Update: First, people coming to this weblog for the first time should know that I moderate comments. So if you leave an obnoxious one it’s basically like an email to me (no one will see it). Second, the correlation between height and intelligence is not that high. This association is probably not going to be intuitively visible to anyone, but rather only shows up in large data sets. So please stop offering yourself as a counter-example of the trend (also, the key is to look within families, because the signal here is going to be swamped by other factors when you compare across populations). Third, a friend has sent me another paper which does confirm that even within sibling cohorts there does seem to be a correlation between height and I.Q. The problem is that it is a very small one, so you need large data sets with a lot of power to see it.
One moderately interesting social science finding is that there is a positive correlation between height and measured intelligence (e.g., on an I.Q. test). Setting aside the possibility that I.Q. tests designs are culturally biased against shorter people, one wonders why this is so. Height is a highly heritable trait where most of the variation within the population is due to variation as numerous genes. In other words, there isn’t a “tall” or “short” gene, but thousands and thousands of variants which shape the variation of the trait across the population. When I say it is highly heritable, I mean to imply that most of the variation in height in developed societies is due to genes (80-90%). As it happens intelligence is somewhat similar in its genetic architecture, heritable due to small effects across many genes. In general estimates for the heritability of intelligence tend to be somewhat lower, on the order of ~50% rather than 80-90%.
It is due to the highly polygenic nature that both of these traits have been posited as candidates for a “good genes” model of sexual selection. Presumably individuals with a higher mutational load will have lower intelligence and be shorter, all things equal, because these traits have extensive genome-wide coverage and are big targets. Geoffrey Miller’s The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature, was predicated on this logic. If the mutational load argument holds then the reduced I.Q. of shorter individuals may simply be due to the same cause: “bad genes.”
A quick mea culpa. Yesterday I put up a post on the difference in height between northern and southern Europe, following the lead of the heading of the paper which I blogged. But, in the text they do note that their sample is skewed toward northern Europe. Additionally, their geographic coverage is stated in the supplements. As noted by some commenters not only is it northern Europe skewed, but it’s really western Europe biased. There’s nothing wrong with that as such, but it leaves much of Europe outside of this west-central transect unsampled. Therefore, I’m a little more cautious of making pan-European latitudinal generalizations.
In part, genes. Luke Jostins reported this from a conference last year, so not too surprising. Evidence of widespread selection on standing variation in Europe at height-associated SNPs. Let me jump to the summary:
In summary, we have provided an empirical example of widespread weak selection on standing variation. We observed genetic differences using multiple populations from across Europe, thereby showing that the adult height differences across populations of European descent are not due entirely to environmental differences but rather are, at least partly, genetic differences arising from selection. Height differences across populations of non-European ancestries may also be genetic in origin, but potential nongenetic factors, such as differences in timing of secular trends, mean that this inference would need to be directly tested with genetic data in additional populations. By aggregating evidence of directionally consistent intra-European frequency differences over many individual height-increasing alleles, none of which has a clear signal of selection on its own, we observed a combined signature of widespread weak selection. However, we were not able to determine whether this differential weak selection (either positive or negative) favored increased height in Northern Europe, decreased height in Southern Europe or both. One possibility is that sexual selection or assortative mating (sexual selection for partners in similar height percentiles) fueled the selective process. It is also possible that selection is not acting on height per se but on a phenotype closely correlated with height or a combination of phenotypes that includes height.
Two points of note. First, simulations suggested that the genetic architecture is unlikely to be due to drift alone. In other words, natural selection. Selection on quantitative traits isn’t magic, there’s a whole agricultural industry based around this phenomenon. For the purposes of understanding human evolution the key is that we are now moving beyond looking for traits which emerged due to novel mutations (e.g., lactase persistence), and now trying to understand how selection and drift may work on standing variation. For example, humans have become smaller in overall size, and also in cranial capacity, over the past 10,000 years. Second, they validated their findings using a sibling cohort. This is something I always look for when people make inter-population inferences. A number of population wide correlations don’t pan out when you are looking within families. This matters in trying to understand causation.
There’s a fair amount of social science and anecdata that tall males are more reproductively fit. More precisely, males one to two standard deviations above the norm in height seem to be at the “sweet spot” as an idealized partner (e.g., leading males). And, short men often have fewer children. Short women will pair up with tall men. Tall women will generally not pair up with shorter men. The question then has to be asked: why isn’t natural selection producing a situation where we’re all tall?
As it is, height is a highly heritable trait where there’s a lot of genetic variation present in the population. One hypothesis might be that short(er) people are simply individuals with a higher mutational load. In other words, there’s going to be variation in the load of deleterious alleles from person to person, and one’s value on quantitative traits (intelligence, height) is a reflection of one’s genetic fitness. There are problems with this model, starting with the fact that one you need to tease apart inter-population variation. Also, within families there doesn’t seem to be a correlation between height and intelligence, which you would expect to see if quantitative traits are reflections of variation in mutational load.
So naturally you have to move the possibility of balancing selection. I have suggested in the past that inter-population differences in height may be a function of expected levels of nutritional stress. Short people are smaller, and need to eat less. The same dynamic could produce variation in height within populations as well. But a new paper outlines what I think I think is the most elegant solution (though elegant does not mean right!), Intralocus sexual conflict over human height:
Evidence of Inbreeding Depression on Human Height, a paper with over 1,000 authors! (I exaggerate) It’s interesting because it seems to establish that inbreeding does have a deleterious effect on traits whose genetic architecture is presumably polygenic and additive. Why is this theoretically important? Because inbreeding depression is often assumed to be driven by the exposure of rare recessive larger effect alleles, which recombine in near relations. Using tens of thousands of individuals from across a dozen European nations the authors found that there is a consistent relationship between inbreeding and reduction in height.
As the authors note height is a convenient trait to explore. First, it’s highly heritable. 80 to 90 percent of the variation in the population is explained by variation in genes. Second, it’s easy to measure. Also, implicit in the paper is the fact that in Europe today there is far less of a environmental effect on height (that’s why the heritability value is high). Even in poor European nations most people have enough to eat, so height is highly heritable, allowing for appropriate cross-national comparison.
The Pith: Even traits where most of the variation you see around you is controlled by genes still exhibit a lot of variation within families. That’s why there are siblings of very different heights or intellectual aptitudes.
In a post below I played fast and loose with the term correlation and caused some confusion. Correlation is obviously a set of precise statistical terms, but it also has a colloquial connotation. Additionally, I regularly talk about heritability. Heritability is in short the proportion of phenotypic variance which can be explained by genetic variance. In other words, if heritability is ~1 almost all the variation in the trait is due to variation in genes, while if heritability is ~0 almost none of it is. Correlation and heritability of traits across generations are obviously related, but they’re not the same.
This post is to clarify a few of these confusions, and sharpen some intuitions. Or perhaps more accurately, banish them.
In the comments below a reader asks about the empirical difference in heights between siblings. I went looking…and I have to say that the data isn’t that easy to find, people are more interested in the deeper inferences on can make from the resemblances than the descriptive first-order data itself. But here’s one source I found:
|Average difference||Identical twins||Identical twins raised apart||Full siblings|
These data indicate that IQ and height variation among sibling cohorts is on the order of ~2/3rd to 3/4th of the variation that one can find within the general population (my estimate of standard deviation of 2.5 inches for height below is about right, if a slight underestimate according to the latest data). But I also found a paper with more detailed statistics.
Kobe Bryant is an exceptional professional basketball player. His father was a “journeyman”. Similarly, Barry Bonds and Ken Griffey Jr. both surpassed their fathers as baseball players. Both of Archie Manning’s sons are superior quarterbacks in relation to their father. This is not entirely surprising. Though there is a correlation between parent and offspring in their traits, that correlation is imperfect.
Note though that I put journeyman in quotes above because any success at the professional level in major league athletics indicates an extremely high level of talent and focus. Kobe Bryant’s father was among the top 500 best basketball players of his age. His son is among the top 10. This is a large realized difference in professional athletics, but across the whole distribution of people playing basketball at any given time it is not so great of a difference.
What is more curious is how this related to the reality of regression toward the mean. This is a very general statistical concept, but for our purposes we’re curious about its application in quantitative genetics. People often misunderstand the idea from what I can tell, and treat it as if there is an orthogenetic-like tendency of generations to regress back toward some idealized value.
Going back to the basketball example: Michael Jordan, the greatest basketball player in the history of the professional game, has two sons who are modest talents at best. The probability that either will make it to a professional league seems low, a reality acknowledged by one of them. In fact, from what I recall both received special attention and consideration because they were Michael Jordan’s sons. It is still noteworthy of course that both had the talent to make it onto a roster of a Division I NCAA team. This is not typical for any young man walking off the street. But the range in realized talent here is notable. Similarly, Joe Montana’s son has been bouncing around college football teams to find a roster spot. Again, it suggests a very high level of talent to be able to plausibly join a roster of a Division I football team. But for every Kobe Bryant there are many, many, Nate Montanas. There have been enough generations of professional athletes in the United States to illustrate regression toward the mean.
The Pith: When it comes to the final outcome of a largely biologically specified trait like human height it looks as if it isn’t just the genes your parents give you that matters. Rather, the relationship of their genes also counts. The more dissimilar they are genetically, the taller you are likely to be (all things equal).
Dienekes points me to an interesting new paper in the American Journal of Physical Anthropology, Isolation by distance between spouses and its effect on children’s growth in height. The results are rather straightforward: the greater the distance between the origin of one’s parents, the taller one is likely to be, especially in the case of males. These findings were robust even after controlling for confounds such as socioeconomic status. Their explanation? Heterosis, whether through heterozygote advantage or the masking of recessive deleterious alleles.
The paper is short and sweet, but first one has to keep in mind the long history of this sort of research in the murky domain of human quantitative genetics. This is not a straight-forward molecular genetic paper where there’s a laser-like focus on one locus, and the mechanistic issues are clear and distinct. We are talking about a quantitative continuous trait, height, and how it varies within the population. We are also using geographical distance as a proxy for genetic distance. Finally, when it comes to the parameters affecting these quantitative traits there are a host of confounds, some of which are addressed in this paper. In other words, there’s no simple solution to the fact that nature can be quite the tangle, more so in some cases than others.
Because of the necessity for subtlety in this sort of statistical genetic work one must always be careful about taking results at face value. From what I can gather the history of topics such as heterosis in human genetics is always fraught with normative import. The founder of Cold Spring Harbor Laboratory, Charles Davenport, studied the outcomes of individuals who were a product of varied matings in relation to genetic distance in the early 1920s. This was summed up in his book Race Crossing in Jamaica:
A quantitative study of 3 groups of agricultural Jamaican adults: Blacks, Whites, and hybrids between them; also of several hundred children at all developmental stages. The studies are morphological, physiological, psychological, developmental and eugenical. The variability of each race and sex in respect to each bodily dimension and many basis vary just as morphological traits do. In some sensory tests the Blacks are superior to Whites; in some intellectual tests the reverse is found. A portion of the hybrids are mentally inferior to the Blacks. The negro child has, apparently, from birth on, different physical proportions than the white child.
It is known that Northern Europeans tend to be somewhat taller than Southern Europeans. This seems intuitively obvious if you spend a bit of time around representative populations. Growing up in the Pacific Northwest I’ve always been on the short side at 5 feet 8 inches, but when I was in Italy for 3 weeks one year back (between Milan and Rome, with disproportionate time spent in the Piedmont) I didn’t feel as small (I recall feeling similarly when I was in Cajun country in the early 2000s). Steve Hsu alerts me to the fact that Luke Jostins is back blogging at Genetic Inference, reporting from the Biology of Genomes meeting. Apparently Michael Turchin has found that:
1) Alleles known to be associated with greater height are found at higher frequencies in Northern Europeans
2) Alleles known to be associated with greater height also exhibit signatures of natural selection
The Pith: There has been a long running argument whether Pygmies in Africa are short due to “nurture” or “nature.” It turns out that non-Pygmies with more Pygmy ancestry are shorter and Pygmies with more non-Pygmy ancestry are taller. That points to nature.
In terms of how one conceptualizes the relationship of variation in genes to variation in a trait one can frame it as a spectrum with two extremes. One the one hand you have monogenic traits where the variation is controlled by differences on just one locus. Many recessively expressed diseases fit this patter (e.g., cystic fibrosis). Because you have one gene with only a few variants of note it is easy to capture in one’s mind’s eye the pattern of Mendelian inheritance for these traits in a gestalt fashion. Monogenic traits are highly amenable to a priori logic because their atomic units are so simple and tractable. At the other extreme you have quantitative polygenic traits, where the variation of the trait is controlled by variation on many, many, genes. This may seem a simple formulation, but to try and understand how thousands of genes may act in concert to modulate variation on a trait is often a more difficult task to grokk (yes, you can appeal to the central limit theorem, but that means little to most intuitively). This is probably why heritability is such a knotty issue in terms of public understanding of science, as it concerns the component of variation in quantitative continuous traits which is dispersed across the genome. The traits where there is no “gene for X.” Additionally, quantitative traits are likely to have a substantial environmental component of variation, confounding a simple genotype to phenotype mapping.
Arguably the classic quantitative trait is height. It is clear and distinct (there aren’t arguments about the validity of measurement as occurs in psychometrics), and, it is substantially heritable. In Western societies with a surfeit of nutrition height is ~80-90% heritable. What this means is that ~80-90% of the variance of the trait value within the population is due to variance of the genes within the population. Concretely, there will be a very strong correspondence between the heights of offspring and the average height of the two parents (controlled for sex, so you’re thinking standard deviation units, not absolute units). And yet height is at the heart of the question of the “missing heriability” in genetics. By this, I mean the fact that so few genes have been associated with variation in height, despite the reality that who your parents are is the predominant determination of height in developed societies.
Steve Hsu, The mystery of height:
I was looking at The Formosan Encounter: Notes on Formosa’s Aboriginal Society, A Selection of Documents from Dutch Archival Sources. The Dutch came to Taiwan (then called Formosa) in the early 17th century and these translated documents record their impressions of the Austronesian natives. (Both the Dutch and Chinese settlers traded with the natives during this period.)
One report states that the aboriginal men were taller by a head and neck, on average, than the Dutch. (The average Dutchman came only to the shoulder of the average native?) Another report describes the aborigines as tall and sturdily built, like semi-giants. This paper on historical Dutch height suggests that 17th century Dutchmen were about 170 cm or so on average. Holland was the richest country in Europe at the time, but nutritional conditions for average people were still not good by modern standards. So how tall were the aborigines? Presumably well above 180cm since “a head and neck” would be at least 20cm! (Some Native Americans were also very tall when the Europeans first encountered them.)
But, strangely, the descendants of these aborigines are not known for being particularly tall. This paper reports that modern day aboriginal children in Taiwan are shorter than their Han counterparts. On the other hand, the Dutch are now the tallest people in the world, with average male height exceeding 6 feet (183 cm). This kind of reversal makes one wonder whether, indeed, most groups of humans have similar potential for height under ideal conditions, as claimed here. (Note the epigenetic effects — several generations of good nutrition might be required for a group to reach its full height.)
And now from the The Economist:
In a nation of ~1 billion, even one where a large minority are positively malnourished, you’d expect some really tall people. So not that surprising: NBA Awaits Satnam From India, So Big and Athletic at 14:
In a country of 1.3 billion people, 7-foot, 250-pound Satnam Singh Bhamar has become a beacon for basketball hope.
At age 14.
That potential starts with his size, which is incredible itself. At age 14, he is expected to grow for another couple of years. For now, he wears a size-22 basketball shoe. His hands swallow the ball. His father, Balbir Singh Bhamara, is 7-2. His grandmother on his father’s side is 6-9.
Punjab is one of India’s more prosperous states. Interestingly this kid’s paternal grandmother is as tall in standard deviation units as her son or grandson. In Western developed societies height is 80-90% heritable. That means that there’s very little expected regression back to the population mean for any given child. The article doesn’t mention the mother’s height though. If she is of more normal size then Satnam is either a fluke, or, there are dominant large effect rare alleles being passed down by the father, perhaps from the paternal grandmother.
I recall projections in the early 2000s that 25% of the American population would be employed as systems administrators circa 2020 if rates of employment growth at that time were extrapolated. Obviously the projections weren’t taken too seriously, and the pieces were generally making fun of the idea that IT would reduce labor inputs and increase productivity. I thought back to those earlier articles when I saw a new letter in Nature in my RSS feed this morning, Hundreds of variants clustered in genomic loci and biological pathways affect human height:
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2, 3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
The supplements run to nearly 100 pages, and the author list is enormous. But at least the supplements are free to all, so you should check them out. There are a few sections of the paper proper that are worth passing on though if you can’t get beyond the paywall.
I knew that Yao Ming’s parents are very tall. Though his father, at 6’7, arguably contributed less than his mother, at 6’3, which is farther above the female mean in standard deviation units. But check this out from Superfusion: How China and America Became One Economy and Why the World’s Prosperity Depends on It:
Yao had essentially been bred. Both his parents played basketball. His 6’2 [different height from Wikipedia -Razib] mother, Fang Fengdi, perhaps the tallest woman in China, had been married to an even taller man. She had served as a Red Guard during the height of the Cultural Revolution and had been an ardent Maoist. She enthusiastically participated in the glorious plan of the local government to use her and her husband to produce a sports superstar. The Shanghai authorities who encouraged the match had gone back several generations to ensure that size was embedded in the bloodline. The result was Yao, a baby behemoth who just kept getting bigger.