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By Matt Carey

A recent effort supported by the Autism Science Foundation sought to gather information on the status and needs of adult autistics. The UJA Adult with ASD Survey used an online survey as part of the Interactive Autism Network (IAN). The survey collection ended December 31st of 2012, but shortly afterwards the results of another IAN based survey were published by a team from Johns Hopkins and the Kennedy Krieger Institute. The paper, The association between bullying and the psychological functioning of children with autism spectrum disorders, was based on a survey of parents of school aged autistic children. This appears to be the same study whose preliminary results were released last year as IAN Research Report: Bullying and Children with ASD. I’ll work from the abstract (below) and the IAN preliminary report both as they are publicly available. And, since the IAN preliminary report is so accessible, I won’t go into great detail here.

The results are not surprising: autistics are bullied more often. While this may not come as a shock, having this data is the first step to effecting change. And, yes, autistics can play the role of the bully, but often with different motivations than their non-autistic peers. This figure from the preliminary report says a great deal: a much higher (about 3x more) percentage of autistics were bullied.

BulliedPastMonthComparison

Those with Asperger syndrome were reported as being bullied more often than those with other ASD diagnoses. The preliminary report also lists behaviors and traits that increased the likelihood of bullying:

•Clumsiness
•Poor hygiene
•Rigid rule keeping (enforcing adults’ rules when other children would not)
•Continuing to talk about a favorite topic even when others are bored or annoyed
•Frequent meltdowns
•Inflexibility or rigidity

Sadly, one group that was frequently bullied was children with ASD who wanted to interact with other children, but had a hard time making friends. Of these, 57% were bullied, compared to only 25% of children who prefer to play alone and 34% of children who will play, but only if approached. The one slightly bright spot was that children who had learned to make friends successfully were bullied at a lower rate: 34%.

While autistics bully more often than their non-autistic peers, they mostly play the role of “bully-victims”. From the preliminary report: Unlike victims who are more passive, bully-victims insult their tormentors or otherwise try to fight back in a way that only makes the situation worse.

Again, IAN has an excellent discussion of this study. It is worth noting that a study creates awareness in the research community and provides the type of data from which questions can be formed. Just as we can hope that this study will spark further work, we can hope that the UJA Adult with ASD Survey will provide a basis for more work, and some solutions to the issues uncovered.

Here is the abstract for the published paper:

OBJECTIVE: : Bullying has become a major national concern, particularly as it affects children with disabilities. The current study aimed to determine the association between psychiatric comorbid conditions, involvement in bullying (victim, bully, or bully-victim), and the immediate psychological correlates of bullying among children with autism spectrum disorders (ASDs).

METHODS: : A national sample of 1221 parents completed a survey dedicated to the bullying and school experiences of their child with ASD, reporting on the immediate consequences of bullying involvement, including their child’s psychological well-being and any psychiatric comorbidity. Multivariate logistic regressions were performed to determine whether specific psychiatric comorbidities were associated with an increased risk of involvement as victim, bully, or bully-victim. Analyses of variance determined the relationship between bullying frequency and psychological functioning. All models adjusted for child and school covariates.

RESULTS: : Children who were frequently victimized were more likely to present with internalizing symptoms, whereas children who frequently bullied others were more likely to exhibit emotion regulation problems. Children who were identified as frequent bully-victims presented with both internalizing symptoms and emotion regulation problems. Children with attention-deficit hyperactivity disorder (ADHD) and depression were more likely to have been victimized, whereas children with conduct disorder (CD) or oppositional defiant disorder (ODD) were more likely to have bullied other children. Children identified as bully-victims were more likely to have ADHD, CD, or ODD.

CONCLUSIONS: : Children with ASDs who had displayed bullying behaviors in the past month exhibited psychological impairments, including psychiatric comorbidity. The frequency of bullying behaviors was significantly associated with the level of impairment.

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By Matt Carey

A 2011 study in Pediatrics suggested that autism risk might be higher for siblings born within a few years of an older sibling, with the risk falling as the spacing between pregnancies increased (Closely spaced pregnancies are associated with increased odds of autism in California sibling births). This suggests prenatal environment would be involved in such a risk factor. In a study published on November 30, 2012 in PLoS One, researchers look at the characteristics of autistics born after a first sibling with autism. They look at measures of intelligence (both verbal and nonverbal), repetitive behaviors and social response. In The effects of birth order and birth interval on the phenotypic expression of autism spectrum disorder, researchers found that younger autistic siblings scored lower on these scales than their older autistic siblings. In other words, the challenges associated with autism tend to be higher for autistic younger siblings.

While the sample size for families with three autistic siblings was small, the trend seems to continue with a third sibling.

Here are results for the Ravens Colored Progressive Matrices, a test of nonverbal intelligence:

journal.pone.0051049.g002

The fraction of individuals who the researchers deemed “untestable” increased for younger siblings. Where about 20% of first autistic siblings were “untestable”, this increased to about 40% for second and third autistic siblings.

journal.pone.0051049.t001

Measures of motor skills (Vineland) were mostly the same for older and younger autistic siblings. Social measures (Social Responsiveness Scale) differed, but only when the age difference was under 2 years.

The authors give some discussion to what factors might be involved in these findings. While they acknowledge that social factors cannot be ruled out, this study, and the pediatrics paper before it, point to the prenatal environment as a possible avenue for environmental risk factor research.

Papers in PLoS are free to the public and this one can be found at The Effects of Birth Order and Birth Interval on the Phenotypic Expression of Autism Spectrum Disorder.

A rise in the prevalence of diagnosed cases of autism spectrum disorder (ASD) has been reported in several studies in recent years. While this rise in ASD prevalence is at least partially related to increased awareness and broadened diagnostic criteria, the role of environmental factors cannot be ruled out, especially considering that the cause of most cases of ASD remains unknown. The study of families with multiple affected children can provide clues about ASD etiology. While the majority of research on ASD multiplex families has focused on identifying genetic anomalies that may underlie the disorder, the study of symptom severity across ASD birth order may provide evidence for environmental factors in ASD. We compared social and cognitive measures of behavior between over 300 first and second affected siblings within multiplex autism families obtained from the Autism Genetic Resource Exchange dataset. Measures included nonverbal IQ assessed with the Ravens Colored Progressive Matrices, verbal IQ assessed with the Peabody Picture Vocabulary Test, and autism severity assessed with the Social Responsiveness Scale (SRS), an instrument established as a quantitative measure of autism. The results indicated that females were more severely impacted by ASD than males, especially first affected siblings. When first and second affected siblings were compared, significant declines in nonverbal and verbal IQ scores were observed. In addition, SRS results demonstrated a significant increase in autism severity between first and second affected siblings consistent with an overall decline in function as indicated by the IQ data. These results remained significant after controlling for the age and sex of the siblings. Surprisingly, the SRS scores were found to only be significant when the age difference between siblings was less than 2 years. These results suggest that some cases of ASD are influenced by a dosage effect involving unknown epigenetic, environmental, and/or immunological factors.

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By Matt Carey

When I attended IMFAR in 2011, the work of Eric Courchesne’s group at UCSD was highlited in the press conference . The main study highlighted was Abnormally Accelerated Development of Higher-Order Long-Distance Cerebral Tracts In ASD Infants and Toddlers, which was a structural (MRI) study of brains in autistic children.

Another study presented by Prof. Courchesne’s group at the conference was Blood-Based Transcriptomic Biomarker Profiles of Autistic Spectrum and Other Developmental Disorders. The results were intriguing: mRNA expression in the blood was different for autistics than either typically developing or developmentally disabled young children. The genes involved were related to mitotic cell cycle regulation as well as cerebral cortex development and other processes which might shed light on etiology. What was particularly intriguiing was the conclusion of the conference abstract:

[peripheral blood mononuclear cells] may serve as a useful tissue for deriving biomarker profiles of ASDs that are highly specific to particular neurodevelopmental disorders. Ongoing longitudinal analyses of these subjects will determine if these blood-based biomarker profiles fluctuate as symptom profiles change over time with intensive behavioral treatment.

In other words: these mRNA expressions might be specific enough to serve as a biomarker.

Blood-based gene expression signatures of infants and toddlers with autism.

OBJECTIVE:
Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with autism have yet emerged.
METHOD:
Using a community-based, prospective, longitudinal method, we identified 60 infants and toddlers at risk for ASDs (autistic disorder and pervasive developmental disorder), 34 at-risk for language delay, 17 at-risk for global developmental delay, and 68 typically developing comparison children. Diagnoses were confirmed via longitudinal follow-up. Each child’s mRNA expression profile in peripheral blood mononuclear cells was determined by microarray.
RESULTS:
Potential ASD biomarkers were discovered in one-half of the sample and used to build a classifier, with high diagnostic accuracy in the remaining half of the sample.
CONCLUSIONS:
The mRNA expression abnormalities reliably observed in peripheral blood mononuclear cells, which are safely and easily assayed in infants, offer the first potential peripheral blood-based, early biomarker panel of risk for autism in infants and toddlers. Future work should verify these biomarkers and evaluate whether they may also serve as indirect indices of deviant molecular neural mechanisms in autism.

The published study follows the conservative approach of the IMFAR abstract: the title is not focused on the potential for this discovery to be used as a biomarker, but the conclusions point out that this is a possibility. Had I not been watching for published studies such as this from Prof. Courchesne’s group, I might have passed over this abstract after reading the title.

Autism is currently diagnosed based on behaviors. Because of this many autistics are missed. For example, the CDC autism prevalence estimates identify individuals who previously were undiagnosed, and the median age of diagnosis in the recent study from Sweden was 8 years old. A blood based biomarker would be very helpful in helping to provide therapies and supports to autistics from an early age.

Prof Courchesne has worked as a grant reviewer for the Autism Science Foundation.

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By Matt Carey

The prevalence of autim spectrum disorders in Sweden is estimated at about 1% (1.15%) based on a study just released using the Stockholm Youth Cohort. This prevalence is consistent with current estimates in the U.S. and the U.K., and with a subset of the population from a previous Swedish study. Autism prevalence is relatively flat with age, especially for children born in the 1990’s.

Most autism prevalence data is from Europe and the United States, with the U.S. as the largest source of data. CDC prevalence estimates are reported every two years. CDC estimates use a record-review methodology. While this methodology has its own limitations, including likely underestimating autism prevalence, relying upon administrative registries (such as the California Department of Developmental Services datasets or medical registries) are likely to give an even greater underestimation of autism prevalence. A whole-population approach, such as that used in a recent study of autism prevalence in Korea, should give the most accurate estimates, but are more costly to perform and typically limited to the number of study subjects.

The recent study presents autism prevalence in Sweden, using the Stockholm Youth Cohort (a medical registry). The paper, Autism Spectrum Disorders in the Stockholm Youth Cohort: Design, Prevalence and Validity, is in the journal PLoS ONE, which means the full article is available online.

A previous report, from 2006, gave the prevalence of autistic disorder in Sweden (from data in 2001) at 20.5 per 10,000, with other ASD’s at 32.9 per 10,000. This for a population born from 1977-1994. The prevalence in the youngest population in the study (7-12 years old at time of the study) was 1.23%. Yes, 1.23% for kids born in 1989-1994. That’s a prevalence comparable to the recent CDC estimate for U.S. kids born in 2000.

Back to the present Sweden study. The authors note the potential problem with using medical registries:

Furthermore, Scandinavian studies have frequently ascertained ASD cases via health care registries [8], [9], [10], [11]. This approach may underestimate the prevalence of ASD, since affected children require social and educational interventions more often than health care.

Stockholm county has a very active surveillance program:

All ASD related services, including diagnosis and follow-up health, special educational and social care are provided by services run by, or contracted with the Stockholm County Council and available free of charge. Referrals for diagnostic evaluation of suspected ASD are commonly made by child healthcare centres, whose health- and developmental surveillance program engages 99.8% of all preschool children [15]. Developmental surveillance is performed by specially trained child healthcare centre nurses at regular intervals (1, 2, 6, 10–12, 18, 36, 48 and 60 months of age), with examination by a paediatrician at key ages (2, 6, 10–12 months) and in case of developmental deviation or according to need at other age intervals. Speech abilities and language comprehension are evaluated by nurses at 36 and 48 months, and examination of sight and hearing is made at 48 months.

Interestingly, even with this tight surveillance effort, the median age of diagnosis is 8. Children with intellectual disability were identified as autistic earlier. Girls were identified later.

Where such information was available (n = 148), the median age at diagnosis was 8.0 years for ASD overall (range 1–19, interquartile range [IQR] 8.0). For cases without and with intellectual disability (n = 80 and 68), the corresponding ages were 11.5 (range 4–19, IQR 6.0) and 6.0 (range 1–17, IQR 4.0) years. Girls (n = 48) were older than boys (n = 100) at diagnostic assessment (median age 11.0 as compared to 8.0 years).

The authors were able to test the validity of the diagnoses by checking on a subset of autistic children (starting from a sample of 100 with and 100 without intellectual disability). The researchers were able to check records on 85% of this subset, and 96% of the records checked were consistent with a diagnosis of ASD.

Unlike U.S. CDC prevalence estimates, this study gives prevalence estimates for a range of ages. The graph below (and larger here) is part of Figure 1 from the study:

The prevalence is given for children born between 1983 and 2003, with a peak ASD prevalence of about 1.5% for children born between 1990 and 1997. Lower autism prevalence for younger children is likely due to underdiagnosis: the average age of diagnosis being about 8. The lower prevalence for older autistics is possibly due to “key registers used for case ascertainment only being started in 1997 and 2001, respectively, may have deflated the observed ASD prevalence among older children.”

For those interested in how this ties into the failed notion of thimerosal causing an autism epidemic: Swedish children had low exposures to thimerosal in the 1980’s and it was phased out in 1993. The flat prevalence though the 1990’s speaks strongly against the notion. In fact, the data, especially for autistics without intellectual disability, speaks against a strong rise in autism prevalence, especially during the 1990’s.

The prevalence of ASD without intellectual disability is higher than that with ID throughout the entire age range of the study. The Male:Female ratio (not shown in the graph above) changes with age. It is often about 4-5 to 1, with males predominant. For the older individuals, the ratio decreased from 5.1:1 at age 8 to 1.9:1 at age 18.

What’s most important is that this is only the first report on the autistics in the Stockholm Youth Cohort. The researchers now have a cross section of ages to work with to look at outcomes, risk factors and other studies.

Here is the abstract for the study:

Objective
Reports of rising prevalence of autism spectrum disorders (ASD), along with their profound personal and societal burden, emphasize the need of methodologically sound studies to explore their causes and consequences. We here present the design of a large intergenerational resource for ASD research, along with population-based prevalence estimates of ASD and their diagnostic validity.

Method
The Stockholm Youth Cohort is a record-linkage study comprising all individuals aged 0–17 years, ever resident in Stockholm County in 2001–2007 (N = 589,114). ASD cases (N = 5,100) were identified using a multisource approach, involving registers covering all pathways to ASD diagnosis and care, and categorized according to co-morbid intellectual disability. Prospectively recorded information on potential determinants and consequences of ASD were retrieved from national and regional health and administrative registers. Case ascertainment was validated through case-note review, and cross validation with co-existing cases in a national twin study.

Results
The 2007 year prevalence of ASD in all children and young people was 11.5 per 1,000 (95% confidence interval 11.2–11.8), with a co-morbid intellectual disability recorded in 42.6% (41.0–44.2) of cases. We found 96.0% (92.0–98.4) of reviewed case-notes being consistent with a diagnosis of ASD, and confirmed ASD in 85.2% (66.2–95.8) of affected twins.

Conclusions
Findings from this contemporary study accords with recently reported prevalence estimates from Western countries at around 1%, based on valid case ascertainment. The Stockholm Youth Cohort, in light of the availability of extensive information from Sweden’s registers, constitutes an important resource for ASD research. On-going work, including collection of biological samples, will enrich the study further.

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By Matt Carey

What factors are there that may influence a child being autistic? What might increase or lower the chances that any given child will be diagnosed with autism? These are obviously major questions within the autism stakeholder communities and the autism research community. There have been indications since the 1970’s that the prenatal environment might play a key role in some part of autism. The work of Stella Chess pointed to congenital rubella syndrome as a risk factor for autism. Since then other possible exposures during pregnancy have been identified, including thalidomide, valproic acid and others. But while these exposures point to gestation as the key period for environmental risks, there is no reason to expect that they are an exhaustive list.

The journal Pediatrics released a new autism study today which presents more possible risk factors: Maternal Metabolic Conditions and Risk for Autism and Other Neurodevelopmental Disorders.  The study by authors from the University of California, Davis (including the MIND Institute) and Vanderbilt University. One thing I like about Pediatrics is that they give good lay summaries of the papers they publish, with “what is known on this subject” and “what this study adds”. In this case:

WHAT’S KNOWN ON THIS SUBJECT: Diabetes during pregnancy has been associated with general development impairments in
offspring; however, associations between autism and maternal diabetes have been inconsistent. Few studies have examined
related conditions accompanied by underlying increased insulin resistance and their association with developmental outcomes.

WHAT THIS STUDY ADDS: This population-based study in young children provides evidence that maternal metabolic conditions
are a risk factor for autism, developmental delay without autistic symptoms, and impairments in several domains of development,
particularly expressive language, after adjusting for sociodemographic and other characteristics.

The study, part of the CHARGE Study, posed the question of whether metabolic conditions (MC’s) in pregnant women pose a risk for autism and other developmental disabilities. In specific, they looked at maternal diabetes, hypertension, and obesity as risk factors. They found that in their study group, mothers who reported that they had these MC’s were more likely to have children with autism or other developmental disabilities. For autism, the risk was 60% higher (odds ratio 1.61) while for developmental disabilities the risk was over double (odds ratio 2.35) when the mother had one of these metabolic condition.

If this sounds somewhat familiar, it’s worth noting that preliminary results from this study were presented at IMFAR last year and this study was highlighted at the press conference.

The CHARGE study draws families locally to the MIND Institute by way of the regional centers, recruitment efforts by MIND personnel (my family was recruited but was just outside the catchment area at 130 miles from MIND). One strength of the CHARGE study is that they don’t rely upon existing records; they test each child (ADOS, ADI-R, Mullen Scales of Early Learning, Vineland, etc.) in-house. Information on metabolic conditions during pregnancy were taken from structured interviews with some cross-checking of medical records to confirm the accuracy of the interviews:

Demographic and medical information was obtained from the CHARGE Environmental Exposure Questionnaire
(EEQ; available for 97.6% of participants), birthfiles, and medicalrecords (available for 57.7% of participants). The EEQ is a structured telephoneadministered interview with the biological mother and includes questions about demographic characteristics,
maternal medical history, and various environmental exposures. Trained study staff extracted data from medical records

The primary focus metabolic condition was diabetes (type 2 diabetes and gestational diabetes) with obesity (body mass index >30) and hypertension also studied.

Table 2 from the paper (click to enlarge) shows the odds ratio for autism spectrum disorders (ASD) and other developmental disorders (DD) vs. typically developing (TD) for children born to mothers with diabetes and other maternal metabolic conditions:

As noted above, the odds are about 50% higher (and more, depending on condition) for ASD, and even higher for other developmental disabilities. The authors didn’t stop there. They explored how these maternal metabolic conditions might affect language and other measures of development. Table 3 (click to enlarge) shows comparisons of test scores for children with and without ASD and whose mothers had or did not have diabetes. (MSEL: Mullen Scales of Early Learning. VABS: Vineland Adaptive Behavior Scales)

Maternal diabetes may result in lower language scores, for both ASD and non-ASD kids. The authors wrote:

Within the ASD group, children of mothers with diabetes performed 0.37 SD lower on the MSEL expressive language scale compared with children of nondiabetic mothers (P = .01; Table 3); MSEL receptive language and VABS communication scores were also lower among children of diabetic mothers, with differences approaching statistical significance. No significant differences in MSEL or VABS scores were observed regarding MCs collectively among children with ASD.

The authors repeated the comparison, but for all metabolic conditions instead of just diabetes. Their Table 4 (click to enlarge) showed that there were no significant differences within the ASD group on maternal metabolic conditions. But for the non-ASD group, on every measure of the Mullens and Vineland tests, children of mothers with metabolic conditions scored lower than children whose parents did not have diabetes, obesity and/or hypertension.

This shouldn’t be surprising since the non-ASD group includes those with developmental disabilities other than ASD. So in some way this is basically telling that story in another way: maternal metabolic conditions increase the risk of developmental disabilities.

The study was relatively large, with 1004 subjects. Some of the subgroups were small, limiting the power of the study in those areas. These numbers can be found in Table 2. The most common maternal metabolic condition, by far, was obesity. The number of children whose mothers had hypertension were relatively few, leading to large confidence intervals for those odds ratios.

Another limitation is that they rely upon parent-reported medical conditions. The authors address this issue and tie together the conditions studied (diabetes, hypertension and obesity) in this paragraph:

Reliance on self-reported medical conditions was a limitation of this study. However, in the 56% of participants for
whom medical records were available, we found the 2 sources to be in good agreement. Thus, despite this limitation, we can have confidence in our results. Furthermore, although biological measurements (eg, glucose, insulin, lipids, immune biomarkers) before and during pregnancy would have been ideal, we chose conditions (T2D/GDM, hypertension, and obesity) highly indicative of increased insulin resistance as proxy measures of dysregulated metabolism and chronic inflammation because we lacked these biological measurements for most of the participants.

Without biological measurements during pregnancy the authors can’t draw specific conclusions about what behind these conditions might raise the risks of autism and developmental disorders. But they do pose some possibilities such as increased levels of glucose, fetal iron deficiency, increased levels of the cytokine interleukin-6 and others.

In the end, the authors conclude rather simply:

The prevalence of obesity and diabetes among US women of childbearing age is 34% and 8.7%, respectively. Our findings raise concerns that these maternal conditions may be associated with neurodevelopmental problems in children and therefore could have serious public health implications.

Until these results are replicated, these maternal metabolic conditions should be considered as strong potential candidates for autism risk factors. As the authors say, “these maternal conditions may be associated with neurodevelopmental problems in children”. But such a conservative conclusion takes nothing away from the potential impact of this study nor the fact that researchers can start to incorporate this new information into their models of autism etiology right away.

The paper: Maternal Metabolic Conditions and Risk for Autism and Other Neurodevelopmental Disorders
The authors: Paula Krakowiak, MS, Cheryl K. Walker, MD, Andrew A. Bremer, MD, PhD, Alice S. Baker, BA, Sally
Ozonoff, PhD, Robin L. Hansen, MD, and Irva HertzPicciotto, PhD

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by Matt Carey

There has been a great deal of media coverage recently about the new autism prevalence estimate released by the CDC. The CDC provides a good summary page on prevalence data as well as the full report. If those who may see the report as a bit long, here is a bit of a summary of the findings.

The United States Centers for Disease Control (CDC) releases autism prevalence estimates as part of their MMWR (Morbidity and Mortality Weekly Report). They also maintain a page of information on autism. Today the CDC released the latest MMWR on autism: Prevalence of Autism Spectrum Disorders — Autism and Developmental Disabilities Monitoring Network, 14 Sites, United States, 2008. The one number from it that will be quoted most often is “1 in 88”, the new prevalence estimate.

The researchers working for the CDC use existing records: school, medical or both. So, in one area they may use school records. In another they may use school and medical records. What they don’t do is actually screen individual children and give them tests like the ADOS. This means that if a kid is not flagged somewhere in the records, they won’t find him/her. On the other hand, they don’t just count which kids already have autism diagnoses. They review the records and evaluate them to determine which kids are autistic or not. They cross check, meaning that for some fraction of the kids they use more than one person to check the records and they see how well the various researchers agree.

The CDC works with groups in a subset of states in the U.S.. For this report they used Alabama, Arizona, Arkansas, Colorado, Florida, Maryland, Missouri, New Jersey, North Carolina, Pennsylvania, South Carolina, Utah, West Virginia, and Wisconsin, most of which were used in previous reports.

Overall, the prevalence was 1 in 88 (11.3 per 1,000). This continues the upward trend in prevalence estimates from the CDC. This figure (here for bigger) is from the CDC:

This varied a great deal state-to-state. Alabama had the lowest estimated prevalence at 4.1 per 1,000. Utah the highest at 21.2 per 1,000. Or, there is about a five fold variation in autism prevalence estimates, state-to-state.

Prevalence estimates also varied by race/ethnicity. The report states “the estimated prevalence among non-Hispanic white children (12.0 per 1,000) was significantly greater than that among non-Hispanic black children (10.2 per 1,000) and Hispanic children (7.9 per 1,000). ” The estimate for Hispanic in Alabama was 1.4 per 1,000 and for whites in Utah as 40 per 1,000. More than a 20 fold difference.

This figure (click to enlarge)was interesting in showing two things. First in showing the state-to-state variability in prevalence estimates. The second interesting point to me is the difference between sites with just medical records and those with medical and education records. The sites with health-only records have lower prevalence estimates. i.e. more kids are picked up by their school records.

As with previous CDC reports, a large fraction of the children identified were not classified as autistic previously. This figure (click to enlarge) shows state-by-state and year-by-year what percent were previously unidentified. The figure also shows how many were previously unidentified but where a suspicion of autism was noted. In 2002, as many as 40% in some states were not classified as autistic before their records were reviewed. In general, over time the fraction previously unidentified has gone down. This would be consistent with schools and medical personnel getting better over time with identification of autism.

Many children identified had IQ test scores (or examiner statements) showing “normal” or borderline-normal values. This figure (click to enlarge) shows the percentages in many states with IQ>85, IQ=71–85 and IQ<70 (for children where the IQ data were available).

In Utah, for an extreme example, over 70% of those identified as autistic have IQ scores above 85. The CDC report reads:

When data from these seven sites were combined, 38% of children with ASDs were classified in the range of intellectual disability (i.e., IQ >70 or an examiner’s statement of intellectual disability), 24% in the borderline range (IQ 71–85), and 38% had IQ scores >85 or an examiner’s statement of average or above-average intellectual ability.

I.e. most children were borderline or above. Of course, the other way to read this is most children were borderline or below. Intellectual Disability is roughly defined as IQ below 70, so most children (about 62%) identified as autistic in this report were not intellectually disabled. States with higher prevalence estimates had higher percentages of non-intellectually disabled children.

The prevalence estimates are going up with time.

While ASD prevalence estimates in the overall population increased 23% for the 2-year period 2006–2008, and 78% during the 6-year period 2002–2008, the largest increases over time were noted among Hispanic children and non-Hispanic black children and among children without co-occurring intellectual disability. Better identification in these specific groups explains only part of the overall increase, however, as estimated ASD prevalence increased in all groups when data were stratified by sex, race/ethnicity, and intellectual ability.

The CDC report does have some limitations, and they note two primary limitations:

First, increases in awareness and access to services have improved the ability of the ADDM Network to identify children with ASD over time, and this likely contributes to the increase in estimated prevalence. The proportion of the increase that is attributable to such changes in case ascertainment or attributable to a true increase in prevalence of ASD symptoms cannot be determined. Ongoing monitoring is an important tool to learn why more children are being identified with ASDs and can provide important clues in the search for risk factors.

This study can’t say if there is an increase in the number of autistic children, or if there is, what would be the cause.

Also,

Second, the surveillance areas were not selected to be representative of the United States as a whole, nor were they selected to be representative of the states in which they are located. Limitations regarding population size, surveillance areas, and the consistency of these attributes were considered when analysts evaluated comparisons across multiple time points.

So, these numbers may not represent the United States as a whole.

It is valid to say that while these factors limit the ability of the CDC to define a true autism rate for the United States, the factors that go into these limitations are valid research concerns in themselves. It is very much worthwhile and valuable to ask why there are such variations state-to-state, for example. Answering this could lead to better identification and service provision overall. Likewise, understanding the effects of rising awareness could feed back into more efficient awareness campaigns to, again, help in identifying more autistic children and providing support and services to them.

The CDC concludes:

ASDs continue to be an important public health concern. The findings provided in this report confirm that prevalence estimates of ASD continue to increase in the majority of ADDM Network communities, and ongoing public health surveillance is needed to quantify and understand these changes over time. Further work is needed to evaluate multiple factors affecting ASD prevalence over time. ADDM Network investigators continue to explore these factors in multiple ways, with a focus on understanding disparities in the identification of ASDs among certain subgroups and evaluating temporal changes in the prevalence of ASDs. CDC also is engaged with other federal, state, and private partners in a coordinated response to identify risk factors for ASDs and meet the needs of persons with ASDs and their families. Additional information is available at http://www.cdc.gov/autism.

We need these data. Limitations and all. We need to know what the autism prevalence is, what the makeup is of the autistic population, and where we can do better identifying autisics. Most countries have no autism prevalence information. Other countries have few or even just one study. In my opinion we are fortunate to have the CDC and other researchers focusing on these questions here in the United States.

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By Matt Carey

We live in a plugged-in world. With the internet and smart phones, people never have to be more than a step away from a vast amount of information. I know people who wake up and pretty much immediately check email, Facebook, Twitter, etc.. I’m one of them. Except that I wake up and check for the latest emails from PubMed. I have a number of alerts set up, and it just so turns out that the emails arrive just about as I wake up each day.

The growth in published autism research has been amazing. In 1990 there were 55 abstracts under the topic “autism.” 55 total.
Today, there are days when dozens of abstracts come in on autism, plus more on intellectual disability, developmental disability and other topics I monitor. Most have seen graphs of the growth in the numbers of children diagnosed with autism throughout the 1990’s and 2000’s. I once plotted the number of autism-related research abstracts by year and, after normalizing, found an amazing correlation between the number of abstracts and the number of clients in the California Department of Developmental Disabilities in the autism category. If correlation were causation, we could say that autism research causes autism. More likely is that the same awareness factors are behind much of the increases in diagnoses as well as the number of researchers entering the field.

Below I discuss just a few of the many studies that have recently come out. They are a good cross section of the many areas of autism research being actively pursued today. Mostly, they are the studies which, for one reason or another, caught my eye.

Autism is a broad area of research, and the abstracts reflect that. For example, language delays are common with autism. One question I have personally seen come up is whether a bilingual household would contribute to speech delays. Two recent studies, one from McGill and one from the University of British Columbia indicate that no, bilingual environments do not add to delays. The McGill team wrote “Bilingually-exposed children with ASDs did not experience additional delays in language development”. Perhaps these will help autism parents in multilingual families with the decision about whether to expose their children to more than one language.

Of course, a major focus of autism research involves causation. One in the series of studies using data from Denmark suggests that the risk of autism may be somewhat higher for infants whose amniotic fluid has higher levels of the Monocyte Chemotactic Protein-1 (MCP-1) chemokine.

Low birth weight has been reported to be a risk factor for autism, with a five times higher risk. Some news outlets were confused in their reporting, and cited the risk as higher for preterm births, which was not the focus of the study.

Researchers at Kings College London studied adults diagnosed with autism as children and whether they developed epilepsy. By adulthood, 22% had developed epilepsy, with most the onset was after age 10. Most had generalised tonic–clonic seizures. Thankfully, the majority (28/31) were able to control their seizures with medication, but this goes to show that more work is needed in understanding epilepsy and how to control it.

Personally, I am curious as to whether the 22% prevalence figure will change over time. The characteristics of the autism population are changing with time. California Department of Developmental Services (CDDS) statistics show that the fraction of their clients with epilepsy was going down with time. The adults in the Kings College study were diagnosed in the 1990’s, a time when the CDDS client base had a larger fraction with epilepsy.

A recent study from Stanford looking at adults in Sweden is interesting in that it claims a strong risk for epilepsy with preterm births, in a somewhat tangentially complimentary result to the low birthweight study noted above.

A Harvard study using the Nurse’s Health Study II looked at pregnancy complications and the risk of autism. They found that in general complicated pregnancies increase the risk of autism (about 50% greater risk) and that gestational diabetes in specific was associated with about 75% greater risk.

While studies such as this from the Nurse’s Health Study point to potential prenatal risk factors, developmentally, the first year or two after birth are a time when autistic children often show differences compared to non-autistic peers. For example, in 2003 Eric Courchesne’s group at UCSD discovered that brain overgrowth–rapid growth of the brain during the first years of life–was common in autistic children. A recent study by the Yale Child Center (paper available in full online) found that not only were the brains in autistics on average larger, but the infants were longer and heavier. The increased skeletal growth was evident at 4-5 months, and preceded the head circumference growth which became apparent at 10-11 months.

Autism is diagnosed based on behaviors. This makes diagnosing autism far from a fast process. This is a problem not just for those seeking the diagnosis, but also for researchers looking to expand the number of study subjects available. A study out of Vanderbilt looks at using parent reporting methods as a rapid screening method. In particular they looked at the Social Communication Questionnaire and the Social Responsiveness Scale. While they found that these methods can give rapid results, the slower clinical assessments are still required: “While the rapid phenotyping measures were able to accurately identify a large number of children with ASD, they also frequently failed to differentiate children with ASD from children with other complex neurobehavioral profiles.”

Two more studies from Vanderbilt caught my eye, and these look at family members of developmentally disabled children. One looked at depressive symptoms in mothers following the diagnosis of autism in their children. The study is relatively small, but the authors wrote: “Depressive symptoms immediately following diagnosis were not related to initial global characteristics of child functioning, but were related to reported child problem behaviors and financial barriers at follow-up.” While not specific to autism, another Vanderbilt study considered whether siblings of children with mild intellectual deficits were more likely to work in helping professions or in volunteerism as adults. They found that female siblings were more likely to be in these “helping” professions than male siblings.

Researchers at Harvard and UCLA looked at neurological co-morbidities in autistic individuals. They found that epilepsy, sleep disorders and motor impairments were common.

These are just a few of the studies which have come out in the past couple of weeks. Not every week sees a breakthrough in research in any field. But as long as autism research is supported, every week is a step forward.

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