Monday 30 May 2011

Are our ‘gold standard’ autism diagnostic instruments fit for purpose?

In 1985, Simon Baron-Cohen, Alan Leslie and Uta Frith published a landmark paper entitled “Does the autistic child have a theory of mind?” It described a small study that Simon Baron-Cohen completed for his doctoral thesis which, according to Google Scholar, has been cited 2800 times. If the same paper were submitted for publication today, most journals would reject it. Why? The paper stated: “The 20 autistic children had been diagnosed according to established criteria (Rutter, 1978)”. Nowadays this would be deemed inadequate. Many editors and reviewers insist that studies of autism use two diagnostic procedures, the Autism Diagnostic Interview - Revised (ADI-R) and the Autism Diagnostic Observation Schedule - Generic (ADOS-G). According to the NIH National Database for Autism Research, requiring people to use these “gold standard” assessments will “help accelerate scientific discovery”. But use of these instruments adds hugely to the time and money costs of research. Small-scale studies of autism by PhD students have become nonviable, and large-scale genetic and epidemiological studies are bogged down by the need to spend hours just establishing the phenotype for each case. Researchers from countries where ADI-R and ADOS-G are not available are at a serious disadvantage. And, as I shall argue, the end result is not a clearcut diagnosis.

Autism has three key defining features: impairments in communication, social interaction and behavioural repertoire. The latter encompasses both repetitive behaviours such as stereotyped movements, and restricted interests, e.g., an obsessive fascination with aeroplanes. After autism was first described by Leo Kanner in 1943, the diagnosis quickly became popular, but there were concerns that it was over-used. There was a clear need to translate Kanner’s clinical descriptions into more objective diagnostic criteria. The first step was to develop checklists of symptoms, and these were included for the first time in the 1980 version of the Diagnostic and Statistical Manual of the American Psychiatric Association, DSM-III. However, this still left room for uncertainty: clinicians might, for instance, disagree about interpretation of terms such as: “Pervasive lack of responsiveness to other people”.

The Autism Diagnostic Interview (ADI) was designed to address this problem. It was first published in 1989, with a revised form, ADI-R, appearing in 1994. The ADI-R typically takes 1.5 to 3 hours to administer, and covers all the symptoms of autism and related conditions. Items are coded on a 4-point scale, from 0 (absent) to 3 (present in extreme form). The scores from a subset of items are then combined to give a total for each of the three autism domains, and a diagnosis of autism is given if scores on all three domains are above cutoffs, and onset was evident by 36 months. Validation of the ADI-R was carried out by comparing scores for 25 preschool children who had clinically diagnosed autism and 25 nonautistic children with intellectual retardation or language impairment.

Right from the outset, however, there was concern that diagnosis of autism should not be made on the basis of parental report alone. Some parents are poor informants. On the one hand, they may fail to remember key features of their child’s behaviour; on the other hand, their memories may have been coloured by reading about autism. Parental report therefore needs to be backed up by observation of the child. The Autism Diagnostic Observation Schedule (ADOS), published in 1989, was designed for this purpose. It exposes the child to a range of situations designed to elicit autistic features, and particular behaviours, such as eye contact, are then coded by a trained examiner. ADOS-G, a generic version, was published in 2000, and covers a wide age range, from toddlers through to adults.

ADI-R and ADOS-G quickly became the instruments of choice for autism diagnosis. It was generally appreciated that if we use standard instruments, researchers and clinicians should be able to communicate about autism with a fair degree of confidence that they are referring to individuals who meet the same diagnostic criteria.

There is, however, a downside. ADI-R and ADOS-G were designed to be comprehensive, but they were not designed to be efficient. As noted above, ADI-R takes up to 3 hours to administer and score. ADOS-G takes about 45 minutes. In addition, testers must be trained to use each instrument, and it may take some months to find a place on a training course. Each course lasts around one week, and the trainee then has to do further assessments which are recorded and sent for validation by experts. This process can easily add another 6 months. For anyone under time pressure, such as a doctoral student or grant-holder with research assistants on fixed term contracts, the training requirements can make a study impossible to do. Inclusion of both ADI-R and ADOS-G in a test protocol can double or treble the duration of a project, especially where it is necessary to travel to interview parents who may be available only during anti-social hours.

So, does autism diagnosis need to involve such a lengthy process? This was a question I was prompted to consider when I was asked to speak at a roundtable debate on diagnostic tools for autism at the International Meeting For Autism Research (IMFAR) in London in 2008. I concluded that the answer is almost certainly no. As Matson et al (2007) put it: “Some measures emphasize the fact that they are very detailed. We would argue that detail equals time. From a pragmatic perspective, our view is that a major priority should be to develop the balance between obtaining relevant information to make a diagnosis, while parsing out items that do not enhance that goal”. (p. 49). I was surprised when I first undertook ADI-R training to find that the interview included many items that did not feature in the final algorithm. When I (and others) queried this, we were told that the interview worked in its entirety, and to pull out selected items would disrupt a natural flow. Also, the non-algorithm items might be useful for diagnosing conditions other than autism. While both points may be important in a clinical setting, they have much less force for the poor graduate student who is doing a doctorate on, say, perceptual processing in autism, and only wants to use the ADI-R to confirm a diagnosis that has already been made by a clinician. There was a short form, I was told, but it was not recommended and should only be used by clinicians, not researchers. I was even more surprised to find how the algorithm was devised. I was familiar with discriminant function analysis, whereby you take a set of scores on two (or more) groups, and find the best weighted sum of scores to discriminate the groups. You can then use the correlations between items to drop items from the algorithm successively until you get to the point where accuracy of diagnostic assignment declines if further items are dropped. I had assumed that this kind of statistical data reduction had been used to identify the optimal set of items for identifying autism. I was wrong. It seemed that the items were selected on the basis of their match to clinical descriptions of autism, and no attempt had been made to test the efficiency of the algorithm by dropping items.

There is good reason to believe that a much shorter and simpler procedure would be feasible. In 1999, a study was published comparing diagnostic accuracy of the ADI with a 40-item screening questionnaire. The accuracy of the questionnaire was as good as the interview. My impression is that this finding did not lead to rejoicing at the prospect of a shorter diagnostic procedure, but rather alarm that diagnosis could be reduced to a trivial box-checking exercise. While I have some sympathy with that view, I feel these results should have made the researchers pause to consider whether a much shorter and more efficient approach to diagnosis might be feasible.

But the problems get worse. As Jon Brock recently pointed out on his blog, Kanner’s view of autism as a distinct syndrome is no longer accepted. It’s clear that autism symptoms can occur in milder form, and that they do not necessarily all go together. The broader term ‘Autism Spectrum Disorder’ (ASD) is nowadays used to encompass these cases. The schematic illustration in Figure 1 illustrates the diagnostic problem: one has to decide where to place boundaries on the figure to distinguish ASD from normality, when in reality, all three domains of the autism triad of symptoms shade into normality, with no sharp cutoffs. The ADI-R algorithm specifies whether or not you have autism, and does not give cutoffs for milder forms of ASD. The ADOS-G does have cutoffs for milder forms, but is inappropriate for detailed assessment of repetitive behaviours/restricted interests, so it is not watertight. This means that, when it comes to diagnosis of ASD, a great deal is left to clinician’s judgements. These, rather, than algorithm scores, are used to arrive at diagnoses.

Figure 1: Schematic of autism as a spectrum disorder: Circle correspond to areas of deficit, red = social impairment, blue = communication difficulties; yellow = repetitive behaviour/restricted interests, with depth of colour indicating severity of impairment. Individuals with all three features (centre of the figure) meet full diagnostic critieria for autism, but those falling outside this region, who have milder or partial difficulties are candidates for a diagnosis of autism spectrum disorder. Note, however, there is no clearcut boundary between autistic spectrum disorder and normal variation.
There were quite a few researchers at the IMFAR meeting who complained that their papers were rejected by journals because they relied on a diagnosis made by an expert, rather than ADI-R and ADOS-G. They would be baffled to see that several recent state-of-the-art epidemiological studies use consensus judgement by expert clinicians to make their diagnoses - and these diagnoses don’t necessarily agree with ADI-R and ADOS-G. So, for instance, Baird et al had 81 cases who met a consensus clinical diagnosis of childhood autism, but only 53 (65%) were classified as autistic by the algorithms of both the ADOS-G and the ADI-R. They also identified 77 children with consensus diagnosis of ‘other ASD’ of whom 69% met criteria for autism on the ADI-R, and 38% met cutoff for PDD or autism on the ADOS. On the ADOS-G, 10% of non-autistic children scored above cutoff for either ASD or autism. This fits my experience: high scores can reflect lack of engagement, shyness, or language difficulties. Similarly, Baron-Cohen et al identified four cases of autism and seven with other ASDs in a population screening of children aged 5 to 9 years in Cambridgeshire. All the autism cases met autism criteria on both ADI-R and ADOS-G. Of the other ASD cases, five met criteria for autism on ADI-R but not ADOS-G, and two did not meet criteria for autism or ASD on either instrument. In describing these findings, I am not criticising the authors of these studies, whose methods were transparently reported and are consistent with practice as it has evolved in the field. But it is ironic that we seem to have come full circle. ADI-R and ADOS-G were developed to make diagnosis more objective, but because they aren’t geared up to diagnose ASD, we are thrown back on ‘expert clinical opinion’. This is far from reassuring, given that a recent study reported that, after months of training, researchers agreed well on scoring standardized instruments, but “consistent differences between sites in overall clinical impression were reported”.

My own recommendation is for a two-step procedure. The first step would involve a much briefer version of the ADI-R, which would be designed to pick up clear-cut cases of autism that everyone would agree on and distinguish them from clearly non-autistic cases. It’s an empirical question, but I suspect that if we were to do a stepwise discriminant analysis to identify a minimum set of diagnostic items, this would be considerably shorter than the current set used in ADI-R. The interview may then need redesigning so that it still flows fluently and follows a logical course, but this should not be impossible. In clinical settings, those identified might require further direct assessment to confirm diagnosis and identify specific needs, but this would not be necessary for determining who should be included in a research study. This would leave a group of children in whom autism was suspected but not confirmed. The question here is whether we will ever arrive at a diagnostic procedure that will clearly separate such children into ASD and non-ASD. I was involved in a study with just such a group of ‘marginal’ cases a few years ago, where we administered ADI-R and ADOS-G. The results were all over the place: some children looked autistic on ADI-R and not on ADOS-G and others showed the opposite pattern. Some had evidence of marked change in behaviour between preschool and school-age years. When I asked an autism expert how such cases should be categorised, he suggested I get an expert clinical opinion. Yet expert clinical opinion is not seen as adequate by many journal editors! And there is documented evidence that even experienced clinicians will disagree in cases where the child has a confusing pattern of symptoms, and that expert diagnoses are not stable over time. My suggestion is that in our current state of knowledge it makes no sense to try and get reliable cutoffs for identifying ASD. Instead we should aim to assess the nature and degree of impairments in different domains. Assessments such as the 3Di or Social Responsiveness Scale, which treat autistic features as dimensions rather than all-or-none symptoms, seem better suited to this task than the existing gold standards.

Finally, I must emphasise that, although I think the ADI-R and ADOS-G are not optimal for diagnosing ASD for research purposes, they nevertheless have value. They distill a great deal of clinical wisdom in the assessment process, and are cleverly crafted to pinpoint the key features of autism. Anyone who undergoes training in their use will come away with a far greater understanding of autism than they had when they started. However, these instruments are not well suited for addressing the NIH aim of “accelerating scientific discovery”. In research contexts they have the opposite effect, by making researchers go through an unnecessarily long and complex diagnostic process which does not yield suitable quantitative results for assessing the dimensional aspect of ASD.

Rondeau E, Klein LS, Masse A, Bodeau N, Cohen D, & Guilé JM (2010). Is Pervasive Developmental Disorder Not Otherwise Specified Less Stable Than Autistic Disorder? A Meta-Analysis. Journal of autism and developmental disorders PMID: 21153874

Wednesday 25 May 2011

Scientific communication: the Comment option

1. Think of something interesting to say

2. Hit the link saying ‘comment’.

3. Find you have to register. Enter first name, surname, title, job description, qualifiations, place of work, phone number, fax number, address.

4. Spend several minutes looking for England, then Great Britain on the drop-down list, before hitting on United Kingdom. Press enter, while wondering how often someone from Azerbaijan makes a comment.

4. Back to step 3 because failed to enter a zip code in the correct format.

5. Realise that the special security software that was installed to prevent unauthorised access to the computer has barred interaction with the site, and everything you have entered has been lost.

6. Select ‘allow this site’ in the security software.

7. Back to step 3.

8. Select a password.

9. Retype the password.

10. Retyped password fails to match password. Back to step 8.

11. Hooray! All entered.

12. Try to log in. System tells you someone with this email address has already registered with a different password.

13. Alarm husband with sudden outburst of profanities and table thumping.

14. Try to guess password.

15. Fail.

16. Loop back to step 14 several times.

17. Request new password.

18. Open email to look for message re new password.

19. No sign of email re password. Get distracted by other emails. Ponder on why as a neuropsychologist have been invited to contribute an article to Journal of Plant Membranes.

20. Delete messages with header ‘Dear Friend in Christ’. Don’t they realise I’m an atheist?

21. Password message appears in Inbox.

22. Back to login screen.

23. Login, only to find there is a saved password already.

24. Use of saved password gives error message.

25. Relogin with new password. Yes!

26. Search for original site for comments. Can’t find it.

27. Back to twitter to find the address of the original article that I wanted to comment on.

28. Find the article.

29. Hit the comment button.

30. Now what was it I wanted to say?

Monday 16 May 2011

Autism diagnosis in cultural context

A review of Isabel’s World by Roy Richard Grinker

In 1993, when Roy Grinker’s daughter, Isabel, was two years old she did not talk or gesture, flapped her hands and arms, and did not make eye contact. At 32 months, she had mastered about 70 words, which she spoke clearly, but all were nouns and the list did not include ‘mommy’ or ‘daddy’. She didn’t say ‘yes’ or ‘no’ and pulled someone to the refrigerator when she was hungry. Nowadays it’s hard to imagine a paediatrician would fail to recognise classic symptoms of autism, but for the Grinkers the process of getting a diagnosis was protracted and painful. At best they met with ignorance, and at worst with professionals who were imbued with the ideas of Bruno Bettelheim and attributed Isabel’s problems to the fact that her mother went out to work. Once a diagnosis was obtained, the Grinkers still had to fight for appropriate educational provision. They came up against people who had no experience of autism and were unwilling or unable to engage with Isabel. Gradually, though, the battle was won. Isabel, whose high nonverbal ability was eventually recognised, was able to attend a mainstream school with support. Now in her teens, she still has major problems with communication and social interaction, and her parents accept she will not able to live independently. She has, however, found a niche in her community where she has friends, can enjoy her interests in music and animals, and is accepted for who she is.

Grinker’s book is more than a parent’s first-hand account of his daughter’s autism: it is also influenced by the fact that he is a cultural anthropologist, with a special interest in attitudes to health and disability in different parts of the world. He uses his professional insights to comment on two related issues: the rise in autism diagnosis in the USA, and attitudes to autism in other cultures, particularly France, Korea, South Africa and India.

Figure 1
The rise in autism diagnosis is a hotly debated topic. In general, there is agreement about the facts: the number of children receiving an autism diagnosis in the USA has risen sharply since the 1970s. The data in Figure 1 were taken from a website relating to the Individuals with Disability Education Act (IDEA), and they show a more than four-fold increase in children identified with autism in the ten year period between 1997 and 2006. I have previously noted in a PLOS One article that research on autism, as assessed by funding and publications, has skyrocketed over the same period.

The debate is over the reason for the increase: is it due to some environmental factor that causes autism, or can it be explained simply in terms of changes in diagnostic criteria and related factors? Grinker comes down solidly in favour of the latter explanation, and a substantial part of the book is devoted to tracing the history of autism diagnosis and related socio-cultural factors. A major turning point was the publication in 1987 of the third revision of the diagnostic and statistical manual of the American Psychiatric Association, DSM-III-R. Grinker cites a study of 194 children suspected of autism which found that whereas 51% met criteria on DSM-III, 91% met criteria on DSM-III-R. He also reports a typographic error that was made in the publication of DSM-IV in 1994 that led to the ‘autism spectrum’ disorder of PDDNOS being defined on the basis of a child having impairments in social interaction or verbal/nonverbal communication skills, when it should have required impairment in both domains.

Grinker tackles a question often asked by those who think the autism epidemic is genuine: if it’s just due to a change in diagnostic practices, where were all the undiagnosed autistic children in the past? Surely we would have noticed them? On the basis of a follow-up of a small sample of UK children with severe language impairments, our group found cases who would now be regarded as unambiguously autistic, but who were diagnosed as language-impaired when they were seen in the 1980s, prior to DSM-IIIR. So are we just engaging in 'diagnostic substitution', whereby the same child who is now regarded as autistic was previously given a different label? If so, we'd expect to see that as autism diagnosis goes up, language disorder diagnosis goes down. This would be consistent with an analysis of doctor's records in the UK, which found that the proportion of children with diagnoses such as speech/language disorder went down over the same period as autism diagnoses went up. In the IDEA data, however, I found no evidence for such a process: over the 1997-2006 time period, there's actually a slight increase in diagnoses of speech/language diagnoses. Grinker, however, suggests that, in the US, children with autism would, in the past, often have been diagnosed with mental retardation. Consistent with this, the IDEA data do show a corresponding decrease in diagnosis of mental retardation over the same time period as autism diagnoses increase (see Figure 1).

Another point stressed by Grinker is that a diagnosis of autism has consequences for the child’s access to services. A diagnosis may get your child Medicaid waivers so that they can receive a host of interventions at reduced cost. Grinker describes how he lost hundreds of dollars because a speech pathologist who worked with Isabel submitted the bills under the diagnosis of “Mixed Receptive-Expressive Language Disorder”. When the diagnosis was changed to autism, the bills were automatically reimbursed. There is therefore considerable pressure on paediatricians to give a diagnosis of autism rather than some other condition.

The implications of an autism diagnosis for intervention is very different in some other countries. In France, where the legacy of psychoanalysis has been long-lasting, autism is seen as a psychodynamic disorder and there is little educational provision for affected children. In India, the diagnosis is seldom made, even if doctors recognise autism, because there seems no point: there are no facilities for affected children. Grinker has particular interest in South Korea, his wife’s birthplace, where the stigma attached to disability is so great that children with autism will be hidden away, because otherwise their siblings’ marriage prospects will be blighted. Education is seen as the route to success in Korea, and it is normal for children to spend hours after school being coached; a child who struggles at school or who does not conform to expected standards of behaviour brings shame to the family.

Grinker’s book shows that the impact of labels is immense, even if they are worryingly arbitrary. It seems crazy, for instance, that a child with educational difficulties will get insurance cover for interventions, or special help at school on the basis of a diagnosis of autism, whereas a child with equally serious needs who is diagnosed with mental retardation or receptive language disorder gets nothing. But on the positive side, he notes how the growing awareness and acceptance of autism has brought huge benefits to children and their families. Just as in Korea, it used to be common for people in the US to be baffled or even frightened by autism, and for schools to shun children with any kind of disability. The landscape has changed massively over the past twenty years. Grinker notes how Isabel’s schoolmates look out for her, and how her presence in a mainstream classroom has beneficial effects on all pupils. Cultural stereotypes are being challenged, so much so that it is no longer regarded as amazing if a university student tells you they have autism.

This brings Grinker to a final point: which kinds of cultural setting are most supportive for people with autism? He presents some fascinating data showing that rural communities are usually far more positive than urban ones for people with all kinds of disability. In a small community, everyone will know the person with a disability, and see them as an individual. In the context of neurodevelopmental disorders in general, I’ve long been advocating that we need an educational system that doesn’t just try to ‘fix’ children, but rather identifies activities they enjoy and can do well, as a basis for finding them a niche in society.  This view is cogently expressed by Grincher “… in order to help people with autism we don’t always need to fully mainstream them, or pretend that they are not different, and we don’t need to simply reduce stigma. Rather, we need to provide roles in our communities for pepole with autism, some of which they may, in fact, be able to perform better than anyone else…” (p. 342).

Bishop, D., Whitehouse, A., Watt, H., & Line, E. (2008). Autism and diagnostic substitution: evidence from a study of adults with a history of developmental language disorder Developmental Medicine & Child Neurology, 50 (5), 341-345 DOI: 10.1111/j.1469-8749.2008.02057.x

Wednesday 11 May 2011

The X and Y of sex differences

Why and how are men and women different? My interest in this topic is fuelled by my research on neurodevelopmental disorders of language and literacy that typically are much more common in males than females. In this post, I am ranging far from my comfort zone in psychology to discuss what we know from a genetic perspective. My inspiration was a review in Trends in Genetics by Wijchers and Festenstein called “Epigenetic regulation of autosomal gene expression by sex chromosomes”. Despite the authors' sterling efforts to explain the topic clearly, I suspect their paper will be incomprehensible to those without a background in genetics, so I'll summarise the main points - with apologies to the authors if I over-simplify or mislead.

So, to start with, some basic facts about chromosomes in humans:
•    We have 23 pairs of chromosomes, one member of each pair inherited from the father, and the other from the mother.
•    For chromosome pairs 1-22, the autosomes, there is no difference between males and females.
•    Chromosome pair 23 is radically different for males and females: females have two X chromosomes, whereas males have an X chromosome paired with a much smaller Y chromosome
•    The Y chromosome carries a male-determining gene, SRY, which causes testes to develop. The testes produce male hormones which influence body development to produce a male.
•    The X chromosome contains over 1000 genes, compared to 78 genes on the Y chromosome.
•    In females, only one X chromosome is active. The other is inactivated early in development by a process called methylation. This leads to the DNA being formed into a tight package (heterochromatin), so genes from this chromosome do not get expressed. X-inactivation randomly affects one member of the X-chromosome pair early in embryonic development, and all cells formed by division of an original cell will have the same activation status. The patches of orange and black fur on a calico cat arise when a female has different versions of a gene for coat colour on the two X chromosomes, so patches of orange and black fur occur at random.
•    In both X and Y chromosomes, there is a region at the tip of the chromosome called the pseudoautosomal region, which behaves like an autosome, i.e., it contains homologous genes on X and Y chromosomes, which are not inactivated, and which recombine during the formation of sperm and eggs.
•    In addition, a proportion of genes on the X chromosome (estimated around 20%) escape X-inactivation, despite being outside the pseudoautosomal region.

These basic facts are summarised in Figure 1. Genes are symbolised by red dots, grey shading denotes an inactivated region, and yellow is the pseudoautosomal region.

Figure 1
Note that because (a) the male Y chromosome has few genes on it and (b) one X chromosome is largely inactivated in females, normal males (XY) and females (XX) are quite similar in terms of sex chromosome function: i.e., most of the genes that are expressed will come from a single active X chromosome.
Studies of mice and other species have, however, demonstrated differences in gene expression between males and females, and these affect tissues other than the sex organs, including the brain. Most of these sex differences are small, and it is usually assumed that they are the result of hormonal influences. Thus the causal chain would be that SRY causes the testes to develop, the testes generate male hormones, and those hormones affect how genes are expressed throughout the body.

You can do all kinds of things to mice that you wouldn't want to do to humans. For a start you can castrate them. You can then dissociate the effect of the XY genotype from the effect of circulating hormones. When this is done, many of the sex differences in gene expression disappear, confirming the importance of hormones.
There's some evidence, though, that this isn't the whole story. For a start, it is possible to find genes that are differently expressed in males and females very early in development, before the sex organs are formed. These differences can't be due to circulating hormones. You can go further and create genetically modified mice in which chromosome status and biological sex are dissociated.  For instance, if Sry (the mouse version of SRY) is deleted from the Y chromosome, you end up with a biologically female mouse with XY chromosome constitution. Or an autosomal Sry transgene can be added to a female to give a male mouse with XX constitution. A recent study using this approach showed that there are hundreds of mouse genes that are differently expressed in normal XX females vs. XY females, or in normal XY males vs. XX males. For these genes, there seems to be a direct effect of the  X or Y chromosome on gene expression, which isn't due to hormonal differences in males and females.

Wijchers and Festenstein consider four possible mechanisms for such effects.
1. SRY has long been known to be important for development of testes, but that does not rule out a direct role of this gene in influencing development of other organs. An in mice there is indeed some evidence for a direct effect of Sry on neuronal development.
2. Imprinting of genes on the X chromosome. This is where it starts to get really complicated. We have already noted how genes on the X chromosome can be inactivated. I've told you that X-inactivation occurs at random, as illustrated by the calico cat. However, there's a mechanism known as imprinting whereby expression of a gene depends on whether the gene is inherited from the father or the mother. Imprinting was originally described for genes on the autosomes, but there's considerable interest in the idea of imprinting affecting genes on the X chromosome, as this could lead to sex differences. The easiest way to explain this is by a mouse experiment. It's possible to make a genetically modified mouse with a single X chromosome. The interest is then in whether the single X chromosome comes from the mother or the father. And indeed, there's growing evidence for differences in brain development and cognitive function between  genetically modified mice with a single maternal or paternal X chromosome: i.e., evidence of imprinting. Now this has implications for sex differences in normal, unmodified mice. XY male mice have just one X chromosome, which always comes from the mother, and will always be expressed. But XX female mice have a mixture of active maternal and paternal X-chromosomes. Any effect that is specific to a paternally-derived X-chromosome will therefore only be seen in females.
What about humans? Here we can study girls with Turner syndrome, a condition in which there is one rather than two X chromosomes. Skuse and colleagues found differences in cognition, especially social functioning between girls with a single maternal X vs. those with a single paternal X. There are few studies of this kind, because it is difficult to recruit large enough samples, so the results need replicating. But potentially this finding has tremendous implications, not just for finding out about Turner syndrome itself, but for understanding sex differences in development and disorders of social cognition.
3. Although most X-chromosome genes are expressed from only one X-chromosome, as noted above, some genes escape inactivation, and for these genes females have two active copies. In the main, these are genes with a homologue on the Y-chromosome, but there are exceptions, and in such cases females have twice the dosage of gene product compared to males (see Figure 1). And even where there is a homologue gene on the Y chromosome, this may have different effects from the active X-chromosome gene.
4. The Y chromosome contains a lot of inactive DNA with no genes. Recent studies on fruit flies has found that this inactive DNA can affect expression of genes on the autosomes, by affecting availability in the cell nucleus of factors that are important for gene expression or repression. It's not clear if this applies to humans.

My interest in this topic has led me to study children who do not inherit the normal complement of sex chromosomes. These include girls with a single X chromosome (XO, Turner syndrome), girls with three X chromosomes (triple X or XXX syndrome), (see figure 2) and boys with an extra X (XXY or Klinefelter’s syndrome), and boys with an extra Y (XYY syndrome).(see Figure 3).
Figure 2

Figure 3
Affected children typically don’t have intellectual disability and attend regular mainstream school. As illustrated in Figures 2 and 3 , this makes sense because the genetic differences between those with missing or extra sex chromosomes and those with the normal XX or XY complement are not great. In Turner syndrome there is only one X chromosome, whereas children with XXX or XXY will have all but one X chromosome inactivated. The extra Y in boys with XYY contains only a few genes.

Nevertheless, although children with atypical sex chromosomes are not severely handicapped, distinctive neuropsychological profiles have been described. Girls with Turner syndrome often have poor visuospatial function and arithmetical ability, whereas language skills are typically impaired in children with an extra sex chromosome. To explain these effects, researchers have proposed a role for genes that normally escape inactivation, which will be underexpressed in Turner syndrome, or over-expressed in children with three sex chromosomes (sex chromosome trisomy) - see point 3 above.

Wijchers and Festenstein note the importance of individuals with sex chromosome anomalies for informing our understanding of sex chromosome effects on development, but their account is not very satisfactory, as they state that “females with triple X syndrome (47,XXX) seem normal in most cases.” Although it is the case that many girls with XXX go undetected, surveys of prenatally or neonatally identified cases indicate that they have cognitive problems. Language deficits are found at high levels in all three cases of trisomy, XXX, XXY and XYY, with a trend for lower overall IQ in girls with XXX than boys with XXY or XYY. We did a study based on parental report, and found a diagnosis of autism spectrum disorder was more common in boys with XXY and XYY than in boys with normal XY chromosome status. But there was considerable variability from child to child, with some having no evidence of any educational or social difficulties, and others with more serious learning difficulties or autism. We currently lack data that would allow us to relate the cognitive profile in such children to their detailed genetic makeup, but this in an area researchers are starting to explore. We are optimistic that such research will not only be helpful in predicting which children are likely to need additional help, but also may throw light on more global questions about the genetic basis of sex differences in cognitive abilities and disabilities.

What are the implications of this research for the debate about sex differences in everyday human behaviour? This was very much in the news in 2010 with the publication of Cordelia Fine’s book Delusions of Gender, which was reviewed in The Psychologist, with a reply by Simon Baron-Cohen. Fine focused on two key issues: first, she questioned the standards of evidence used by those claiming biologically-based sex differences in behaviour, and second she noted how there were powerful cultural factors that affected gender-specific behaviour and that were all too often disregarded by those promoting what she termed ‘neurosexism’. I don’t know the literature well enough to evaluate the first point, but on the second, I would agree with Fine that biological factors do not occur in a vacuum. The evidence I’ve reviewed on genes shows unequivocally that there are sex differences in gene expression, but it does not exclude a role for experience and culture. This is nicely illustrated by the research of Michael Meaney and his colleagues demonstrating that gene expression in rats and mice can be influenced by maternal licking of their offspring, and that this in turn may differ for male and female pups!  Genes are complex and fascinating in their effects, but they are not destiny.

Further reading
Davies, W., & Wilkinson, L. S. (2006). It is not all hormones: Alternative explanations for sexual differentiation of the brain. Brain Research, 1126, 36-45. doi: 10.1016/j.brainres.2006.09.105.
Gould, L. (1996). Cats are not peas: a calico history of genetics: Copernicus.
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