Gene Expression

DARC and HIV: a false positive due to population structure?

noreply@blogger.com (p-ter) — Sat, 19 Jul 2008 14:45:00 +0000

The recent report that the Duffy null allele is associated with increased risk of HIV infection recieved a lot of press (see Razib's comments on it here), mostly positive. In Nick Wade's New York Times article on the paper, however, some smart people publicly express some doubts. It's a tribute to Wade that he actually tries to summarize those doubts in the limited space allotted to him:

Dr. Goldstein said that in parts of the United States, African-Americans have a higher infection rate than European-Americans, and that patients with a higher proportion of African genes may be more vulnerable to H.I.V. for reasons unconnected to the SNP. Nonetheless, the SNP would show up in a greater proportion of infected people simply because of their African heritage. If so, the gene's apparent association with H.I.V. infection could be just coincidental, not causal.

In somewhat more technical terms, the issue referred to here is the potential for false positives in an association study due to population structure[1]. The issues involved in accounting for structure in an admixture mapping study are somewhat more subtle than in a classic case-control study, but are generally similar. In particular, it's important to take individual levels of admixture into account[2]; this is generally done by including an estimate of individual admixture as a covariate in any regression model.

The authors are aware of this potential confounder, and develop a measure of admixture based on 11 SNPs to include as a covariate in their regression. However, this measure is kind of weak, which I imagine in the sticking point for the skeptics in the Times article. If you have access to the supplemental information, take a look at it--several of these 11 SNPs are in the same gene, which means they're not independent, and several don't even have big frequency differences between African and European samples (if you're trying to judge via SNPs whether someone is more African or European, those SNPs better have a big frequency difference between Africa and Europe). This is probably not a precise measure of ancestry. In fact, the Duffy null allele they claim as associated is a better predictor of ancestry than any of these SNPs.

So it's quite possible that the authors have simply shown a correlation between level of African ancestry and susceptibility to HIV (which could be due to any number of sociological, demographic, or genetic factors), rather than an association between Duffy null and susceptibility to HIV. Here's a relatively simple test of this possibility: genotype rs1426654 (the nonsynonymous SNP in SLC24A5) in their sample and perform exactly the same test as performed with Duffy. The motivation for this is that this SNP shares the property of Duffy null of being highly informative about ancestry, while being in a gene that presumably plays no role in HIV infection. If you get an association there, it seriously calls the Duffy result into question; if not, you feel a bit more comfortable.

[1] For the classic extreme example of how population structure leads to false positive associations, consider a case-control association study on, say, diabetes, where the cases are all from Nigeria and the controls from France. Clearly, the cases are all going to have a high frequency of the Duffy null allele, and the controls are all going to have a low frequency (as Duffy null is essentially fixed in Africa and absent elsewhere), and one might naively conclude that Duffy null causes diabetes. But of course, the Duffy blood group has absolutely nothing to do diabetes (I don't think!), and the researchers have simply been confused by not matching their cases and controls. Obviously, this example is extreme, but more subtle population structure can also confound an association study (and methods for correcting for it are an active area of research; see here, for example)

[2] It's well-known that African-Americans are an admixed population, with about 15-20% European ancestry on average. But there's great variability in this--a single sample of self-defined "African-Americans" can contain individuals with essentially no European ancestry and individuals who look genetically to be completely European. And on a larger scale, within the United States there's heterogeneity in admixture proportions as well (see Parra et al.). How could this create false positives? Essentially, if risk for a disease is correlated with ancestry for any reason, there's the potential for getting false positives. In this particular example, if HIV rates are higher in metropolitan areas where there's been more admixture, or if there are other genetic factors that make Europeans more resistant to HIV, etc., any "African allele" (like Duffy null) will show up as associated with HIV despite playing absolutely no role in the disease.

The Inheritance of Inequality: Big Insight, Small Error

noreply@blogger.com (Herrick) — Fri, 18 Jul 2008 22:58:00 +0000

Gintis and Bowles have done great work cleaning up a lot of the discussion about cooperation, evolution, and economic outcomes. A Google Scholaring of their names turns up 14 items with over 100 citations, most of which would be well worth reading for GNXP regulars.

But that said, in their 2002 Journal of Economic Perspectives piece "The Inheritance of Inequality," they appear to make a small error. It's an error that's all-too-easy for even good folks to make: They apparently squared the h-squared.

Their big insight and their small error are all part of answering a simple question: How much of the correlation of income between parent and child can be explained by the heritability of IQ? You might think it's straightforward: IQ is highly heritable, so if there's some channel linking IQ to income, then it's all over but the shouting.

But numbers matter. And Gintis/Bowles work out the numbers, finding that there's a weak link in that causal chain: The low correlation (0.27 according to Gintis and Bowles) between IQ and wages. The causal chain goes like this:

1. Parental earnings have a 0.27 correlation with parent's IQ.
2. Heritability of IQ between parent and child is a bit more than 1/2 of h-squared (why a bit more? assortive mating). They take an h-squared of 0.5 for IQ.
3. Child's earnings have a 0.27 correlation with child's IQ.

So the net result is 0.27*0.3*0.27 = 0.022 (page 10). A very small number, especially since the raw parent-child income correlation in U.S. data is about 0.4. So yes, knowing a parent's income helps you predict their adult (especially male) child's income. But only 5% (or 0.022/0.4) of the total correlation can be explained by IQ's impact on wages. Small potatoes.

(Oh, but where's the small error? It's where Gintis and Bowles report that the net result is 0.01 instead of 0.022--a difference that I can most easily attribute to a mistaken squaring of the h-squared.)

If I really wanted to get that net result up from a measly 5%--if I knew in my heart that IQ really was a driving force in intergenerational income inequality--then how would I do it? Well, I might use a higher heritability of IQ, I might assume more assortive mating, or I might assume a bigger correlation between wages and IQ.

Hard to do much to budge that IQ/wage link: Zax and Rees's paper only has a 0.3 correlation between teenage IQ and middle-aged wages, and when Cawley, Heckman et al. regress NLSY wages on the first 10 principal components of the AFQT, they get a similar result.

So you think maybe a higher heritability of IQ will save you? Well, let's just go all the way to perfect heritability of IQ and perfect assortive mating on IQ. In other words, let's see if "IQ clones" will be have enough similarity in wages to match the 0.4 intergenerational correlation of income.

Will the IQ clones have similar incomes? Not so much. (0.3^2)*1 still equals something small: 0.09. Less than 1/4 of the intergeneration correlation in income. Medium-sized potatoes, but we had to make a ton of ridiculous assumptions to get there.

It's that doggone low correlation between IQ and wages, a correlation that has to be squared because we're comparing parent to child. So a high heritability of IQ doesn't imply a high heritability of IQ-caused-income. Another reminder that lots of things impact your wages: Not just how smart you are.

Gintis and Bowles work through some finger exercises to argue for big environmental effects, and that's all well and good. But to my mind, the interesting fact is that income is still highly heritable!

G/B report that MZT (identical twin) earnings correlation is 0.56, and DZT (fraternal twin) earnings correlation is 0.36, so using the crudest of approximations, the heritability of earnings is still (0.56-0.36)*2=0.4. So income apparently has a modestly high heritability, but most of it can't be explained by the IQ-wage channel. Looks like the genetic heritability of income is being driven mostly by non-IQ channels.

sextroverts

noreply@blogger.com (ben g) — Fri, 18 Jul 2008 20:20:00 +0000

Truism of the day: Introverted nerds don't get laid much. Or, in more scientific terms, extroversion in men is linked to a higher number of sex partners.[1] Men and women have similar levels of extroversion, though-- in fact, women have slightly higher levels of it.[2] This begs for explanation; after all, extroversion is significantly heritable (~50%)[3], so why shouldn't it have been positively selected for in males?

It turns out that, while men aren't more extroverted than women, they are more extroverted in the areas where it "counts.""The table below[2] of extroversion and its sub-traits sheds some light:

Trait	Mean Difference (Female - Male)	High (%F)	Very Low (%F)
Extraversion	1.8	58	44
Warmth	1.3	67	35
Gregariousness	1.0	63	38
Assertiveness	-0.9	45	58
Activity	0.5	64	45
Sensation seeking	-1.5	42	70
Positive emotions	1.3	78	36

(mean difference is the mean difference between men and women on the trait. high %F and low %F are the percent of women who are at the very high and very low tail-ends of the distribution.)

With the exception of 'ideas' (F-M=-1.6), a sub-trait of Openness to Experience, none of the 30 Big-Five sub-traits show more skew towards men than do assertiveness and excitement-seeking. While these -.9 and -1.5 mean differences may seem minor on their face, it is worth considering how they affect the tails of the distributions. In the case of sensation-seeking, 70% of people who are significantly low on excitement-seeking are female. A great deal of meaningful sexual dimorphism here, so let's look into it...

Sensation-seeking

Browsing through the sensation-seeking literature I came across this very interesting study; sensation-seeking was one of many variables examined in a study of college mens' number of sexual partners.[4] The other variables looked at (and all measured through questionnaires unless otherwise indicated) were: age, attractiveness (measured by self-rating, and female, male interviewer ratings), social intimacy, sexual affect, dominance, hypermasculinity, Eysenck's psychoticism trait measure, and testosterone levels (measured chemically through saliva samples).

Sensation seeking correlated more so than any other variable with both lifetime number of sexual partners (.38) and with maximum partners in one month (.37). Trailing way behind it was hypermasculinity (.29, .29), followed by attractiveness (.20, .28).[4,5]

I'm not going to attempt to unwind the complex causal chains which correlate sensation-seeking to short term mating success. It should suffice to say that there is significant evidence that these traits are both intrinsically attractive to women, and that they serve as an impetus to sexual pursuit of women by men in the first place.[7] Sensation- seeking has the highest narrow-sense heritability of any (Big-5) sub-trait-- .36, and a relatively high broad-sense heritability of .52, by the way.[3]

A Pet Hypothesis

It seems plausible that sensation-seeking garnered a greater number of female mates in the Pleistocene , just as it does now, and that there was therefore positive selection for it in men. I would posit that if this positive selection existed, it was limited in effect by the negative aspects of extroversion, visible in our day in age-- extroverts are more at risk for STD's, being jailed, getting in fights, and generally doing stupid risky things.

The fact that Extraversion has a higher degree of heritability in men than in women (.57 versus .38)[3] might be considered as evidence. I am not knowledgeable enough of the behavior genetics involved to say whether this is meaningful evidence.

The most specific, and testable part of my hypothesis is this: that ADHD (note that I'm not saying ADD) is to some extent the result of "overclocking" for male sensation-seeking. Consider this-- estimates of the male:female ratio for ADHD range from 4:1 to 9:1.[8] People with ADHD are more extroverted than other people, yes, but they are especially more sensation-seeking than other people. Unsurprisingly, people with ADHD have a higher number of sexual partners than people without.[9] The discrepancy between males without ADHD and those with it is probably underestimated because of the widespread use of drugs like Ritalin.

Notes

1. (Nettle 2004).
2. (Corbitt & Widiger 1995). See the table in their article for all of mean differences and percentile differences at the tails of the bell curves between men and women.
3. (Loehlin & Bouchard, 2001)
4. (Bogaert et. al 1995)
5. Sensation seeking correlated trivially with age, .14 with Attractiveness, .26 with dominance, .41 with hypermasculinity, and .45 with psychoticism. Statistically eliminating virgins from the sample had no major effects on these correlations. For you data crunchers out there I suggest you read the study yourself if you want to analyze their factor and regression analyses.
6. (McCoul & Haslam 2001).
7. There's a good summary of some of the studies on why sensation-seeking might cause more mates in (McCoul & Haslam 2001).
8. (Gutman 2002)
9. (White 1998)

References

Nettle, D. (2004). An evolutionary approach to the extraversion continuum. Evolution and Human Behavior
Corbitt, E.M. and W.A. (1995). Sex Differences Among the Personality Disorders: An Exploration of the Data. Clinical Psychology: Science and Practice.
Loehlin, J.C., & Bouchard, T.J. (2001). Genes, Evolution, and Personality. Behavior Genetics.
Bogaert, A.F. and Fisher, W.A. (1995). Predictors of University Men's Number of Sexual Partners. The Journal of Sex Research
Maryann D. McCoul and Nick Haslam (2001). Predicting high risk sexual behaviour in heterosexual and homosexual men: the roles of impulsivity and sensation seeking. Personality and Individual Differences
Gutman, A. (2002). ADHD -- Perspectives From Child to Adult. Retrieved July 18, 2008, from the MedScape Web site
White, J.D. (1998). Personality, temperament and ADHD: a review of the literature. Personality and Individual Differences.
Kate et al (2006). Childhood ADHD Predicts Risky Sexual Behavior in Young Adulthood. Journal of Clinical Child and Adolescent Psychology

R. A. Fisher and Epistasis

noreply@blogger.com (DavidB) — Fri, 18 Jul 2008 12:21:00 +0000

My next note on Sewall Wright will cover the exciting subject of the adaptive landscape. As every schoolboy knows, Wright considered epistatic gene interactions very important in determining the 'peaks' of the landscape. A sharp contrast is sometimes drawn between Wright and R. A. Fisher in this respect. For example:

Fisher believed that the process of genetical evolution occurred through selection that acts on the additive effects of genes in large populations. Although Fisher formally considered gene interactions, he was also dismissive of them, likening epistatic genetic variation to nonheritable (i.e. nontransmissible) environmental variations of phenotype. In contrast, Wright believed that nonadditive, or epistatic, effects were of primary importance, particularly in subdivided populations.
- from the editors' Preface to Epistasis and the Evolutionary Process

What is said here about Wright seems broadly correct, but what is said about Fisher is seriously misleading. Before continuing with my notes on Wright, I will therefore try to clarify Fisher's views on epistasis.[Note: due to formatting problems, italics and other refinements may be omitted.]

First, it is necessary to say something about the meaning of epistasis. The term 'epistasis' itself seems to have emerged around 1917. The first use cited in the OED is from the index to the 1917 volume of the journal Genetics. Around the same time Fisher, in writing his 1918 paper on the Correlation of Relatives, coined the term 'epistacy', but this never caught on. Both terms were derived from the adjective 'epistatic'. Like much of the terminology of genetics (including the word 'genetics' itself) this was coined by William Bateson, in 1907. Bateson used it with a relatively limited meaning to describe cases where a gene at one locus masked or suppressed the action of genes at another locus. For example, genes at one locus might affect the pigmentation of an animal's fur, but a gene at another locus might suppress the production of pigment entirely, causing albinism. In this case the trait of albinism (or the gene producing it) would be called epistatic (literally 'standing over'), while the traits that were masked would be called 'hypostatic' (literally 'standing under'). This limited usage of 'epistatic' is still sometimes found in medical genetics, but in evolutionary genetics a wider usage is more common. In the wider usage, epistasis is any kind of interaction between genes at different loci. Of course, many traits are affected by genes at more than one locus, but this does not necessarily imply interaction. The meaning of 'interaction' is that the genes at different loci do not act independently. For qualitative traits, the usual test of this is that the traits of the offspring do not show the expected Mendelian ratios (which is how epistasis in Bateson's sense was originally discovered). For quantitative traits, the usual criterion is that the value of the trait is not simply the sum of the values attributable to the individual genes concerned. If it is simply the sum, the genes are often said to have a purely 'additive' effect. If not, the trait either shows dominance (if the interaction is between genes at the same locus) or epistasis (if at different loci).

Assuming that epistasis can be identified (which in practice is often very difficult for small effects), it may be asked how the effects of epistatic interaction on a quantitative trait can be measured. One answer to this would be to decide that where interaction is involved, the entire effect of the interacting genes should be counted as epistatic. But this seems unreasonable if the same genes would still have some effect even if there were no interaction. An ideal solution might be to find cases in which the genes concerned are not involved in any epistatic relations, and measure their effect in these circumstances, then subtract this from the effect in the case of epistasis. But if epistasis is a widespread phenomenon, it would be difficult to find these non-epistatic cases, since most genes would show some effects of interaction. In any event, a different approach is generally taken.

The usual approach to measuring the effects of epistasis is roughly as follows. Each gene is assigned a value (the 'average effect' of the gene) based on the average value for the trait concerned among those members of the population who carry that gene, expressed as a deviation from the population mean. Each genotype (gene combination) is then assigned a value based simply on the sum of these average values. This is called the 'breeding value', since it is the part of the genetic makeup of the individual which enables the traits of its offspring to be predicted for breeding purposes. These breeding values will have a certain variance, relative to the population mean, usually called the additive genetic variance. The actual observed values will have a greater variance than this, due to the effects of environment, dominance, epistasis, and various other complications. The portion of the observed variance attributable to epistasis is estimated after the effects of environment and dominance have been subtracted. Genes with epistatic effects are not excluded from the analysis, and they may contribute to both additive and (in a more complicated way) to dominance variance as well as to the specific epistatic or 'genetic interaction' variance. All this is explained more fully, and no doubt more clearly, in Falconer. For a simple worked example of my own see Note 1.

The standard terminology is unfortunate. It cannot be stressed too strongly that 'additive' variance is not the same as the variance due to genes with purely additive effects. The additive variance takes account of the average effects of all genes, including those that may show strong dominance or epistasis. These average effects depend in part on the gene frequencies present in the population in question, and assume that all possible genotypes occur in the proportions expected under a given system of mating (usually assumed to be random). Part of the average effect is therefore due to the effects of gene interactions. Conversely, the so-called 'epistatic variance' covers only a part - usually the minority - of the effects that might intuitively be ascribed to interaction. Enthusiasts for epistasis (as in the volume already cited) sometimes complain that the standard method of apportioning variance tends to understate the effects of epistasis, and makes it difficult to detect. For example, James Cheverud comments that 'most tests for epistasis rely on the epistatic variance alone and ignore its contribution to additive and dominance variance' (p.65) and Edmund Brodie says that 'under a wide range of allele frequencies and strengths of interaction, the majority of variance produced by gene interaction is actually additive' (p.10). It would be possible in principle to use alternative measures which assign more of the observed variance to epistasis. But the standard method does have the advantage that it is possible to estimate the additive variance from the observed correlation between parents and offspring, and conversely to estimate the value of offspring from that of parents. This is particularly important if we wish to predict the effects of natural or artificial selection. Whatever we call it, the 'additive' variance is a useful concept and is not going to go away.

It is also desirable to distinguish between epistasis for fitness and for other traits of the organism. Fitness itself (whether measured simply by number of offspring or otherwise) shows epistasis if the effects on fitness of genes at different loci are not purely additive. If fitness is measured in relation to some particular trait, the fitness may show epistasis even if the trait as such does not. (And presumably vice versa, though I cannot think of a plausible scenario for this.) For example, a trait such as body size might be influenced by several genes acting purely additively in their effects on body size, but epistatically in their effect on fitness. This will often be the case if fitness is highest for some intermediate value of the trait. The fitness effects of genes tending to raise (or lower) the value of the trait will then depend crucially on the other genes they happen to be combined with. In the simplest case, if there are two haploid loci, with alleles H and L (for High and Low) at one locus, and h and l at the other, the combinations Hl and hL, which give intermediate size, may be favoured by selection, while the combinations Hh and Ll, which give high and low size respectively, are selected against. In this case the fitness is epistatic even though the direct effect of the genes on the phenotype is additive.

After all these preliminaries, I turn to discuss what Fisher actually said about epistasis.

Correlation of relatives

As already mentioned, Fisher's great 1918 paper on the 'Correlation of Relatives' proposed the term 'epistacy' to allow for the interaction of genes at different loci, and devised the standard method for apportioning variance. Fisher introduces his definition of 'epistacy' as follows: 'There is in dominance a certain latency. We may say that the somatic [phenotypic] effects of identical genetic changes are not additive, and for this reason the genetic similarity of relations is partly obscured in the statistical aggregate [see Note 2]. A similar deviation from the addition of superimposed effects may occur between different Mendelian factors [genes at different loci]. We may use the term Epistacy to describe such deviation, which although potentially more complicated, has similar statistical effects to dominance. If the two sexes are considered as Mendelian alternatives, the fact that other Mendelian factors affect them to different extents may be regarded as an example of epistacy. The contributions of imperfectly additive genetic factors divide themselves for statistical purposes into two parts: an additive part which reflects the genetic nature without distortion, and gives rise to the correlations which one obtains, and a residue which acts in much the same way as an arbitrary error introduced into the measurements. ' (p.404) Note that Fisher says here quite explicitly that part of the contribution of 'imperfectly additive' genes is itself additive, or as we would say, falls within the additive variance. Fisher does not say a great deal more about 'epistacy' in this paper (but see p.408-9 for the mathematical treatment of epistatic variance), and one of the contributors to the volume cited earlier claims that in his 1918 paper Fisher 'dismissed gene interactions as being of only minor importance in the evolutionary process, analogous to nonheritable modifications of the phenotype' (p.125). This goes beyond anything Fisher says. What he does say is that 'Throughout this work it has been necessary not to introduce any avoidable complications, and for this reason the possibilities of Epistacy have only been touched upon...' (p.432). For Fisher's specific purpose in this paper, which was to explain the correlation between relatives on Mendelian principles, and not to discuss evolutionary theory in general, his brief treatment of 'epistacy' seems sufficient. Fisher finds that with his methods the existing data on the correlation of relatives (mainly the data of Karl Pearson on humans) can be explained satisfactorily by additive variance, dominance, and assortative mating, without much influence of other factors, which by implication include epistatic variance. Fisher is more explicit about this in his 1922 paper on the Dominance Ratio, where he says that 'special causes, such as epistacy, may produce departures [from the expected correlations], which may in general be expected to be very small from the general simplicity of the results'. But before interpreting this as a general pronouncement on the insignificant role of epistasis in evolution, we should note that (a) the additive variance includes much of the effect of 'epistatic' genes, and (b), the discussion was concerned with ordinary traits such as height, and not with fitness. As emphasised earlier, there may be epistasis for fitness even if the underlying traits are purely additive.

The evolution of dominance

One of Fisher's best-known, and most controversial, theories is that of the evolution of dominance. Noting that harmful mutations are usually (though not always), recessive in their effects, Fisher sought to explain this by the action of modifier genes at other loci, which would be gradually selected to minimise the harmful effects of common recurring mutations by making them recessive. The theory has not been generally accepted, and Wright in particular opposed it, mainly on the grounds that the selective advantage of modifier genes would be so weak that it would usually be overpowered by their other, more direct, effects. Regardless of whether Fisher was right or wrong on this issue, the point to note here is that his theory depends entirely on epistatic effects! In this respect, at least, Fisher was more enthusiastic about epistasis than Wright himself.

Mimicry

A whole chapter of the Genetical Theory of Natural Selection is concerned with Mimicry. In discussing the underlying genetics of mimicry, Fisher emphasises the role of modifier genes, including those that act as 'switches' for other genes. For example, discussing the 'hooded' gene in rats, he says 'The gene, then, may be taken to be uninfluenced by selection, but its external effect may be influenced, apparently to any extent, by means of the selection of modifying factors' (p.185). And in discussing another case he goes on to say 'The gradual evolution of such mimetic resemblances is just what we should expect if the modifying factors, which always seem to be available in abundance, were subjected to the selection of birds or other predators' (p.185). While modifiers might in principle be purely additive in effect, they are more likely to be epistatic. This is presumably always the case with 'switch' genes.

Sex

Chapter 6 of GTNS deals with a variety of issues concerning sex, sexual selection, sex-limited traits, and speciation. Some of these could well involve epistasis - indeed, 'sex-limited' traits (those which are only manifested in one sex) do so almost by definition, if sex is genetically determined. (As mentioned in Fisher's paper on 'Correlation of Relatives', quoted above, differences between the sexes can be regarded as a case of 'epistacy'.) However, I find only one definite reference in the chapter to epistatic effects. In his discussion of speciation, Fisher points out that the adaptiveness of genes will vary in the different parts of a species's range, and says that 'In addition to those genes which are selected differentially by the contrasted environments, we must moreover add those, the selective advantage or disadvantage of which is conditioned by the genotype in which they occur, and which will therefore possess differential survival value, owing not directly to the contrast in environments, but indirectly to the genotypic contrast which these environments induce' (p.141). A difference in the selective advantage of a gene according to the genotypic background implies epistatic fitness. What Fisher is describing here is actually what is often called a 'co-adapted gene complex', much beloved of Wrightians.

The Fundamental Theorem of Natural Selection

The Fundamental Theorem of Natural Selection states that 'The rate of increase in fitness of any organism at any time is equal to its genetic variance in fitness at that time' (GTNS p.37). The FTNS is notoriously difficult to interpret, and I do not intend to say much about it here. It is however now generally accepted, following the interpretations by George Price and A. W. F. Edwards, that when Fisher refers to 'genetic variance' he means the 'additive' genetic variance. The additive variance takes account of the average effect of genes in all the various environmental circumstances and genetic combinations in which they are found, in the proportions to be expected under a given system of mating. (See expecially p.31 of GTNS, where Fisher defines 'average excess' and 'average effect'.) It therefore incorporates the effects of dominance and epistasis to the extent that these contribute to the additive value of the genes. There is no reason at all to suppose that genes with epistatic effects are excluded from the FTNS. What is excluded is only that part of the total variance that is not covered by the contribution of those genes to additive variance. This can be justified on the grounds that the non-additive variance does not predictably change gene frequencies in the next generation and therefore has little effect on evolution. As Cheverud admits, 'the rate of evolution is determined by the additive genic [sic] variance alone' (p.65).

Selection at two loci

Before 1930 neither Fisher nor Wright had treated selection at more than one locus. As so often, the pioneer of the subject was J. B. S. Haldane, in 1926. In 1930 Fisher did however give the subject a short section in Chapter 5 of GTNS, under the heading 'Equilibrium involving two factors'. (This chapter is one of several that appear to be invisible to some readers.) The interesting situation, as Fisher recognises, is where two different combinations of alleles (e.g. AB and ab) are both favoured by selection, while the same genes are disadvantageous in other possible combinations (e.g. Ab and aB). Fitness in this case is therefore clearly epistatic. In his chapter summary Fisher says that stable equilibria may be established, but he is rather vague about the conditions for stability. But his main point is that there will be selection in favour of closer linkage between favourable gene combinations on the same chromosomes, and it is therefore a puzzle why recombination is as frequent as it is. I think this remains a problem. In any event, it is a case where Fisher clearly recognised the role of epistasis.

Selection of metrical characters

One of the most intriguing, but difficult, sections of GTNS is the one (also in the 'invisible' Chapter 5) on 'Simple metrical characters'. (I sometimes wonder if Fisher's use of the word 'simple' was a sly joke.) The case of interest is where a quantitative character, such as the size of a tooth, is regulated by genes at more than one locus, and subject to stabilising selection in favour of an intermediate size. Egbert Leigh has described this (in his 'Afterword' to the 1990 reprint of Haldane's 'The Causes of Evolution') as 'a topic still replete with mysteries and surprises'. Fisher's account is even more tangled than most, because he attempts to explain simultaneously selection of the metrical trait itself and selection for dominance of the genes controlling it. I cannot pretend to understand everything he says on the subject, but what is clear for the present purpose is that fitness in this case is epistatic, and that there may be more than one outcome of selection, depending on the initial frequencies of the genes concerned: 'the conditions of equilibrium are always unstable. Whichever gene is at less than its equilibrium frequency will tend to be further diminished by selection' (p.121). This is precisely the situation which Wright often emphasised as leading to alternative 'selective peaks'. But unlike Wright, Fisher did not believe a species was likely to get 'stuck' permanently on a selective peak (not that Fisher had much time for the adaptive landscape anyway). Fisher believed that following any change in the optimum phenotypic value due to environmental change there would be sufficient genetic variation (in a large population) for selection to shift organisms quickly towards the new optimum. His confidence in this was based mainly on the results of artificial selection, as he referred to 'the extreme rapidity with which such measurements are modified when selection is directed to this end' (p.119). The effects of such changes on gene frequencies might be lasting, even if the initiating circumstances were temporary. In Fisher's analogy, which may be more illuminating to physicists than to me, 'the system resembles one in which a tensile force is capable of producing both elastic and permanent strain, and in which the permanent deformations always tend to relieve the elastic forces which are set up' (p. 125).

This section of GTNS raises a rather intriguing historical possibility. As Provine has noted in his biography of Wright (Provine p.285-6), there was an unexplained change in Wright's account of the 'shifting balance' theory between his exposition in 'Evolution in Mendelian Populations' (1931), and his next major account in 1932. In 1931 he had asserted that temporary changes in the environment would only have temporary effects on the gene pool, being essentially reversible. Hence his emphasis on genetic drift in small subpopulations, as the only possible means of shifting from one peak to another. In 1932, on the other hand, he accepted that environmental changes could also shift a population from one stable peak to another, so that their effects might be lasting even after the change in environment had reversed. Unfortunately Wright did not explain the reasons for his change of mind, nor did he draw attention to the change, which is really very important, since it greatly weakens Wright's argument for the importance of genetic drift in small local subpopulations. Provine speculates, plausibly enough, that Wright's correspondence with Fisher, his reading of GTNS, and Fisher's own published review of 'Evolution in Mendelian Populations', had something to do with the change. My own suggestion, to build on this, is that Fisher's discussion of metrical characters in Chapter 5 of GTNS was a particular influence. But I have no direct evidence of this, so it will probably remain a mere speculation.

Conclusions

The main purpose of this note has been to identify and document what R. A. Fisher himself, as opposed to the straw man 'Fisher', actually said and believed about epistasis. Readers will be able to draw their own conclusions, but I will briefly indicate my own.

a) Fisher did not deny the existence of epistasis, in the broad sense, and in some specific cases - including the evolution of dominance, selection at two loci, and quantitative (metrical) traits under stabilising selection - he gave it an important role.

b) Fisher agreed with Wright (and Haldane) that in some circumstances, including stabilising selection, there could be more than one outcome of selection in terms of the resulting gene frequencies. Unlike Wright (in 1931), but like Wright (in 1932), he believed that temporary environmental change could shift a population durably from one equilibrium set of gene frequencies to another. Fisher's treatment of the problem in GTNS may have influenced Wright's unexplained volte-face on this important issue.

c) Fisher did not believe populations were likely to get stuck on a local peak in the selective landscape, but this was not because he did not believe in epistatic effects, but because he did not believe in the validity of the selective landscape concept at all. I will probably say more about Fisher's thinking on this in another post.

d) Fisher's general concept of evolutionary change, as expressed in the Fundamental Theorem of Natural Selection, does not exclude epistatic effects. The FTNS takes account of epistasis (and dominance) precisely to the extent that they do affect the rate of evolutionary change. The FTNS is neutral with respect to the importance of epistasis: whether it is important or unimportant cannot be inferred from the theorem, which takes account of additive variance in fitness whatever its source. Unfortunately much confusion has arisen about the meaning of 'additive' and 'epistatic' variance. If it is not understood that 'additive' variance includes much of the effect of epistatic genes, while 'epistatic' variance excludes much of that effect, the scope of the FTNS will be seriously misconstrued. It would be better to call additive variance something like 'heritable variance', while the non-additive effects of dominance and epistasis are clearly labelled in such a way as to make it clear that they are only part of the total effect of gene interactions.

e) Unlike Wright, Fisher did not, at least in his published works, put any emphasis on epistasis as a major factor in evolution. It is necessary to read GTNS quite carefully (or at least to look at all the chapters!) to find the references I have gathered together here. It is an empirical matter whether epistasis plays the central role that Wright gave it. Or it might have an important role that neither Wright nor Fisher had thought of, as suggested in Kondrashov's theory of sex.

I have not dealt here with another aspect of Fisher's views, namely his rejection of the importance in evolution of large single mutations. I have no doubt that Fisher believed that evolution occurred mainly through the selection of a large number of genes with individually small effects. I have not discussed this because (a) it was not a point of disagreement between Fisher and Wright, and (b) it does not seem relevant to the issue of epistasis. As far as I can see, large mutations are no more or less likely to have epistatic effects than small ones.

Addendum

After writing the above, I came across a further reference to epistasis in Fisher's correspondence. Writing to Leonard Darwin in 1928, Fisher said 'I am inclining to the idea that the main work of evolution lies in the discovery by trial of perhaps rare combinations of its existing variants, which work better than the commoner combinations. A slight increase in the number of individuals bearing such a favourable combination will then set up selection in favour of all the genes in the combination, with marked evolutionary results. Many of these genes would have been previously rare mutant types (not necessarily rare mutations) unfavourable to survival. I think of the species not as dragged along laboriously by selection like a barge in treacle, but as responding extremely sensitively whenever a perceptible selective difference is established. All simple characters, like body size, must be always very near the optimum, so much so that the average body sizes of two alternative genes must be balanced on either side of the optimum, selection always tending to eliminate the rarer because it is further from the optimum...' (Correspondence p.88). In his Introduction to the correspondence, J. H. Bennett draws attention to this letter, and remarks that 'It is interesting, and perhaps needs emphasizing, that both Fisher and Wright considered systems of interacting genes to be of critical importance in evolution. A fundamental difference in their views of the evolutionary process concerned the means by which interaction systems could be exploited' (p.47) While I agree with Bennett that Fisher took some account of 'interaction systems' , in other words epistasis in the broad sense, this letter of 1928 seems a good deal more positive on the subject than anything I have noticed in his published works. I take this opportunity to say that Bennett's Introduction is one of the most useful things yet written on Fisher's work and ideas, and deserves repeated reading.

Note 1

Consider the simplest case of a haploid organism with a quantitative trait determined by genes at two loci. I assume complete genetic determination. Let the alleles in the population be A and a at one locus, and B and b at the other, each with a frequency of 50% in the population. Under random mating the four genotypes AB, Ab, aB and ab will therefore all have the frequency 25%. (In a diploid there would be nine genotypes to consider, and the possible complication of dominance, which is why I have chosen the haploid case.)

Let us suppose that the measurements of the trait for the four genotypes are as follows, where c and d are any numerical values:

AB........c + d
Ab........c
aB........c
ab.........c

I have chosen these values to dramatise the situation. Intuitively, one would say that all of the variation in the trait was due to the epistatic interaction of A and B, since all other genotypes than AB have the identical value c. So let us see how the variance comes out under the standard method.

The mean value of the trait in the population is evidently .75c + .25(c + d) = c + .25d. The mean values for each gene considered separately, measured by the average value of the individuals who possess that gene, are:

A........ .5(c + d) + .5c = c + .5d
a......... c
B........ .5(c + d) + .5c = c + .5d
b........ c

Expressed as deviations from the population mean, c + .25d, these values come out as:

A........ + .25d
a......... - .25d
B........ + .25d
b........ - .25d

These are known as the 'average effects' of the genes in question.

The so-called 'breeding value' of a genotype is simply the sum of the average effects of its component genes, so for the four genotypes we have the breeding values:

AB.......... + .5d
Ab.......... 0
aB.......... 0
ab.......... - .5d

It may be noted that the combination ab has a substantial (negative) breeding value, even though there is, intuitively, no interaction between a and b. This reflects the fact that the interaction of A and B pulls up the population mean, and therefore affects the deviation values of other alleles and genotypes. The combination ab falls as far below the resulting mean as the combination AB rises above it. The symmetry is of course a consequence of the symmetry of the chosen assumptions about gene frequencies, etc.

The breeding values are already deviations from the population mean, so for the variance of breeding values (the so-called additive genetic variance) we have:

.25(.5d)^2 + .25(0)^2 + .25(0)^2 + .25(.5d)^2 = .125d^2.

It is already apparent that although the variance is intuitively entirely due to epistasis, the 'additive' variance is not zero. For comparison, we can measure the total variance of the values of the genotypes. The deviation values are as follows:

AB.......... c + d - (c + .25d) = .75d
Ab, aB, and ab.......... c - (c + .25d) = - .25d

Taking account of the proportions of the genotypes in the population we therefore have the variance of genotypic values as follows:

.25(.75d)^2 + .75(- .25d)^2 = .1875d^2

Subtracting the 'additive' variance from the total genotypic variance we find only .0625d^2 left for the 'epistatic' variance. So even where we have rigged the example to give a strong influence to epistasis, 2/3 of the resulting variance is 'additive', and only 1/3 'epistatic'!

Note 2: I think that by 'genetic changes' in this sentence Fisher means not just mutations, but any gene substitution, such as may occur through the normal processes of sexual reproduction. So, for example, if at a single locus the combination aa is replaced by the combination Aa, there will be a certain measurable effect of the change. If the effect of substituting two As is twice the effect of substituting just one A, the effect is additive. Otherwise the locus shows some degree of dominance.

References:

D. S. Falconer: Introduction to Quantitative Genetics, 3rd. edn., 1989

R. A Fisher: The Genetical Theory of Natural Selection, 1930. I have given page references to the revised Dover edition of 1958, but the quoted passages are all unchanged from the first edition. For scholarly purposes the best edition is now the Variorum edition of 1999, edited by Henry Bennett.

Fisher's papers are cited from the online copies available from the archives at Adelaide (see link on sidebar)

Natural Selection, Heredity and Eugenics: Including selected correspondence of R. A. Fisher with Leonard Darwin and others, edited by J. H. Bennett (1983). Much of the correspondence is also available online from the archives at Adelaide.

Epistasis and the Evolutionary Process, ed. J. B. Wolf, E. D. Brodie, and M. J. Wade. 2000

William B. Provine: Sewall Wright and Evolutionary Biology, 1986. (Paperback edn. 1989)

Studying natural variation leads to interesting biology

noreply@blogger.com (p-ter) — Fri, 18 Jul 2008 02:17:00 +0000

Model organisms are models for a number of reasons: they're relatively easy to work with in the lab, or there are a lot of experimental tools available, or maybe even simple interia. But given that they're models and various neat mutagenesis assays are available for toying around with them, people often forget that even model organisms often show a massive amount of natural variation. There's a reason to map this natural variation over variation due to mutagenesis: it's been visible to selection, and so may highlight key nodes of networks that are open for adaptive (or neutral change).

A beautiful example of this has just been published in an elegant paper in Nature, in the nemotode C. elegans. In some strains of this species, after a male mates with a hemaphrodite (males are rare, and most reproduction occurs via selfing), it deposits a "copulatory plug" that decreases the fitness of those males that follow him (stained red in the figure on the right). In other strains, there's no such plug. So a natural question is: what's the genetic basis for this phenotype, and what is its evolutionary history?

First, the answer to the first question: the authors map the trait to a retrotransposon insertion into a previously unknown gene. This gene share homology with the mucins, and is specifically expressed in around 12 cells of the male vas deferens (in green on the right). Personally, I never cease to be amazed by the discovery of new genes in sequenced model organisms, but it's happened so much that perhaps I should get used to it.

The authors then go on to show that strains that express the plug overlap in their ranges considerably with strains that don't. This suggests little fitness effect of the retrotransposon insertion, and this seems to make sense--C. elegans evolved from a species with obligate male=female reproduction (where presumably the plug was advantageous) to a species where most reproduction is by selfing (where a plug is likely more neutral). Overall, a really nice story.

Against Latin

noreply@blogger.com (Razib) — Wed, 16 Jul 2008 18:02:00 +0000

Sebastian Flyte has a critique of my overuse of Latin. One thing I do want to add is that it's not all part of my "style," I used to the term "thickly scaffolded" in the post Sebastian highlights to allude to thick description, which I assume some of you will know about. I guess I could have referred explicitly to thick description, but I thought the idea of a scaffold was more precise in terms of what I perceived the exposition style of Ross & Reihan in GNP to be (and since many here have molecular biology in the background I also thought it would be a useful word to put there). But yeah, I use a lot of Latin-derived terms....

Genetic Diversity and Economic Development: A Goldilocks Story

noreply@blogger.com (Herrick) — Wed, 16 Jul 2008 06:22:00 +0000

From Oded Galor and his promising grad student Quamrul Ashraf, another paper that ties together genes and group productivity.

Their big result (Figure 5 below) is that a population cluster's genetic heterozygosity has a Goldilocks relationship with population density in 1500AD: Too much heterozygosity (Sub-Saharan Africa) or too little heterozygosity (Americas) predicts low population density. And in a pre-modern world (heck, even in the modern world), population density is a rough measure of technological progress.

Surprisingly, the Goldilocks result holds even when you control for a bunch of other stuff like arable land and the timing of a population's agricultural transition. And perhaps most surprisingly, the much-hyped correlation between latitude and population density vanishes when you control for pretty much anything in addition to latitude. So the "distance from the equator" variable that growth economists spend so much time on may just be epiphenomenal.

The authors admit they don't have a great theory for why the warm porridge tastes best–the goal of their paper is basically to get the Goldilocks result out there for others to work on. Here's hoping some economists take the bait.....

Bonus: Portfolio's Zubin Jelveh gets Galor to comment on what all this means for Jared Diamond.

Regional differences in intelligence?

noreply@blogger.com (Razib) — Wed, 16 Jul 2008 05:32:00 +0000

In the post below, Colder climates favor civilization even among Whites alone, I made a few comments about possible differences between Germans in Illinois and Germans in Texas, based on nothing much more than a hunch. I trust my hunches, but there's no reason you should, so I decided to see if there was anything here in regards to my assumption about interregional differences in intelligence and how they might track across ethnic groups. So of course I went to the GSS website, and checked the mean WORDSUM scores of various white ethnic groups broken down by region. I specifically focused on whites who stated that their ancestors were from England & Wales, Germany and Ireland. My reasoning is that these are three groups with very large N's within the GSS sample and they are well represented across the regions in absolute numbers. My main motivation was see if the differences across regions were similar for all three groups. Here are the states for each region (the Census made up these categories):

New England - Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut
Middle Atlantic - New York, New Jersey, Pennsylvania
East North Central - Ohio, Indiana, Illinois, Michigan, Wisconsin
West North Central - Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, Kansas
South Atlantic - Delaware, Maryland, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida
East South Central - Kentucky, Tennessee, Alabama, Mississippi
West South Central - Arkansas, Louisiana, Oklahoma, Texas
Mountain - Montana, Idaho, Wyoming, Colorado, New Mexico, Arizona, Utah, Nevada
Pacific - Washington, Oregon, California, Alaska, Hawaii

Obviously the breakdown isn't ideal. I think Delaware and Maryland arguably should be Mid-Atlantic. I also believe that Wisconsin is more plausibly in the West North Central than Missouri or Kansas is. But those are the regional breakdowns and I can't do anything about them.

So, WORDSUM is a vocabulary test on a 0-10 scale. For the whole GSS sample the mean was 6.00, with 1 standard deviation being 2.16. Below is a chart which shows the relationship between WORDSUM scores (Y axis) for various regions (X axis) for each of the three ethnic groups:

The tables below are pretty self-explanatory. At the top you see the mean WORDSUM scores for each ethnic group for each region. I put the N's in there as well so you can see that the sample sizes were pretty big. Note that there is more interregional variation within an ethnic group than there is interethnic variation within a region (the standard deviation across the columns is 50% bigger than across the rows). Just to be clear, I also included some tables which show the differences in WORDSUM mean scores between the regions like so: (row - column) = value.

	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific	N
England & Wales	7.4	7.09	6.71	6.65	6.66	6.2	6.87	6.84	7.1	2,462
Germany	7.7	6.31	6.01	6.33	6.16	5.83	6.2	6.37	6.36	3,316
Ireland	6.98	7.07	6.15	6.46	6.06	5.66	6.03	6.51	6.88	2,207

England & Wales
	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	0.31	0.69	0.75	0.74	1.2	0.53	0.56	0.3
Middle Atlantic	-	-	0.38	0.44	0.43	0.89	0.22	0.25	-0.01
East North Central	-	-	-	0.06	0.05	0.51	-0.16	-0.13	-0.39
West North Central	-	-	-	-	-0.01	0.45	-0.22	-0.19	-0.45
South Atlantic	-	-	-	-	-	0.46	-0.21	-0.18	-0.44
East South Central	-	-	-	-	-	-	-0.67	-0.64	-0.9
West South Central	-	-	-	-	-	-	-	0.03	-0.23
Mountain	-	-	-	-	-	-	-	-	-0.26
Pacific	-	-	-	-	-	-	-	-	-


Germany	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	1.39	1.69	1.37	1.54	1.87	1.5	1.33	1.34
Middle Atlantic	-	-	0.3	-0.02	0.15	0.48	0.11	-0.06	-0.05
East North Central	-	-	-	-0.32	-0.15	0.18	-0.19	-0.36	-0.35
West North Central	-	-	-	-	0.17	0.5	0.13	-0.04	-0.03
South Atlantic	-	-	-	-	-	0.33	-0.04	-0.21	-0.2
East South Central	-	-	-	-	-	-	-0.37	-0.54	-0.53
West South Central	-	-	-	-	-	-	-	-0.17	-0.16
Mountain	-	-	-	-	-	-	-	-	0.01
Pacific	-	-	-	-	-	-	-	-	-


Ireland	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	-0.09	0.83	0.52	0.92	1.32	0.95	0.47	0.1
Middle Atlantic	-	-	0.92	0.61	1.01	1.41	1.04	0.56	0.19
East North Central	-	-	-	-0.31	0.09	0.49	0.12	-0.36	-0.73
West North Central	-	-	-	-	0.4	0.8	0.43	-0.05	-0.42
South Atlantic	-	-	-	-	-	0.4	0.03	-0.45	-0.82
East South Central	-	-	-	-	-	-	-0.37	-0.85	-1.22
West South Central	-	-	-	-	-	-	-	-0.48	-0.85
Mountain	-	-	-	-	-	-	-	-	-0.37
Pacific	-	-	-	-	-	-	-	-	-

Colder climates favor civilization even among Whites alone

noreply@blogger.com (agnostic) — Tue, 15 Jul 2008 09:12:00 +0000

Last year I had a crazy idea about how winged insects might influence civilization. I only pointed to winged insects as an exemplar, not to suggest a "Mosquito Theory of History" or something stupid and sexy like that. The reasoning is simple: insects are more likely to be winged in certain climates, and that means more effective vectors of disease in such environments; and a greater disease burden makes you dumber, more tired, and more irritable, which stunts the growth of civilization. [1] A qualitative follow-up post looked at where civilizations have ever appeared, and in what climate types they existed.

Well, now I've done some quantitative work, and it turns out that I was right. One critique against an international study is that natural selection may have adapted people to be more or less civilized in different environments, so that the only influence of climate is as a selection pressure for genetic change. There are at least two such studies already out there: one by Templer & Arikawa (2006) and another by Vanhanen (2004). I'm arguing that it matters even when people start out pretty much the same genetically, so I will look just at the US. It varies enough in climate and degree of civilization that any correlation should jump out.

Motivation

In particular, I will look at the correlation, on the level of states, between average annual temperature and the average IQ of Whites, post-secondary degrees awarded to Whites per capita, and the percent of the White population that's imprisoned. I only look at Whites in order to avoid the confound of climate with racial composition (for example, the cold Mountain states are heavily White, while Blacks make up a larger fraction in the hot Southeast).

The reason I look at basic measures like IQ or being in jail, as opposed to the loftier things we associate with civilization, is that smarts is the key determinant of propelling the institutions of civilization forward, while crime gives us a good rough idea of how barbaric we are on a personal level. I'm sure that governments can improve or screw things up too, but it's the raw cognitive and behavioral materials that matter most, as Lynn and Varhanen show in IQ and the Wealth of Nations (see all GNXP posts on this topic). Moreover, studies of representative samples of the population always show a strong influence of IQ on how cultured a person is. See, for example, a National Endowment for the Arts report on the demographics of arts attendees (PDF p. 19), which shows that attendance increases nearly monotonically by education level.

The results

As you can see, hotter average temperature is associated with lower White IQs, fewer degrees being awarded to Whites per capita, and a higher percentage of the White population being imprisoned. The relationship looks pretty linear in each case, and the data are on an interval scale, so we check the Pearson correlation coefficient: between White IQ and temperature, it is -0.48 (p = 0.0005, two-tailed); between degrees to Whites and temperature, it is -0.57 (p = 0.00002, two-tailed); and between percent of Whites in jail and temperature, it is +.40 (p = 0.005, two-tailed). Even conservatively correcting for three independent hypotheses still leaves all results significant (and IQ and getting a college degree are not even independent). At any rate, average temperature accounts for 23%, 32%, and 16% of the variance in White IQ, degrees to Whites, and percent of Whites in jail, respectively -- pretty damn good for social science. [2]

Methods

I took the average annual temperature for each of the 48 continental states (Alaska and Hawaii were not included in the source, so I left them out). Next, I used Audacious Epigone's estimates of White IQ by state, which are based on NAEP data from 8th grade math and science test scores (read about his methods here). I turned to Statemaster.com for the per capita number of post-secondary degrees awarded to Whites. For the number of Whites in prison per 100K Whites in the state's population, I used the data from 1997 in a study by the National Center on Institutions and Alternatives (PDF here), which separates non-Hispanic Whites from Hispanics, unlike most crime data from government agencies. [3]

Discussion

Here, correlation probably is causation, as climate precedes the other three variables in causality, and again because these are unlikely to be genetic differences that reflect adaptation to different environments -- one of the few cases where natural selection "has not had enough time."

An objection is that the differences could reflect a "brain drain," whereby smart people flock to colder states, and their smart children boost the state's NAEP scores. Even in this case, where climate does not cause group differences in IQ, it still confirms the hypothesis that colder climates favor civilization -- why else would smarties flock there? But I doubt this anyway, since Montana, Wyoming, and North and South Dakota are not exactly fonts of civilization that smarties pour into, yet they have White IQs on par with the highly developed New York City metro area.

If it is causation, as seems likely, the mechanism could be anything. Pathogen load is surely part of it, hence the fields of study called "tropical disease" and "tropical medicine." Also, you might sweat too much in hotter environments, bringing you closer to dehydration. As mild as these effects may seem, when accumulated over the course of development, they could result in your body spending more resources on bodily maintenance than on luxury items like IQ and toil. Heat could also just make you more fatigued -- that wouldn't affect IQ, but it would affect your work ethic, making you less likely to complete college and more likely to pursue quick fixes like crime to get what you want.

The correlation is stronger for getting a college degree than performance on 8th grade math and science tests, and that could be because college work is more g-loaded, because it also taps into work ethic aside from IQ, and because out-of-staters show up in the college figures but not the 8th grade figures. As tough as the environment may seem to natives, it must seem unbearable to college students raised in a different climate.

To the best of my knowledge, as the saying goes, this is the first demonstration of an association between climate type and IQ, civilization-related achievement, and crime, even among a population that's pretty homogenous genetically (for the traits of interest, at least). Even what genetic diversity there is among Whites would underestimate the effect -- Whites adapted to hotter environments, such as Italians and Greeks, are far more concentrated in the colder states within the US. To put the final nail in the coffin, though, you'd want to look at babies of Whites who are adopted into White families in a state of noticeably different temperature than that of the biological parents.

Still, it seems pretty unavoidable: hotter environments are less conducive to civilization, at least for Whites, and not just in extreme cases like the failed attempt to colonize sub-Saharan Africa. Civilization may have started in hot areas, but that was then. It apparently flourishes much more in colder climates. Just as we provide iodine in table salt to prevent a nutrient deficiency from lowering IQ, it might be just as well to encourage people to settle colder areas.

It's not like they'd be abandoning civilization -- just the opposite. They could take their accents, music, and whatever else with them, but they would not suffer the environmental insults that lower their group's IQ, lower their ability to get a college degree, and make them more likely to commit crime. Fortunately for them -- and unfortunately for current residents -- the Mountain states have incredibly low population densities and could absorb some Whites from hotter states. That would certainly burden the locals for a generation, but again since lower White IQ in the Southeast is probably due to largely treatable environmental causes, it won't take long for them to contribute as citizens on the same level as the locals.

Notes

[1] Underlying this is likely a tendency for all sorts of things to be more migratory in such environments -- winged insects were chosen because there's lots of solid data to illustrate the point. Basically, environments that are highly unstable favor migratory features since your environment may go from good to bad from one day to the next, or from one spot to the next -- and being able to quickly move on to greener pastures will be well worth it. When environmental quality does not change much in space or time, then the expensive wings (or whatever) will not pay off.

[2] If you don't have statistical software, you can do a lot for free on Wessa.net, including correlation.

[3] Although I didn't run a test of normality on the distributions for temperature, iq, degrees, or crime, I did check the skewness of all, and only crime was significantly skewed: for crime, skewness is +2.1 standard errors of skewness (SES); for temperature, +1.24 SES; for degrees, +0.35 SES; and for IQ, -1.51 SES.

Addendum from Razib: I put up a related post at my other weblog.