Parental Wealth is Pop Strat

 This paper discusses how parental wealth is a strongly prone to assortative mating. 

...parental wealth homogamy is high at the very top of the parental wealth distribution, and individuals from wealthy families are relatively unlikely to partner with individuals from families with low wealth. Parental wealth correlations among partners are higher when only parental assets rather than net wealth are examined, implying that the former might be a better measure for studying many social stratification processes. Most specifications indicate that homogamy increased in the 2000s relative to the 1990s, but trends can vary depending on methodological choices. The increasing levels of parental wealth homogamy raise concerns that over time, partnering behavior has become more consequential for wealth inequality between couples.

The reason this is important in terms of genetic studies, is that it creates population stratification that will no doubt present itself as genetic correlations, giving the impression that genes exist for income (yes such studies have been done), as well as other things like educational attainment, when all that is really happening is that the rich are keeping it in the family, so to speak.  They noted that it was less common, but still an issue in Denmark, where the study was done, but worse in other countries (US and UK, for example). Thus these GWAS that purport to show such genetic correlations are likely really demonstrating that certain social/ethnic groups have an unfair proportion of wealth. By this token, if you were going to use "polygenic scores" for educational attainment to decide who should get into an elite school, it would more fair for those with the lowest scores to be given preference...

The Tarot of Reading Neuroimaging

 I'm linking to this piece discussing the lack of consistency among researchers reading and interpreting Neuroimaging studies, because I think this highlights why it is akin to phrenology or perhaps Tarot card readings. 

 Research Teams Reach Different Results From Same Brain-Scan Data 

 "When 70 independent teams were tasked with analyzing identical brain images, no two teams chose the same approach and their conclusions were highly variable. "

The fact that these are static neuroimages gives the impression of some sort of consistent, definitive interpretation. But Tarot Cards are also the same deck no matter who is laying out the cards. "It's in the cards," they will say. But, in truth, it is in the card reader. 

 

My Four Laws of the Behavioral Genetics Fallacy

 I discussed these in more length, here as a response to Eric Turkheimer's Three Laws of Behavior Genetics. But just wanted to lay them out in one short post (credit Turkheimer for the second, which is his third).

My Four Laws of the Behavioral Genetics Fallacy:

1. Any behavioral trait studied within a society will be correlated genetically to specific subpopulations, regardless of whether these genetic correlations are directly related to the trait.

2. A substantial portion of the variation in complex human behavioral traits is not accounted for by the effects of genes or families.

3. Differences in human behavior, intelligence and personality are not accounted for by structural or functional differences in the brain.

4. Advancements in understanding human behavior and psychology require inner exploration from the scientist, the subject or both.

Some Comments on "The Three Laws of Behavior Genetics" (and the two other laws)

Twenty years ago, Eric Turkheimer wrote an often cited paper titled:

Three Laws of Behavior Genetics and What They Mean

This paper is still often cited today and perhaps has taken on a life of its own, with a more deterministic interpretation than Turkheimer apparently intended and for which he recently clarified in a blog post his original intent. Nonetheless, much of the criticism of his paper comes from those in the genetic determinism camp, with the extremes being the "race scientist" crowd. So, since I sit on the other end of the see saw from the genetic determinists with Turkheimer poised somewhere in the middle, I will weigh in with my own thoughts about his three laws, as well as the two additional non-Turkheimer laws added into the soup. In the process of this, I will posit my own Four Laws of the Behavioral Genetics Fallacy. First, let's lay out the three laws that Turkheimer posits:

First Law. All human behavioral traits are heritable.

Second Law. The effect of being raised in the same family is smaller than the effect of genes.

Third Law. A substantial portion of the variation in complex human behavioral traits is not accounted for by the effects of genes or families.

I agree with perhaps one and a half of these laws. I’ll start with my half agreement with the First Law. For starters, I take issue with the use of the term “heritable,” because the term predates genetics and has had many different meanings and interpretations over the years, as this article points out:

The term ‘heritability,’ as it is used today in human behavioral genetics, is one of the most misleading in the history of science. Contrary to popular belief, the measurable heritability of a trait does not tell us how ‘genetically inheritable’ that trait is. Further, it does not inform us about what causes a trait, the relative influence of genes in the development of a trait, or the relative influence of the environment in the development of a trait.

Genetic Prediction of Schizophrenia via Polygenic Risk Score Has No Clinical Utility

 A new study from Schizophrenia Bulletin tested various risk factors on a group of individuals in a Netherlands. In addition to other risk factors, they used Polygenic Risk Score (PRS) developed from previous studies. This summarizes the results:

We calculated the relative contribution of each (group of) risk factor(s) to the variance in (change in) mental health. In the combined model, familial and environmental factors explained around 17% of the variance in mental health, of which around 5% was explained by age and sex, 30% by social circumstances, 16% by pain, 22% by environmental risk factors, 24% by family history, and 3% by PRS for schizophrenia (PRS-SZ). Results were similar, but attenuated, for the model of mental health change over time. Childhood trauma and gap between actual and desired social status explained most of the variance.

 This is a weak result all around, but particularly bad was the PRS which had a predictive success of 0.5 % (3% of 17%). Thus, just knowing a person's age and sex was almost twice as predictive as the PRS. If the person had a history of pain or other medical complaints, that alone was 4 times more predictive for schizophrenia. This is simply a dismal failure and the continued hope that this will be good enough to be clinically useful is little more than wishful thinking. Realistically, to be clinically useful, it would have to be 25 to 50 times better than this and I am guessing it has come close to peaking.

Yet More UK BioBank Pop Strat Issues Noted.

 There are so many studies coming out noting population stratification issues that it is hard to keep track. This is an interesting preprint looking at CAD and BMI:

Fine-scale population structure confounds genetic risk scores in the ascertainment population

From the Abstract:

we investigated the accuracy of two different GRS across population strata of the UK Biobank, separated along principal component (PC) axes, considering different approaches to account for social and environmental confounders. We found that these scores did not predict the real differences in phenotypes observed along the first principal component, with evidence of discrepancies on axes as high as PC45. These results demonstrate that the measures currently taken for correcting for population structure are not sufficient, and the need for social and environmental confounders to be factored into the creation of GRS. 

One interesting aspect of this study, I think, is that it highlights how it can be necessary to have a good working knowledge of the population you are studying.  This plot is striking in that respect:

This was confined only to white European descent, but still had this kind of stratification. A larger point here is that more and more pop/strat issues arise, many of which were not accounted for in earlier studies and perhaps should lead to corrections. Moreover, for those doing GWAS in the future, particularly in the UK BioBank, it is worth having a bit of skepticism that at least some of what you are seeing is pop/strat that has yet to be recognized.