Genetic group differences in height and recent human evolution

These recent Nature Genetics papers offer more evidence that group differences in a complex polygenic trait (height), governed by thousands of causal variants, can arise over a relatively short time (~ 10k years) as a result of natural selection (differential response to varying local conditions). One can reach this conclusion well before most of the causal variants have been accounted for, because the frequency differences are found across many variants (natural selection affects all of them). Note the first sentence above contradicts many silly things (drift over selection, genetic uniformity of all human subpopulations due to insufficient time for selection, etc.) asserted by supposed experts on evolution, genetics, human biology, etc. over the last 50+ years. The science of human evolution has progressed remarkably in just the last 5 years, thanks mainly to advances in genomic technology.

Cognitive ability is similar to height in many respects, so this type of analysis should be possible in the near future.

See discussion in earlier posts:
Height, breeding values and selection
Recent human evolution: European height
Eight thousand years of natural selection in Europe
No genomic dark matter

Population genetic differentiation of height and body mass index across Europe

Nature Genetics 47, 1357–1362 (2015) doi:10.1038/ng.3401

Across-nation differences in the mean values for complex traits are common1, 2, 3, 4, 5, 6, 7, 8, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10−8; BMI, P < 5.95 × 10−4), and we find an among-population genetic correlation for tall and slender individuals (r = −0.80, 95% CI = −0.95, −0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).

Height-reducing variants and selection for short stature in Sardinia

Nature Genetics 47, 1352–1356 (2015) doi:10.1038/ng.3403 

We report sequencing-based whole-genome association analyses to evaluate the impact of rare and founder variants on stature in 6,307 individuals on the island of Sardinia. We identify two variants with large effects. One variant, which introduces a stop codon in the GHR gene, is relatively frequent in Sardinia (0.87% versus <0.01% elsewhere) and in the homozygous state causes Laron syndrome involving short stature. We find that this variant reduces height in heterozygotes by an average of 4.2 cm (−0.64 s.d.). The other variant, in the imprinted KCNQ1 gene (minor allele frequency (MAF) = 7.7% in Sardinia versus <1% elsewhere) reduces height by an average of 1.83 cm (−0.31 s.d.) when maternally inherited. Additionally, polygenic scores indicate that known height-decreasing alleles are at systematically higher frequencies in Sardinians than would be expected by genetic drift. The findings are consistent with selection for shorter stature in Sardinia and a suggestive human example of the proposed 'island effect' reducing the size of large mammals.

Where men are men, and giants walk the earth

In this earlier post I advocated for cognitive filtering via study of hard subjects

Thought experiment for physicists: imagine a professor throwing copies of Jackson's Classical Electrodynamics at a group of students with the order, "Work out the last problem in each chapter and hand in your solutions to me on Monday!" I suspect that this exercise produces a highly useful rank ordering within the group, with huge differences in number of correct solutions.

In response, a Caltech friend of mine (Page '87, MIT PhD in Physics) sent this old article from the Caltech News. It describes Professor William Smythe and his infamous course on electromagnetism, which was designed to "weed out weaklings"! The article lists six students who survived Smythe's course and went on to win the Nobel prize in Physics. (Click for larger version.)

Vernon Smith, a "weakling" who deliberately avoided the course, went on to win a Nobel prize in Economics. Smith wrote

The first thing to which one has to adapt is the fact that no matter how high people might sample in the right tail of the distribution for "intelligence," ... that sample is still normally distributed in performing on the materials in the Caltech curriculum.

I remind the reader of the Page House motto: Where men are men, and giants walk the earth :-)

See also Colleges ranked by Nobel, Fields, Turing and National Academies output.

Note added: The article mentions George Trilling, a professor at Berkeley I knew in graduate school. I once wrote an electrodynamics solution set for him, and was surprised that he had the temerity to complain about one of my solutions 8-)

Drone invasion

I bought one of these today for the kids -- their 10th birthday is coming up. Very fun to fly -- reminds me a bit of flying kites when I was a kid. At one point it got away from us and ended up across the street in a neighbor's tree -- the dreaded kite eating tree :-)

See also Drone Art.

W-2's don't lie

These numbers are derived from aggregate W-2 incomes for 158 million working Americans (see link for full table).

The "raw" average wage, computed as net compensation divided by the number of wage earners, is $7,050,259,213,644.55 divided by 158,186,786, or $44,569.20. Based on data in the table below, about 67.2 percent of wage earners had net compensation less than or equal to the $44,569.20 raw average wage. By definition, 50 percent of wage earners had net compensation less than or equal to the median wage, which is estimated to be $28,851.21 for 2014.

Some rough earnings thresholds by percentile: 90th ~ $95k , 95th ~ $125k , 99th ~ $275k , 99.9th ~ $900k , 99.99th ~ $3.5M.

The Tragedy of Great Power Politics?

Both sides of this issue are well argued in the debate -- in particular by opponents John Mearsheimer and Kevin Rudd. See also The Tragedy of Great Power Politics.

Fear Not!

For relentless technological advance, powered by high g researchers, venture capitalists, capital markets, and government investment in basic research, continues to deliver a cornucopia of benefits to the average joe.

(Note, however, that Moore's Law itself has stalled out recently ...)

BBC interview with Robert Plomin

I recommend this BBC interview with Robert Plomin. Robert is a consummate gentleman and scholar, working in a field that inevitably attracts controversy. (Via Dominic Cummings.)

Professor Robert Plomin talks to Jim Al-Khalili about what makes some people smarter than others and why he's fed up with the genetics of intelligence being ignored. Born and raised in Chicago, Robert sat countless intelligence tests at his inner city Catholic school. College was an attractive option mainly because it seemed to pay well. Now he's one of the most cited psychologists in the world. He specialized in behavioural genetics in the mid seventies when the focus in mainstream psychology was very much on our nurture rather than our nature, and genetics was virtually taboo. But he persisted, conducting several large adoption studies and later twin studies. In 1995 he launched the biggest longitudinal twin study in the UK, the TED study of ten thousand pairs of twins which continues to this day. In this study and in his other work, he's shown consistently that genetic influences on intelligence are highly significant, much more so than what school you go to, your teachers or home environment. If only the genetic differences between children were fully acknowledged, he believes education could be transformed and parents might stop giving themselves such a hard time.

Men Are Easy

@9 min: 26 million matches per day on Tinder. Male preferences easy to predict, females more complex! Linear vs Multivariate Nonlinear preferences? Calling Geoffrey Miller ...

Some data from OKcupid:

Global Impact Initiative

MSU will be hiring over 100 new professors (beyond ordinary hiring such as retirement replacements), primarily in science and technology areas that address key global challenges. Priority areas include Computation, Advanced Engineering, Genomics, Plant Sciences, Food/Environment, Precision Medicine, and Advanced Physical Sciences. MSU total funding from the Department of Energy and the National Science Foundation ranks in the top 10 among US universities.

Proximate to my own field of theoretical physics, we intend to build one of the best lattice QCD groups in the US. I predict that in the coming decade lattice QCD applied to low-energy nuclear physics will allow first-principles (starting from the level of quarks and gluons) calculations of important dynamical quantities in nuclear physics, such as scattering amplitudes and reaction rates. For the first time, strongly coupled nuclear systems will become amenable to direct computation using the quantum field theory of quarks and gluons.

Three faculty positions in Lattice Quantum Chromodynamics

The Department of Physics & Astronomy (PA), National Superconducting Cyclotron Laboratory (NSCL), and a new department of Computational Math Science and Engineering (CMSE) invite applications from outstanding candidates for three faculty positions at Michigan State University in the area of computational Lattice Quantum Chromodynamics (LQCD). We anticipate filling one or more of the positions at a senior level with tenure. We are looking for candidates with an excellent record in applying large-scale computing to solving cutting-edge scientific problems in the domains of nuclear physics (relevant to the Facility for Rare Isotope Beams) and high energy physics. We expect that the three hires will work together to establish an internationally prominent and well-funded activity in LQCD and its applications to high energy and nuclear physics. These positions are part of a committed multi-year effort to build the computational sciences programs at Michigan State University. Each position will be a joint appointment between the new CMSE department and PA/NSCL. Faculty will have a primary appointment in one of the three participating units (PA, NSCL, CMSE), and we anticipate one appointment in each of these units. In addition to developing a world-leading research group with strong disciplinary and interdisciplinary collaborations, the new faculty members are expected to contribute to the development of an innovative curriculum in computational sciences, at both the graduate and undergraduate levels.

BTW, I almost cried when I saw this happen! Go Green!

Mein Krieg: time and memory

The footage in this documentary will appeal to any History or WWII buff. The interviews with the old men, juxtaposed with moving images of their wartime youth, are a poignant meditation on time and memory.

Mein Krieg (1991)
Review/Film; Movies Shot By 6 Germans In the War

By JANET MASLIN (NYTimes)

The documentary "Mein Krieg" ("My Private War") offers stunningly un-self-conscious World War II memories from six German veterans, each of whom took a home movie camera with him into the fray. As directed with chilling simplicity by Harriet Eder and Thomas Kufus, it presents both a compilation of eerie wartime scenes and a catalogue of the photographers' present-day attitudes toward their experience. "I wouldn't be talking about these things if my conscience weren't clear as crystal," one of them calmly declares.

The film makers have their own ideas about their interviewees' complicity, as demonstrated by the emphasis they place on that particular remark. But their approach is restrained as they allow each of these six veterans to reminisce about everything from the condition of their movie cameras (which are well maintained and have yielded high-quality home movies) to the indelible sights they have seen. "Here we're going into Warsaw, and this is a tour of the buildings destroyed in '39," one man says, casually describing his images of wholesale destruction.

Much of the material seen here has a peculiar gentleness, as German soldiers cook and exercise and smile for the cameras. (There do not appear to have been restrictions on what the soldiers could photograph, since the later part of the film also includes glimpses of mass graves and civilian casualties.) And some of it recalls the more calculated wartime images we are more used to seeing in connection with Allied troops. So pretty nurses beam at Nazi soldiers; the soldiers' faces betray both fear and determination; the troops are seen celebrating after they shoot down an enemy plane. They were, a photographer recalls about the plane's dead Russian pilot, "full of joy over having been able to destroy this hornet." ...

Neoreaction and the Dark Enlightenment

An essay on neoreaction and the dark enlightenment from The Awl.

See also Fukuyama and Zhang on the China Model , Is there a China model? and Power and paranoia in Silicon Valley.

The Darkness Before the Right

A right-wing politics for the coming century is taking shape. And it’s not slowing down.

... Land’s case for democratic dysfunction is simply stated. Democracy is structurally incapable of rational leadership due to perverse incentive structures. It is trapped in short-termism by the electoral cycle, hard decisions become political suicide, and social catastrophe is acceptable as long as it can be blamed on the other team. Moreover, inter-party competition to “buy votes” leads to a ratchet effect of ever-greater state intervention in the economy—and even if this is periodically reversed, in the long-run it only moves in one direction. ... Rather than accept creeping democratic socialism (which leads to “zombie apocalypse”), Land would prefer to simply abolish democracy and appoint a national CEO. This capitalist Leviathan would be, at a bare minimum, capable of rational long-term planning and aligning individual incentive structures with social well-being (CEO-as-Tiger-Mom). Individuals would have no say in government, but would be generally left alone, and free to leave. This right of “exit” is, for Land, the only meaningful right, and it’s opposed to democratic “voice,” where everyone gets a say, but is bound by the decisions of the majority—the fear being that the majority will decide to self-immolate.

Anti-democratic sentiment is uncommon in the West, so Land’s conclusions appear as shocking, deliberate provocations, which they partly are. ... Pointing to Singapore, Hong Kong, and Shanghai, it argues that economically and socially effective government legitimizes itself, with no need for elections. And this view isn’t limited to the internet right. ...

This brand of authoritarian capitalism has a certain fascist sheen, but in truth it’s closer to a rigidly formalized capitalist technocracy. There’s no mass mobilization, totalitarian social reorganization, or cult of violence here; governing will be done by the governors, and popular sovereignty replaced by the market Mandate of Heaven. There is a strange sort of disillusioned cultural conservatism here as well, albeit one absolutely stripped of moralism. In fact, what’s genuinely creepy about it is the near-sociopathic lack of emotional attachment; it’s a sort of pure incentive-based functionalism, as if from the perspective of a computer or alien. If a person doesn’t produce quantifiable value, they are, objectively, not valuable. Everything else is sentimentality.

...

Capitalism, in this view, is less something we do than something done to us. Contra business-class bromides about the market as the site of creative expression, for Land, as for Marx, capitalism is a fundamentally alien institution in which “the means of production socially impose themselves as an effective imperative.” This means simply that the competitive dynamics of capitalism drive technical progress as an iron law. If one capitalist doesn’t want to build smarter, better machines, he’ll be out-competed by one who does. If Apple doesn’t make you an asshole, Google will. If America doesn’t breed genetically modified super-babies, China will. The market doesn’t run on “greed,” or any intentionality at all. Its beauty—or horror—is its impersonality. Either you adapt, or you die.

Accelerating technological growth, then, is written into capitalism’s DNA. Smart machines make us smarter allowing us to make smarter machines, in a positive feedback loop that quickly begins to approach infinity, better known in this context as “singularity.” ...

Somehow I ended up on this "map of neoreaction" -- without my consent, of course. Who are all these people? ;-)

Additivity in yeast quantitative traits

A new paper from the Kruglyak lab at UCLA shows yet again (this time in yeast) that population variation in quantitative traits tends to be dominated by additive effects. There are deep evolutionary reasons for this to be the case -- see excerpt below (at bottom of this post). For other examples, including humans, mice, chickens, cows, plants, see links here.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast (http://dx.doi.org/10.1101/019513)

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here, we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTLQTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL-QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies.


Genetic interactions arise when the joint effect of alleles at two or more loci on a phenotype departs from simply adding up the effects of the alleles at each locus. Many examples of such interactions are known, but the relative contribution of interactions to trait variation is a subject of debate1–5. We previously generated a panel of 1,008 recombinant offspring (“segregants”) from a cross between two strains of yeast: a widely used laboratory strain (BY) and an isolate from a vineyard (RM)6. Using this panel, we estimated the contribution of additive genetic factors to phenotypic variation (narrow-sense or additive heritability) for 46 traits and resolved nearly all of this contribution (on average 87%) to specific genome-wide-significant quantitative trait loci (QTL). ...

We detected nearly 800 significant additive QTL. We were able to refine the location of the QTL explaining at least 1% of trait variance to approximately 10 kb, and we resolved 31 QTL to single genes. We also detected over 200 significant QTL-QTL interactions; in most cases, one or both of the loci also had significant additive effects. For most traits studied, we detected one or a few additive QTL of large effect, plus many QTL and QTL-QTL interactions of small effect. We find that the contribution of QTL-QTL interactions to phenotypic variance is typically less than a quarter of the contribution of additive effects. These results provide a picture of the genetic contributions to quantitative traits at an unprecedented resolution.

... One can test for interactions either between all pairs of markers (full scan), or only between pairs where one marker corresponds to a significant additive QTL (marginal scan). In principle, the former can detect a wider range of interactions, but the latter can have higher power due to a reduced search space. Here, the two approaches yielded similar results, detecting 205 and 266 QTL-QTL interactions, respectively, at an FDR of 10%, with 172 interactions detected by both approaches. In the full scan, 153 of the QTL-QTL interactions correspond to cases where both interacting loci are also significant additive QTL, 36 correspond to cases where one of the loci is a significant additive QTL, and only 16 correspond to cases where neither locus is a significant additive QTL.

For related discussion of nonlinear genetic models, see here:

It is a common belief in genomics that nonlinear interactions (epistasis) in complex traits make the task of reconstructing genetic models extremely difficult, if not impossible. In fact, it is often suggested that overcoming nonlinearity will require much larger data sets and significantly more computing power. Our results show that in broad classes of plausibly realistic models, this is not the case.

Determination of Nonlinear Genetic Architecture using Compressed Sensing (arXiv:1408.6583)
Chiu Man Ho, Stephen D.H. Hsu
Subjects: Genomics (q-bio.GN); Applications (stat.AP)

We introduce a statistical method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. The computational and data resource requirements are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. Our method uses a generalization of compressed sensing (L1-penalized regression) applied to nonlinear functions of the sensing matrix. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using both real and simulated human genomes.

I've discussed additivity many times previously, so I'll just quote below from Additivity and complex traits in mice:

You may have noticed that I am gradually collecting copious evidence for (approximate) additivity. Far too many scientists and quasi-scientists are infected by the epistasis or epigenetics meme, which is appealing to those who "revel in complexity" and would like to believe that biology is too complex to succumb to equations. ...

I sometimes explain things this way:

There is a deep evolutionary reason behind additivity: nonlinear mechanisms are fragile and often "break" due to DNA recombination in sexual reproduction. Effects which are only controlled by a single locus are more robustly passed on to offspring. ...

Many people confuse the following statements:

"The brain is complex and nonlinear and many genes interact in its construction and operation."

"Differences in brain performance between two individuals of the same species must be due to nonlinear (non-additive) effects of genes."

The first statement is true, but the second does not appear to be true across a range of species and quantitative traits. On the genetic architecture of intelligence and other quantitative traits (p.16):

... The preceding discussion is not intended to convey an overly simplistic view of genetics or systems biology. Complex nonlinear genetic systems certainly exist and are realized in every organism. However, quantitative differences between individuals within a species may be largely due to independent linear effects of specific genetic variants. As noted, linear effects are the most readily evolvable in response to selection, whereas nonlinear gadgets are more likely to be fragile to small changes. (Evolutionary adaptations requiring significant changes to nonlinear gadgets are improbable and therefore require exponentially more time than simple adjustment of frequencies of alleles of linear effect.) One might say that, to first approximation, Biology = linear combinations of nonlinear gadgets, and most of the variation between individuals is in the (linear) way gadgets are combined, rather than in the realization of different gadgets in different individuals.

Linear models work well in practice, allowing, for example, SNP-based prediction of quantitative traits (milk yield, fat and protein content, productive life, etc.) in dairy cattle. ...

See also Explain it to me like I'm five years old.

"1-bit" Compressed Sensing and Genetic Disease

This is an ASHG poster (click for larger version) describing work on predictive modeling of genetic disease using Compressed Sensing. Our previous work dealt with continuous traits (quantitative phenotypes). In the case of disease, one sometimes only has binary data to work with: individuals in the sample are either cases (have the condition) or controls (do not have the condition). Their underlying genetic susceptibility to the condition is not directly measurable. However, sophisticated techniques can use even this type of data to deduce the underlying genetic architecture. As in our earlier work, we demonstrate a "phase transition" in the performance of our algorithms as the amount of data available increases.

See related posts on quantitative traits: linear models 2, linear models, nonlinear method, and this talk: Genetic architecture and predictive modeling of quantitative traits.

Understanding Genius: Helix Center roundtable video

You can watch the 2+ hour video of the roundtable on YouTube. I enjoyed the discussion but I don't like watching or listening to recordings of myself, so you'll have to tell me what you think of it ...

I was very flattered that several readers of the blog showed up for the event. Thanks to everyone who made it!



I'll be part of this roundtable discussion Saturday, Oct 3 in NYC. It's open to the general public and will be live streamed at the YouTube link above. I'm pleased to be on the panel with (among others) Dean Simonton, a UC Davis psychology professor and author of numerous books related to the theme of this meeting.

The Helix Center for Interdisciplinary Investigation
The Marianne & Nicholas Young Auditorium
247 East 82nd Street
New York, NY 10028

Understanding Genius

Schopenhauer defined genius in relation to the more conventional quality of talent. “Talent hits a target others miss. Genius hits a target no one sees.” Is originality indeed the sine qua non of genius? Is there, following Kant, a radical separation of the aesthetic genius from the brilliant scientific mind? What further distinctions might be made between different types of genius? If “The Child is father of the Man,” why don’t child prodigies always grow up to become adult geniuses?