Wiring the Brain

A debate is raging in human genetics these days as to why the massive genome-wide association studies (GWAS) that have been carried out for every trait and disorder imaginable over the last several years have not explained more of the underlying heritability. This is especially true for many of the so-called complex disorders that have been investigated, where results have been far less than hoped for. A good deal of effort has gone into quantifying exactly how much of the genetic variance has been “explained” and how much remains “missing”.

The problem with this question is that it limits the search space for the solution. It forces our thinking further and further along a certain path, when what we really need is to draw back and question the assumptions on which the whole approach is founded. Rather than asking what is the right answer to this question, we should be asking: what is the right question?

The idea of performing genome-wide association studies for complex disorders rests on a number of very fundamental and very big assumptions. These are explored in a recent article I wrote for Genome Biology (referenced below; reprints available on request). They are:

1) That what we call complex disorders are unitary conditions. That is, clinical categories like schizophrenia or diabetes or asthma are each a single disease and it is appropriate to investigate them by lumping together everyone in the population who has such a diagnosis – allowing us to calculate things like heritability and relative risks. Such population-based figures are only informative if all patients with these symptoms really have a common etiology.

2) That the underlying genetic architecture is polygenic – i.e., the disease arises in each individual due to toxic combinations of many genetic variants that are individually segregating at high frequency in the population (i.e., “common variants”).

3) That, despite the observed dramatic discontinuities in actual risk for the disease across the population, there is some underlying quantitative trait called “liability” that is normally distributed in the population. If a person’s load of risk variants exceeds some threshold of liability, then disease arises.

All of these assumptions typically go unquestioned – often unmentioned, in fact – yet there is no evidence that any of them is valid. In fact, the more you step back and look at them with an objective eye, the more outlandish they seem, even from first principles.

First, what reason is there to think that there is only one route to the symptoms observed in any particular complex disorder? We know there are lots of ways, genetically speaking, to cause mental retardation or blindness or deafness – why should this not also be the case for psychosis or seizures or poor blood sugar regulation? If the clinical diagnosis of a specific disorder is based on superficial criteria, as is especially the case for psychiatric disorders, then this assumption is unlikely to hold.

Second, the idea that common variants could contribute significantly to disease runs up against the effects of natural selection pretty quickly – variants that cause disease get selected against and are therefore rare. You can propose models of balancing selection (where a specific variant is beneficial in some genomic contexts and harmful in others), but there is no evidence that this mechanism is widespread. In general, the more arcane your model has to become to accommodate contradictory evidence, the more inclined you should be to question the initial premise.

Third, the idea that common disorders (where people either are or are not affected) really can be treated as quantitative traits (with a smooth distribution in the population, as with height) is really, truly bizarre. The history of this idea can be traced back to early geneticists, but it was popularised by Douglas Falconer, the godfather of quantitative genetics (he literally wrote the book).

In an attempt to demonstrate the relevance of quantitative genetics to the study of human disease, Falconer came up with a nifty solution. Even though disease states are typically all-or-nothing, and even though the actual risk of disease is clearly very discontinuously distributed in the population (dramatically higher in relatives of affecteds, for example), he claimed that it was reasonable to assume that there was something called the underlying liability to the disorder that was actually continuously distributed. This could be converted to a discontinuous distribution by further assuming that only individuals whose burden of genetic variants passed an imagined threshold actually got the disease. To transform discontinuous incidence data (mean rates of disease in various groups, such as people with different levels of genetic relatedness to affected individuals) into mean liability on a continuous scale, it was necessary to further assume that this liability was normally distributed in the population. The corollary is that liability is affected by many genetic variants, each of small effect. Q.E.D.

This model – simply declared by fiat – forms the mathematical basis for most GWAS analyses and for simulations regarding proportions of heritability explained by combinations of genetic variants (e.g., the recent paper from Eric Lander’s group). To me, it is an extraordinary claim, which you would think would require extraordinary evidence to be accepted. Despite the fact that it has no evidence to support it and fundamentally makes no biological sense (see Genome Biology article for more on that), it goes largely unquestioned and unchallenged.

In the cold light of day, the most fundamental assumptions underlying population-based approaches to investigate the genetics of “complex disorders” can be seen to be flawed, unsupported and, in my opinion, clearly invalid. More importantly, there is now lots of direct evidence that complex disorders like schizophrenia or autism or epilepsy are really umbrella terms, reflecting common symptoms associated with large numbers of distinct genetic conditions. More and more mutations causing such conditions are being identified all the time, thanks to genomic array and next generation sequencing approaches.

Different individuals and families will have very rare, sometimes even unique mutations. In some cases, it will be possible to identify specific single mutations as clearly causal; in others, it may require a combination of two or three. There is clear evidence for a very wide range of genetic etiologies leading to the same symptoms. It is time for the field to assimilate this paradigm shift and stop analysing the data in population-based terms. Rather than asking how much of the genetic variance across the population can be currently explained (a question that is nonsensical if the disorder is not a unitary condition), we should be asking about causes of disease in individuals:

- How many cases can currently be explained (by the mutations so far identified)?

- Why are the mutations not completely penetrant?

- What factors contribute to the variable phenotypic expression in different individuals carrying the same mutation?

- What are the biological functions of the genes involved and what are the consequences of their disruption?

- Why do so many different mutations give rise to the same phenotypes?

- Why are specific symptoms like psychosis or seizures or social withdrawal such common outcomes?


These are the questions that will get us to the underlying biology.


Mitchell, K. (2012). What is complex about complex disorders? Genome Biology, 13 (1) DOI: 10.1186/gb-2012-13-1-237

Manolio, T., Collins, F., Cox, N., Goldstein, D., Hindorff, L., Hunter, D., McCarthy, M., Ramos, E., Cardon, L., Chakravarti, A., Cho, J., Guttmacher, A., Kong, A., Kruglyak, L., Mardis, E., Rotimi, C., Slatkin, M., Valle, D., Whittemore, A., Boehnke, M., Clark, A., Eichler, E., Gibson, G., Haines, J., Mackay, T., McCarroll, S., & Visscher, P. (2009). Finding the missing heritability of complex diseases Nature, 461 (7265), 747-753 DOI: 10.1038/nature08494

Zuk, O., Hechter, E., Sunyaev, S., & Lander, E. (2012). The mystery of missing heritability: Genetic interactions create phantom heritability Proceedings of the National Academy of Sciences, 109 (4), 1193-1198 DOI: 10.1073/pnas.1119675109

It takes a lot of genes to wire the human brain. Billions of cells, of a myriad different types have to be specified, directed to migrate to the right position, organised in clusters or layers, and finally connected to their appropriate targets. When the genes that specify these neurodevelopmental processes are mutated, the result can be severe impairment in function, which can manifest as neurological or psychiatric disease.

How those kinds of neurodevelopmental defects actually lead to the emergence of particular pathological states – like psychosis or seizures or social withdrawal – is a mystery, however. Many researchers are trying to tackle this problem using mouse models – animals carrying mutations known to cause autism or schizophrenia in humans, for example. A recent study from my own lab (open access in PLoS One) adds to this effort by examining the consequences of mutation of an important neurodevelopmental gene and providing evidence that the mice end up in a state resembling psychosis. In this case, we start with a discovery in mice as an entry point to the underlying neurodevelopmental processes.

In just the past few years, over a hundred different mutations have been discovered that are believed to cause disorders like autism or schizophrenia. In many cases, particular mutations can actually predispose to many different disorders, having been linked in different patients to ADHD, epilepsy, mental retardation or intellectual disability, Tourette’s syndrome, depression, bipolar disorder and others. These clinical categories may thus represent more or less distinct endpoints that can arise from common neurodevelopmental origins.

For a condition like schizophrenia, the genetic overlap with other conditions does not invalidate the clinical category. There is still something distinctive about the symptoms of this disorder that needs to be explained. I have argued that schizophrenia can clearly be caused by single mutations in any of a very large number of different genes, many with roles in neurodevelopment. If that model is correct, then the big question is: how do these presumably diverse neurodevelopmental insults ultimately converge on that specific phenotype? It is, after all, a highly unusual condition. The positive symptoms of psychosis – hallucinations and delusions, for example – especially require an explanation. If we view the brain from an engineering perspective, then we can say that the system is not just not working well – it is failing in a particular and peculiar manner.

To try to address how this kind of state can arise we have been investigating a particular mouse – one with a mutation in a gene called Semaphorin-6A. This gene encodes a protein that spans the membranes of nerve cells, acting in some contexts as a signal to other cells and in other contexts as a receptor of information. It has been implicated in controlling cell migration, the guidance of growing axons, the specification of synaptic connectivity and other processes. It is deployed in many parts of the developing brain and required for proper development in the cerebral cortex, hippocampus, thalamus, cerebellum, retina, spinal cord, and probably other areas we don’t yet know about.

Despite widespread cellular disorganisation and miswiring in their brains, Sema6A mutant mice seem overtly pretty normal. They are quite healthy and fertile and a casual inspection would not pick them out as different from their littermates. However, more detailed investigation revealed electrophysiological and behavioural differences that piqued our interest.

Because these animals have a subtly malformed hippocampus, which looks superficially like the kind of neuropathology observed in many cases of temporal lobe epilepsy, we wanted to test if they had seizures. To do this we attached electrodes to their scalp and recorded their electroencephalogram (or EEG). This technique measures patterned electrical activity in the underlying parts of the brain and showed quite clearly that these animals do not have seizures. But it did show something else – a generally elevated amount of activity in these animals all the time.

What was particularly interesting about this is that the pattern of change (a specific increase in alpha frequency oscillations) was very similar to that reported in animals that are sensitised to amphetamine – a well-used model of psychosis in rodents. High doses of amphetamine can acutely induce psychosis in humans and a suite of behavioural responses in rodents. In addition, a regimen of repeated low doses of amphetamine over an extended time period can induce sensitisation to the effects of this drug in rodents, characterised by behavioural differences, like hyperlocomotion, as well as the EEG differences mentioned above. Amphetamine is believed to cause these effects by inducing increases in dopaminergic signaling, either chronically, or to acute stimuli.

This was of particular interest to us, as that kind of hyperdopaminergic state is thought to be a final common pathway underlying psychosis in humans. Alterations in dopamine signaling are observed in schizophrenia patients (using PET imaging) and also in all relevant animal models so far studied.

Unlike in many other animals, injured nerve fibres in the mammalian central nervous system do not regenerate – at least not spontaneously. A lot of research has gone in to finding ways to coax them to do so, unfortunately with only modest success. The main problem is that there are many reasons why central nerve fibres don’t regenerate after an injury – tackling them singly is not sufficient. A new study takes a combined approach to hit two distinct molecular pathways in injured nerves and achieves substantial regrowth in an animal model.

Many lower vertebrates, like frogs and salamanders, for example, can regrow damaged nerves quite readily. And even in mammals, nerves in the periphery will regenerate and reconnect, given enough time. But nerve fibres in the brain and spinal cord do not regenerate after an injury. Researchers trying to solve this problem focused initially on figuring out what is different about the environment in the central versus the peripheral nervous system in mammals.

It was discovered early on that the myelin – the fatty sheath of insulation surrounding nerve fibres – in the central nervous system is different from that in the periphery. In particular, it inhibits nerve growth. A number of groups have tried to figure out what components of central myelin are responsible for this activity. Myelin is composed of a large number of proteins, as well as lipid membranes. One of these, subsequently named Nogo, was discovered to block nerve growth. This discovery prompted understandable excitement, especially because an antibody that binds that protein was found to promote regrowth of injured spinal nerves in the rat. (It even prompted a film, Extreme Measures, with Gene Hackman and Hugh Grant – an under-rated thriller with some surprisingly accurate science and some very serious medical malfeasance).

Unfortunately, the regrowth in rats that is promoted by blocking the Nogo protein is very limited. Similarly, mice that are mutant for this protein or its receptor show very minor regeneration. What is observed in some cases is extra sprouting of uninjured axons downstream of the spinal injury site. This can lead to some minor recovery of function but it’s really remodelling, rather than regeneration.

But it does suggest an answer to the question: why would we have evolved a system that seems actively harmful, that prevents regeneration after an injury? Well, first, the selective pressure in mammals to be able to regenerate damaged nerves is probably not very great, simply because injured animals would not typically get the chance to regenerate in the wild. And second, it suggests that the function of proteins like Nogo may not be to prevent regeneration but to prevent sprouting of nerve fibres after they have already made their appropriate connections. A lot of effort goes in to wiring the nervous system, with exquisite specificity – once that wiring pattern is established, it probably pays to actively keep it that way.

There are a number of reasons why blocking the Nogo protein does not allow nerves to fully regenerate. First, it is not the only protein in myelin that blocks growth – there are many others. Second, the injury itself can give rise to scarring and inflammation that generates a secondary barrier. And third, neurons in the mature nervous system may simply not be inclined to grow. (Not only that – the distances they may have to travel in the fully grown adult may be orders of magnitude longer than those required to wire the nervous system up during development. There are nerves in an adult human that are almost a metre long but these connections were first formed in the embryo when the distance was measured in millimetres.)

This last problem has been addressed more recently, by researchers asking if there is something in the neurons themselves that changes over time – after all, neurons in the developing nervous system grow like crazy. That propensity for growth seems to be dampened down in the adult nervous system – again, once the nervous system is wired up, it is important to restrict further growth.

Researchers have therefore looked for biochemical differences between young (developing) neurons and mature neurons that have already formed connections. The hope is that if we understand the molecular pathways that differ we might be able to target them to “rejuvenate” damaged neurons, restoring their internal urge to grow. The lab of Zhigang He at Harvard Medical School has been one of the leaders in this area and has previously found that targeting either of two biochemical pathways allowed some modest regeneration of injured neurons. (They study the optic nerve as a more accessible model of central nerve regrowth than the spinal cord).

In a new study recently published in Nature, they show that simultaneously blocking both these proteins leads to remarkably impressive regrowth – far greater than simply an additive effect of blocking the two proteins alone. The two proteins are called PTEN and SOCS3 – they are both intracellular regulators of cell growth, including the ability to respond to extracellular growth factors. The authors used a genetic approach to delete these genes two weeks prior to an injury and found that regrowth was hugely promoted. That is obviously not a very medically useful approach however – more important is to show that deleting them after the injury can permit regeneration and indeed, this is what they found. Presumably, neurons in this “grow, grow, grow!” state are either insensitive to the inhibitory factors in myelin or the instructions for growth can override these factors.

They went on to characterise the changes that occur in the neurons when these genes are deleted and observed that many other proteins associated with active growth states are upregulated, including ones that get repressed in response to the injury itself. The hope now is that drugs may be developed to target the PTEN and SOCS3 pathways in human patients, especially those with devastating spinal cord injuries, to encourage damaged nerves to regrow. As with all such discoveries, translation to the clinic will be a difficult and lengthy process, likely to take years and there is no guarantee of success. But compared to previous benchmarks of regeneration in animal models, this study shows what looks like real progress.

Sun F, Park KK, Belin S, Wang D, Lu T, Chen G, Zhang K, Yeung C, Feng G, Yankner BA, & He Z (2011). Sustained axon regeneration induced by co-deletion of PTEN and SOCS3. Nature, 480 (7377), 372-5 PMID: 22056987

“Scientists discover gene for autism” (or ovarian cancer, or depression, cocaine addiction, obesity, happiness, height, schizophrenia… and whatever you’re having yourself). These are typical newspaper headlines (all from the last year) and all use the popular shorthand of “a gene for” something. In my view, this phrase is both lazy and deeply misleading and has caused widespread confusion about what genes are and do and about their influences on human traits and disease.

The problem with this phrase stems from the ambiguity in what we mean by a “gene” and what we mean by “for”. These can mean different things at different levels and unfortunately these meanings are easily conflated. First, a gene can be defined in several different ways. From a molecular perspective, it is a segment of DNA that codes for a protein, along with the instructions for when and where and in what amounts this protein should be made. (Some genes encode RNA molecules, rather than proteins, but the general point is the same). The function of the gene on a cellular level is thus to store the information that allows this protein to be made and its production to be regulated. So, you have a gene for haemoglobin and a gene for insulin and a gene for rhodopsin, etc., etc. (around 25,000 such genes in the human genome). The question of what the gene is for then becomes a biochemical question – what does the encoded protein do?

But that is not the only way or probably even the main way that people think about what genes do – it is certainly not how geneticists think about it. The function of a gene is commonly defined (indeed often discovered) by looking at what happens when it is mutated – when the sequence of DNA bases that make up the gene is altered in some way which affects the production or activity of the encoded protein. The visible manifestation of the effect of such a mutation (the phenotype) is usually defined at the organismal level – altered anatomy or physiology or behaviour, or often the presence of disease. From this perspective, the gene is defined as a separable unit of heredity – something that can be passed on from generation to generation that affects a particular trait. This is much closer to the popular concept of a gene, such as a gene for blue eyes or a gene for breast cancer. What this really means is a mutation for blue eyes or a mutation for breast cancer.

The challenge is in relating the function of a gene at a cellular level to the effects of variation in that gene, which are most commonly observed at the organismal level. The function at a cellular level can be defined pretty directly (make protein X) but the effect at the organismal level is much more indirect and context-dependent, involving interaction with many other genes that also contribute to the phenotype in question, often in highly complex and dynamic systems.

If you are talking about a simple trait like blue eyes, then the function of the gene at a molecular level can actually be related to the mutant phenotype fairly easily – the gene encodes an enzyme that makes a brown pigment. When that enzyme is not made or does not work properly, the pigment is not made and the eyes are blue. Easy-peasy.

But what if the phenotype is in some complex physiological trait, or even worse, a psychological or behavioural trait? These traits are often defined at a very superficial level, far removed from the possible molecular origins of individual differences. The neural systems underlying such traits may be incredibly complex – they may break down due to very indirect consequences of mutations in any of a large number of genes.

For example, mutations in the genes encoding two related proteins, neuroligin-3 and neuroligin-4 have been found in patients with autism and there is good evidence that these mutations are responsible for the condition in those patients. Does this make them “genes for autism”? That phrase really makes no sense – the function of these genes is certainly not to cause autism, nor is it to prevent autism. The real link between these genes and autism is extremely indirect. The neuroligin proteins are involved in the formation of synaptic connections between neurons in the developing brain. If they are mutated, then the connections that form between specific types of neurons are altered. This changes the function of local circuits in the brain, affecting their information-processing parameters and changing how different regions of the brain communicate. Ultimately, this impacts on neural systems controlling things like social behaviour, communication and behavioural flexibility, leading to the symptoms that define autism at the behavioural level.

So, mutations in these genes can cause autism, but these are not genes for autism. They are not even usefully or accurately thought of as genes for social behaviour or for cognitive flexibility – they are required, along with the products of thousands of other genes, for those faculties to develop.

But perhaps there are other genetic variants in the population that affect the various traits underlying these faculties – not in such a severe way as to result in a clinical disorder, but enough to cause the observed variation across the general population. It is certainly true that traits like extraversion are moderately heritable – i.e., a fair proportion of the differences between people in this trait are attributable to genetic differences. When someone asks “are there genes for extraversion?”, the answer is yes if they mean “are differences in extraversion partly due to genetic differences?”. If they mean the function of some genetic variant is to make people more or less extroverted, then they have suddenly (often unknowingly) gone from talking about the activity of a gene or the effect of mutation of that gene to considering the utility of a specific variant.

This suggests a deeper meaning – not just that the gene has a function, but that it has a purpose – in biological terms, this means that a particular version of the gene was selected for on the basis of its effect on some trait. This can be applied to the specific sequence of a gene in humans (as distinct from other animals) or to variants within humans (which may be specific to sub-populations or polymorphic within populations).

While geneticists may know what they mean by the shorthand of “genes for” various traits, it is too easily taken in different, unintended ways. In particular, if there are genes “for” something, then many people infer that the something in question is also “for” something. For example, if there are “genes for homosexuality”, the inference is that homosexuality must somehow have been selected for, either currently or under some ancestral conditions. Even sophisticated thinkers like Richard Dawkins fall foul of this confusion – the apparent need to explain why a condition like homosexual orientation persists. Similar arguments are often advanced for depression or schizophrenia or autism – that maybe in ancestral environments, these conditions conferred some kind of selective advantage. That is one supposed explanation for why “genes for schizophrenia or autism” persist in the population.

Natural selection is a powerful force but that does not mean every genetic variation we see in humans was selected for, nor does it mean every condition affecting human psychology confers some selective advantage. In fact, mutations like those in the neuroligin genes are rapidly selected against in the population, due to the much lower average number of offspring of people carrying them. The problem is that new ones keep arising – in those genes and in thousands of other required to build the brain. By analogy, it is not beneficial for my car to break down – this fact does not require some teleological explanation. Breaking down occasionally in various ways is not a design feature – it is just that highly complex systems bring an associated higher risk due to possible failure of so many components.

So, just because the conditions persist at some level does not mean that the individual variants causing them do. Most of the mutations causing disease are probably very recent and will be rapidly selected against – they are not “for” anything.

Jamain S, Quach H, Betancur C, Råstam M, Colineaux C, Gillberg IC, Soderstrom H, Giros B, Leboyer M, Gillberg C, Bourgeron T, & Paris Autism Research International Sibpair Study (2003). Mutations of the X-linked genes encoding neuroligins NLGN3 and NLGN4 are associated with autism. Nature genetics, 34 (1), 27-9 PMID: 12669065

I have a new post on BigThink on engineering viruses to trace neural connections.

Apologies for not posting anything recently. I have something in the works at BigThink and a few more in the pipeline but it has been hard finding the time to blog recently. I hope to be back to it in a couple of weeks.

A new study suggests that a gene known to be causally linked to schizophrenia and other psychiatric disorders is involved in the formation of connections between the two hemispheres of the brain. DISC1 is probably the most famous gene in psychiatric genetics, and rightly so. It was discovered in a large Scottish pedigree, where 18 members were affected by psychiatric disease.
The diagnoses ranged from schizophrenia and bipolar disorder to depression and a range of “minor” psychiatric conditions. It was found that the affected individuals had all inherited a genetic anomaly – a translocation of genetic material between two chromosomes. This basically involves sections of two chromosomes swapping with each other. In the process, each chromosome is broken, before being spliced back to part of the other chromosome. In this case, the breakpoint on chromosome 1 interrupted a gene, subsequently named Disrupted-in-Schizophrenia-1, or DISC1.

That this discovery was made using classical “cytogenetic” techniques (physically looking at the chromosomes down a microscope) and in a single family is somehow pleasing in an age where massive molecular population-based studies are in vogue. (A win for “small” science).

The discovery of the DISC1 translocation clearly showed that disruption of a single gene could lead to psychiatric disorders like schizophrenia. This was a challenge to the idea that these disorders were “polygenic” – caused by the inheritance in each individual of a large number of genetic variants. As more and more mutations in other genes are being found to cause these disorders, the DISC1 situation can no longer be dismissed as an exception – it is the norm.

It also was the first example of a principle that has since been observed for many other genes – namely that the effects of the mutation can manifest quite variably - not as one specific disorder, but as different ones in different people. Indeed, DISC1 has since been implicated in autism as well as adult-onset disorders. It is now clear from this and other evidence that these apparently distinct conditions are best thought of as variable outcomes that arise, in many cases at least, from disturbances of neurodevelopment.

Since the initial discovery, major research efforts of a growing number of labs have been focused on the next obvious questions: what does DISC1 do? And what happens when it is mutated? What happens in the brain that can explain why psychiatric symptoms result?

We now know that DISC1 has many different functions. It is a cytoplasmic protein - localised inside the cell - that interacts with a very large number of other proteins and takes part in diverse cellular functions, including cell migration, outgrowth of nerve fibres, the formation of dendritic spines (sites of synaptic contact between neurons), neuronal proliferation and regulation of biochemical pathways involved in synaptic plasticity. Many of the proteins that DISC1 interacts with have also been implicated in psychiatric disease.

This new study adds another possible function, and a dramatic and unexpected one at that. This function was discovered from an independent angle, by researchers studying how the two hemispheres of the brain get connected – or more specifically, why they sometimes fail to be connected. The cerebral hemispheres are normally connected by millions of axons which cross the midline of the brain in a structure called the corpus callosum (or “tough body” – (don’t ask)). Very infrequently, people are born without this structure – the callosal axons fail to cross the midline and the two hemispheres are left without this major route of communication (though there are other routes, such as the anterior commissure).

The frequency of agenesis of the corpus callosum has been estimated at between 1 in 1,000 and 1 in 6,000 live births – thankfully very rare. It is associated with a highly variable spectrum of other symptoms, including developmental delay, autistic symptoms, cognitive disabilities extending into the range of mental retardation, seizures and other neurological signs.

Elliott Sherr and colleagues were studying patients with this condition, which is very obvious on magnetic resonance imaging scans (see Figure). They initially found a mother and two children with callosal agenesis who all carried a deletion on chromosome 1, at position 1q42 – exactly where DISC1 is located. They subsequently identified another patient with a similar deletion, which allowed them to narrow down the region and identify DISC1 as a plausible candidate (among some other genes in the deleted region). Because the functions of proteins can be affected not just by large deletions or translocations but also by less obvious mutations that change a single base of DNA, they also sequenced the DISC1 gene in a cohort of callosal agenesis patients and found a number carrying novel mutations that are very likely to disrupt the function of the gene.

While not rock-solid evidence that it is DISC1 that is responsible, these data certainly point to it as the strongest candidate to explain the callosal defect. This hypothesis is strongly supported by findings from DISC1 mutant mice (carrying a mutation that mimics the effect of the human translocation), which also show defects in formation of the corpus callosum. In addition, the protein is strongly expressed in the axons that make up this structure at the time of its development.

The most obvious test of whether disruption of DISC1 really causes callosal agenesis is to look in the people carrying the initial translocation. Remarkably, it is not known whether the original patients in the Scottish pedigree who carry the DISC1 translocation show this same obvious brain structural phenotype. They have, very surprisingly, never been scanned.

This new paper raises the obvious hypothesis that the failure to connect the two hemispheres results in the psychiatric or cognitive symptoms, which variously include reduced intellectual ability, autism and schizophrenia. This seems like too simplistic an interpretation, however. All we have now is a correlation. First, the implication of DISC1 in the acallosal phenotype is not yet definitive – this must be nailed down and replicated. But even if it is shown that disruption of DISC1 causes both callosal agenesis and schizophrenia (or other psychiatric disorders or symptoms), this does not prove a causal link. DISC1 has many other functions and is expressed in many different brain areas (ubiquitously in fact). Any, or indeed, all of these functions may in fact be the cause of psychopathology.

One prediction, if it were true that the lack of connections between the two hemispheres is causal, is that we would expect the majority of patients with callosal agenesis to have these kinds of psychiatric symptoms. In fact, the rates are indeed very high – in different studies it has been estimated that up to 40% of callosal agenesis patients have an autism diagnosis, while about 8% have the symptoms of schizophrenia or bipolar disorder. (Of course, these patients may have other, less obvious brain defects as well, so even this is not definitive).

Conversely, we might naively expect a high rate of callosal agenesis in patients with autism or schizophrenia. However, we know these disorders are extremely heterogeneous and so it is much more likely that this phenotype might be apparent in only a specific (possibly very small) subset of patients. This may indeed be the case – callosal agenesis has been observed in about 3 out of 200 schizophrenia patients (a vastly higher rate than in the general population). Another study, just published, has found that mutations in a different gene – ARID1B – are also associated with callosal agenesis, mental retardation and autism. More generally, there may be subtle reductions in callosal connectivity in many schizophrenia or autism patients (including some autistic savants).

Whether this defect can explain particular symptoms is not yet clear. For the moment, the new study provides yet another possible function of DISC1, and highlights an anatomical phenotype that is apparently present in a subset of autism and schizophrenia cases and that can arise due to mutation in many different genes (of which DISC1 and ARID1B are only two of many known examples).


One final note: formation of the corpus callosum is a dramatic example of a process that is susceptible to developmental variation. What I mean is this: when patients inherit a mutation that results in callosal agenesis, this phenotype occurs in some patients but not all. This is true even in genetically identical people, like monozygotic twins or triplets (or in lines of genetically identical mice). Though the corpus callosum contains millions of nerve fibres, the initial events that establish it involve very small numbers of cells. These cells, which are located at the medial edge of each cerebral hemisphere, must contact each other to enable the fusion of the two hemispheres, forming a tiny bridge through which the first callosal fibres can cross. Once these are across, the rest seem able to follow easily. Because this event involves very few cells at a specific time in development, it is susceptible to random “noise” – fluctuations in the precise amounts of various proteins in the cells, for example. These are not caused by external forces – the noise is inherent in the system. The result is that, in some people carrying such a mutation the corpus callosum will not form at all, while in others it forms apparently completely normally (see figure of triplets, one on left with normal corpus callosum, the other two with it absent). So, an all-or-none effect can arise, without any external factors involved.

This same kind of intrinsic developmental variation may also explain or at least contribute to the variability in phenotypic outcome at the level of psychiatric symptoms when these kinds of neurodevelopmental mutations are inherited. Even monozygotic twins are often discordant for psychiatric diagnoses (concordance for schizophrenia is about 50%, for example). This is often assumed to be due to non-genetic and therefore “environmental” or experiential factors. If these disorders really arise from differences in brain wiring, which we know are susceptible to developmental variation, then differences in the eventual phenotype could actually be completely intrinsic and innate.


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Halgren C, Kjaergaard S, Bak M, Hansen C, El-Schich Z, Anderson CM, Henriksen KF, Hjalgrim H, Kirchhoff M, Bijlsma EK, Nielsen M, den Hollander NS, Ruivenkamp CA, Isidor B, Le Caignec C, Zannolli R, Mucciolo M, Renieri A, Mari F, Anderlid BM, Andrieux J, Dieux A, Tommerup N, & Bache I (2011). Corpus Callosum Abnormalities, Mental Retardation, Speech Impairment, and Autism in Patients with Haploinsufficiency of ARID1B. Clinical genetics PMID: 21801163

There is a common view that the human genome has two different parts – a “constant” part and a “variable” part. According to this view, the bases of DNA in the constant part are the same across all individuals. They are said to be “fixed” in the population. They are what make us all human – they differentiate us from other species. The variable part, in contrast, is made of positions in the DNA sequence that are “polymorphic” – they come in two or more different versions. Some people carry one base at that position and others carry another. The idea is that it is the particular set of such variations that we inherit that makes us each unique (unless we have an identical twin). According to this idea, we each have a hand dealt from the same deck.

The genome sequence (a simple linear code made up of 3 billion bases of DNA in precise order, chopped up onto different chromosomes) is peppered with these polymorphic positions – about 1 in every 1,250 bases. That makes about 2,400,000 polymorphisms in each genome (and we each carry two copies of the genome). That certainly seems like plenty of raw material, with limitless combinations that could explain the richness of human diversity. This interpretation has fuelled massive scientific projects to try and find which common polymorphisms affect which traits. (Not to mention personal genomics companies who will try to tell you your risk of various diseases based on your profile of such polymorphisms).

The problem with this view is that it is wrong. Or at least woefully incomplete.

The reason is it ignores another source of variation: very rare mutations in those bases that are constant across the vast majority of individuals. There is now very good evidence that it is those kinds of mutations that contribute most to our individuality. Certainly, they are much more likely to affect a protein’s function and much more likely to contribute to genetic disease. We each carry hundreds of such rare mutations that can affect protein function or expression and are much more likely to have a phenotypic impact than common polymorphisms.

Indeed, far from most of the genome being effectively constant, it can be estimated that every position in the genome has been mutated many, many times over in the human population. And each of us carries hundreds of new mutations that arose during generation of the sperm and egg cells that fused to form us. New mutations may spread in the pedigree or population in which they arise for some time, depending in part on whether they have a deleterious effect or not. Ones that do will likely be quickly selected against.

A new paper from the 1000 genomes project consortium shows that:

“the vast majority of human variable sites are rare and that the majority of rare variants exhibit, at most, very little sharing among continental populations”.

This is a much more fluid picture of genetic variation than we are used to. We are not all dealt a genetic hand from the same deck – each population, sub-population, kindred, nuclear family has a distinct set of rare genetic variants. And each of these decks contains a lot of jokers – the new mutations that arise each time a hand is dealt.

Why have such rare mutations generally been ignored while the polymorphic sites have been the focus of intense research? There are several reasons, some practical and some theoretical. Practically, it has until recently been almost impossible to systematically find very rare mutations. To do so requires that we sequence the whole genome, which has only recently become feasible. In contrast, methods to survey which bases you carry at all the polymorphic sites across the genome were developed quite some time ago now and are relatively cheap to use. (They rely on sampling about 500,000 such sites around the genome – because of unevenness in the way different bits of chromosomes get swapped when sperm and eggs are made, this sample actually tells you about most of the variable sites across the whole genome). So, there has been a tendency to argue that polymorphic sites will be major contributors to human phenotypes (especially diseases) because those have been the only ones we have been able to look at.

Unfortunately, the results of genome-wide association studies, which aim to identify common variants associated with traits or diseases, have been disappointing. This is especially true for disorders with large effects on fitness, such as schizophrenia or autism. Some variants have been found but their effects, even in combination are very small. Most of the heritability of most of the traits or diseases examined to date remains unexplained. (There are some important exceptions, especially for diseases that strike only late in life and for things like drug responses, where selective pressures to weed out deleterious alleles are not at play).

In contrast, many more rare mutations causing disease are being discovered all the time, and the pace of such discoveries is likely to increase with technological advances. The main message that emerges from these studies has been called by Mary-Claire King the “Anna Karenina principle”, based on Tolstoy’s famous opening line:

“Happy families are all alike; every unhappy family is unhappy in its own way”

But can such rare variants really explain the “missing heritability” of these disorders? Some people have argued that they cannot, but this seems to me to be based on a pervasive misconception of how the heritability of a trait is measured and what it means. According to this misconception, if a trait is heritable across the population, that heritability cannot be accounted for by rare variants. After all, if a mutation only occurs in one or a few individuals, it could only minimally (nearly negligibly) contribute to heritability across the whole population. That is true. However, heritability is not measured across the population – it is measured in families and then averaged across the population.

In humans, it is usually derived by comparing phenotypes between people of different genetic relatedness (identical versus fraternal twins, siblings, parents, cousins, etc.). The values of these comparisons are then averaged across large numbers of pairs to allow estimates of how much genetic variance affects phenotypic variance – the population heritability. While a specific rare mutation may only affect the phenotype within a single family, such mutations could, collectively, explain all of the heritability. Completely different sets of mutations could be affecting the trait or causing the disease in different families.

The next few years will reveal the true impact of rare mutations. We should certainly expect complex genetic interactions and some real effects of common polymorphisms. But the idea that our traits are determined simply by the combination of variants we inherit from a static pool in the population is no longer tenable. We are each far more unique than that.

(And if your personal genomics company isn’t offering to sequence your whole genome, it’s not personal enough).


Gravel S, Henn BM, Gutenkunst RN, Indap AR, Marth GT, Clark AG, Yu F, Gibbs RA, The 1000 Genomes Project, & Bustamante CD (2011). Demographic history and rare allele sharing among human populations. Proceedings of the National Academy of Sciences of the United States of America, 108 (29), 11983-11988 PMID: 21730125

Walsh CA, & Engle EC (2010). Allelic diversity in human developmental neurogenetics: insights into biology and disease. Neuron, 68 (2), 245-53 PMID: 20955932

McClellan, J., & King, M. (2010). Genetic Heterogeneity in Human Disease Cell, 141 (2), 210-217 DOI: 10.1016/j.cell.2010.03.032