Genes, brains and lateralisation: how solid is the evidence?

If there were a dictionary of famous neurological quotes, “Nous parlons avec l'hémisphère gauche” by Paul Broca (1865) would be up there among the top hits. Broca’s realisation that the two sides of the brain are functionally distinct was a landmark observation. It was based on a rather small series of patients, but has since been confirmed in numerous studies. After localised brain injury, aphasia (language impairment) is far more likely after damage to the left side than the right side. And nowadays, we can visualise greater activation of the left side in neurologically intact people as they do language tasks in a brain scanner.

There are many fascinating features of cerebral lateralisation, but I’m going to focus here on just one specific question: what do we know about genetic influences on brain asymmetry in humans?  There are really two questions here: (1) how do genes lead to asymmetric brain development? (2) are there genetic variants that can account for individual variation?  – e.g. the fact that a minority of people have right hemisphere language. I hope to return to question 2 at a later date, but for now, I’ll focus on question 1, because after reading a key paper on this topic, I've struck a whole load of questions that I can’t answer. I’m hoping that some of my genetically-sophisticated readers will be able to help me out.

It’s sometimes stated that cerebral lateralisation is a uniquely human trait, but that’s not true. Nevertheless, we are very different from our primate cousins, insofar as we show a strong population bias to right-handedness, and most people have left-hemisphere language. There are other species which show consistent brain asymmetries, but they are a long way from us on the evolutionary tree. Most of the research I’ve come across is on nematode worms, zebrafish, or songbirds. This is a long way from my comfort zone, but there are some nice reviews that document research on genes influencing asymmetries in these creatures (e.g. here and here). It’s clear, though, that it’s complicated: not just in terms of the range of genes involved, but in the different ways they can generate asymmetry. And there don't seem to be obvious parallels to human brain development.

Despite all this uncertainty, there’s growing evidence that brain asymmetries are present from very early on in life –in newborn babies and even in foetal life. This field is still in its infancy (forgive the pun), and samples of babies are typically too small to reveal reliable relationships between structure and function. Nevertheless, there’s considerable interest in the idea that physical differences between the two sides of the brain may be an indicator of potential for language development.

A particularly exciting topic is genetic determinants of cerebral lateralisation. One study in particular, by Sun et al made a splash when it was published in Science in 2005, since when it has attracted over 140 citations. The authors looked for asymmetric gene expression in post mortem embryonic brains. Their conclusions have been widely cited: “We identified and verified 27 differentially expressed genes, which suggests that human cortical asymmetry is accompanied by early, marked transcriptional asymmetries.” The fact that several different genes were identified was of particular interest to me, because genetic theories by neuropsychologists have typically assumed that just a single gene is responsible for human cerebral lateralisation. I’ve never found a single-gene theory plausible, so I was all too ready to accept evidence that involved multiple genes. But first I wanted to drill down deeper into the methods to find out how the authors reached their conclusions. I’m a psychologist, not a geneticist, and so this was rather challenging. But my deeper reading raised a number of questions.

Sun et al used a method called Serial Analysis of Gene Expression (SAGE) which compares gene expression in different tissues or – as in this case – in corresponding left and right regions of the embryonic brain. The analysis looks for specific sequences of 10 DNA base-pairs, or tags, which index particular genes. SAGE output consists of simple tables, giving the identity of each tag, its count (a measure of cellular gene expression) and an identifier and more detailed description of the corresponding gene. These tables are available for left and right sides for three brain regions (frontal, perisylvian and occipital) for 12- and 14-week old brains, and for perisylvian only for a 19-week-old brain. The perisylvian region is of particular interest because it is the brain region that will develop into the planum temporale, which has been linked with language development.  One brain at each age was used to create the set of SAGE tags.

To identify asymmetrically expressed genes the authors state performed a Monte Carlo test and verified this using the chi square test. I haven’t tracked down the specifics of the Monte Carlo test, which is part of the SAGE software package, but the chi square is pretty straightforward, and involves testing whether the distribution of expression on left and right is significantly different from the distribution of left vs. right expression across all tags in this brain region – which is close to 50%.  In the left-right perisylvian region of a 12-week-old embryonic human brain, there were 49 genes with chi square greater than 6.63 (p < .01): 21 were more highly expressed on the left and 28 more highly expressed on the right.  But for each region the authors considered several thousand tags. So I wondered whether the number of asymmetrically expressed genes was any different from what you’d expect if asymmetry was just arising by chance.

It was possible to check this out from the giant supplementary Excel files that accompany the paper, but this proved far from straightforward.  It turns out that the relationship between tags and genes is not one-to-one.  For around 40% of the tags, there is more than one corresponding gene. It was not clear which gene was selected in such cases, and why. I did find some cases where two genes were assigned to a tag, but my impression was that this was unintentional and in general the authors aimed to avoid double-counting tags. We also have the further problem that some genes are indexed by numerous tags, a point I will return to below.

But let’s just focus first on the individual tags. I compiled a master list of all tags that were expressed in any region at any age, and then made a chart of the frequency of expression in each brain region/age. I excluded any tags where the total expression count on both sides was three or less, as this is too small to show lateralisation, and this left me with 3800 to 4600 tags for analysis in each brain region. I did compute chi square as described by Sun et al, but this is not recommended for small numbers, and so I also evaluated the significance of asymmetry using a two-tailed binomial test. This doesn’t make a huge difference, but is more accurate when comparing small numbers.  Figure 1 shows the proportion of the sample for each brain region where the binomial test gives a p-value of a given size. If the distribution of expression in left and right was purely determined by chance, we’d expect the points to fall on the line. If there were genes for asymmetry we would expect the observed values to fall above the line, especially at low levels of p. It is clear this is not the case. I did cross-check my figures against those of Sun et al, and found they appeared to have missed some cases of significant asymmetry, which meant that in general they found rather fewer cases of significant asymmetry than are shown in Figure 1.

Fig 1. Proportion of tags with "significant" asymmetry, by Age/Brain Region

Sun et al didn’t rely solely on statistical tests of SAGE data to establish asymmetrical expression.  They reported validation studies using a different method for assessing gene expression (real-time PCR). But this used genes selected on the basis of a chi square value of 1.9 or greater (P < .17), which included many where the degree of asymmetry was not large. One goal of PCR analysis was to confirm asymmetric expression levels in the same embryonic brains as the SAGE analysis. Of more interest is whether the findings generalise to new brains. The authors did further cross-validation using real-time PCR with six additional brains of different ages, and reported results for the LMO4 gene, where higher perisylvian expression on the right was evident in two brains at 12 and 14 weeks of age, as well as in the original two brains of the same age. Four other brains, aged 16 to 19 months, did not show asymmetry of expression. Some of the other asymmetrically expressed genes were also tested using real-time PCR in the two other brains, and 27 showed consistent asymmetric expression. It was, however, not clear to me how the significance of asymmetry was assessed in these replication samples.

There is one particular issue I find confusing when I try to evaluate the robustness of the asymmetry results. My expectation was that if a gene was asymmetrically expressed, then this should be evident in all the tags indexing that gene. But Table 1 shows that this isn’t so. For the LMO4 gene, which is the focus of special attention in this paper, there are seven tags that are linked with the gene in at least one brain region: only one of these (in red) shows the rightward asymmetry that is the focus of the paper. Another tag (in blue) shows leftward asymmetry in one sample, and the rest have low levels of expression. Maybe there’s a simple explanation for this – if so I hope that expert geneticists among my readers may be able to comment on this aspect.

Table 1. Left- and right-expression levels for seven tags for the LMO4 gene

I’m aware of two other studies (here and here) that looked for asymmetric gene expression in embryonic human brains but failed to find it . One possible reason for this discrepancy is that these studies focused on later stages of development, rather than the 12-14 week-old period where Sun et al found asymmetry. In addition, power is always low in these studies because of the small number of brains available. As Lambert et al (2011) noted, as well as possible effects of age and gender, there may be individual variation from brain to brain, but typically only one or two samples are available at each age.

So what do I conclude from all of this? I realise for a start that these studies are very hard to do. I also realise we have to make a start somewhere, even if the amount of post mortem material is limited. But I have to say I’m not convinced from the evidence so far that the researchers have demonstrated significant asymmetry of genetic expression in embryonic brains. The methods seem to take insufficient account of the possibility of chance fluctuations in the measurements, and the numbers of asymmetries that have been found don't seem impressive, given the huge number of genes that were investigated. Clearly, something has to be responsible for the physical asymmetries that have been found in foetal and neonatal brains, and the odds seem high that genes are implicated. But is the evidence from Sun et al convincing enough to conclude that we have found some of those genes? I'd love to hear views from readers who have more expertise in this area of research.

P.S. 7th Jan 2013
Thanks to Silvia Paracchini, who drew my attention to further relevant articles:
Johnson, M. B., et al (2009). Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron, 62(4), 494-509. doi: 10.1016/j.neuron.2009.03.027
This paper looked at a slightly later developmental stage - 18 to 23 weeks gestational age - and did correct for the number of genes considered (False Discovery Rate). They reported striking symmetry of gene expression in the mid-gestational period, even though structural brain asymmetries have been described at this stage of development. Note, however, that this is not incompatible with Sun et al, who did not find evidence of asymmetry after 17 weeks gestational age.
Kang, H. J., et al (2011). Spatio-temporal transcriptome of the human brain. Nature, 478(7370), 483-489. 
This is a much larger study, covering the range from 4 weeks gestational age through childhood up to adulthood and old age. This paper does not explicitly report on asymmetry, but they describe genes where the expression varies from brain region to region, or from age to age, after adjustment for False Discovery Rate. I could find no overlap in the list of the genes identified by Sun et al and Kang et al's list of differentially expressed genes.

References 

Abrahams, B. S., Tentler, D., Peredely, J. V., Oldham, M. C., Coppola, G., & Geschwind, D. H. (2007). Genome-wide analyses of human perisylvian cerebral cortical patterning. Proceedings of the National Academy of Sciences, 104, 17849-17854.
 
Dehaene-Lambertz, G., Hertz-Pannier, L., & Dubois, J. (2006). Nature and nurture in language acquisition: anatomical and functional brain-imaging studies in infants. Trends in Neurosciences, 29, 367-373.
 
Kivilevitch, Z., Achiron, R., & Zalel, Y. (2010). Fetal brain asymmetry: in utero sonographic study of normal fetuses. American Journal of Obstetrics and Gynecology, 202(4). doi: 359.e1
10.1016/j.ajog.2009.11.001
 
Lambert, N., Lambot, M.-A., Bilheu, A., Albert, V., Englert, Y., Libert, F., . . . Vanderhaeghen, P. (2011). Genes expressed in specific areas of the human fetal cerebral cortex display distinct patterns of evolution. PLOS One, 6(3), e17753. doi: 10.1371/journal.pone.0017753
 
Lash, A. E., Tolstoshev, C. M., Wagner, L., Schuler, G. D., Strausberg, R. L., Riggins, G. J., & Altschul, S. F. (2000). SAGEmap: A public gene expression resource. Genome Research, 10(7), 1051-1060. doi: 10.1101/gr.10.7.1051
 
Sagasti, A. (2007). Three ways to make two sides: Genetic models of asymmetric nervous system development. Neuron, 55(3), 345-351. doi: 10.1016/j.neuron.2007.07.015
 
Sun T, Patoine C, Abu-Khalil A, Visvader J, Sum E, Cherry TJ, Orkin SH, Geschwind DH, & Walsh CA (2005). Early asymmetry of gene transcription in embryonic human left and right cerebral cortex. Science (New York, N.Y.), 308 (5729), 1794-8 PMID: 15894532

Sun, T., & Walsh, C. A. (2006). Molecular approaches to brain asymmetry and handedness. Nature Reviews Neuroscience, 7, 655-662.
 

Psychology: Where are all the men?

There's a lot of interest in under-representation of women in certain science subjects, but in psychology, there's more concern about a lack of men. A quick look at figures from UCAS* (Universities & Colleges Admissions Service) shows massive differences in gender ratios for different subjects. In figure 1 I’ve plotted the percentage of women accepted for subjects that had at least 6000 successful applicants to degree courses in 2011.

Fig. 1. % Females accepted on popular UK degree courses 2011

Given the large sample sizes, the sex differences are statistically significant for all subjects except Media Studies, which is bang on 50%. As a psychologist, I found the most surprising thing about this plot was the huge preponderance of women in psychology. This didn’t square with my experiences: my colleagues include a good mix of men and women, so I was keen to find the explanation for the mismatch. There seemed to be several possible explanations, which aren’t mutually exclusive, namely:

• Oxford University, where I work, may be biased in favour of men
• The proportions of women decline with career stage
• The proportion of women in psychology may have increased since I was a student
• The proportion of women may vary with sub-area of psychology

So I set off to track down the evidence for these different explanations.

Is Oxford University biased against women?

I’m leading our department’s Athena SWAN panel, whose remit is to identify and remove barriers to women’s progress in scientific careers. In order to obtain an Athena SWAN award, you have to assemble a lot of facts and figures about the proportions of women at different career stages, and so I already had at my fingertips some relevant statistics. (You can find these here). Over the past three years, our student intake ranged from 66% -71% women: rather lower than the UCAS figure of 78%. However, acceptance rates were absolutely equivalent for men and women. The same was true for staff appointments: the likelihood of being accepted for a job did not differ by gender. So with a sigh of relief I think we can exclude this line of explanation.

Does the proportion of women in psychology decline with career stage?

I have a research post and so don’t do much teaching. Have I got a distorted view of the gender ratios because my interactions are mostly with more senior staff? This looks believable from the data on our department. Postgraduate figures ranged from 65%-70% women. Ours is a small department, and so it is difficult to be confident in trends, but in 2011 there were 16/27 (59%) female postdocs, 6/11 (55%) female lecturers, 6/13 (46%) senior researchers and 4/11 (36%) female professors. This trend for the proportion of women to decline as one advances through a career is in line with what has been observed in many other disciplines. We also obtained data from other top-level psychology departments for comparison, and similar trends were seen.

Has the proportion of women in psychology increased over time?

My recollection of my undergraduate days was that male psychology students were plentiful. However, I was an undergraduate in the dark ages of the early 1970s when there were only five Oxford colleges that accepted women, and a corresponding shortage of females in all subjects. So I had a dig around to try to get more data. The UCAS statistics go back only to 1996, and the proportion of women in psychology hasn’t changed: 78% in 1996, 78% in 2011. However, data from the USA show a sharp increase in the proportion of women obtaining psychology doctorates from 1960 (18%) through 1972 (27%) to 1984 (50%). This, of course, is in part a consequence of the increase of women in higher education in general. But that isn’t a total explanation: Figure 2 compares proportions of female PhDs over time in different subject areas, and one can see that psychology shows a particularly pronounced increase compared with other disciplines.

Fig 2. Percentages of PhDs by women in the USA: 1950-1984

Does the proportion of women in psychology vary with sub-area?

The term ‘psychology’ covers a huge range of subject matter with different historical roots. Most areas of academic psychology make some use of statistics, but they vary considerably in how far they require strong quantitative or computational skills. For instance, it would be difficult to specialise in the study of perception or neuroscience without being something of a numbers nerd: that’s generally less true for developmental, clinical, interpersonal or social psychology, which require other skills sets. I looked at data from the American Psychological Association (APA), which publishes the numbers of members and fellows in its different Divisions. The APA is predominantly a professional organisation, and non-applied areas of psychology are not strongly represented in the membership. Nevertheless, one can see clear gender differences, which generally map on to the expectation that women are more focused on the caring professions, and men are more heavily represented in theoretical and quantitative areas. Figure 3 shows relevant data for sections with at least 700 members. It is also worth noting that the graph illustrates the decrease in the proportions of women going from membership to fellowship, a trend bucked by just one Division.

Fig 3. Data from American psychological association: Division membership 2011

What, if anything, should we do?

The big question is how far we should try to manipulate gender differences when we find them. I’ve barely scratched the surface in my own discipline, psychology, yet it’s evident that the reasons for such differences are complex. Figure 2 alone makes it clear that women in Western societies have come a long way in the past half-century: far more of us go to university and do PhDs than was the case fifty years ago. Yet the proportion of women declines as we climb the career ladder. In quantifying this trend, it’s important to compare like with like: those who are in senior positions now are likely to have trained at a time when the gender ratio was different. But it's clear from many surveys that demographics changes can't explain the dearth of women in top jobs: there are numerous reasons why women are more likely than men to leave an academic career – see, for instance, this depressing analysis of reasons why women leave chemistry. In our department we are committed to taking steps to ensure that gender does not disadvantage women who want to pursue an academic career, and I am convinced that with even quite minor changes in culture we can make a difference.

The point I want to stress here, though, is that I see this issue - creating a female-friendly environment for women in psychology-  as separate from the issue of subject preference. I worry that the two issues tend to get conflated in discussions of gender equality. My personal view is that psychology is enriched by having a mix of men and women, and I share the concerns expressed here about difficulties that arise when the subject becomes heavily biased to one gender. However, I am pretty uncomfortable with the idea of trying to steer people’s career choices in order to even out a gender imbalance.

Where this has been tried, my impression is that it's mostly been in the direction of trying to encourage more girls into male-dominated subjects. In effect, the argument is that girl's preferences  are based on wrong information, in that they are unduly influenced by stereotypes. For instance, the Institute of Physics has done a great deal of work on this topic, and they have shown that there are substantial influences of schooling on girls’ subject choices. They concluded that the weak showing of girls in physics can be attributed to lack of inspirational teaching, and a perception among girls that physics is a boys’ subject. They have produced materials to help teachers overcome these influences, and we’ll have to wait and see if this makes any appreciable difference to the proportions of girls taking up the subject (which according to UCAS figures has been pretty stable for 15 years: 19% in 1996 and 18% in 2011).

It's laudable that the Institute of Physics is attempting to improve the teaching of physics in our schools, and to ensure girls do not feel excluded. But if they are right, and gender stereotyping is a major determinant of subject choices, shouldn’t we then adopt similar policies to other subjects that show a gender bias, whether this be in favour of girls or boys?

Interestingly, Marc Smith has produced relevant data in relation to A-level psychology, which is dominated by girls, and perceived by boys as a ‘girly’ subject. So should we try to change that? As Smith notes, the female bias seems linked to a preference for schools to teach A-level psychology options that veer away from more quantitative cognitive topics. Here we find that psychology provides an interesting test case for arguments around gender, because within the subject there are consistent biases for males and females to prefer one kind of sub-area to another. This implies that to alter the gender balance you might need to change what is taught, rather than how it is taught, by giving more prominence to the biological and cognitive aspects of psychology. If true, it might be easier to alter gender ratios in psychology than in physics, but only by modifying the content of the syllabus.

One of the IOP's recommendations is: "Co-ed schools should have a target to exceed the current national average of 20% of physics A-level students being girls." But surely this presumes an agenda whereby we aim for equality of genders in all subjects, with equivalent campaigns to recruit more boys into nursing, psychology and English? I'm not saying this would necessarily be a bad thing, but I wonder at the automatic assumption that it has to be a good thing - or even an achievable thing. There are obvious disadvantages of gender imbalances in any subject area - they simply reinforce stereotypes, while at the same time creating challenges at university and in the workplace for those rare individuals who buck the trend and take a gender-atypical subject. But the kinds of targets set by the IOP make me uneasy nonetheless. The downside of an insistence on gender balance is a sense of coercion, whereby children are made to feel that their choice of subject isn't a real choice, but is only made because they  have been brainwashed by gender stereotypes. Yes, let's do our best to teach boys and girls in an inspiring and gender-neutral fashion, but, as the example of psychology demonstrates, we are still likely to find that females and males tend to prefer different kinds of subject matter.

References  
Smith, M (2011). Failing boys, failing psychology The Psychologist, 24 (5), 390-391 Other: WOS:000290745000037  

Howard, A., & et al, . (1986). The changing face of American psychology: A report from the Committee on Employment and Human Resources. American Psychologist, 41 (12), 1311-1327 DOI: 10.1037//0003-066X.41.12.1311

*Update 10th March 2016: The link I originally had for UCAS data ceased to work. I have a new link, and think this should be the correct dataset, but I have not rechecked the figures.
https://www.ucas.com/sites/default/files/eoc_data_resource_2015-dr3_019_01.pdf