The fact that the adult brain is very plastic is often held up as evidence against the idea that many psychological, cognitive or behavioural traits are innately determined. At first glance, there does indeed appear to be a paradox. On the one hand, behavioural genetic studies show that many human psychological traits are strongly heritable and thus likely determined, at least in part, by innate biological differences. On the other, it is very clear that even the adult brain is highly plastic and changes itself in response to experience.

The evidence on both sides is very strong. In general, for traits like intelligence and personality characteristics such as extraversion, neuroticism or conscientiousness, among many others, the findings from genetic studies are remarkably consistent. Just as for physical traits, people who are more closely related resemble each other for psychological traits more than people with a more distant relationship. Twin study designs get around the obvious objection that such similarities might be due to having been raised together. Identical twins tend to be far more like each other for these traits than fraternal twins, though the family environment is shared in both cases. Even more telling, identical twins who are raised apart tend to be pretty much as similar to each other as pairs who are raised together. Clearly, we come fairly strongly pre-wired and the family environment has little effect on these kinds of traits.

Yet we know the brain can “change itself”. You could say that is one of its main jobs in fact – altering itself in response to experience to better adapt to the conditions in which it finds itself. For example, as children learn a language, their auditory system specialises to recognise the typical sounds of that language. Their brains become highly expert at distinguishing those sounds and, in the process, lose the ability to distinguish sounds they hear less often. (This is why many Japanese people cannot distinguish between the sounds of the letters “l” and “r”, for example, and why many Westerners have difficulty hearing the crucial tonal variations in languages like Cantonese). Learning motor skills similarly improves performance and induces structural changes in the relevant brain circuits. In fact, most circuits in the brain develop in an experience-dependent fashion, summed up by two adages: “cells that fire together, wire together” and “use it or lose it”.

Given the clear evidence for brain plasticity, the implication would seem to be that even if our brains come pre-wired with some particular tendencies, that experience, especially early experience, should be able to override them.

I would argue that the effect of experience-dependent development is typically exactly the opposite – that while the right kind of experience can, in principle, act to overcome innate tendencies, in practice, the effect is reversed. The reason is that our innate tendencies shape the experiences we have, leading us to select ones that tend instead to reinforce or even amplify these tendencies. Our environment does not just shape us – we shape it.

A child who is naturally shy – due to innate differences in the brain circuits mediating social behaviour, general anxiety, risk-aversion and other parameters – will tend to have less varied and less intense social experience. As a result, they will not develop the social skills that might make social interaction more enjoyable for them. A vicious circle emerges – perhaps intense practice in social situations would alter the preconfigured settings of a shy child’s social brain circuits but they tend not to get that experience, precisely because of those settings. In contrast, their extroverted classmates may, by constantly seeking out social interactions, continue to develop this innate faculty.

This circle may be most vicious in children with autism, most of whom have a reduced level of innate interest in other people. They tend, for example, not to find faces as intrinsically fascinating as other infants. This may contribute to a delay in language acquisition, as they miss out on interpersonal cues that strongly facilitate learning to speak.

A similar situation may hold for children who have difficulties in reading or with mathematics. Dyslexia seems to be caused by an innate difficulty in associating the sounds and shapes of letters. This can be traced to genetic effects during early development of the brain, which may cause interruptions in long-range connections between brain areas. This innate disadvantage is cruelly amplified by the typical experience of many dyslexics. Learning to read is hard enough and requires years of practice and active instruction. For children who have basic difficulties in recognising letters and words, reading remains effortful for far longer and they will therefore tend to read less, missing out on the intensive practice that would help their brain circuitry specialise for reading.

Though less widely known, dyscalculia (a selective difficulty in mathematics) is equally common and shares many characteristics with dyslexia. The initial problem is in innate number sense – the ability to estimate and compare small numbers of objects. This faculty is present in very young infants and even shared with many other animal species, notably crows. Formal mathematical instruction is required to build on this innate number sense but also crucially relies on it. As with reading, mathematics requires hard work to learn and if numbers are inherently mysterious then this will change the nature of the child’s experience, lessen interest and reduce practice. At the other end of the spectrum, those with strong mathematical talent may gravitate towards the subject, further amplifying the differences between these two groups.

Thus, while a certain type of experience can alter the innate tendency, the innate tendency makes getting that experience far less likely. Brain plasticity tends instead to amplify initial differences.

That sounds rather fatalistic, but the good news is that this vicious circle can be broken if innate difficulties are recognised early enough – by actively changing the nature of early experience. There is good evidence that intense early intervention in children with autism (such as Applied Behaviour Analysis) allows them to compensate for innate deficits and lead to improvements in cognitive, communication and adaptive skills. Similarly intense intervention in children with dyslexia has also proven effective. Thus, even if it is not possible to reverse whatever neurodevelopmental differences lead to these kinds of deficits, it should at least be possible to prevent their being amplified by subsequent experience.

Duff FJ, & Clarke PJ (2011). Practitioner Review: Reading disorders: what are the effective interventions and how should they be implemented and evaluated? Journal of child psychology and psychiatry, and allied disciplines, 52 (1), 3-12 PMID: 21039483

Vismara, L., & Rogers, S. (2010). Behavioral Treatments in Autism Spectrum Disorder: What Do We Know? Annual Review of Clinical Psychology, 6 (1), 447-468 DOI: 10.1146/annurev.clinpsy.121208.131151 ]]> http://www.gnxp.com/new/2011/10/01/does-brain-plasticity-trump-innateness/feed/ 19 http://www.gnxp.com/new/2011/07/08/environmental-influences-on-autism-splashy-headlines-from-dodgy-data/ http://www.gnxp.com/new/2011/07/08/environmental-influences-on-autism-splashy-headlines-from-dodgy-data/#comments Fri, 08 Jul 2011 13:04:53 +0000 http://www.gnxp.com/wp/?p=1364 A couple of recent papers have been making headlines in relation to autism, one claiming that it is caused less by genetics than previously believed and more by the environment and the other specifically claiming that antidepressant use by expectant mothers increases the risk of autism in the child. But are these conclusions really supported by the data? Are they strongly enough supported to warrant being splashed across newspapers worldwide, where most readers will remember only the headline as the take-away message? The legacy of the MMR vaccination hoax shows how difficult it can be to counter overblown claims and the negative consequences that can arise as a result.

So, do these papers really make a strong case for their major conclusions? The first gives results from a study of twins in California. Twin studies are a classic method to determine whether something is caused by genetic or environmental factors. The method asks, if one twin in a pair is affected by some disorder (autism in this case), with what frequency is the other twin also affected? The logic is very simple: if something is caused by environmental factors, particularly those within a family, then it should not matter whether the twins in question are identical or fraternal – their risk should be the same because their exposure is the same. On the other hand, if something is caused by genetic mutations, and if one twin has the disorder, then the rate of occurrence of the disorder in the other twin should be much higher if they are genetically identical than if they only share half their genes, as fraternal twins do.

Working backwards, if the rate of twin concordance for affected status are about the same for identical and fraternal twins, this is strong evidence for environmental factors. If the rate is much higher in monozygotic twins, this is strong evidence for genetic factors. Now to the new study. What they found was that the rate of concordance for monozygotic (identical) twins was indeed much higher than for dizyogotic (fraternal) twins – about twice as high on average.

For males: MZ: 0.58, DZ: 0.21
For females: MZ: 0.60, DZ: 0.27

Those numbers are for the diagnosis of strict autism. The rate of “autism spectrum disorder”, which encompasses a broader range of disability, showed similar results:

Males: MZ: 0.77, DZ: 0.31
Females: MZ: 0.50, DZ: 0.36.

These numbers fit pretty well with a number of other recent twin studies, all of which have concluded that they provide evidence for strong heritability of the disorder – i.e., that whether or not someone develops autism is largely (though not exclusively) down to genetics.

So, why did these authors reach a different conclusion and should their study carry any more weight than others? On the latter point, the study is significantly larger than many that have preceded it. This study looked at 192 twin pairs, each with at least one affected twin. However, some recent studies have been comparable or even larger: Lichtenstein and colleagues looked at 117 twin pairs and Rosenberg and colleagues looked at 277 twin pairs. These studies found eveidence for very high heritability and negligible shared environmental effects.

Another potentially important difference is in how the sample was ascertained. Hallmayer and colleagues claim that their assessment of affected status was more rigorous than for other studies and this may be true. However, it has previously been found that less rigorous assessments correlate extremely well with the more standardised assessments, so this is unlikely to be a major factor. In addition, there is very strong evidence that disorders like autism, ADHD, epilepsy, intellectual disability, tic disorders and others all share common etiology – having a broader diagnosis is therefore probably more appropriate.

In any case, the numbers they came up with for concordance rates were pretty similar across these studies. So, why did they end up with a different conclusion? That’s not a rhetorical question – I actually don’t know the answer and if anyone else does I would love to hear it. Given the data, I don’t know how they conclude that they provide evidence for shared environmental effects.

The methodology involves some statistical modeling that tries to tease out the sources of variance. However, this modeling is based completely on a multifactorial threshold model for the disorder – the idea that autism arises when the collective burden of individually minor genetic or environmental insults passes some putative threshold. Sounds plausible, but there is in fact no evidence – at all – that this model applies to autism. In fact, it seems most likely that autism really is an umbrella term for a collection of distinct genetic disorders caused by mutations in separate genes, but which happen to cause common phenotypes (or symptoms).

If that is the case, then what the twin concordance rates actually measure is the penetrance of such mutations – if one inherits mutation X, how often does that actually lead to autism? For monozygotic twins, let us assume that the affected proband (the first twin diagnosed) has such a mutation. Because they are genetically identical, the other one must too. The chance that the other twin will develop autism thus depends on the penetrance of the mutation – some mutations are more highly penetrant than others, giving a much higher probability of developing a specific phenotype. If we average across all MZ twin pairs we therefore get an average penetrance across all such putative mutations. Now, if such mutations are dominant, as many of the known ones are, then the chance that a dizygotic twin will inherit it is 50%, while the penetrance should remain the same. So, this model would predict that the rate of co-occurrence in DZ twins should be about half that of MZ twins, exactly as observed. (No stats required).

The conclusions from this study that the heritability is only modest and that a larger fraction of variance (55%!) is caused by shared environment thus seem extremely shaky. This is reinforced by the fact that the confidence intervals for these estimates are extremely wide (for the effect of shared environment the 95% confidence interval ranges from 9% to 81%). Certainly not enough to overturn all the other data from other studies.

What about epidemiological studies that have shown statistical evidence of increased risk of autism associated with a variety of other factors, including maternal diabetes, antidepressant use, season and place of brith? All of these factors have been linked with modest increases in the risk of autism. Don’t these prove there are important environmental factors? Well, first, they don’t prove causation, they provide a statistical evidence for an association between the two factors, which is not at all the same thing. Second, the increase in risk is usually on the order of about two-fold. Twice the risk may sound like a lot, but it’s only a 1% increase (from 1 to 2%), compared with some known mutations, which increase risk by 50-fold or more.

The main problem with these kinds of studies (and especially with how they are portrayed in the media) is that they are correlational and so you cannot establish a causal link directly from them. In some cases, two different correlated parameters (like red hair and freckles, for example) may actually be caused by an unmeasured third parameter. For example, in the recently published study, the use of antidepressants of the SSRI (selective serotonin reuptake inhibitor) class in mothers was associated with modestly increased risk of autism in the progeny. This association could be because SSRIs disrupt neural development in the fetus (perfectly plausible) but could alternatively be due to the known genetic link between risk of depression and risk of autism. Rates of depression are known to be higher in relatives of autistic people, so SSRI use could just be a proxy for that condition. The authors claim to have corrected for that by comparing rates of autism in the progeny of depressed mothers who were not prescribed SSRIs versus those who were but one might imagine that the severity of depression would be higher among those prescribed an antidpressant. In addition, the authors are careful to note that their findings were based on a small number of children exposed and that “Further studies are needed to replicate and extend these findings”. As with many such findings, this association may or may not hold up with additional study.

As for season and place of birth, those findings are better replicated and, interestingly, also found for schizophrenia. There is a theory that these effects may relate to maternal vitamin D levels, which can also affect neural development. This also seems plausible enough. However, the problem in really having confidence in these findings and in knowing how to interpret them is that they are population averages with small effect sizes. Overall, it seems quite possible that the environment – especially the prenatal environment – can play a part in the etiology of autism. At the moment, splashy headlines notwithstanding, genetic factors look much more important and genetic studies much more likely to give us the crucial entry points to the underlying biology.

Mirrored from Wiring the Brain.

Hallmayer J, Cleveland S, Torres A, Phillips J, Cohen B, Torigoe T, Miller J, Fedele A, Collins J, Smith K, Lotspeich L, Croen LA, Ozonoff S, Lajonchere C, Grether JK, & Risch N (2011). Genetic Heritability and Shared Environmental Factors Among Twin Pairs With Autism. Archives of general psychiatry PMID: 21727249

Lichtenstein P, Carlström E, Råstam M, Gillberg C, & Anckarsäter H (2010). The genetics of autism spectrum disorders and related neuropsychiatric disorders in childhood. The American journal of psychiatry, 167 (11), 1357-63 PMID: 20686188

Rosenberg, R., Law, J., Yenokyan, G., McGready, J., Kaufmann, W., & Law, P. (2009). Characteristics and Concordance of Autism Spectrum Disorders Among 277 Twin Pairs Archives of Pediatrics and Adolescent Medicine, 163 (10), 907-914 DOI: 10.1001/archpediatrics.2009.98

Croen LA, Grether JK, Yoshida CK, Odouli R, & Hendrick V (2011). Antidepressant Use During Pregnancy and Childhood Autism Spectrum Disorders. Archives of general psychiatry PMID: 21727247

However, these studies also highlight the limits of genetic determinism, which is especially evident in comparisons of monozygotic (identical) twins, who share all their genetic inheritance in common. Though they are obviously much more like each other in psychological traits than people who are not related to each other, they are clearly NOT identical to each other for these traits. For example, if one twin has a diagnosis of schizophrenia, the chance that the other one will also suffer from the disorder is about 50% – massively higher than the population prevalence of the disorder (around 1%), but also clearly much less than 100%.

What is the source of this extra variance? What forces make monozygotic twins less identical? I have argued previously that random variation in the course of development is a major contributor. The developmental programme that specifies brain connectivity is less like a blueprint than a recipe (a recipe without a cook) – an incredibly complicated set of processes carried out by mindless biochemical algorithms mediated by local interactions between billions of individual components. As each of these processes is subject to some level of “noise” at the molecular level, it is not surprising that the outcome of this process varies considerably, even between monozygotic twins.

While such developmental variation can be referred to as “non-genetic”, a new study suggests that one important component of this variation may be genetic after all, just not inherited. Mutations can be passed on from parents to offspring or arise during generation of sperm or eggs and thus be inherited, but they can also arise any time DNA is replicated. So, each time a cell divides as an embryo grows and develops, there is a very small chance of new mutations being introduced. These “somatic” mutations (meaning ones that happen in the body and not in the germline) will be inherited by all the cells that are descendants of that new cell and so will be present in some fraction of the final cells of the individual. Mutations arising earlier in development will be inherited by more cells than those arising later.

Each person will therefore be a mosaic of cells with slightly different genetic make-up. The vast majority of such mutations will not have any effect of course (with the obvious exception of those that cause dysregulation of cellular differentiation and result in cancer). But sometimes a new mutation will affect a trait and cause a detectable difference. The most obvious examples are in genes affecting hair or eye colour – where a patch of hair may be a different colour, or the two eyes may be different colours.

But what if the mutations in question are linked to a psychiatric disorder? If such a mutation arises early in the development of the brain and is therefore inherited by many of the cells in the brain then this could lead to the psychiatric disorder, just as if the mutation had been inherited in a germ cell.

A new study adds to the evidence that such mutations do indeed occur at an appreciable frequency and may help explain the discordance in phenotype between pairs of twins where one has schizophrenia and the other does not. The authors analysed the DNA from blood cells of pairs of twins discordant for schizophrenia and their parents. They were looking for two different kinds of mutation: ones that changes the identity of a single base of DNA (one letter of the genetic code to another), called point mutations, and ones that delete or duplicate whole chunks of chromosomes, called copy number variants, or CNVs.

As expected, they were able to detect both inherited mutations (present in one of the parents) and de novo mutations (present in both twins but not in the blood cells of either parent). What is more remarkable though, is that they also detected de novo mutations present in the blood cells of one twin but not the other – lots of them. About 1,000 point mutations and 2-3 new CNVs not shared by the other twin. The implication is that these mutations arose during the somatic development of one twin. They identify a couple CNVs in the twins affected by schizophrenia, raising the (very speculative) possibility that those mutations may contribute to the development of the disorder. It will obviously require a lot more work to test that specific hypothesis.

An earlier study also found a high rate of somatic mosaicism for CNVs – this time by analysing the DNA of multiple tissues taken from single (deceased) individuals. Across 34 tissue samples from 3 subjects they identified six CNVs present in one tissue but not others. What this implies is that not only do we carry additional mutations making us even more different from one another, our cells and tissues can also be genetically different from each other.

Time will tell whether such mutations really do contribute to psychiatric disorders, but it certainly seems plausible that they might. This adds to a couple other potential mechanisms of increasing individual variance: the transposition of mobile DNA elements in somatic tissues, especially neurons, and the “epigenetic” silencing of regions of the genome, which may be clonally inherited in groups of cells and contribute to differences between twins.

This has one immediate and important consequence for clinical genetics. When a mutation in an offspring is not carried by either parent it is usually interpreted as having arisen de novo. The implication is that the risk of another offspring carrying the same mutation is negligible. Clinical geneticists are finding this is not necessarily always the case, however – apparently de novo mutations may have actually arisen at an early stage in the germline and not just at the final division generating the sperm or egg. The parent in question may not actually “carry” the mutation, but their germline does. Great care must therefore be taken when advising parents with one affected child of the risk to future offspring.

Maiti S, Kumar KH, Castellani CA, O’Reilly R, & Singh SM (2011). Ontogenetic de novo copy number variations (CNVs) as a source of genetic individuality: studies on two families with MZD twins for schizophrenia. PloS one, 6 (3) PMID: 21399695

Piotrowski, A., Bruder, C., Andersson, R., de Ståhl, T., Menzel, U., Sandgren, J., Poplawski, A., von Tell, D., Crasto, C., Bogdan, A., Bartoszewski, R., Bebok, Z., Krzyzanowski, M., Jankowski, Z., Partridge, E., Komorowski, J., & Dumanski, J. (2008). Somatic mosaicism for copy number variation in differentiated human tissues Human Mutation, 29 (9), 1118-1124 DOI: 10.1002/humu.20815

Fraga, M. (2005). From The Cover: Epigenetic differences arise during the lifetime of monozygotic twins Proceedings of the National Academy of Sciences, 102 (30), 10604-10609 DOI: 10.1073/pnas.0500398102

Mirrored from the Wiring the Brain blog