Autism and Childhood Disintegrative Disorder

A review of: Palomo, R., Thompson, M., Colombi, C., Cook, I., Goldring, S., Young, G.S., Ozonoff, S. (2008). A Case Study of Childhood Disintegrative Disorder Using Systematic Analysis of Family Home Movies. Journal of Autism and Developmental Disorders DOI: 10.1007/s10803-008-0579-1

I’m always hesitant to discuss or review case reports on this blog. Case reports have a very limited target audience (related researchers and clinicians) and even more limited utility. These are reports on single clinical cases, often of extremely rare conditions that are difficult to study with traditional research methods. Often, case reports include very detail information about a particular issue that is intended to stimulate questions for future research. Case reports are not intended to present generalizable data about the nature of a condition, such as the causes or efficacy of a treatment, etc. Unfortunately, case reports are often picked up by the media, which incorrectly reports the findings as scientific evidence for X or Y. Case reports, regardless of the question, population, or condition, of interest, do not provide scientific evidence for anything. They are needed, and useful, but only as they stimulate questions for future research.

In line with this position on case reports, I won’t necessary report the results of this study. Instead, I want to comment on a couple of interesting issues that the authors discussed. This case report was an examination of a child presenting with childhood disintegrative disorder (CDD). In the study, the authors examined home movies taken throughout the child’s early infancy and early childhood to validate the diagnostic description of CDD as compared to regressive autism. A major strength of this report is its use of home videos as a source of observable data about the kids’ behavior. This technique provides a great tool for both researchers and clinicians who often have to rely only on parental reports. Although home videos are not completely free of problems and biases, they do provide clinicians with added information about the child, and specially changes in the child’s behavior over time.

The authors also discussed the diagnostic overlap between childhood disintegrative disorder and childhood autism of regressive type. In this particular case report, the child showed typical development until the age of 4, which was followed by an abrupt loss of skills and functioning. After this regression, the child clinical profile was consistent with a diagnosis of autism, and he actually received a diagnosis of autism. However, upon analysis of home videos and extensive interview with the parents, the diagnosis was changed to CDD because there was no evidence of atypical development prior to the age of 4. Although in this case the differential diagnosis is clear (assuming typical development until the age of 4), when the regression occurs earlier, the differential diagnosis becomes more complex. The authors noted:

“In theDSM-IV-TR, there is a 1-year period of overlap for the timing of the regression, such that a child experiencing developmental losses between ages 2 and 3 could meet criteria for either Autistic Disorder or CDD (American Psychiatric Association 2000). Another point of potential overlap is that some reported cases of CDD present with atypical development prior to the regression (Volkmar 1992; Volkmar and Rutter 1995), just as do some children with autistic regression (Ozonoff et al. 2005)”

But why the semantic splitting? Does it really matter if the child has Autism or CDD? At the individual level, based current available treatment interventions, no. Unless, as reported in this case, access to services is more limited after a diagnosis of CDD as compared to a diagnosis of autism. Therefore, when diagnostic criteria are met for both conditions, one should consider the effect that a specific diagnosis could have on the child's ability to access needed services. But in general, the utility of this differential diagnosis may be more relevant to researchers, as it defines a possible source of heterogeneity that may inform the research on developmental trajectories, causes, and treatments for different types of autism-like childhood conditions.

Autism and Inhibition of Return - A note about sample size

A review of: Rinehart, N.J., Bradshaw, J.L., Moss, S.A., Brereton, A.V., Tonge, B.J. (2008). Brief report: Inhibition of return in young people with autism and Asperger's disorder. Autism, 12(3), 249-260. DOI: 10.1177/1362361307088754

The authors designed an interesting experiment based on Minshew’s Complex Information Processing theory of autism, which seeks to understand the neuropsychological patterns of strengths and weaknesses in Autism as the foundations for the specific deficits in social cognition observed in Autism.

Side Note: Please note that the ‘Neuropsychological’ is usually misinterpreted, even by trained researchers and clinicians, as referring to physiological, as in ‘biological psychology’. Instead, neuropsychological refers in general to neurocognitive functioning – that is, cognitive and motor domains linked to brain processes. Thus, a test of neuropsychological functioning would include assessment of memory, attention, motor control, visual perception, auditory skills, general intelligence, language, etc.

Neuropsychological researchers have noted intact or superior abilities to detect unique patterns or items in visual search tasks in children with autism. This is inconsistent with the finding that these children also show difficulty with visual orientation and attentional set-shift (controlling the shifting of attention when needed from one set of items/tasks to others). Thus, how could children with autism have excellent item detection skills in light of their difficulty with attention and visual orientation? One possible explanation explored by the authors is that children with autism have a pronounced Inhibition of Return (IOR). IOR is a cognitive process that facilitates visual search by inhibiting searching on areas that have already been searched. For example, when looking for a letter ‘p’ on a poster full of letters ‘b’ and ‘d’, IOR allows you to search more effectively and those with a more pronounce IOR would be faster.

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In this study the authors compared 12 kids with high functioning autism, 12 kids with Asperger’s, and 12 typically developing kids, all matched for age (mean 10), sex, and IQ. Diagnoses were confirmed via ADI. The participants completed a series of tasks to measure IOR. The authors found no significant differences in IOR between those with ASD and typically developing kids. However, there was a trend at the (p = .052) level suggesting a more pronounced IOR among children with Asperger’s than the other two groups. This is worth noting because the authors ability to find statistically significant results is directly affected by the number of participants in each group. Thus, if these same results had been obtained with more participants, it is very likely that the difference observed would be statistically significant. This sample size related effect is more of a concern when the N of participants is very small. Thus, I will be more likely to ‘trust’ non-significant findings from a study using 1,000 participants than those from a study using only 20. One rule of thumb you can use when examining studies with small sample size (number of participants) is that statistically significant results are more "informative" than results not showing statistical significance. Why? Because the small sample size makes it more difficult to find statistically significant differences, so they require greater differences between the groups you are comparing. Thus, when you see a study using a small sample size that found a statistically significant difference, you can assume that the difference between the groups is there (assuming no other methodological problems). However, when the results show no statistical difference, this could mean that the difference between the groups does not exist, or that they needed a larger sample size.

Mercury Exposure and Autism: Should you check for nearby power plants?

...But this study is compelling in showing an association between mercury exposure and autism rates, and scientists can not just ignore it under the basis of its imperfect design and inability to make causal links – if that is the case, then only carefully controlled laboratory studies, with poor external validity, should be published and accepted as contributors to our greater scientific knowledge.

A review of: PALMER, R., BLANCHARD, S., WOOD, R. (2008). Proximity to point sources of environmental mercury release as a predictor of autism prevalence. Health & Place DOI: 10.1016/j.healthplace.2008.02.001

This fascinating, yet bound to be controversial, study hit the news yesterday as it was made available (pre-publication) by the Journal Health & Place. The study is simple, straightforward, elegant, with some powerful findings. In fact, the findings are somewhat daunting given the simplicity of the design. The researchers reviewed the amount of mercury release reported by industrial facilities and power plants in the State of Texas in 1997 from data provided by US Environmental Protection Agency Toxics Release Inventory. They compared these data against autism rates in 1997 and 2002 as measured by schools' autism classifications provided by the Texas Education Agency. Using a specialized geographical analysis system, the authors were able to locate each source of mercury and calculate the distance between each mercury source and each school. The results:

Industrial release of mercury and distance to industrial sources independently predicted increased rates of autism. The association with industrial release of mercury was not linear, instead the statistical model fit suggested an accelerated risk. This association remained statistically significant after controlling for specific variables such as SES, urbanicity, and race.

Power plant release of mercury and distance to power plant independently predicted increased rates of autism. In this case the association was linear (not accelerated). Again, this association remained statistically significant after controlling for other variables.

It is easy to dismiss these findings as inconsequential because they are ‘correlational’ in nature, or do not really prove anything. Researchers are too often guilty of selective acceptance of research: those studies that fit the consensus are accepted while those that don’t are dismissed for their methodological flaws – even though the studies we accept are equally flawed.

In the spirit of fairness I have to say that these findings are strong. Their methodology and analytical process are not any different from what is commonly seen in social science or epidemiology research. Is it perfect? Far from it. Is it useful or informative? Definitively! The data speak very clearly: In Texas, mercury release from industrial sources and power plants in 1997, and school proximity to these sources, are associated with rates of autism in 2002 as measured by school special education classifications.

Does this mean that mercury causes autism? Not at all. In the last sentence of the previous paragraph you can not replace the words are associated with with the word cause. There is a major difference. The data, albeit strong, have limitations. For example, the most obvious (to me) alternative explanation is that mercury release and proximity to these sources is also associated with another mystery factor that is causing this apparent association and that in fact, mercury release has nothing to do with autism rates in 2002. Let’s hypothesize that these power plants and industrial sources also release another toxin – let’s call this toxin autisimic (this is a made up toxin). These sources release mercury and autisimic at the same rate, so for each pound of mercury released there is a pound of autisimic released. It is possible then that this autisimic toxin directly increases the risk for autism, and this could explain completely the strong (but now obviously inaccurate) association between mercury release and autism.

Does this study show that vaccines cause autism? Absolutely not. I know this question may sound ludicrous to some, but I pose it rhetorically because I am certain that some will make the wide leap and link these findings to the vaccine issue.

There are other problems and limitations with this study, such as how autism rates were calculated (using all children instead of only those born inor after 1997), whether the autism rates are truly climbing and not explained by other factors, whether there are other variables that could be explaining this relation, etc, etc --- and yes, this study does not prove or directly indicate that autism is caused by mercury exposure (click here for a much more critical review of this study). But this study is compelling in showing an association between mercury exposure and autism rates, and scientists can not just ignore it under the basis of its imperfect design and inability to make causal links – if that is the case, then only carefully controlled laboratory studies, with poor external validity, should be published and accepted as contributors to our greater scientific knowledge. This is study is far, far, from perfect, and many changes should have been requested prior to publication, but I can say the same of 90% of what is published today.

A micro history of the recent mercury autism controversy.

A commentary on: Aschner, M. (2008). Response to Article by DeSoto and Hitlan on the Rlationship Between Mercury Exposure and Autism. Journal of Child Neurology, 23(4), 463-463. DOI: 10.1177/0883073808314647

DeSoto, M.C., Hitlan, R.T. (2008). Concerning Blood Mercury Levels and Autism: A Need to Clarify. Journal of Child Neurology, 23(4), 463-465. DOI: 10.1177/0883073808314718

The latest issue of the Journal of Child Neurology includes two letters regarding the mercury-autism controversy. For most people familiar with this issue, this summary will not present anything new, but for those interested in knowing the basics of this latest controversy, here is a micro-crash course on the mercury-autism link.

In 2004 authors Ip, Wong, HO, Lee, and Wong, published an article in the Journal of Child Neurology comparing the blood and hair mercury levels of children with and without autism in order to examine if a mercury-autism link existed. The results were as follow:

There was no difference in the mean mercury levels [between the group]. The mean blood mercury levels of the autistic and control groups were 19.53 and 17.68 nmol/L, respectively (P = .15), and the mean hair mercury levels of the autistic and control groups were 2.26 and 2.07 ppm, respectively (P = .79).

The conclusion, which was supposedly inconsistent with the theory that mercury causes autism, shocked some members of the autism community. I said ‘supposedly’ because whether or not the mercury theory is correct, the manner in which the results are presented goes beyond what the data can actually say. Specifically, the authors concluded that:

Thus, the results from our cohort study with similar environmental mercury exposure indicate that there is no causal relationship between mercury as an environmental neurotoxin and autism.

The problem here is that this data only speak to concurrent levels of mercury and autism diagnosis. So it is entirely possible that in some children pre- or post-natal exposure to this toxin results in neurodevelopmental changes leading to autism symptoms. This idea does not imply that mercury levels would remain high in affected children. It only implies that that these children were exposed to this toxin. A similar example would be exposure to alcohol during pregnancy leading to fetal alcohol syndrome (FAS). Children with FAS do not have higher levels of alcohol in their blood than typically developing kids. I am not endorsing the mercury theory, but I am stating that the conclusions as stated by Ip go beyond what their data say.

But back to the Ip et al. (2004) study. In 2007, DeSoto and Hitlan published an article in the Journal of Child Neurology after they found a major mathematical mistake in the original findings reported by Ip. Specifically, they found that the non-significant differences in blood levels reported by Ip was an error and significant differences were actually observed. I did the calculations myself, and yes in fact, the kids with autism had significantly higher mercury levels than the control group (t = 2.6163; df = 135; p>.01).

Then in the latest issue of the Journal of Child Neurology, Dr. Michael Aschner published the following short correspondence:

In a recent article DeSoto and Hitlan1 reanalyzed an original data set, concluding that a relationship exists between blood mercury levels and the diagnosis of autism spectrum disorder (ASD). The conclusion is based on the reanalysis of hair to blood mercury ratios. Hair to mercury concentration ratios while informative need to be considered within the context of a temporal relationship. As elegantly demonstrated by Grandjean and colleagues, mercury levels in the hair reflect a delayed average compared to the blood mercury level averages. That is, mercury hair concentrations at hypothetical time point T reflect blood mercury levels at T minus 1 to 2 months. Chelation therapy and changes in diet and fish consumption (both more likely to occur in the ASD group) in the 2 months preceding the mercury analysis are likely to affect blood, but not hair mercury sample concentrations. The analysis by DeSoto and Hitlan, which presumes that the 2 biomarkers are equally affected, is clearly erroneous. Thus, absent appropriate corrections for the temporal fluctuations in mercury levels, the conclusions should be interpreted with utmost caution and revalidated taking the above issue into account.

This was followed by a response from DeSoto and Hitlan explaining further that their 2007 study addressed directly the error in blood sample Mean differences as reported by Ip et al in 2004. DeSoto and Hitlan re-analyzed Ip's data showing that in fact blood mercury levels in the autistic group were higher than in the control group. This finding, and the original Ip error, had nothing to do with hair-to-blood ratios as described by Dr. Aschner. Dr. Aschner criticism is much more applicable to a separate hair analysis performed by DeSoto and Hitlan showing that the autism group had lower hair mercury levels than expected based on their blood samples, which is inconsistent with the idea that chelation therapy may have affected the blood levels. I explain: blood levels reflect immediate levels of mercury while hair levels reflect levels 1 to 2 month prior to testing. Thus, if blood levels at Time 1 were 20 (I’m using random numbers as example), then hair levels at Time 2 (2 month later) should be 20. If after Time 1 the child undergoes chelation therapy, then theoretically, blood levels at time 2 (2 month later) should be lower than 20 but hair levels should remain 20. Thus at Time 2, blood levels should be lower than hair levels. This was not supported by DeSotos’ analyses. What does this mean? Simply that the differences in blood levels found between the autism and control group are unlikely to have been affected by chelation therapy in the autistic group since the hair-blood analysis was not consistent with what is expected if chelation therapy had occur. WARNING: this is not a statement supporting chelation therapy, it is just a clarification of a possible interpretation of this data.

Does this mean that vaccines cause autism? Not at all. Again, although we would like to think that data can give us the entire story, data speak in morphemes rather than words, or sentences. This data only indicate that this particular group of children with autism had higher mercury levels than typically developing children. This could mean many things, such as that the children with autism have difficulty processing mercury or that the children with autism were exposed to higher levels of mercury, and these explanations in turn, may or may not have anything to do with the symptoms observed in children with autism, both in terms of symptom presentation, severity, or causes. These data simply do not give us that information.

More recent articles about the Autism and Mercury controversy and the Autism and Vaccines controversy can be found here.

Autism epidemic and symptom substitution

Study provides evidence for the symptom substitution theory explaining the dramatic increases in autism during the last 20 years.

A review of: 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 and Child Neurology, 50, 1-5.

One theory that has been proposed as a possible explanation of the dramatic increase in autism diagnoses during the 1990’s and 2000s is the Diagnostic Substitution phenomena. The basic premise of this position is that increases in autism diagnoses are not due to a true increase in the number of ‘cases’ of autism, but instead to a change in diagnostic practices so that individuals who are now diagnosed with autism would have been diagnosed with a different condition 20 or 30 years ago.

What are the basic assumptions about this theory that can be tested? First, an increase in diagnoses of autism should be accompanied by an equally dramatic decrease in diagnoses of other related disorders that are believed to drive the substitution. Sullivan at Gray Matter – White Matter provides a great example of this phenomenon by looking at the rates of autism and mental retardation in Alabama. Another way to test this theory would be to examine retrospectively the clinical presentation of adults who have been diagnosed with a non-autism disorder, and determine if the clinical presentation of these individuals during childhood would have led to a diagnosis of Autism today. That is, would children with the same presentation receive a diagnosis of autism today?

In this study, the authors examined 38 adults (age 15 to 31) who had received a diagnosis of language disorder during childhood but not a diagnosis of Autism. The authors were mostly interested in a particular type of language disorder diagnosis called pragmatic language impairment (PLI), since this disorder has many similarities with autism. The authors conducted full ADOS and ADI evaluations of these individuals. They found that 55% of the participants with PLI met the criteria of autism as indicated by the ADOS or the ADI, and 40% met the criteria of autism as indicated by both, the ADOS and the ADI.

These findings are consistent with the diagnostic substitution theory. The implication is that a significant percentage of people who were diagnosed with PLI in the past would now receive a diagnosis of autism instead. Likely this substitution is not sufficient to explain, in its entirety, the dramatic increase in autism diagnoses; but it is reasonable to conclude that such substitution could partially explain such increase. In addition, the PLI substitution is just one of several proposed substitutions (see for example MR as described here). Finally, it could be argued that these individuals received the correct diagnosis of PLI as children and developed autism symptoms as adults. Although this is a plausible explanation, it is not consistent with what we know of the developmental progression of autism symptoms.

Hospitalization of Children with Autism: Predictors and Frequency

Aggressive behaviors increase risk for hospitalization by more than 400%; more than any other variable.

A review of: Mandell, D.S. (2007). Psychiatric Hospitalization Among Children with Autism Spectrum Disorders. Journal of Autism and Developmental Disorders DOI: 10.1007/s10803-007-0481-2

In this large-scale study the authors examined the frequency and predictors of psychiatric hospitalization in children with autism spectrum disorders. The sample included 760 children and young adults with a diagnosis of autism, Asperger’s or PDD-NOS and their parents (age range of the children 5 to 21) living in Pennsylvania. 10.8% of the sample had a history of psychiatric hospitalization. A number of external factors were more common in children and young adults with ASDs. Those with a history of hospitalization were more likely to be: older, African-American, adopted, living in a single parent household, and have parents making less than 40,000 per year and without a college degree. In addition to these external factors, those with a history of hospitalization were also more likely to: have a diagnosis of Autism or Asperger’s (as opposed to PDD-NOS), display self-injurious behaviors, be aggressive towards others, display less stereotypies, and have more co-morbid diagnoses.

When examining the predictors of hospitalization a slightly different picture was noted. Each year of age was associated with a decrease in hospitalization risk (OR=.81). This sounds like it contradicts the finding reported above - that those with a history of hospitalization are more likely to be older. However, these are two different questions. At the group level, older people, likely simply by virtue of living longer, are more likely to have a history of hospitalization. However, at the individual level, the risk of hospitalization decreases with age, so that it becomes less likely in each subsequent year. Aggressive behavior towards others was the stronger predictor of hospitalization increasing the odds more than 400% (OR= 4.83). This was followed by having a co-morbid diagnosis of depression (OR = 2.48) or obsessive compulsive disorder (OR=2.35), and displaying self-injurious behaviors (OR=2.14). One parental variable were also identified. Living in a single parent home more than double the odds of being hospitalized (OR=2.54).

One of the most interesting issues addressed by this research is that it seems that there are two factors related to risk of hospitalization: factors that are directly reflective of the severity of the disorder (aggression, self-injurious behaviors, etc) and social-familial factors that are possibly unrelated to the disorder (SES, being a single parents, etc). It is possible that the effectiveness and utility of hospitalization may depend upon the underlying reasons as to why a child may be hospitalized. In addition, this data suggest that interventions targeted to reducing the rate of hospitalization among children with ASD should focus on: early treatment of aggressive and self-injurious behaviors, and providing better services and resources to families at risk for seeking hospitalization for their children.

Autism Symptoms and Signs | A review of the DSM-IV criteria of Autism.

As several parents have contacted Translating Autism asking me to discuss the symptoms of autism spectrum disorders, I decided to write this brief post explaining the DSM-IV criteria of Autism.

Autism and related disorders are categorized within the larger concept of “Pervasive Developmental Disorders”. These disorders include: Autistic Disoder, Rett’s Disorder, Childhood Disintegrative Disorder, Asperger’s Disorder and Pervasive Developmental Disorder NOS. In this review I will focus only on the symptoms and signs of Autism, and soon I will write additional blog reviews of the diagnostic criteria for the other Pervasive Developmental Disorders.

The diagnosis of autism is made on the basis of symptoms observed or reported within 3 categories. The categories include (information in italics are examples I provide):

1. Qualitative Impairment in social interactions such as: a) impairment in the use of nonverbal behaviors (eye gaze, facial expressions, etc), b) failure to develop age appropriate peer relationships, lack of spontaneous seeking of enjoyment, interests, or achievement with others (does he/she show you something he/she made, does he/she invites you to play with him/her, etc), & c) lack of emotion reciprocity (does he/she get sad when you are sad? Does he/she show worry when you hurt yourself, etc). For diagnosis, at least two of these symptoms must be present.
2. Qualitative Impairment in communication such as: a) delay or lack of development of spoken language, b) lack of ability to initiate and maintain conversation with others, c) stereotype and repetitive language (repeating the last words you said or frequently repeating a phrase he/she heard) or idiosyncratic language (does he/she uses her own language or words for specific objects, etc, above what is expected based on the child’s age), and d) lack of varied, spontaneous make believe or interactive play (does he/she do pretend play? Does he/she engage in cooperative play with peers?). For diagnosis at least one of these symptoms must be present.
3. Restricted repetitive and stereotyped patterns of behaviors, interest, and activities such as: a) preoccupation with one or more stereotyped and restricted patterns of interest that is abnormal in intensity or focus (is he/she obsessed with plates? Antennas? Argentina? Red dots? above and beyond what is common in today’s society – thus in most cases obsession with video games doesn’t count), b) inflexible adherence to specific, non-functional routines (do you always need to turn off the light before opening the door? etc), c) stereotyped and repetitive motor mannerisms (hand flapping, twisting, etc), and d) persistent preoccupation with parts of objects (can he/she spend hours staring at the cord of a fan, the tip of a pen, etc?) For diagnosis at least one of these symptoms must be present.

In addition to the symptoms included above, there must be a history of abnormal functioning prior to the age of 3 in at least one of these areas: Social Interaction, language use in social communication, and symbolic or imaginative play.

Also, if a diagnosis of Rett’s disorder or Childhood Disintegrative Disorder is met, such diagnoses supersede the autism diagnosis and no autism diagnosis should be provided.

Finally, note that the issue of mental retardation is not addressed anywhere in the diagnostic criteria. That is because these are two separate diagnoses that are taxonomically unrelated. The diagnosis of mental retardation is provided on the basis of IQ performance on standardize tests. If a child with autism also meets the full diagnostic criteria for metal retardation, that child may also receive a secondary diagnosis of MR, although the practice of providing such co-morbid diagnosis varies, often due to questions about the utility of such secondary diagnosis and the ability of intellectual assessment tests to accurately assess the intellectual abilities of people with Autism.

I hope you find this post useful and feel free to ask any question or request clarifications.

Nestor L. Lopez-Duran PhD
Translating Autism: An Autism Research Blog

Autism services in Canada and Neuropsychological evaluations

A review of:McLennan, J.D., Huculak, S., Sheehan, D. (2008). Brief Report: Pilot Investigation of Service Receipt by Young Children with Autistic Spectrum Disorders. Journal of Autism and Developmental Disorders DOI: 10.1007/s10803-007-0535-5

This is a brief report published in the Journal of Autism and Developmental Disorders. The authors contacted over 1,100 families who had obtained services from specialized clinics for children with developmental disabilities. The centers were located in Alberta, Canada. Sixty four of these families reported having at least one child with ASD. The authors examined the different services that these families received and compared these with the recommended practice guidelines. The percentage of families receiving specific services were as follows: Speech and Language assessment (94%), Psychological Assessment (42%), Genetic Testing (31%), Speech and Language therapy (88%), occupational therapy (78%). The authors concluded that the rates of services received did not correspond with the recommended practice guidelines. The authors reported the post-diagnosis evaluation guidelines as proposed by the American Academy of Child and Adolescent Psychiatry, the National Research Council, the American Academy of Neurology, and the child Neurology Society:
1. Screening for lead, tuberous sclerosis, and Fragile X
2. Neuropsychological testing (audiological function, cognition, adaptive function, and expressive-receptive language)
3. Occupational and physical therapy assessment if needed.

My clinical practice is in pediatric neuropsychology. While working at a large hospital in Michigan conducting mostly neuropsychological evaluations for children with ASD, I assumed that most families received this service. However, once I left that setting and was exposed to clinics that do not have neuropsychological services, I realized that only a small portion of these families receive a full neuropsychological evaluation. The reasons for this vary, from limited access to trained neuropsychologists, unfamiliarity with the possible benefits of these evaluations, and sadly, limited insurance coverage in some States. In my experience, if families are informed about the nature and limitations of these evaluations, Neuropsychological evaluations are very useful in helping coordinate and determine interventions that are targeted to the pattern of strengths and weaknesses of each child, and monitor the progress of the child over time. But I also agree that some families do not find these evaluations as useful.

Here are the sources of the guidelines:

Filipek, P. A., Accardo, P. J., Ashwal, S., Baranek, G. T., Cook, E. H. Jr., Dawson, G., et al. (2000). Practice parameter: Screening and diagnosis of autism: Report of the Quality Standards Subcommittee of the American Academy of Neurology and the Child Neurology Society. Neurology, 55(4), 468–479.

National Research Council (2001). Educating children with autism. Washington, DC: National Academy Press.

Volkmar, F., Cook, E. H. Jr., Pomeroy, J., Realmuto, G., & Tanguay, P. (1999). ractice parameters for the assessment and treatment of children, adolescents, and adults with autism and other pervasive developmental disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 38(12 Suppl),
32S–54S.

“Leaky Gut” revisited: Intestinal problems in children with autism.

Title: Intestinal Permeability and Glucagon-like peptide-2 in Children with Autism: A Controlled Pilot Study.
Source:Robertson, M.A., Sigalet, D.L., Holst, J.J., Meddings, J.B., Wood, J., Sharkey, K.A. (2008). Intestinal Permeability and Glucagon-like peptide-2 in Children with Autism: A Controlled Pilot Study. Journal of Autism and Developmental Disorders DOI: 10.1007/s10803-007-0482-1

One of the many theories that have been proposed to explain possible causes of autism is the "leaky-gut, opioid-excess" theory. This theory suggests that children with autism have increased permeability of their intestinal track leading to faster absorption of peptides which could disrupt neural development during the early stages of life. To test this theory, the authors measured intestinal permeability in a group of 14 children with autism (diagnosed via DSM-IV criteria by a developmental pediatrician), 7 typically developing siblings of these children, and 8 typically developing additional children. They tested the leaky gut theory in two ways. First they observed the levels of a hormone (GLP-2) in response to feeding, which is believed to control satiation. Low levels of this hormone could lead to, or reflect, dysregulated peptide absorption. Second, intestinal permeability was assessed via a differential sugar-absorption test. They used different types of sugars that have different molecular weights. In a normal intestinal system, sugars with small molecular weight will pass through the walls easily as compared to heavy sugars, leading to high levels of the small sugars in urine. However, in a highly permeable intestinal system, the ratio of these two sugars in urine will change as the sugars with large molecular weights pass through the intestinal barrier at a higher rate. Results: The authors found no differences between any of the 3 groups of children in GLP-2 response to feeding or the ratio of sugars in urine. The authors concluded that in this small sample of children with autism there was no evidence of increased intestinal permeability as hypothesized in the ‘leaky-gut’ hypothesis.

Side note: I always thought "Developmental Pediatrician" was a completely redundant label, and comparable to 'heart cardiologist' or 'eye ophthalmologist'. Although sadly, my experience with some pediatricians does suggest that some really don't know anything about human development.

The use of Virtual Reality in children with Autism

Title:Development of symbolic play through the use of virtual reality tools in children with autistic spectrum disorders
Source:Herrera, G., Alcantud, F., Jordan, R., Blanquer, A., Labajo, G., De Pablo, C. (2008). Development of symbolic play through the use of virtual reality tools in children with autistic spectrum disorders: Two case studies. Autism, 12(2), 143-157. DOI: 10.1177/1362361307086657

In general, I tend to stay away from case reports (studies using one or just a couple of participants). Usually I don’t even read them, since most of the time I feel that, given what we know about methodology today, case reports should not even be published. I say ‘most of the time’ because once in a while a case report is published that reminds me why case reports are important: to provide us with insight as to where future research could focus. So I want to briefly review a case report published in the last issue of Autism as simply food for thought.

Clinically, the absence of pretend play in early childhood is one of the most common features of ADSs. Parents report that their children do not engage in imaginary or pretend play and do not use toys as expected when play requires symbolic understanding. For example, when provided with a box of Star Wars figurines, a child may simply line up the figures making patterns on the floor and may not use the figures to recreate situations or scenes as expected. The assumption is that the child does not view the figures as symbolic representations of people. The authors of this paper wanted to use Virtual Reality as a tool to teach children with autism to use symbolic play. There is some evidence that suggest that symbolic play is of significant importance for the development of several cognitive skills including language, spontaneity, intention, etc. Thus, the authors argued that interventions that teach children to use symbolic play could be of benefit to children with ADSs.

The authors used a computer virtual reality game “the Virtual Supermarket” to teach children to move from physically manipulating the objects (picking up items from the shelves), to engaging in functional play (dressing a doll with miniature clothing), to finally engaging in symbolic play (using a pair of trousers as an imaginary road). The authors used this game with two children, age 8 and 15, who had been diagnosed with Autism based on DSM-IV criteria. The two individuals received 28 sessions of this type of games during 2 ½ months. They were tested on a variety of measures before and after the intervention period. The authors stated that after the intervention period the children demonstrated improvement in functional use of objects, functional play (measured via the Test of Pretend Play – ToPP), symbolic play (ToPP), imagination understanding, and magic understanding.

Although this study suffers from the common limitations of case studies, it is extremely interesting, and it should encourage future research in the use of virtual reality as an intervention tool for the teaching of symbolic understanding.

Autism, IQ, and the Stanford–Binet

Title: Brief Report: Data on the Stanford–Binet Intelligence Scales (5th ed.) in Children with Autism Spectrum Disorder
Source: Coolican, J., Bryson, S.E., Zwaigenbaum, L. (2008). Brief Report: Data on the Stanford–Binet Intelligence Scales (5th ed.) in Children with Autism Spectrum Disorder. Journal of Autism and Developmental Disorders , 38(1), 190-197.

In 2003 the Stanford-Binet-Intelligence Scales published a new edition (The SB-5). The SB is one of the most commonly used IQ scales for the assessment of children with special needs because it is believed to provide a more valid estimate of the child’s cognitive capacities. Although such assertion is still debated, in my experience working at several outpatient and hospital settings, the SB was always the tool of choice when conducting assessment with children with autism. Now, the problem that clinicians and researchers encounter is that when a new version of the test is launched, there is little information, apart for what is provided by the publisher, about how children with specific neurodevelopmental disorders are expected to perform. Thus, a team a Dalhousie University in Canada provided this brief report on the performance on the SB-5 by children with ASDs. The study included 63 children (12 girls and 51 boy) who have received a diagnosis of Autism, Asperger’s, or PDD-NOS via ADI or ADOS evaluation. The final count included 32 children with autism, 20 children with Asperger’s, and 11 children with PDD-NOS. Here are the most relevant results: Age was not significantly associated with performance as expected. This means that when compared to very large population sample of peers of the same age, younger children and older children perform at the same level in relation to their peers. Thus, differences between these children and the population sample do not change with age. The average full scale IQ scores using the entire SB-5 for the groups were 67.75 for Autism, 105.60 for Asperger’s, and 82.18 for PDD-NOS. When using an abbreviated version of the SB-5, the results were slightly higher but this varied significantly by individual. When comparing the Verbal vs. Non-Verbal subscales, it was surprising that in all three groups the scores in these scales were very similar, without any major discrepancy between verbal and non-verbal performance. This is surprising because traditionally children with Asperger’s show a pattern of performance consistent with a Non-verbal learning disability. That is, you would expect a significant discrepancy with much higher verbal scores as compared to non-verbal scores.

Commentary: The issue of IQ and intellectual assessment in children with Austim is highly controversial. However, the controversy is largely political and outside the research and clinical world. I want to address two issues that seem to be commonly debated in the autism community. First I want to briefly explain when, why and how an intellectual assessment test is used. An intellectual assessment is never, or should never, be provided in isolation. That is, an IQ test for the sake of knowing an IQ score provides no clinical utility. IQ scores, outside the larger scope of a full neurocognitive or educational evaluation conducted to answer specific clinical questions, are simply meaningless. Instead, an intellectual assessment is provided as part of a larger evaluation to understand the specific patterns of relative neurocognitive strengths and weaknesses with the ultimate goal of providing recommendations for services, treatment, accommodations, etc , which will maximize the functional capacities of the child and will facilitate growth and improvement. Second, there is usually a debated as to whether these intellectual assessment tools truly reflect the capacities of the child. This is a very, very, very important question. For example, performance in these types of tests is highly influenced by social desirability (wanting to please). A typically developing child may be attentive to instructions in order to please the clinician. But what if the child simply has other priorities at that particular moment than to listen to the clinicians explain how to do this clearly boring task? Does poor performance on this task reflect limited capacity in the area of functioning assessed? That is, did the child performed poorly because he/she couldn’t do it, or simply because he/she didn’t want to do it? So to the extent that IQ tests measure TRUE capacity, or are reflective of the child’s TRUE abilities, we simply have to say we don’t know. We hope that our assessment tools tap and real capacities as much as possible, but it is nearly impossible to ascertain why someone did not perform well in a particular task. HOWEVER, what the test does, at least more accurately, is to assess for FUNCTIONAL capacity. From a purely theoretical perspective, we can say that it does not matter why the child performed poorly if such performance generalizes into other contexts and affect the functional capacity of the child (not being able to do school work, difficulty keeping a job, etc). Thus, to the extend that neurocognitive assessment tools reflect functional capacities and help us provide recommendations that result in REAL benefits for the child, then I see these tests as important tools if used correctly for the right reasons and in the right context.

Update - Clarification: I was asked to clarify the statement “the controversy is largely political and outside the research and clinical world”. I apologize and agree that I should have been more precise about what I meant with that statement. I did not mean to imply that there is no controversy regarding the relative utility or appropriates of particular instruments (SB vs. WISC vs. TONY vs. other non-verbal assessment tool, etc). I was making a commentary about the commonly accepted position that in the right context, intellectual assessment as part of a comprehensive evaluation provides useful clinical information that could benefit the child or adult with autism. In my experience, the utility of using intellectual assessment tools has not been an issue of major controversy in any of the clinical settings I have worked in, including large university-based hospitals and autism clinics. In addition, I just conducted another superficial review of the two top journals in autism during the last 24 months and I was unable to find articles that provide appropriate empirical support for the idea that intellectual assessments should not be conducted in children with autism, although there are compelling articles discussing the appropriateness of specific tests. However, I accept that it is possible that the controversy in the research and clinical arena about this issue could more pronounced than how I characterized it, and if that is the case I stand corrected.

Autism, Services, and Co-morbidity: Insights from Kansas. PART II

Title: Characteristics of children with autism spectrum disorders who received services through community mental health centers.
Authors: Stephanie A. Bryson, Susan K. Corrigan, Thomas P. Mcdonald, and Cheryl Holmes
Source: Autism 2008 12: 65-82. (January).

I apologize for the lack of posts since Friday. I was in Washington at a National Institutes of Health round table discussion on research in childhood-onset disorders. Although the meeting was focused on child depression, there are several issues that were debated that apply to Autism research and I will post some observations later this week.

This is the second part of my summary of the Kansas community mental health study. Please see the previous post for some background and basic description of the methodology. As you may remember, the authors compared children with autism to children with other ASD, all of whom had received services at community mental health centers in Kansas. The researchers explored differences in a variety of demographic factors but they were most interested in examining differences in rates of co-morbid disorders. Here are their basic findings: Children with PDD and Asperger’s, when compared to children with autism, had higher rates of co-morbid ADHD, Depressive Disorders, Oppositional Defiant Disorder, Bi-Polar Disorder, and Post Traumatic Stress Disorder. Children with Asperger’s and PDD were also more likely to have experienced a psychiatric hospitalization. Yet, children with Autism were more likely to receive special education services than children with other ASDs.

Brief Commentary: The authors discussed some possible interpretations of the data, and I want to reiterate one major point. At least 2 things may be at play here. It is possible that children with PDD and Asperger’s do in fact experience higher rates of these disorders. Some of the findings are consistent with our current understanding of ASDs. For example, some researchers have characterized the differences between Asperger’s and Autism (especially high functioning autism) to be mostly related to differences in social desirability. The basic premise is that children with Asperger’s HAVE a desire for social interactions and relationships with peers, but they have social limitations that make it difficult for them to develop such social interactions. One the other hand, children with autism are believed to lack an “explicit or apparent” desire to establish and maintain relationships with peers. This limited social desirability may actually be “protective” for depression and other disorders in children with Autism; while the apparent social affiliation needs of children with Asperger’s, coupled with their social limitations, may lead to higher levels of frustration and possibly more emotional distress. HOWEVER, the results may also be a byproduct of our clinical diagnostic practices. There are many reasons why clinicians may provide a co-morbid diagnosis. In my own clinical experience, most often a second diagnosis is provided only when such diagnosis serves a function that helps the child. For example, up to 70% of children with autism score in the mental retardation range of standard IQ tests, yet most kids with Autism do not receive a second diagnosis of Mental Retardation. Why? Because it serves no purpose (in addition to other theoretical consideration). However, I have seen children receive a second diagnosis of MR when such diagnosis served a purpose, such as allowing the family and child to receive extended services, insurance coverage, etc. Thus it is possible that the differences in diagnoses observed by the researchers are not differences in ACTUAL rates of the disorders but instead in the relevant utility of providing a co-morbid diagnosis to children with PDD, Asperger’s, and Autism.

About Science and faith-based advocacy.

I had a discussion with a colleague about a disclaimer I had added to the bottom of the review of the Pediatrics Thimerosal study. In that disclaimer I mentioned that the overwhelming evidence disputes the vaccine-autism relationship. Although most researchers agree with that statement, two things prompted me to delete that note from the post. First, with that statement I did not intend to declare an advocacy position. To the contrary, the statement was made in the context of a commentary regarding the role of “beliefs” in science. Specifically, I stated that what I believe doesn’t really matter, because “beliefs” rapidly turn into blind faith, even amongst scientists. Instead, good science only occurs when positions are flexible and reflective only of the status of the research (data) at any given time. Second, the addition of that particular disclaimer went beyond a discussion of the results and possible interpretation of the data presented in that particular study. This departed significantly from the spirit of the Translating Research Project, and for that I apologize (thank you to the 2 readers who brought this to my attention). Therefore, I’m committed to preserving the spirit and purpose of this blog: To review the latest findings in the nature, causes, and treatments of autism spectrum disorders and translate these findings into information that is useful to parents, educators, and clinicians; and I seek to do this while distancing myself, and all blogs belonging to the Translating Research Project, from any advocacy position.