Innate: How the Wiring of Our Brains Shapes Who We Are. Kevin J. Mitchell. Princeton, New Jersey, USA:
Princeton University Press, 2018, 293 pages, hardcover. ISBN:
978-0-691-17388-7.
This is a preprint of a review written for the Journal of Mind and Behavior.
Most of us are
perfectly comfortable hearing about biological bases of differences between
species, but studies of biological bases of differences between people can make
us uneasy. This can create difficulties for the scientist who wants to do
research on the way genes influence neurodevelopment: if we identify genetic variants
that account for individual differences in brain function, then it is may seem
a small step to concluding that some people are inherently more valuable than
others. And indeed in 2018 we have seen
calls for use of polygenic risk scores to select embryos for potential
educational attainment (Parens et al, 2019). There has also been widespread
condemnation of the first attempt to create a genetically modified baby using
CRISPR technology (Normile, 2018), with the World Health Organization
responding by setting up an advisory committee to develop global standards for
governance of human genome editing (World Health Organization, 2019).
Kevin Mitchell's
book Innate is essential reading for anyone concerned about the genetics behind
these controversies. The author is a superb communicator, who explains complex
ideas clearly without sacrificing accuracy. The text is devoid of hype and
wishful thinking, and it confronts the ethical dilemmas raised by this research
area head-on. I'll come back to those later, but will start by summarising
Mitchell's take on where we are in our understanding of genetic influences on
neurodevelopment.
Perhaps one of
the biggest mistakes that we've made in the past is to teach elementary
genetics with an exclusive focus on Mendelian inheritance. Mendel and his peas
provided crucial insights into units of inheritance, allowing us to predict
precisely the probabilities of different outcomes in offspring of parents
through several generations. The
discovery of DNA provided a physical instantiation of the hitherto abstract
gene, as well as providing insight into mechanisms of inheritance. During the first half of the 20th
century it became clear that there are human traits and diseases that obey
Mendelian laws impeccably: blood groups, Huntington's disease, and cystic
fibrosis, to name but a few. The problem is that many intelligent laypeople
assume that this is how genetics works in general. If a condition is inherited,
then the task is to track down the gene responsible. And indeed, 40 years ago, many researchers
took this view, and set out to track genes for autism, hearing loss, dyslexia
and so on. Ben Goldacre's (2014) comment
'I think you'll find it's a bit more complicated than that' was made in a
rather different context, but is a very apt slogan to convey where genetics
finds itself in 2019. Here are some of
the key messages that the author conveys, with clarity and concision, which
provide essential background to any discussion of ethical implications of
research.
1.
Genes are not a blueprint
The same DNA
does not lead to identical outcomes. We know this from the study of inbred
animals, from identical human twins, and even from studying development of the
two sides of the body in a single person. How can this be? DNA is a chemically
inert material, which carries instructions for how to build a body from
proteins in a sequence of bases. Shouldn't two organisms with identical DNA
should turn out the same? The answer is no, because DNA can in effect be
switched on and off: that's how it is possible for the same DNA to create a
wide variety of different cell types, depending on which proteins are
transcribed and when. As Mitchell puts it: "While DNA just kind of sits
there, proteins are properly impressive – they do all sorts of things inside
cells, acting like tiny molecular machines or robots, carrying out tens of
thousands of different functions." DNA is chemically stable, but messenger
RNA, which conveys the information to the cell where proteins are produced, is
much less so. Individual cells transcribe messenger RNA in bursts. There is
variability in this process, which can lead to differences in development.
2.
Chance plays an important role in neurodevelopment
Consideration of
how RNA functions leads to an important conclusion: factors affecting
neurodevelopment can't just be divided into genetic vs. environmental
influences: random fluctuations in the transcription process mean that chance
also plays a role.
Moving from the
neurobiological level, Mitchell notes that the interpretation of twin studies
tends to ignore the role of chance. When identical (monozygotic or MZ) twins
grow up differently, this is often attributed to the effects of 'non-shared
environment', implying there may have been some systematic differences in their
experiences, either pre- or post-natal, that led them to differ. But, such
effects don't need to be invoked to explain why identical twins can differ:
this can arise because of random effects operating at a very early stage of
neurodevelopment.
3.
Small initial differences can lead to large variation in outcome
If chance is one
factor overlooked in many accounts of genetics, development is the other. There
are interactions between proteins, such that when messenger RNA from gene A
reaches a certain level, this will increase expression of genes B and C. Those genes in turn can affect others in a
cascading sequence. This mechanism can amplify small initial differences to
create much larger effects.
4.
Genetic is not the same as heritable
Genetic variants
that influence neurodevelopment can be transmitted in the DNA passed from
parent to child leading to heritable disorders and traits. But many genetically-based neurodevelopmental
disorders do not work like this; rather, they are caused by 'de novo'
mutations, i.e. changes to DNA that arise early in embryogenesis, and so are
not shared with either parent.
5.
We all have many mutations
The notion that
there is a clear divide between 'normal people' with a nice pure genome and
'disordered' people with mutations is a fiction. All of us have numerous copy
number variants (CNVs), chunks of DNA that are deleted or duplicated (Beckmann,
Estivill, & Antonarakis, 2007), as well as point mutations, - i.e. changes
in a single base pair of DNA. When the scale of mutation in 'normal' people was
first discovered, it created quite a shock to the genetics community, jamming a
spanner in the works for researchers trying to uncover causes of specific conditions.
If we find a rare CNV or point mutation in
a person with a disorder, it could just be coincidence and not play any causal
role. Converging evidence is needed. Studies of gene function can help
establish causality; the impact on brain development will depend on whether a
mutation affects key aspects of protein synthesis; but even so, there have been
cases where a mutation thought to play a key role in disorder then pops up in
someone whose development is entirely unremarkable. A cautionary tale is
offered by Toma et al (2018), who studied variants in CNTNAP2, a gene that was thought
to be related to autism and schizophrenia. They found that the burden of rare
variants that disrupted gene function were just as high in individuals from the
general population as in people with autism or schizophrenia.
6.
One gene – one disorder is the exception rather than the rule
For many
neurodevelopmental conditions, e.g. autism, intellectual disability, and epilepsy,
associated mutations have been tracked down. But most of them account for only
a small proportion of affected individuals, and furthermore, the same mutation
is typically associated with different disorders. Our diagnostic categories don't map well onto
the genes.
This message is
of particular interest to me, as I have been studying the impact of a major
genetic change – presence of an extra X or Y chromosome - on children's
development: this includes girls with an additional X chromosome ( trisomy X ),
boys with an extra X (XXY or Klinefelter's syndrome) and boys with an extra Y
(XYY constitution). The impact of an extra sex chromosome is far less than you
might expect: most of these children attend mainstream school and live
independently as adults. There has been much speculation about possible contrasting
effects of an extra X versus extra Y chromosome. However, in general, one finds
that variation within a particular trisomy group is far greater than variation
between them. So, with all three types of trisomy, there is an increased
likelihood that the child with have educational difficulties, language and
attentional problems, and there's also a risk of social anxiety. In a minority
of cases the child meets criteria for autism or intellectual disability
(Wilson, King & Bishop, 2019). The range of outcomes is substantial –
something that makes it difficult to advise parents when the trisomy is
discovered. The story is similar for some other mutations: there are cases
where a particular gene is described as an 'autism gene', only for later
studies to find that individuals with the same mutation may have attention
deficit hyperactivity disorder, epilepsy, language disorder, intellectual
disability – or indeed, no diagnosis at all.
For instance, Niarchou et al (2019) published a study of a sample of children
with deletion or duplication at a site on chromosome 16 (16p11.2), predicting
that the deletion would be associated with autism, and duplication with autism
or schizophrenia. In fact, they found that the commonest diagnosis with both
conditions was attention deficit hyperactivity disorder, though rates of
intellectual disability and autism were also increased. 52% of the cases with
deletion and 37% of those with a duplication had no psychiatric diagnosis.
There are several
ways in which such variation in outcomes might arise. First, the impact of a
particular mutation may depend on the genetic background – for instance, if the
person has another mutation affecting the same neural circuits, this 'double
hit' may have a severe impact, whereas either mutation alone would be
innocuous. A second possibility is that there may be environmental factors that
affect outcomes. There is a lot of interest in this idea because it opens up
potential for interventions. The third option, though, is the one that is often
overlooked: the possibility that differences in outcomes are the consequence of
random factors early in neurodevelopment, which then have cascading effects
that amplify initial minor differences (see points 2 and 3).
6.
A mutation may create general developmental instability
Many geneticists
think of effects of mutations in terms of the functional impact on particular
developmental processes. In the case of neurodevelopment, there is interest in
how genes affect processes such as neuronal migration (movement of cells to
their final position in the brain), synaptic connectivity (affecting communication
between cells) or myelination (formation of white matter sheaths around nerve
fibres). Mitchell suggests, however,
that mutations may have more general effects, simply making the brain less able
to adapt to disruptive processes in development. Many of us learn about genetics in the
context of conditions like Huntington's disease, where a specific mutation
leads to a recognisable syndrome. However, for many neurodevelopmental
conditions, the impact of a mutation is to increase the variation in
outcomes. This makes sense of the
observations outlined in point 5: a mutation can be associated with a range of
developmental disabilities, but with different conditions in different people.
7.
Sex differences in risk for neurodevelopmental disorders have genetic origins
There has been
so much exaggeration and bad science in research on sex differences in the
brain, that it has become popular to either deny their existence, or attribute
them to sex differences in environmental experiences of males and females. Mitchell
has no time for such arguments. There is ample evidence from animal studies
that both genes and hormones affect neurodevelopment: why should humans be any
different? But he adds two riders: first, although systematic sex differences
can be found in human brains, they are small enough to be swamped by individual
variation within each sex. So if you want to know about the brain of an
individual, their sex would not tell you very much. And second, different does
not mean inferior.
Mitchell argues
that brain development is more variable in males than females and he cites
evidence that, while average ability scores are similar for males and females, males
show more variation and are overrepresented at the extremes of distributions of
ability. The over-representation at the lower end has been recognised for many
years and is at least partly explicable in terms of how the sex chromosomes
operate. Many syndromes of intellectual disability are X-linked, which means
they are caused by a mutation of large effect on the X chromosome. The mother
of an affected boy often carries the same mutation but shows no impairment:
this is because she has two X chromosomes, and the effect of a mutation on one
of them is compensated for by the unaffected chromosome. The boy has XY
chromosome constitution, with the Y being a small chromosome with few genes on
it, and so the full impact of an X-linked mutation will be seen. Having said
that, many conditions with a male preponderance, such as autism and
developmental language disorder, do not
appear to involve X-linked genes, and some disorders, such as depression, are
more common in females, so there is still much we need to explain. Mitchell's
point is that we won't make progress in doing so by denying a role for sex
chromosomes or hormones in neurodevelopment.
Mitchell moves
into much more controversial territory in describing studies showing
over-representation of males at the other end of the ability distribution: e.g.
in people with extraordinary skills in mathematics. That is much harder to
account for in terms of his own account of genetic mechanisms, which questions
the existence of genetic variants associated with high ability. I have not
followed that literature closely enough to know how solid the evidence of male
over-representation is, but assuming it is reliable, I'd like to see studies
that looked more broadly at other aspects of cognition of males who had
spectacular ability in domains such as maths or chess. The question is how to
reconcile such findings with Mitchell's
position – which he summarises rather bluntly by saying there are no genes for
intelligence, only genes for stupidity. He does suggest that greater
developmental instability in males might lead to some cases of extremely
high-functioning, but that is at odds with his general view that instability
generally leads to deficits, not strengths. I'd be interested in studies of
these exceptional high achievers to look at their skills across a wider range
of domains. Is it really the case that males at the very top end of the IQ
distribution are uniformly good at everything, or are there compensating
deficits? It's easy to think of anecdotal examples of geniuses who were lacking
in what we might term social intelligence, and whose ability to flourish was limited
to a very restricted ecological niche in the groves of academe. Maybe these are
people whose specific focus on certain topics would have been detrimental to
reproductive fitness in our ancestors, but who can thrive in modern society where
people are able to pursue exceptionally narrow interests. If so, we can predict that at the point in the
distribution where exceptional ability has a strong male bias, we should expect
to find that the skill is highly specific and accompanied by limitations in
other domains of cognition or behaviour.
8.
It is difficult to distinguish polygenic effects from genetic heterogeneity
Way back in the
early 1900s, there was criticism of Mendelian genetics because it maintained
that genetic material was transmitted in quanta, and so it seemed not to be
able to explain inheritance of continuous traits such as height, where the
child's phenotype may be intermediate between those of parents. Reconciliation
of these positions was achieved by Ronald Fisher, who showed that if a
phenotype was influenced by the combined impact of many genes of small effect,
we would expect correlations between related individuals in continuous traits. This
polygenic view of inheritance is thought to apply to many common traits and
disorders. If so, then the best way to discover genetic bases for disorder is
not to hunt through the genome looking for rare mutations, but rather to search
for common variants of small effect. The problem with that is that on the one
hand it requires enormous samples to identify tiny effects, and on the other
it's easy to find false positive associations. The method of Genome Wide Association
has been developed to address these issues, and has had some success in
identifying genetic variants that have little effect in isolation, but which in
aggregate play a role in causing disorder.
Mitchell,
however, has a rather different approach. At a time when most geneticists were
embracing the idea that conditions such as schizophrenia and autism were the
result of the combined effect of the tiny influence of numerous common genetic
variants, Mitchell (2012) argued for another possibility - that we may be
dealing with rare variants of large effect, which differ from family to family.
In Innate, he suggests it is a mistake to reduce this to an either/or question:
a person's polygenic background may establish a degree of risk for disorder,
with specific mutations then determining how far that risk is manifest.
This is not just
an academic debate: it has implications for how we invest in science, and for
clinical applications of genetics. Genome-wide association studies need
enormous samples, and collection, analysis and storage of data is expensive.
There have been repeated criticisms that the yield of positive findings has
been low and they have not given good value for money. In particular, it's been
noted that the effects of individual genetic variants are minuscule, can only
be detected in enormous samples, and throw little light on underlying
mechanisms (Turkheimer, 2012, 2016). This has led to a sense of gloom that this
line of work is unlikely to provide any explanations of disorder or improvements
in treatment.
An approach that
is currently in vogue is to derive a Polygenic Risk Score, which is based on all
the genetic variants associated with a condition, weighted by the strength of
association. This can give some probabilistic information about likelihood of a
specific phenotype, but for cognitive and behavioural phenotypes, the level of
prediction is not impressive. The more
data is obtained on enormous samples, the better the prediction becomes, and
some scientists predict that Polygenic Risk Scores will become accurate enough
to be used in personalised medicine or psychology. Others, though, have serious
doubts. A thoughtful account of the pros
and cons of Polygenic Risk Scores is found in an interview that Ed Yong (2018)
had with Daniel Benjamin, one of the authors of a recent study reporting on
Polygenic Risk Scores for educational attainment (Lee et al, 2018). Benjamin
suggested that predicting educational attainment from genes is a non-starter,
because prediction for individuals is very weak. But he suggested that the
research has value as we can use a Polygenic Risk Score as a covariate to
control for genetic variation when studying the impact of environmental
interventions. However, this depends on results generalising to other samples.
It is noteworthy that when the Polygenic Risk Score for educational attainment was
tested for its ability to explain within-family variation (in siblings), its
predictive power dropped (Lee et al, 2018).
It is often
argued that knowledge of genetic variants contributing to a Polygenic Risk
Score will help identify the functions controlled by the relevant genes, which
may lead to new discoveries in developmental neurobiology and drug design.
However, others would question whether Polygenetic Risk Scores have the
necessary biological specificity to fulfil this promise (Reimers et al, 2018). Furthermore,
recent papers have raised concerns that population stratification means that
Polygenetic Risk Scores may give misleading results: for instance, we might be
able to find a group of SNPs predictive of 'chopsticks-eating skills', but this
would just be based on genetic variants that happen to differ between ethnic
groups that do and don't eat with chopsticks (Barton et al, 2019).
I think Mitchell
would in any case regard the quest for Polygenic Risk Scores as a distraction
from other more promising approaches that focus on finding rare variants of big
effect. Rather than investing in analyses that require huge amounts of big data
to detect marginal associations between phenotypes and SNPs, his view is that we
will make most progress by studying the consequences of mutations. The tussle
between these viewpoints is reflected in two articles that appeared at the end
of 2017. Boyle, Li, and Pritchard (2017) queried some of the assumptions behind
genome-wide association studies, and suggested that most progress will occur if
we focus on detecting rare variants that may help understand the biological
pathways involved in disorder. Wray et al (2017) countered by arguing that
while exploring for de novo mutations is important for understanding severe
childhood disorders, this approach is unlikely to be cost-effective when
dealing with common diseases, where genome-wide associations with enormous
samples is the optimal strategy. In fact, the positions of these authors are not
diametrically opposed: it is rather a question of which approach should be
given most resources. The discussion involves more than just scientific disagreement:
reputations and large amounts of research funding are at stake.
Ethical implications
And so we come
to the ethical issues around modern genetics. I hope I have at least convinced
readers that in order to have a rational analysis of moral questions in this
field, one needs to move away from simplistic ideas of the genome as some kind
of blueprint that determines brain structure and function. Ethical issues which
are quite hard enough when things are deterministic are given a whole new layer
of complexity when we realise that there's a large contribution of chance in
most relationships between genes and neurodevelopment.
But let's start
with the simpler and more straightforward case where you can reliably predict
how a person will turn out from knowledge of their genetic constitution. There
are then two problematic issues to grapple with: 1) if you have knowledge of
genetic constitution prenatally, under what situations would you consider using
the information to select an embryo or terminate a pregnancy? 2) if a person
with a genetically-determined condition exists, should they be treated
differently on the basis of that condition?
Some religions
bypass the first question altogether, by arguing that it is never acceptable to
terminate a pregnancy. But, if we put absolutist positions to one side, I
suspect most people would give a range of answers to question 1, depending on
what the impact of the genetic condition is:
termination may be judged acceptable or even desirable if there are such
severe impacts on the developing brain that the infant would be unlikely to
survive into childhood, be in a great deal of distress or pain, or be severely
mentally impaired. At the other extreme, terminating a pregnancy because a
person lacks a Y chromosome seems highly unethical to many people, yet this practice
is legal in some countries, and widely adopted even when it is not (Hvistendahl,
2011). These polarised scenarios may seem relatively straightforward, but there
are numerous challenges because there will always be cases that fall between
these extremes.
It is impossible
to ignore the role of social factors in our judgements. Many hearing people are
shocked when they discover that some Deaf parents want to use reproductive
technologies to select for Deafness in their child (Mand et al., 2009), but those
who wish to adopt such a practice argue that Deafness is a cultural difference
rather than a disability.
Now let's add
chance into the mix. Suppose you have a genetic condition that makes it more
likely that a child will have learning difficulties or behaviour problems, but
the range of outcomes is substantial; the typical outcome is mild educational
difficulties, and many children do perfectly well. This is exactly the dilemma facing parents of
children who are found on prenatal screening to have an extra X or Y
chromosome. In many countries parents may
be offered a termination of pregnancy in such cases, but it is clear that
whether or not they decide to continue with the pregnancy depends on what they
are told about potential outcomes (Jeon, Chen, & Goodson, 2012).
Like Kevin
Mitchell, I don't have easy solutions to such dilemmas, but like him, I think
that we need to anticipate that such thorny ethical questions are likely to
increase as our knowledge of genetics expands – with many if not most genetic
influences being probabilistic rather than deterministic. The science fiction
film Gattaca portrays a chilling vision of a world where genetic testing at
birth is used to identify elite individuals who will have the opportunity to be
astronauts, leaving those with less optimal alleles to do menial work – even
though prediction is only probabilistic, and those with 'invalid' genomes may
have desirable traits that were not screened for. The Gattaca vision is bleak
not just because of the evident unfairness of using genetic screening to
allocate resources to people, but because a world inhabited by a set of clones,
selected for perfection on a handful of traits, could wipe out the diversity
that makes us such a successful species.
There's another
whole set of ethical issues that have to do with how we treat people who are
known to have genetic differences. Suppose we find that someone standing trial
has a genetic mutation that is known to be associated with aggressive
outbursts. Should this genetic information be used in mitigation for criminal
behaviour? Some might say this would be tantamount to letting a criminal get
away with antisocial behaviour, whereas others may regard it as unethical to
withhold this information from the court. The problem, again, becomes
particularly thorny because association between genetic variation and
aggression is always probabilistic. Is
someone with a genetic variant that confers a 50% increase in risk of
aggression less guilty than someone with a different variant that makes then
50% less likely to be aggressive? Of course, it could be argued that the most
reliable genetic predictor of criminality is having a Y chromosome, but we do
not therefore treat male criminals more leniently than females. Rather, we recognise that genetic constitution
is but one aspect of an individual's make-up, and that factors that lead a
person to commit a crime go far beyond their DNA sequence.
As we gain ever
more knowledge of genetics, the ethical challenges raised by our ability to
detect and manipulate genetic variation need to be confronted. To do that we
need an up-to-date and nuanced understanding of the ways in which genes
influence neurodevelopment and ultimately affect behaviour. Innate provides
exactly that.
Acknowledgement
I thank David
Didau for comments on a draft version of this review, and in particular for
introducing me to Gattaca.
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