Month: December 2017

Natural selection in humans (OK, 375,000 British people)

Posted on by Razib Khan

 


The above figure is from Evidence of directional and stabilizing selection in contemporary humans. I’ll be entirely honest with you: I don’t read every UK Biobank paper, but I do read those where Peter Visscher is a co-author. It’s in PNAS, and a draft which is not open access. But it’s a pretty interesting read. Nothing too revolutionary, but confirms some intuitions one might have.

The abstract:

Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.

The stabilizing selection part is probably the most interesting part for me. But let’s hold up for a moment, and review some of the major findings. The authors focused on ~375,000 samples which matched their criteria (white British individuals old enough that they are well past their reproductive peak), and the genotyping platforms had 500,000 markers. The dependent variable they’re looking at is reproductive fitness. In this case specifically, “rRLS”, or relative reproductive lifetime success.

With these huge data sets and the large number of measured phenotypes they first used the classical Lande and Arnold method to detect selection gradients, which leveraged regression to measure directional and stabilizing dynamics. Basically, how does change in the phenotype impact reproductive fitness? So, it is notable that shorter women have higher reproductive fitness than taller women (shorter than the median). This seems like a robust result. We’ve seen it before on much smaller sample sizes.

The results using phenotypic correlations for direction (β) and stabilizing (γ) selection are shown below separated by sex. The abbreviations are the same as above.

 

There are many cases where directional selection seems to operate in females, but not in males. But they note that that is often due to near zero non-significant results in males, not because there were opposing directions in selection. Height was the exception, with regression coefficients in opposite directions. For stabilizing selection there was no antagonistic trait.

A major finding was that compared to other organisms stabilizing selection was very weak in humans. There’s just not that that much pressure against extreme phenotypes. This isn’t entirely surprising. First, you have the issue of the weirdness of a lot of studies in animal models, with inbred lines, or wild populations selected for their salience. Second, prior theory suggests that a trait with lots of heritable quantitative variation, like height, shouldn’t be subject to that much selection. If it had, the genetic variation which was the raw material of the trait’s distribution wouldn’t be there.

Using more complex regression methods that take into account confounds, they pruned the list of significant hits. But, it is important to note that even at ~375,000, this sample size might be underpowered to detect really subtle dynamics. Additionally, the beauty of this study is that it added modern genomic analysis to the mix. Detecting selection through phenotypic analysis goes back decades, but interrogating the genetic basis of complex traits and their evolutionary dynamics is new.

To a first approximation, the results were broadly consonant across the two methods. But, there are interesting details where they differ. There is selection on height in females, but not in males. This implies that though empirically you see taller males with higher rLSR, the genetic variance that is affecting height isn’t correlated with rLSR, so selection isn’t occurring in this sex.

~375,000 may seem like a lot, but from talking to people who work in polygenic selection there is still statistical power to be gained by going into the millions (perhaps tens of millions?). These sorts of results are very preliminary but show the power of synthesizing classical quantitative genetic models and ways of thinking with modern genomics. And, it does have me wondering about how these methods will align with the sort of stuff I wrote about last year which detects recent selection on time depths of a few thousand years. The SDS method, for example, seems to be detecting selection for increasing height the world over…which I wonder is some artifact, because there’s a robust pattern of shorter women having higher fertility in studies going back decades.

Pick the right team, not the right answer (most of the time)

Posted on by Razib Khan

Often you will hear people say “why do people always engage in ‘group-think'”? As if group-think is always a bad thing! The reality is that group-think is often highly adaptive. That’s why people engage in it. You’re outsourcing expensive cognition to the collective, tradition, or in some cases to someone with expertise.

Of course, there are whole domains of heuristics and biases that developed out of exposing how humans do not reason appropriately, but other researchers have argued that our species’ irrationality is often quite useful in our ancestral evolutionary environment. In other words, a lot of what frustrates is us not a bug, but a feature.

For example, in an ancient pre-modern environment where culture and environment were generally stable reasoning to everything basically consists of reinventing the wheel constantly. The contemplative life may have been the starving life. The “way things have been done” may not always seem perfectly optimal, but they were sufficient.

To give an empirical example of this that I’ve always found sad, the Irish were exceptional among European peasants peoples in taking to a potato monoculture without must hesitation. Believe it or not the Russians were tardy at adoption. This resulted in a massive demographic expansion which saw Ireland’s population peak at around 8,000,000. But the cost of this was the Great Famine, which illustrated how the wholesale adoption of practices which were optimal in the short-term were not optimal evaluated over the long-term (Ireland’s population today is less than 5,000,000, though some of this is due to the culture of emigration which emerged during the Great Famine). Evolution is evaluated over the long-term, so universal cognitive ticks which we see across our species are probably there for a reason, whether as a direct cause, or a side-effect.

Finally, intellectuals who enjoin the masses to not engage in group-think have no difficulty in falling into the same practices when operating outside their own domains of expertise. What this suggests is that “critical-rationalism” is not something that emerges in a vacuum. Rather, it is a cognitive method that develops in a particular cultural context, and individually is often the outcome of confidence and experience gained through years of education and mental practice within a narrow topic.

Getting yourself out of the cave and not misinterpreting the shadows can be hard. And truthfully, it probably wasn’t even optimal. The roaches will inherit the earth long after we’re gone, and they likely never even reflect upon their own selfhood.

Motivated reasoning in “science journalism.”

Posted on by Razib Khan

The “reproducibility crisis” has really benefited some sectors of science journalism, as there is less credulous amplification of spurious results. That being said, motivated reasoning is powerful. They “want to believe.”

So when I saw this piece in Quartz, Highly motivated kids have a greater advantage in life than kids with a high IQ, I immediately scanned for what I usually look for, and found it:

Over the next four decades, the Gottfrieds and several colleagues collected a staggering trove of data on the study participants, yielding important insights into working parents, temperament, and other topics. Researchers collected information about participants from parents, teachers and transcripts, tested their IQ and motivation levels,and even visited their homes. In all, the Fullerton Longitudinal Study has amassed an estimated 18,000 pieces of information on each of the remaining 107 participants. “It’s our life’s work,” says Allen cheerfully. “We’ll take it to our grave.”

107 participants. Lots of information huh? Things that make you go hm….. Also, 19% of the children had IQs of 130 or above. About 2% of the population has an IQ at this level. The sample size was relatively small, and the sample was very unrepresentative.

This doesn’t mean that there aren’t real results in these data. But I don’t think they warrant the fanfare in the title, except for the fact that people want a silver bullet that will abolish social inequality.

Even the text itself doesn’t justify the title at all (to be fair, usually headline writers differ from the persons writing the text of a piece): “[Motivation] in itself is accounting for a certain amount of variance in achievement that goes above and beyond IQ….” That is, they don’t even say it accounts for more of the variance, only that there is variance that isn’t accounted for by IQ (which everyone already agreed upon).

Finally, I’ve spent my life around highly educated and intelligent people a bit perplexed and befuddled by my diverse interests. This includes in academia. So I can see that there is a difference between people for whom learning is a means to a professional and social ends, and for those whom learning is the ends. I suspect the ancients could have told you this!

Samsung Galaxy S8 is pretty good

Posted on by Razib Khan

One of the more convenient things with having a blog that has more than a few readers is that you can ask questions and get some answers.

Recently I was figuring out whether I’d go full-Apple, and get an iPhone. I got a lot of feedback, but ultimately I decided to to be boring and get a Samsung Galaxy S8.

The verdict? Bixby sucks. Everything else is pretty good. Would recommend.

Three books to understand the “Dark Matter” of American History

Posted on by Razib Khan

Grand theories of history often have less utility than the claims they make for themselves. Marxism is a classic example.

But that does not mean that theories of history are useless. And arguably, Marxism is a classic example in this case too. Material forces and class conflicts can’t explain all of history, but they do explain some of history. Chris Wickham’s magisterial Framing the Early Middle Ages: Europe and the Mediterranean, 400-800 suffers from its excessive materialist and economistic thesis, but it also benefits from this perspective, because it captures part of the answer.

Moderation in all things, and due consideration to the importance of viewpoints in coloring perceptions, are the keys to comprehension in my opinion..

Today in some quarters it is fashionable to reduce all of history to the interplay between white supremacy and nonwhite peoples, who are depicted implicitly as nearly supine “noble savages,” existing in an Edenic state of nature before the intrusion of European peoples. This is a silly viewpoint from a scholarly perspective, and some of the ideological implications are ones which I object to most strongly.

And yet that begs the question, how does one understand the forces of history? In the American context, I think it is critical to understand the elementary regional folkways which congealed into these United States, and whose “cultural DNA” echoes down through the generations. Much of this is implicit and invisible culture because it is the culture of white English -speaking peoples of British provenance (though not all were Anglo, such as the French Canadians or Hispanos of the southwest).

Recently, Colin Woodward’s American Nations: A History of the Eleven Rival Regional Cultures of North America is the best example of this sort of work, which attempts to trace the historical dark matter the skeleton beneath the flesh. A more scholarly and narrow treatment can be found in David Hackett Fisher’s expansive Albion’s Seed: Four British Folkways in America. Finally, perhaps the most underrated and overlooked offering in this genre is Kevin Phillips’ The Cousins’ Wars: Religion, Politics, Civil Warfare, And The Triumph Of Anglo-America.

While Woodward focuses on all of North America, and Fisher more narrowly on the four folkways which extend from New England to the Deep South, Phillips’ integrates an American history with a broader narrative that shows the connections to events and processes occurring in the British Isles, and in particular England. The peculiarities of New England culture and economics, and their love-hate relationship to the British elites of the late 18th and 19th century, are critical pieces of the puzzle in explaining how the United States diverged from the United Kingdom, and, how the United Kingdom diverged from the United States.

If an understanding of population genetics allows one to decompose evolution and broadly biological phenomena into tractable analytic units, so an understanding of the elementary units of American culture, and their historical antecedents, shines a whole new light upon contemporary developments.

A genetic map of the world

Posted on by Razib Khan


The above map is from a new preprint on the patterns of genetic variation as a function of geography for humans, Genetic landscapes reveal how human genetic diversity aligns with geography. The authors assemble an incredibly large dataset to generate these figures. The orange zones are “troughs” of gene flow. Basically barriers to gene flow.  It is no great surprise that so many of the barriers correlate with rivers, mountains, and deserts. But the aim of this sort of work seems to be to make precise and quantitative intuitions which are normally expressed verbally.

To me, it is curious how the borders of the Peoples’ Republic of China is evident on this map (an artifact of sampling?). Additionally, one can see Weber’s line in Indonesia. There are the usual important caveats of sampling, and caution about interpreting present variation and dynamics back to the past. But I believe that these sorts of models and visualizations are important nulls against which we can judge perturbations.

As I said, these methods can confirm rigorously what is already clear intuitively. For example:

Several large-scale corridors are inferred that represent long-range genetic similarity, for example: India is connected by two corridors to Europe (a southern one through Anatolia and Persia ‘SC’, and
a northern one through the Eurasian Steppe ‘NC’)

We still don’t have enough ancient DNA to be totally sure, but it’s hard to ignore the likelihood that “Ancestral North Indians” (AN) actually represent two different migrations.

India also illustrates contingency of these barriers. Before the ANI migration, driven by the rise in agricultural lifestyles, there would likely have been a major trough of gene flow on India’s western border. In fact a deeper one than the one on the eastern border. And if the high genetic structure statistics from ancient DNA are further confirmed then the rate of gene flow was possibly much lower between demes in the past. Perhaps that would simply re-standardize equally so that the map itself would not be changed, but I suspect that we’d see many more “troughs” during the Pleistocene and early Holocene.

Because there are so many geographically distributed samples for humans, and frankly some of the best methods developers work with human data (thank you NIH), it is no surprise that our species would be mapped first. But I think some of the biggest insights may be with understanding the dynamics of gene flow of non-human species, and perhaps the nature and origin of speciation as it relates to isolation (or lack thereof).

My new podcast with Spencer Wells

Posted on by Razib Khan

Spencer Wells and I have a new podcast, The Insight. On the first episode, we’ll be talking about the Neolithic revolution.

We’ve already got several more in the pipeline that will come out in the next few weeks (being edited), including one with John Hawks. This will be a regular thing, so please subscribe!

Update: Also see: http://insitome.libsyn.com/website.

Update: Here is the podcast embedded:

Helix kit price waived until December 26 at 2:59am EST

Posted on by Razib Khan

Happy Hanukkah! My main qualm with wishing you a happy holiday is that I’m a thorough assimilator and I don’t want to be disemboweled.

For the context, listen to the Stuff You Missed in History Class episode on the Maccabean Revolt. As a Jewish friend of mine once observed, the Maccabees were kind of the Al-Qaeda of their day (today she would have said ISIS).

With that out of the way, I want to give you a heads up that Helix has a sale going until December 26 at 2:59am EST where the $80 kit cost for purchase of any app is waived if you haven’t purchased at app before. Just enter the promotion code HOLIDAY at checkout.

That means presales of Insitome’s Regional Ancestry is no more than $19.99, while Neanderthal is $29.99 and Metabolism is $39.99 (this applies to all of Helix’s products except embodyDNA by Lose It! and Geno 2.0 by National Geographic).

Why does it matter? Again, Helix banks a high quality exome+ (the + is for non-exonic positions) when you purchase any of their apps. If you want subsequent apps you don’t have to sent another kit in, you just buy the app and get the results. Also, I do have to say that from what I’ve seen and heard Helix’s laboratory facilities are top-notch in terms of getting results turned around rapidly.

Your impatience is in your genes! (well, some of it)

Posted on by Razib Khan


Nature Neuroscience has a short communication which is very intriguging, Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry. How’d they get such a large sample size? Collaborating with our friends at 23andMe.

That being said, the abstract leaves a little to be desired:

Delay discounting (DD), the tendency to discount the value of delayed versus current rewards, is elevated in a constellation of diseases and behavioral conditions. We performed a genome-wide association study of DD using 23,127 research participants of European ancestry. The most significantly associated single-nucleotide polymorphism was rs6528024 (P = 2.40 × 10−8), which is located in an intron of the gene GPM6B. We also showed that 12% of the variance in DD was accounted for by genotype and that the genetic signature of DD overlapped with attention-deficit/hyperactivity disorder, schizophrenia, major depression, smoking, personality, cognition and body weight.

First, “Delay discounting (DD)”, is another way to say that you have high time preference. That is, you won’t forgo some gains in the short term for greater gains in the long term. You would really “fail” the marshmallow test.

Though there have been legitimate criticisms of the replicability of the effect size of the marshmallow test, there almost certainly is something to time preference and delayed gratification, and its relationship to the ability of young children to master the marshmallow test. In a macroeconomic sense societies characterized by low time preference can sustain lower interest rates, and lower interest rates have all sorts of stimulative properties on long-term economic growth.

But to be clear, the paper above does not detect a variant SNP, rs6528024, which explains 12% of the variance in DD. Rather, 12% of the variance could be accounted for by SNP-chip variance. That is, one could explain the “missing heritability” using the markers they had. The total heritablity of the trait is quite higher, 46% to 62% proportions are citied in the paper (narrow-sense). This means that of the total variance of the trait about half could be explained by additive genetic variance. Obviously the SNP-chip only captured a small minority of that additive genetic variance.

DD is correlated with a lot of things. There is a positive phenotypic correlation with:

  • Smoking
  • Substance abuse
  • Obesity
  • ADHD

They observed a positive genetic correlation between the variants associated with DD and:

  • Smoking
  • Neuroticism
  • Depression

And a negative genetic correlation with:

  • College completion
  • Years of education
  • Childhood IQ
  • Schizophrenia

In relation to the last, schizophrenia and DD are positively correlated phenotypically. That probably means that the underlying genetic causes of schizophrenia and DD are very different.

The patterns of correlations offer up a lot of avenues to speculate. They do a little of it in the paper, but are appropriately cautious. It seems entirely likely that in the near future we’ll be able to characterize a lot of the heriability genomically. When we figure out time preference and intelligence we’ll have come close to answering many of the questions that explain why different people have different life outcomes.

Note: It is no surprise that there is a negative correlation between DD (high time preference) and conscientiousness. Also, the association they found, GPM6B, has pretty clear biological relevance. It’s almost certainly real.