Common genetic variants and intelligence

The New York Times has run an article on genetic research by Dr. David Goldstein of Duke University. His main finding is that most human diseases with a genetic basis are not due to common alleles. They are apparently due to rare alleles that have not been eliminated by natural selection. This seems to argue against the common variant theory of disease, i.e., natural selection has caused many modern diseases by favoring genetic variants that keep us going as long as we can reproduce and then let us fall apart once we’re reproductively useless.

Dr. Goldstein has also found that common genetic variants do not explain variation in IQ, at least not among different human populations:

He says he thinks that no significant genetic differences will be found between races because of his belief in the efficiency of natural selection. Just as selection turns out to have pruned away most disease-causing variants, it has also maximized human cognitive capacities because these are so critical to survival. “My best guess is that human intelligence was always a helpful thing in most places and times and we have all been under strong selection to be as bright as we can be,” he said.

This is more than just a guess, however. As part of a project on schizophrenia, Dr. Goldstein has done a genomewide association study on 2,000 volunteers of all races who were put through cognitive tests. “We have looked at the effect of common variation on cognition, and there is nothing,” Dr. Goldstein said, meaning that he can find no common genetic variants that affect intelligence. His view is that intelligence was developed early in human evolutionary history and was then standardized.

The finding itself is not surprising. The human brain is a complex organ with more than a trillion nerve cells. Clearly, a lot of genes are brain-related. If natural selection has caused one such gene to vary from one human population to the next, the same selection pressure has probably caused others to vary as well. Thus, in the event that human populations differ genetically in cognitive performance, the overall difference should reflect an accumulation of small differences at many gene sites—often too small to measure.

But what about g? Doesn’t g imply that one gene accounts for most genetic variation in intelligence? Perhaps. Alternately, g may correspond to a large number of brain genes that co-vary because they lie next to each other on the genome. In any case, the chances are not good that we will find g by trolling through the common variants we have discovered so far. The genome is a big place. Such a random search would be like looking for a needle in a haystack.

What is g anyway?

G is general intelligence, a common property we see in the similar test scores that people show for different cognitive tasks. But just what is this common property that makes some people generally smarter than others? There have been attempts to identify g with a specific brain characteristic. Unfortunately, as Anderson (1995) notes:

In general, these attempts have all been failures. It has always been possible to show a disassociation between any putative single psychological process and measures of general intelligence. For example, while it is possible to show correlations between g and memory measures, it is also possible to show normal intelligence in people with severe amnesia, thus eliminating the possible equating of memory and intelligence. While vocabulary measures correlate with IQ, subjects with global aphasia can have normal IQ and subjects with mental retardation can show semantic proficiency and precocity.

Whatever g is, it seems to be some general property and is not eliminated by damage to one brain area. Miller (1994) suggested that g might correlate with myelin, i.e., the fatty sheath that surrounds neurons. More myelination means faster nerve conduction, quicker reaction time and, ergo, higher intelligence. Regrettably, this hypothesis no longer seems tenable:

While IQ correlates with reaction time (RT) encouraging the hypothesis that neuron conduction velocity accounts for the individual variation in IQ, there is also discouraging information. Correcting IQ-RT correlations for neural conduction velocity does not diminish the strength of the relationship and neural conduction velocity does not correlate with RT. (Anderson, 1995).

Barrett and Eysenck (1993) have also failed to find a significant correlation between measures of nerve conduction velocity and IQ.

In his review of the literature, Anderson (1995) discounts other candidates: neuron number (no empirical support); cerebral cortical cell number (does not correlate with problem-solving performance in rats); and volume of the cerebellar granule cell layer (does not correlate with attention to novelty in rats. He concludes that the likeliest candidate seems to be the range and extent of neuronal processes that alter brain connectivity:

Dendritic arborization has been correlated to educational attainment and been shown to be more complex in brain regions critical for language. The molecular layer volume of the cerebellum, which correlated with attention to novelty in rates, is largely composed of Purkinje cell dendritic arborizations. Synapse number correlates with dementia severity in Alzheimer disease. Further, a change in connectivity can explain the IQ-RT correlation and the brain size-IQ correlation. (Anderson, 1995)

Thatcher et al. (2005) come to a similar conclusion in their comparison of EEG measurements to predict performance on the Weschler Intelligence test:

… it is hypothesized that general intelligence is positively correlated with faster processing times in frontal connections as reflected by shorter phase delays. Simultaneously, intelligence is positively related to increased differentiation in widespread local networks or local assemblies of cells as reflected by reduced EEG coherence and longer EEG phase delays, especially in local posterior and temporal lobe relations. The findings are consistent with a ‘network binding’ model in which intelligence is a function of the efficiency by which the frontal lobes orchestrate posterior and temporal neural resources.

Finally, we should not assume that IQ captures all variation in cognitive performance. In general, IQ tests involve answering a series of discrete questions over a limited span of time. Yet this kind of cognitive task is only a subset of all possible tasks that confront the human mind.

For instance, when something puzzles me, I may think about it over several days or longer. It will often sit in the back of my mind until it is re-activated by a piece of relevant information. Sometimes, I will get up in the middle of the night to jot down a possible answer. Then there are the lengthy, monotonous tasks: driving non-stop to Montreal, transcribing old hard copy into an electronic file, keeping track of different ‘things-to-do’ over the course of a day, and so on.

How well does a one-hour test measure performance on such tasks?

References

Anderson, B. (1995). G explained. Medical Hypotheses, 45, 602-604.

Barrett, P.T., & Eysenck, H.J. (1993). Sensory nerve conduction and intelligence: A replication. Personality and Individual Differences, 15, 249-260.

Miller, E. (1994). Intelligence and Brain Myelination: A Hypothesis. Personality and Individual Differences, 17, 803-833.

Thatcher, R.W., North, D., & Biver, C. (2005). EEG and intelligence: Relations between EEG coherence, EEG phase delay and power. Clinical Neurophysiology, 116, 2129-2141.

Decoding ASPM: Part III

Since its discovery two years ago, the new ASPM variant has vanished down the memory hole. Why the hasty burial? One reason is linked to current views about the human mind. The dominant view, at least among psychologists, is that cognitive ability varies similarly among people for all aspects of mental performance, so much so that this variability seems to be explained by one factor alone, called general intelligence or g.

Thus, when Philippe Rushton and his associates studied ASPM, they looked to see whether its variants co-varied with indices of general intelligence, either IQ or brain size. When nothing turned up, they concluded that any relationship to mental ability must be a weak one (Rushton et al., 2007).

In an e-mail, Philippe Rushton went on to explain that:

… these [IQ] tests are highly predictive of work performance, which is often evaluated over long time periods and likely gives plenty of room for excellence from the unmeasured qualities you expect are important. For example, Salgado, Anderson, Moscoso, Bertua, and Fruyt (2003) demonstrated the international generalizability of GMA across 10 member countries of the European Community (EC), thus contradicting the view that criterion-related validity is moderated by differences in a nation's culture, religion, language, socioeconomic level, or employment legislation. They found scores predicted job performance ratings 0.62 and training success 0.54.

Yes, these are high correlations, but they still leave a lot of variability unexplained. Moreover, in the case of ASPM, we may be looking at something that improves mental performance on a very specific task—one that most people no longer engage in. How often do people take dictation nowadays?

And there is evidence that g is not everything. As Steve Sailer notes:

… g, like any successful reductionist theory, has its limits. Males and females, while similar on mean g (but not on the standard deviation of g: guys predominate among both eggheads and knuckleheads), differ on several specific cognitive talents. Men, Jensen reports in passing, tend to be better at visual-spatial skills (especially at mentally rotating 3-d objects) and at mathematical reasoning. Women are generally superior at short-term memory, perceptual speed, and verbal fluency. Since the male sex is stronger at logically manipulating objects, while the female sex prevails at social awareness, that explains why most nerds are male, while most "berms" (anti-nerds adept at interpersonal skills and fashion) are female. Beyond cognition, there are other profound sex dissimilarities in personality, motivation, and physiology.

Clearly, if the new ASPM variant does have an effect on the brain, it cannot be a general one that influences all brain tissues. This was already being pointed out at the time of its discovery by anthropologist John Hawks:

Nobody currently knows what these alleles may have done. It seems likely that people with the allele have some sort of cognitive advantage, which ultimately translates into a reproductive benefit. This advantage is probably not associated with greater brain sizes, because the average brain size appears not to have changed appreciably during the past 30,000 years.

So what is going on now? Nothing really. An article came out a year ago about a possible relationship between the old ASPM variant and tonal languages like Chinese (Dediu & Ladd, 2007). But this was the sort of blackboard musing that I like to indulge in. Currently, as far as I know, no lab research is being done.

References

Dediu D.L. & Ladd D.R. (2007). Linguistic tone is related to the population frequency of the adaptive haplogroups of two brain size genes, ASPM and Microcephalin. Proc. Natl. Acad. Sci. U.S.A., 104 (26), 10944–9. doi:10.1073/pnas.0610848104.

Rushton, J.P., Vernon, PA.., Bons, T.A. (2007). No evidence that polymorphisms of brain regulator genes Microcephalin and ASPM are associated with general mental ability, head circumference or altruism. Biology Letters-UK, 3, 157–60.

Salgado, J. F., Anderson, N., Moscoso, S., Bertua, C., & Fruyt, F. D. (2003). International validity generalization of GMA and cognitive abilities: A European community meta-analysis. Personnel Psychology, 56, 573-605.

Decoding ASPM: Part II

In my last post, I reviewed the debate over ASPM, a gene implicated in regulation of brain growth. A new ASPM variant arose some 6,000 years ago in our species, apparently somewhere in the Middle East. It then spread outward, becoming much more prevalent in the Middle East and Europe than in East Asia. This temporal and spatial spread seems to match that of alphabetical writing, specifically the emergence of literate, scribal classes who had to process alphabetical script under premodern conditions (continuous text with little or no punctuation, real-time stenography, absence of automated assistance for publishing or copying, etc.). Since this subpopulation enjoyed prestige and apparently high reproductive success, it may have been a vector for the new ASPM variant (Frost, 2007).

All of this assumes the existence of a heritable cognitive ability that is specific to reading and writing of alphabetical script. This assumption runs counter to the view, held by many psychologists, that human cognition shows heritable variation only for general intelligence (commonly referred to as g). This view was key to ending debate over human variation in ASPM. As Philippe Rushton and other psychologists have shown, the new ASPM variant does not improve performance on standard IQ tests. Nor does it correlate with increased brain size.

Recently, however, it has been found that ASPM variants do not correlate with brain size in other primate species. Instead, they seem to regulate the growth of specific brain tissues, especially within the cerebral cortex. Parallel to this is another finding that alphabetical script processing is localized within a specific region of the brain, the ‘Visual Word Form Area (VWFA):

Brain imaging studies reliably localize a region of visual cortex that is especially responsive to visual words. This brain specialization is essential to rapid reading ability because it enhances perception of words by becoming specifically tuned to recurring properties of a writing system. The origin of this specialization poses a challenge for evolutionary accounts involving innate mechanisms for functional brain organization. (McCandliss et al., 2003).

Psychological, neuropsychological, and neuroimaging data converge to suggest that the human brain of literate subjects contains specialized mechanisms for visual word recognition (functional specialization), which map in a systematic way onto the properties of a cortical subregion of the left posterior occipitotemporal sulcus (reproducible localization).

… Such observations predict the existence of highly specialized but patchy and distributed neuronal populations coding for alphabetic stimuli at the single-neuron level. The intermingling of such neurons with others coding for objects or faces would translate into a partial regional selectivity at the single-voxel level, which is all that we can presently measure with PET or fMRI. (Cohen & Dehaene, 2004)

One puzzling issue remains: why is there a reproducible cortical site responsive to visual words? Reading is a recent cultural activity of the human species. The 5400 years that have elapsed since its invention are too short to permit the evolution of dedicated biological mechanisms for learning to read. (Cohen & Dehaene, 2004).

Indeed, how could the VWFA have arisen so recently and over such a short time? This is a puzzle only if we assume that evolution creates new features from scratch. But this is not how evolution usually works. Typically, new features evolve through a process of tinkering with old features that may have served some other purpose. And such tinkering may occur over less than a dozen generations. As Harpending and Cochran (2002) note, domestic dog breeds display much diversity in cognitive and behavioral characteristics, yet this diversity has arisen largely within the time span of human history.

A second puzzle is of the chicken and egg sort. If the VWFA is crucial for reading and writing, how did humans first learn to read and write? Some light has been shed on this puzzle by lesion studies, particularly one where part of the VWFA was surgically removed:

… our patient presented a clear-cut reading impairment following surgery, while his performance remained flawless in object recognition and naming, face processing, and general language abilities.

… Furthermore, the deficit was still present 6 months after surgery, albeit with some degree of functional compensation. This confirms that the VWFA is indeed indispensable for expert reading.

(Gaillard et al., 2006)

So a person can learn to read and write without a VWFA. This brain area did not arise to make reading and writing possible. It simply arose to make these tasks easier.

But what about human populations that have never used alphabetical script? This is notably true for the Chinese, who have long had a logographic script:

As the most widely used logographic script, Chinese characters have thousands of diverse word forms and differ markedly from alphabetic scripts in orthography. In Chinese characters, there is a distinctive square-combined configuration within each character and no obvious letter-sound correspondence. … Although some phonological information is encoded in some characters, this information is not consistent and is not at a level of correspondences between phonemes and letters. … In alphabetic stimuli, it is clear that each individual letter is the basic unit of words, so how different letters are combined is critical in defining orthographic regularities. In Chinese, however, it is still not clear what the basic processing units really are. (Liu et al., 2008)

When the brains of Chinese subjects were studied by functional MRI, Chinese characters seemed to be processed in the same region of the brain (the VWFA) that other populations use to process alphabetical characters. The Chinese subjects, however, seemed to be using other regions as well:

These results indicated that in addition to the VWFA being located in the left middle fusiform gyrus (BA 37), the left middle frontal cortex (BA 9) might also be an indispensable area for orthographic processing of Chinese characters, as opposed to alphabetic orthographies. (Liu et al., 2008)

For human populations that use alphabetical scripts, the VWFA seems to be much more of a bottleneck for text processing. This finding seems to dovetail with other evidence suggesting that logographic script evokes meaning more directly and does not impose the same set of cognitive demands (Frost, 2007).

References

Cohen, L., & Dehaene, S. (2004). Specialization within the ventral stream: the case for the visual word form area. Letter to the Editor. NeuroImage, 22, 466-476.

Frost, P. 2007. "The spread of alphabetical writing may have favored the latest variant of the ASPM gene", Medical Hypotheses, 70, 17-20.

Gaillard, R., Naccache, L., Pinel, P., Clémenceau, S., Volle, E., Hasboun, D., Dupont, S., Baulac, M., Dehaene, S., Adam, C., & Cohen, L. (2006). Direct intracranial, fMRI, and lesion evidence for the causal role of left inferotemporal cortex in reading. Neuron, 50, 191-204.

Harpending, H. and G. Cochran. 2002. "In our genes", Proceedings of the National Academy of Sciences, 99(1), 10-12.

Liu, C., Zhang, W-T., Tang, Y-Y., Mai, X-Q., Chen, H-C., Tardif, T., & Luo, Y-J. (2008). The visual word form area: evidence from an fMRI study of implicit processing of Chinese characters. NeuroImage, 40, 1350-1361.

McCandliss, B.D., Cohen, L., and Dehaen, S. (2003). The visual word form area: expertise for reading in the fusiform gyrus. Trends in Cognitive Sciences, 7, 293-299.