*This is a cross post from Evolving Economics.

Evidence from twin studies implies that economic and political traits have a significant heritable component. That is, some of the variation between people is attributable to genetic variation.

Despite this, there has been a failure to demonstrate that the heritability can be attributed to specific genes. Candidate gene studies, in which a single gene (or SNP) is examined for its potential influence on a trait, have long failed to identify effects beyond a fraction of one per cent. Further, many of the candidate gene results fail to be replicated in studies with new samples.

An alternative approach to genetic analysis is now starting to address this issue. Genomic-relatedness-matrix restricted maximum likelihood (GREML – the term used by the authors of the paper discussed below) is a technique that looks to examine how the variance in traits can be explained by all of the SNPs simultaneously. This approach has been used to examine height, intelligence, personality and several diseases, and has generally shown that half of the heritability estimated in twin studies can be attributed to the sampled SNPs.

A new paper released in PNAS seeks to apply this approach to economic and political phenotypes. The paper by Benjamin and colleagues shows that around half the heritability in economic and political behaviour observed in behavioural studies could be explained by the array of SNPs.

The authors used the results of recent surveys of subjects from the Swedish Twin Registry, who had their educational attainment, four economic preferences (risk, patience, fairness and trust) and five political preferences (immigration/crime, foreign policy, environmentalism, feminism and equality, and economic policy) measured. The GREML analysis found that for one economic preference, trust, the level of variance explained by the SNPs was statistically significant, with an estimate of narrow heritability of over 0.2. Two of the political preferences, economic policy and foreign policy, had narrow heritability that was statistically significant, with heritability estimates above 0.3 for each of these. The authors noted that as the estimates are noisy and GREML provides a lower bound, the results are consistent with low to moderate heritability for these traits.

Educational attainment was also found to have a statistically significant result, although the more precise measurement of educational attainment and the availability of this data across all subjects made that result more likely.

This result is corroboration of the evidence from twin studies and provides a basis for believing that molecular genetic data could be used to predict phenotypic traits. However, one interesting feature of the GREML method of analysis is that after conducting this analysis with one sample, the data obtained does not assist in predicting the traits for someone out of the sample. This technique shows the potential of molecular genetic data without directly realising those results.

As a comparison, the authors examined whether any individual SNPs might predict economic or political preferences, but found none that met the significance test standard of 5×10^-8. Such a high level of significance is required to reflect the huge number of SNPs that are being tested.

The authors also conducted the standard comparison between monozygotic (identical) and dizygotic (fraternal) twins, which resulted in heritability estimates consistent with the existing literature, although with a much larger sample than typically used. Looking through the supplementary materials, the major surprise to me was that the twin analysis suggests that patience has low heritability, with a very low correlation between twins and almost no difference between monozygotic and dizygotic twins (in fact, for males, dizygotic twins were more similar).

The authors draw a few conclusions from their work, many which reflect the argument in a Journal of Economic Perspectives article from late last year. The first and most obvious is that we should treat all candidate gene studies with caution. Hopefully some journals that insist on publishing low sample size candidate gene studies will pay attention to this. Where they are going to be conducted, you need very large samples, and significantly larger than are being used in most studies being published.

Meanwhile, they are still hopeful that there can be a contribution from genetic research, particularly if the biological pathways between the gene and trait can be determined. This might include using genes as instrumental variables or as control variables in non-genetic empirical work. The use as instrumental variables does require, however, some understanding of the pathways through which the gene acts as it may have multiple roles (that is, it is pleiotropic). They also suggest that the focus be turned to SNPs for which there are known large effects and the results have been replicated.

On element of analyses of political and economic preferences that makes me slightly uncomfortable is the loose nature of these preferences. For one, the manner in which they are elicited from subjects can vary substantially, as can the nature of the measurement. Take the 2005 paper by Alford and colleagues on political preferences, which canvassed 28 political preferences. Many of the views are likely to change over time and be highly correlated with each other. And why stop at 28?

As a result, it may be preferable to take a step back and ensure that data on higher level traits are collected. I generally consider that IQ and the big five personality traits (openness, conscientiousness, agreeableness, extraversion and stability) are a good starting point and are likely to capture much of the variation in political and economic preferences. For example, preferences such as patience are likely to be reflected in IQ, while openness captures much of the liberal-conservative spectrum of political leaning. Starting from a basis such as this may also give greater scope for working back to the biological pathways.

The Social Science Genetics Association Consortium is doing some work in harmonising phenotypes across large samples. Hopefully their work will lead in this direction.

I’ve been commenting on internet porn for nearly 10 years. One reason is that as someone who graduated high school in the spring of 1995 I’m probably in the very last cohort of American males for whom pornography was an item subject to scarcity. Those who are 2-3 years younger already experienced a totally different world. The furtive quest to find a friend of a friend whose dad was less than vigilant in guarding his porn stash was a rite of adolescent male passage in my cohort, but would seem totally laughable by 1997. There’s a lot of commentary on the effect of porn on society and sexual relations, but from what I can tell nothing much has really changed between then and now, except that hardcore porn has become harder. Before I see hard data I’m skeptical that American males accept more perversion because of watching porn. Read the Kinsey Reports; farm boys long knew some farm boys lost their virginity to animals.

All this must be kept in mind when reading pieces tinged with moral panic, such as this one in The New York Times, So How Do We Talk About This?, which details the reaction of parents to their children discovering porn. There are few specific elements which strike me as manifestly stupid. For example:

Bonnie, a university administrator in North Carolina with a teenage son and two stepdaughters, realized only after discussing the matter that she and her husband had been sending unintended messages by emphasizing safety and self-protection with the girls and limits with her son.

“Later, we realized how terribly, albeit unconsciously, sexist that was,” she said.

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Just a heads up, Dr. Joseph K. Pickrell has begun moving on the Malagasy Ancestry Project. More information:

The genetics of the Malagasy people have been essentially unstudied. Analysis of Y chromosome and mitochondrial DNA markers have corroborated the lingustic evidence that the Malagasy result from admixture between southeast Asian and east African populations [1,2]. However, no genome-wide data from Malagasy individuals has been analyzed to date (with the exception of the individuals in this project).

Our goal is to address a number of questions about the genetics of the Malagasy. These include, but are not limited to:

1. What fraction of ancestry in the Malagasy is from Africa rather than southeast Asia?
2. Does this fraction vary geographically and/or ethnically?
3. Who were the populations that first settled Madagascar?
4. Was Madagascar settled once from southeast Asia, or multiple times?
5. Can we use genetics to more precisely date the arrival of African populations in Madagascar?

Our approach to this project is to use data contributed from Malagasy individuals who have been genotyped by a personal genomics companies. If you would like to contribute your data, please contact us.

Current results are available from the tabs at the top of this site, and will be updated as the project progresses.

Again, thanks to the people who contributed to genotype the second person. Second, there were several complaints in the origin threads that these individuals were not representative. If this is so, get some genotypes!

I stopped reading much in the area of personality and behavior genetics a few years back. The main reason is I had a really hard time believing there were very good quantitative measures of many of the traits. A secondary issue, though probably nearly as important, is that some friends were making it clear that they strongly suspected that a lot of the studies in the area of behavior genomics were “underpowered” in a statistical sense. These two issues gnawed at me to the point where I pretty much threw my hands up in the air. Mind you, I accept that personality is substantially heritable. But just because something is heritable does not mean that it is obvious that you’ll be able to detect “the gene” implicated in the variation of the trait. I accepted decades of findings in behavior genetics. But it didn’t seem like we were going anywhere beyond it.

Now a new paper out in PNAS uses genomics to shed light on this issue in the same manner as with intelligence or height. The paper is The genetic architecture of economic and political preferences, and it is free to all. The two primaries takeaways are:

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I’m not big into music, being of the aesthetically retarded set, but as I age memory becomes more important, and that is strongly colored by music. The 80s anthems of the Beastie Boys were part of the cultural firmament for me, but at that stage I was more of a Transformers kind of guy. In contrast, So What’cha Want takes me back to the summer of ’92 in a very visceral way. I had come to an age where the Beastie Boys were no longer social white noise, but the rhythm of a life which seemed to roll out before me with possibilities (OK, let’s keep it real, at the time the possibilities were quite proximate and driven by hormonal rushes of puberty).

Sahul 10,000 years ago

John Hawks has a very long rumination on the story of blonde Melanesians which came out last week. If I can read between the lines I think some of the implications dovetail with John’s thesis in his 2007 paper on adaptive acceleration. But I’ll leave the deep reading of tea leaves to those better versed in such affairs. Rather, I will comment on two issues. The first is specific. I believe that the TYRP1 R93C allele responsible for blonde hair among the Solomon Islanders is going to be found to be the same one responsible for blonde hair around New Guinea and among some Australian Aboriginals.

There are several reasons why I suspect this. First, these Oceanian populations do seem to be a distinctive clade. There are some disagreements among geneticists as to whether they are the descendants of the first settlers of Oceania in totality, or whether they’re a compound lineage. The natural historical details need to be teased apart, but there’s no doubt that they’re a distinct and separate phylogenetic lineage in relation to other human populations (with some admixture from Austronesians in the case of Melanesians). Second, the phenotype of rather light hair, and dark skin, is striking and parallel among all these populations. It is not entirely impossible that random genetic drift could stumble upon an architecture which results in such a suite of characteristics, but I’m generally skeptical of this possibility of having occurred several times in the same human lineage, when it seems relatively rare in other populations (the loci associated with light eyes and light hair in Eurasians seem to have some effect on skin color as well, so it is difficult, though not impossible, to have  very dark skin and light hair). Third, as noted in John’s post, this seems an “old” variant. A new mutation which rose rapidly in frequency should have a lot of associated markers flanking it (ergo, high linkage disequilibrium). Again, we need to take into account the joint information here; there seem several Oceanian populations where the allele is at high, but still minor, frequency (assuming it is the same allele). Oceanian populations, especially those verging toward Melanesia, have low effective population sizes. If this is an old variant I am curious as to why it has not fixed in any of the daughter populations (recall that if it did fix, and admixture recently drove it below ~100 percent, there would be a lot of linkage disequilibrium). Therefore, I think we have to seriously consider the possibility that balancing selection is maintaining this polymorphism in the Oceanian populations. This does not entail that the selection is targeting the hair color phenotype, though it may.

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Long time readers know that I’m generally OK with reification as long as we don’t take it too seriously. And we do that all the time. An “object” is really only an “object” in a human-sense. Reduced down to particle physics it is an altogether different entity. But on the human-scale asserting that a chair is indeed a chair, rather than cellulose, etc., (or now, polymers), and further down basic macromolecules, is a useful “fudge.” Similarly, I’m generally skeptical of the idea that we have a clear & distinct model for what a “species” is. The framework is very different when you’re talking about prokaryotes, as opposed to plants, as opposed to mammals. The question is not species, but what utility or instrumental value does the category or class species have?

For most of the stuff I’m concerned with, the messy shapes of reality which are the purview of biological science, we are all fundamentally nominalists in our metaphysic. We may accept that we’re idealists in the sense of cognitive or evolutionary psychology, but human intuition does not make it so. The categories and classes we construct are simply the semantic sugar which makes the reality go down easier. They should never get confused for the reality that is, the reality which we perceive but darkly and with biased lenses. The hyper-relativists and subjectivists who are moderately fashionable in some humane studies today are correct to point out that science is a human construction and endeavor. Where they go wrong is that they are often ignorant of the fact that the orderliness of many facets of nature is such that even human ignorance and stupidity can be overcome with adherence to particular methods and institutional checks and balances. The predictive power of modern science, giving rise to modern engineering, is the proof of its validity. No talk or argumentation is needed. Boot up your computer. Drive your car.

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Chatting with Dan MacArthur on twitter about the old days of Usenet, and arguing with Creationists in the days of yore (MacArthur actually flipped a Creationist!). Here’s a toast to the innocence of that bygone age around the turn-of-the-century….

(separate “shout out” to those who remember me from soc.history.what-if)

I haven’t watched much of Henry Louis Gates Jr.’s Finding Your Roots series. It seems like Gates has kind of created a mini-empire in genealogical series on PBS. More power to him, but it hit diminishing returns for me a long time ago. But I see clips online here and there. And something which I saw really kind of disturbed me. From what I can gather Gates regales his subjects with their DNA results, and tells them their ancestral quanta fractions. Nothing too amazing. But it seemed clear to me that when Gates referred to “European”, “Asian” and “African” ancestors, he was communicating to the audience that these quanta really represented those exact populations!

I assume that the geneticists Gates works with explained to him the falsity of this typology. I also understand that the television format results in natural license. But Henry Louis Gates Jr. has produced lots of these shows now. He has the leisure to unpack the concepts for the lay audience. As it is, it seems he is repeating misconceptions of model-based clustering algorithms. Misconceptions mind you which persist even within the biological community. But that doesn’t make it any better.

For those who aren’t getting the essence of what I’m saying, above are my 23andMe results. I’m 60 percent European, 40 percent Asian. But those fractions were produced assuming that I could only be a combination of Northern European, East Asian, and West African! Computational algorithms do not return results of the form “I’m sorry, but the input is going to generate useless output.” So they came back with these results, which are highly misleading. Adding another reference population from South Asia makes the results much more plausible. The take-home is that the terms for each quanta are only mnemonics. They should never be taken literally.

Thought I would pass these on. A graduate student at Rice is trying to raise some funds for research, Genopolitics: Your Genes Affect How You Vote!. The methodology is a twin study:

To test this, I’ll track how genes affect attitudes during the 2012 US Presidential election by running several surveys of twins. Why twins? Well, there are two kinds of twins: identical twins (called monozygotic, or MZ) and fraternal twins (called dizygotic, or DZ). MZ twins share 100% of their DNA, but DZ twins share only about 50% of their DNA just like normal siblings. Every twin is born around the same time as his or her co-twin, so each pair of twins shares a common upbringing. If politics is mostly about upbringing (as traditional theories would have us believe), then fraternal (DZ) twins should be just as similar on average as identical (MZ) twins. But if genes do play a role in political attitudes alongside upbringing, then DZ twins should be less similar to each other than MZ twins, since MZ twins share more of their genes. So by tracking attitude changes during the election, if the attitudes of identical twins change together more than the attitudes of fraternal twins, this would suggest that genes play a role in political attitude change.

Secod, Genomes Unzipped put up a very complimentary review of openSNP. I just went in and added a bunch of phenotypes for me. I’d say openSNP is one of those attempts to bridge the space between the type of people who find 23andMe a bit overwhelming, and those who are comfortable using plink and phasing their genotypes.