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.

End Update

Over the past few days I’ve been very disturbed…and angry. The reason is that I’ve been reading Misha Angrist and Dr. Daniel MacArthur. First, watch this video:

In the very near future you may be forced to go through a “professional” to get access to your genetic information. Professionals who will be well paid to “interpret” a complex morass of statistical data which they barely comprehend. Let’s be real here: someone who regularly reads this blog (or Dr. Daniel MacArthur or Misha’s blog) knows much more about genomics than 99% of medical doctors. And yet someone reading this blog does not have the guild certification in the eyes of the government to “appropriately” understand their own genetic information. Someone reading this blog will have to pay, either out of pocket, or through insurance, someone else for access to their own information. Let me repeat: the government and professional guilds which exist to defend the financial interests of their members are proposing that they arbitrate what you can know about your genome. A friend with a background in genomics emailed me today: “If they succeed in ramming this through, then you will not be able to access your own damn genome without a doctor standing over your shoulder.” That is my fear. Is it your fear? Do you care?

In the medium term this is all irrelevant. Sequencing will be so cheap that it will be impossible for the government and well-connected self-interested parties to prevent you from gaining access to your own genetic information. Until then, they will slow progress and the potential utility of this business. Additionally, this sector will flee the United States and go offshore, where regulatory regimes are not so strict. BGI should give glowing letters of thanks to Jeffrey Shuren and the A.M.A.! This is a power play where big organizations, the government, corporations, and professional guilds, are attempting to squelch the freedom of the consumer to further their own interests, and also strangle a nascent economic sector of start-ups as a side effect.

You are so much more than your genes. So much more than that 3 billion base pairs. But they are a start, a beginning, and how dare the government question your right to know the basic genetic building blocks of who you are. This is the same government which attempted to construct a database of genetic information on foreign leaders. We know very well then who they think should have access to this data. The Very Serious People with a great deal of Power. People with “clearance,” and “expertise,” have a right to know more about about your own DNA sequence than you do.

What can you do? What can we do? Can we affect change? I don’t know, I can’t predict the future. But this is what I’m going to do.

1) I am going to release my own 23andMe sequence into the public domain soon. I encourage everyone to download it. I would rather have someone off the street know my own genetic information than be made invisible by the government. That is my right. For now that right is not barred by law. I will exercise it.

2) Spread word of this video via social networking websites and twitter. The media needs to get the word out, but they only will if they know you care. Do you care? I hope you do. This is a power grab, this is not about safety or ethics. If it was, I assume that the “interpretative services” would be provided for free. I doubt they will be.

3) Contact your local representative in congress. I’ve never done this myself, but am going to draft a quick note. They need to be aware that people care, that this isn’t just a minor regulatory issue.

4) The online community needs to get organized. We’re not as powerful as a million doctors and a Leviathan government, but we have right on our side. They’re trying to take from us what is ours.

5) Plan B’s. We need to prepare for the worst. Which nations have the least onerous regulatory regimes? Is genomic tourism going to be necessary? How about DIYgenomics? The cost of the technology to genotype and sequence is going to crash. I know that the Los Angeles DIYbio group has a cheap cast-off sequencer. For those who can’t afford to go abroad soon we’ll be able to get access to our information in our homes. Let’s prepare for that day.

This is a call to arms, a start. I’ve been complacent about this issue, focusing more on the fascinating aspects of ancestry inference which are enabled by personal genomics. No more. I’ll be doing a lot of reading today. If you have a blog, post the video. Raise awareness. Let’s make our voices heard. If they take away our rights because we’re silent, we have only ourselves to blame. If they take aware our rights despite our efforts, we’ll set up the infrastructure for the day when we can take back what is ours.

P.S. Feel free to post info and ideas in the comments. I just literally woke up to the urgency of this issue in the past 48 hours.

Finally, I know 3-D visualization is bad form, but I went for it anyway. Below is a cube which shows the positions of Gujaratis, Chinese, Mexican Americans, and Utah whites and Tuscans from the HapMap, along with a few extra samples from friends and family. Can you tell where my parents are?

This is what Dienekes also found. Aggregating various ancestral components together to be analogous to what Zack produced at K = 5, you get the bar plot below from his runs:

I assume that all ancestry analyses will find that I have a substantial minority of East Eurasian ancestry. I have a similar amount of ancestry which is obviously connected to West Eurasia. And the rest of my ancestry is going to fall into the catchall which is “South Asian,” which Reich et al. in Reconstructing Indian History argued was in fact a compound between a West Eurasian-like population (“Ancestral North Indian,” ANI) and a South Eurasian population (“Ancestral South Indian,” ASI) which was more closely related to East Eurasians than West Eurasians, though distantly so at that (modern West Eurasians are interchangeable with ANI, but ASI do not exist in unadmixed form).

Finally, here’s an analysis of chromosome 1 and its affinities to various reference populations. I’ve labelled myself. No surprises:

I am HRP002 in HAP. DOD075 in Dodecad. IN8 in BGA. I am willing to submit to any of these new grassroots ancestry projects if they want me. But I doubt I’ll find anything too surprising now. They converge upon the same rough proportions (as they should).

I’m at the stage where I want to look more deeply into the details of how long ago the “eastern” admixture occurred. It seems to come down from both parents. If it was very recent there should be some linkage disequilibrium detectable because recombination should not have broken down the allelic associations distinctive to each ethnic group yet (this is noticeable in African Americans). But I am not so sure it is recent anymore, as I’d thought. I suspect a Tibeto-Burman and Munda element were absorbed by Bengali peasants in the course of demographic expansion in what became Bangladesh between 1000 and 1500 A.D., and that ancestry is well distributed across the population now.

But even though I won’t find anything out for myself, the reason HAP and projects like it are useful is that we need better coverage of the world’s variation. There are big coarse questions which we’ve tapped out, but there are still lots of gaps to fill. I’m willing to do my part in that (or, more precisely, at this point I’ve drafted my parents into the role, since they aren’t related and so represent two independent data points for Bengal).

Addendum: I know for many people of European ancestry this sort of thing doesn’t tell them anything new. Not so for me. I always suspected East Asian admixture due to the phenotype of my extended family (and to some extent, me. I did not need to shave regularly until my 20s), but I was always curious as to its extent. Additionally, for the reasons of phenotype I had assumed my mother had very little of such ancestry while my father had a great deal. It turns out that in fact my mother may marginally be more “eastern” than my father.