequently replicated or are in some way refuted?  Do you ever remove them from the catalog or otherwise make a note of this?
Thanks,
Steve Pittelli

Annalisa Buniello <buniello@ebi.ac.uk>	9:29 AM (5 hours ago)
to me, gwas-info

Dear Steve,

Many thanks for your email and your interest in the GWAS Catalog.

As we also describe in our extraction methods https://www.ebi.ac.uk/gwas/docs/methods, individual SNP-trait associations identified in eligible publications are included in the Catalog only if they are statistically significant  (SNP-trait p-value <1.0 x 10-5) the in the overall (initial GWAS + replication) population. 

But if by not subsequently replicated you mean an association that is later found to not be valid, then the answer to your questions is no. We don’t remove the SNPs from the Catalog once they have been extracted from a previous publication that reported data from the original GWAS.

I hope this answers your question, but please don’t hesitate to contact us if you have further queries or comments on the GWAS Catalog.

Best wishes,

Annalisa

Annalisa Buniello, PhD
Scientific Curator
Open Targets and GWAS Catalog

Hard to argue with this...

"My prediction that GWAS studies would turn up many replicable genetic hits for IQ "within 10 years" was correct. <- My last tweet to you. Bye."

-Stuart Ritchie, with a very thoughtful retort to my contention that GWAS studies are likely all false positives (shortly after calling me a "crank"). At least he actually responded. Notice, by the way, that he said, "replicable" and not replicated. Cute, that.

Addendum:
"Finally, it is also possible that, although specific loci reached genome-wide significance in particular studies, there are false positives, highlighting the importance of well-powered replication studies."

From a study published two weeks later and co-authored by Stuart Ritchie.

A Quick Review of a Dyslexia GWAS study claiming two significant loci

I will try to trim this review down to its barebones for an easier read, but welcome any comments or clarifications.  The study in question can be found here.

Genome Wide Association Scan identifies new variants associated with a cognitive predictor of dyslexia 

The study is on a much smaller scale, with only a few thousand cases, so one might expect fewer false positives.  In this case, likely we have two.

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).