Trends in the prevalence of autism on the basis of special education data

Who Is Attending? The Role of Child Ethnicity and Maternal Demographics in Research Engagement and Early Identification of Autism

Inequitable access to early autism developmental surveillance is evident globally. However, there is limited research examining autism diagnosis, ethnicity, and community profiles when engaging in research for the early identification of autism. We aimed to understand the relationships between child ethnicity, maternal demographics, and autism diagnosis, comparing retrospective data from the 2016 census for eight local government areas (LGAs) in Victoria, Australia. Maternal and child health (MCH) nurses monitored 13,511 children under 42 months for the early signs of autism using the Social Attention Communication Surveillance-Revised (SACS-R) and SACS-R Preschool (SACS-PR) tools during well-child checks. Of these, 340 children with a "high likelihood" of autism attended developmental assessments. Participants' maternal ethnicity ('European maternal ethnicity', EME; 'non-European maternal ethnicity,' N-EME; 'mixed maternal ethnicity,' MME'), socioeconomic factors, and autism prevalence were compared to their LGA community. Results indicated that study participants were representative of their LGA communities, though bi- and multilingualism was higher in our cohort. Differences in current maternal employment, maternal education, annual family income, and autism prevalence were found between the N-EME, EME, and MME groups. Our study found that research engagement was driven by maternal education, maternal employment, and annual family income, and further research is required to understand these relationships.

Dual Identification: Trajectories to English Proficiency for English Learners with Autism Spectrum Disorder

BACKGROUND

There are an increasing number of English Learners (EL) served in schools, including children with Autism Spectrum Disorder (ASD). However, little is known about students who receive school-based services as EL and under autism eligibility.

PURPOSE & METHODS

The present study aimed to examine the sociodemographic characteristics, time to English Language Proficient status by survival analysis, and predictors of English fluency utilizing a logistic regression for dually identified EL and autism eligible students in a large urban school district during the 2011-2019 academic school years.

RESULTS

Overall, dually identified students (N = 849) educated in segregated settings (N = 372) became English proficient at lower rates and at older ages than students included in general education (N = 477).

CONCLUSION

Students placed in segregated special education classrooms were significantly less likely to achieve English Language Proficient classification. The present study begins to illustrate the time to English proficiency of dually identified students and the potential impact it has on their educational opportunities.

Time trends in autism diagnosis over 20 years: a UK population-based cohort study

BACKGROUND

Autism spectrum disorder is a diagnosis that is increasingly applied; however, previous studies have conflicting findings whether rates of diagnosis rates continue to grow in the UK. This study tested whether the proportion of people receiving a new autism diagnosis has been increasing over a twenty-year period, both overall and by subgroups.

METHOD

Population-based study utilizing the Clinical Practice Research Datalink (CPRD) primary care database, which contains patients registered with practices contributing data to the CPRD between 1998 and 2018 (N = 6,786,212 in 1998 to N = 9,594,598 in 2018). 65,665 patients had a diagnosis of autism recorded in 2018. Time trend of new (incident) cases of autism diagnosis was plotted for all, and stratified by gender, diagnostic subtypes, and developmental stage: infancy and preschool, 0-5 years old; childhood, 6-11 years old; adolescence, 12-19 years old; adults, over 19 years old.

RESULTS

There was a 787%, exponential increase in recorded incidence of autism diagnoses between 1998 and 2018; R²  = 0.98, exponentiated coefficient = 1.07, 95% CI [1.06, 1.08], p < .001. The increase in diagnoses was greater for females than males (exponentiated interaction coefficient = 1.02, 95% CI [1.01, 1.03], p < .001) and moderated by age band, with the greatest rises in diagnostic incidence among adults (exponentiated interaction coefficient = 1.06, 95% CI [1.04, 1.07], p < .001).

CONCLUSIONS

Increases could be due to growth in prevalence or, more likely, increased reporting and application of diagnosis. Rising diagnosis among adults, females and higher functioning individuals suggest augmented recognition underpins these changes.

Association Between Essential Metal Elements and the Risk of Autism in Chinese Han Population

Essential metal elements (EMEs) have essential roles in neurological development and maintenance of human homeostasis. We performed a case-control study to explore association between the risk of autism spectrum disorder (ASD) and the 11 EMEs [Calcium (Ca), potassium (K), magnesium (Mg), sodium (Na), manganese (Mn), selenium (Se), cobalt (Co), Molybdenum (Mo), copper (Cu), zinc (Zn), and iron (Fe)] in serum. Ninety-two autistic subjects (cases) and age-sex-matched healthy subjects (controls = 91) from Beijing, China were recruited. In addition, totally 109 mothers of recruited children participated in this study. ICP-AES and ICP-MS were applied to determine the concentration of 11 EMEs in serum. The concentrations of Ca, K, and Mg were significantly higher in the cases than in the controls (OR [95% CI]: 1.031 [1.006-1.058] for Ca; 1.081 [1.046-1.118] for K; 1.161 [1.012-1.331] for Mg), while the concentrations of Zn and Cu were significantly lower (0.997 [0.995-0.999] for Cu; 0.996 [0.992-1.000] for Zn). Clear dose-response relationships between EMEs concentrations and the risk of ASD, as well as the correlation between EME concentrations and the severity of ASD were observed for most of the above EMEs. Six and seven specific correlated pairs between mothers and children were found in the cases and controls separately. The overall profiles of the EMEs were changed in the cases as compared to the controls. This study suggested that the higher levels of Ca, K, and Mg and lower levels of Zn and Cu may be associated with an elevated risk of ASD.

Prevalence of autism spectrum disorder in a large, diverse metropolitan area: Variation by sociodemographic factors

Autism spectrum disorder (ASD) prevalence estimates have varied by region. In this study, ASD prevalence, based on active case finding from multiple sources, was determined at the county and school district levels in the New Jersey metropolitan area. Among children born in 2008, residing in a four-county area and enrolled in public school in 2016, ASD prevalence was estimated to be 36 per 1000, but was significantly higher in one region-54 per 1000 and greater than 70 per 1000, in multiple school districts. Significant variation in ASD prevalence by race/ethnicity, socioeconomic status (SES), and school district size was identified. Highest prevalence was in mid-SES communities, contrary to expectation. Prevalence among Hispanic children was lower than expected, indicating a disparity in identification. Comprehensive surveillance should provide estimates at the county and town levels to appreciate ASD trends, identify disparities in detection or treatment, and explore factors influencing change in prevalence. LAY SUMMARY: We found autism prevalence to be 3.6% in New Jersey overall, but higher in one region (5.4%) and in multiple areas approaching 7.0%. We identified significant variation in autism spectrum disorder (ASD) prevalence by race/ethnicity, socioeconomic status (SES) and school district size. Mapping prevalence in smaller, well-specified, regions may be useful to better understand the true scope of ASD, disparities in ASD detection and the factors impacting ASD prevalence estimation.

Who gains and who loses? Sociodemographic disparities in access to special education services among autistic students

Little is known about differences in the allocation of special education services to students with autism compared with students with other primary learning differences (e.g., intellectual disability [ID], specific learning disability [SLD]) and the comparative impact of sociodemographic factors on special education service receipt. The present study aimed to compare allocation of services (i.e., quantity and types) between students eligible for special education services under autism, SLD and ID, and to identify differences in sociodemographic predictors (e.g., race, neighborhood income) of service allocation. Data were culled from special education administrative records from a large urban, primarily Hispanic, Latino, or Spanish-serving school district from academic years 2011-2012 to 2016-2017. Participants included N = 76,428 students (N_autism  = 18,151, N_SLD  = 54,001, N_ID  = 4,276) ages 2-18. Results showed that autistic students received, on average, more services than students with SLD. Services received by students served under autism and SLD eligibility were more congruent with areas of need (e.g., language, occupational therapy) relative to students served under ID. Student-level socioeconomic status (free and reduced lunch) was more positively predictive of the number of special education services received than the neighborhood income of the school the student attended. Finally, the most significant racial disparities in service allocation were observed among students served under autism eligibility. The present study demonstrates the critical role of economic resources in the quantity and types of services received, and the desirability of a public education for well-resourced families who are possibly best situated to navigate special education services. LAY SUMMARY: An eligibility of autism in special education confers a significant advantage in the number of services a student receives. Disparity in the quantity of special education services exists among autistic students across many sociodemographic factors. Most notably, greater allocation of services to non-Hispanic, Latino, or Spanish, White American, European American, or Middle Eastern American students and students who do not receive free and reduced lunch.

Prevalence of Autism Spectrum Disorder in China: A Nationwide Multi-center Population-based Study Among Children Aged 6 to 12 Years

This study aimed to obtain the first national estimate of the prevalence of autism spectrum disorder (ASD) in Chinese children. We targeted the population of 6 to 12-year-old children for this prevalence study by multistage convenient cluster sampling. The Modified Chinese Autism Spectrum Rating Scale was used for the screening process. Of the target population of 142,086 children, 88.5% (n = 125,806) participated in the study. A total of 363 children were confirmed as having ASD. The observed ASD prevalence rate was 0.29% (95% CI: 0.26%-0.32%) for the overall population. After adjustment for response rates, the estimated number of ASD cases was 867 in the target population sample, thereby achieving an estimated prevalence of 0.70% (95% CI: 0.64%-0.74%). The prevalence was significantly higher in boys than in girls (0.95%; 95% CI: 0.87%-1.02% versus 0.30%; 95% CI: 0.26%-0.34%; P < 0.001). Of the 363 confirmed ASD cases, 43.3% were newly diagnosed, and most of those (90.4%) were attending regular schools, and 68.8% of the children with ASD had at least one neuropsychiatric comorbidity. Our findings provide reliable data on the estimated ASD prevalence and comorbidities in Chinese children.

The Prevalence of Parent-Reported Autism Spectrum Disorder Among US Children

: media-1vid110.1542/5839990273001PEDS-VA_2017-4161Video Abstract OBJECTIVES: To estimate the national prevalence of parent-reported autism spectrum disorder (ASD) diagnosis among US children aged 3 to 17 years as well as their treatment and health care experiences using the 2016 National Survey of Children's Health (NSCH).

METHODS

The 2016 NSCH is a nationally representative survey of 50 212 children focused on the health and well-being of children aged 0 to 17 years. The NSCH collected parent-reported information on whether children ever received an ASD diagnosis by a care provider, current ASD status, health care use, access and challenges, and methods of treatment. We calculated weighted prevalence estimates of ASD, compared health care experiences of children with ASD to other children, and examined factors associated with increased likelihood of medication and behavioral treatment.

RESULTS

Parents of an estimated 1.5 million US children aged 3 to 17 years (2.50%) reported that their child had ever received an ASD diagnosis and currently had the condition. Children with parent-reported ASD diagnosis were more likely to have greater health care needs and difficulties accessing health care than children with other emotional or behavioral disorders (attention-deficit/hyperactivity disorder, anxiety, behavioral or conduct problems, depression, developmental delay, Down syndrome, intellectual disability, learning disability, Tourette syndrome) and children without these conditions. Of children with current ASD, 27% were taking medication for ASD-related symptoms, whereas 64% received behavioral treatments in the last 12 months, with variations by sociodemographic characteristics and co-occurring conditions.

CONCLUSIONS

The estimated prevalence of US children with a parent-reported ASD diagnosis is now 1 in 40, with rates of ASD-specific treatment usage varying by children's sociodemographic and co-occurring conditions.

Trends in Special Education Eligibility Among Children With Autism Spectrum Disorder, 2002-2010

OBJECTIVE

Although data on publicly available special education are informative and offer a glimpse of trends in autism spectrum disorder (ASD) and use of educational services, using these data for population-based public health monitoring has drawbacks. Our objective was to evaluate trends in special education eligibility among 8-year-old children with ASD identified in the Autism and Developmental Disabilities Monitoring Network.

METHODS

We used data from 5 Autism and Developmental Disabilities Monitoring Network sites (Arizona, Colorado, Georgia, Maryland, and North Carolina) during 4 surveillance years (2002, 2006, 2008, and 2010) and compared trends in 12 categories of special education eligibility by sex and race/ethnicity. We used multivariable linear risk regressions to evaluate how the proportion of children with a given eligibility changed over time.

RESULTS

Of 6010 children with ASD, more than 36% did not receive an autism eligibility in special education in each surveillance year. From surveillance year 2002 to surveillance year 2010, autism eligibility increased by 3.6 percentage points ( P = .09), and intellectual disability eligibility decreased by 4.6 percentage points ( P < .001). A greater proportion of boys than girls had an autism eligibility in 2002 (56.3% vs 48.8%). Compared with other racial/ethnic groups, Hispanic children had the largest increase in proportion with autism eligibility from 2002 to 2010 (15.4%, P = .005) and the largest decrease in proportion with intellectual disability (-14.3%, P = .004).

CONCLUSION

Although most children with ASD had autism eligibility, many received special education services under other categories, and racial/ethnic disparities persisted. To monitor trends in ASD prevalence, public health officials need access to comprehensive data collected systematically, not just special education eligibility.

A Predictive Coding Account of Psychotic Symptoms in Autism Spectrum Disorder

The co-occurrence of psychotic and autism spectrum disorder (ASD) symptoms represents an important clinical challenge. Here we consider this problem in the context of a computational psychiatry approach that has been applied to both conditions-predictive coding. Some symptoms of schizophrenia have been explained in terms of a failure of top-down predictions or an enhanced weighting of bottom-up prediction errors. Likewise, autism has been explained in terms of similar perturbations. We suggest that this theoretical overlap may explain overlapping symptomatology. Experimental evidence highlights meaningful distinctions and consistencies between these disorders. We hypothesize individuals with ASD may experience some degree of delusions without the presence of any additional impairment, but that hallucinations are likely indicative of a distinct process.

Description and Validation of a Computerized Behavioral Data Program: "BDataPro"

BDataPro is a Microsoft Windows®-based program that allows for real-time data collection of multiple frequency- and duration-based behaviors, summary of behavioral data (in terms of average responses per min, percentage of 10-s intervals, and cumulative responses within 10-s bins), and calculation of reliability coefficients. The current article describes the functionality of the program. BDataPro is freely available for download from the authors' institution websites.

Development of a Machine Learning Algorithm for the Surveillance of Autism Spectrum Disorder

The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts population-based surveillance of autism spectrum disorder (ASD) among 8-year old children in multiple US sites. To classify ASD, trained clinicians review developmental evaluations collected from multiple health and education sources to determine whether the child meets the ASD surveillance case criteria. The number of evaluations collected has dramatically increased since the year 2000, challenging the resources and timeliness of the surveillance system. We developed and evaluated a machine learning approach to classify case status in ADDM using words and phrases contained in children's developmental evaluations. We trained a random forest classifier using data from the 2008 Georgia ADDM site which included 1,162 children with 5,396 evaluations (601 children met ADDM ASD criteria using standard ADDM methods). The classifier used the words and phrases from the evaluations to predict ASD case status. We evaluated its performance on the 2010 Georgia ADDM surveillance data (1,450 children with 9,811 evaluations; 754 children met ADDM ASD criteria). We also estimated ASD prevalence using predictions from the classification algorithm. Overall, the machine learning approach predicted ASD case statuses that were 86.5% concordant with the clinician-determined case statuses (84.0% sensitivity, 89.4% predictive value positive). The area under the resulting receiver-operating characteristic curve was 0.932. Algorithm-derived ASD "prevalence" was 1.46% compared to the published (clinician-determined) estimate of 1.55%. Using only the text contained in developmental evaluations, a machine learning algorithm was able to discriminate between children that do and do not meet ASD surveillance criteria at one surveillance site.

Prevalence of Autism Spectrum Disorders in Ecuador: A Pilot Study in Quito

This research presents the results of the first phase of the study on the prevalence of pupils with Autism Spectrum Disorder (ASD) in regular education in Quito, Ecuador. One-hundred-and-sixty-one regular schools in Quito were selected with a total of 51,453 pupils. Prevalence of ASD was assessed by an interview with the rector of the school or its delegate. Results show an extremely low prevalence of 0.11 % of pupils with any ASD diagnosis; another 0.21 % were suspected to have ASD, but were without a diagnosis. This low prevalence suggests that children and adolescents with ASD are not included in regular education in Quito. These results are discussed in the light of low diagnostic identification of ASD and low inclusion tolerance.

Comorbidity of intellectual disability confounds ascertainment of autism: implications for genetic diagnosis

While recent studies suggest a converging role for genetic factors towards risk for nosologically distinct disorders including autism, intellectual disability (ID), and epilepsy, current estimates of autism prevalence fail to take into account the impact of comorbidity of these disorders on autism diagnosis. We aimed to assess the effect of comorbidity on the diagnosis and prevalence of autism by analyzing 11 years (2000-2010) of special education enrollment data on approximately 6.2 million children per year. We found a 331% increase in the prevalence of autism from 2000 to 2010 within special education, potentially due to a diagnostic recategorization from frequently comorbid features such as ID. The decrease in ID prevalence equaled an average of 64.2% of the increase of autism prevalence for children aged 3-18 years. The proportion of ID cases potentially undergoing recategorization to autism was higher (P = 0.007) among older children (75%) than younger children (48%). Some US states showed significant negative correlations between the prevalence of autism compared to that of ID while others did not, suggesting state-specific health policy to be a major factor in categorizing autism. Further, a high frequency of autistic features was observed when individuals with classically defined genetic syndromes were evaluated for autism using standardized instruments. Our results suggest that current ascertainment practices are based on a single facet of autism-specific clinical features and do not consider associated comorbidities that may confound diagnosis. Longitudinal studies with detailed phenotyping and deep molecular genetic analyses are necessary to completely understand the cause of this complex disorder.

Neuronal correlates of asocial behavior in a BTBR T (+) Itpr3(tf)/J mouse model of autism

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized, in part, by an inability to adequately respond to social cues. Patients diagnosed with ASD are often devoid of empathy and impaired in understanding other people's emotional perspective. The neuronal correlates of this impairment are not fully understood. Replicating such a behavioral phenotype in a mouse model of autism would allow us insight into the neuronal background of the problem. Here we tested BTBR T(+)Itpr3(tf)/J (BTBR) and c57BL/6J (B6) mice in two behavioral paradigms: the Transfer of Emotional Information test and the Social Proximity test. In both tests BTBR mice displayed asocial behavior. We analyzed c-Fos protein expression in several brain regions after each of these tests, and found that, unlike B6 mice, BTBR mice react to a stressed cagemate exposure in the Transfer of Emotional Information test with no increase of c-Fos expression in either the prefrontal cortex or the amygdala. However, after Social Proximity exposure we observed a strong increase in c-Fos expression in the CA3 field of the hippocampus and two hypothalamic regions of BTBR brains. This response was accompanied by a strong activation of periaqueductal regions related to defensiveness, which suggests that BTBR mice find unavoidable social interaction highly aversive.

All Together Now: Measuring Staff Cohesion in Special Education Classrooms

This study sought to validate a new measure, the Classroom Cohesion Survey (CCS), designed to examine the relationship between teachers and classroom assistants in autism support classrooms. Teachers, classroom assistants, and external observers showed good inter-rater agreement on the CCS and good internal consistency for all scales. Simple factor structures were found for both teacher- and classroom assistant-rated scales, with one-factor solutions for both scales. Paired t tests revealed that on average, classroom assistants rated classroom cohesion stronger than teachers. The CCS may be an effective tool for measuring cohesion between classroom staff and may have an important impact on various clinical and implementation outcomes in school settings.

The incidence of diagnosed autism spectrum disorders in Finland

BACKGROUND

Previous reports indicate an increase in incidence of autism spectrum disorders (ASD).

AIMS

First, to assess the incidence of diagnosed ASD in children born between 1996 and 1998, based on nationwide inpatient and outpatient register information. Second, to investigate the incidence rate over time of diagnosed ASD and specifically childhood autism, Asperger's syndrome and pervasive developmental disorder (PDD-NOS) in children born between 1987 and 1998.

METHODS

This is population-based cohort study with children born in Finland between 1 January 1987 and 31 December 2005; a total of more than 1.2 million children. Children were identified in the Finnish Hospital Discharge Register, and the reported diagnoses were based on the International Statistical Classification of Diseases (ICD-10, ICD-9).

RESULTS

The annual incidence rate of diagnosed ASD based on inpatient and outpatient register data was 53.7 per 10,000 (95% CI 50.4-57.2). Incidence was 82.6 per 10,000 in boys and 23.6 per 10,000 in girls, yielding a sex ratio (boys:girls) of 3.5:1. We report an eightfold increase in the incidence rates in children of diagnosed ASD and specifically in childhood autism, Asperger's syndrome and PDD-NOS and born between 1987 and 1992 based on inpatient register information.

CONCLUSIONS

Increased awareness of ASD, more precise diagnostic criteria and changes in practice for diagnosing autism may have had a substantial effect on the increased incidence of inpatient treated ASD cases from 1987 to 1992. Between 1992 and 1998, the incidence rate based on inpatient and outpatient service use remained rather stable.

Overweight and obesity: prevalence and correlates in a large clinical sample of children with autism spectrum disorder

Autism Spectrum Disorders (ASDs) and childhood obesity (OBY) are rising public health concerns. This study aimed to evaluate the prevalence of overweight (OWT) and OBY in a sample of 376 Oregon children with ASD, and to assess correlates of OWT and OBY in this sample. We used descriptive statistics, bivariate, and focused multivariate analyses to determine whether socio-demographic characteristics, ASD symptoms, ASD cognitive and adaptive functioning, behavioral problems, and treatments for ASD were associated with OWT and OBY in ASD. Overall 18.1% of children met criteria for OWT and 17.0% met criteria for OBY. OBY was associated with sleep difficulties, melatonin use, and affective problems. Interventions that consider unique needs of children with ASD may hold promise for improving weight status among children with ASD.

Potential impact of DSM-5 criteria on autism spectrum disorder prevalence estimates

IMPORTANCE

The DSM-5 contains revised diagnostic criteria for autism spectrum disorder (ASD) from the DSM-IV-TR. Potential impacts of the new criteria on ASD prevalence are unclear.

OBJECTIVE

To assess potential effects of the DSM-5 ASD criteria on ASD prevalence estimation by retrospectively applying the new criteria to population-based surveillance data collected for previous ASD prevalence estimation.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional, population-based ASD surveillance based on clinician review of coded behaviors documented in children's medical and educational evaluations from 14 geographically defined areas in the United States participating in the Autism and Developmental Disabilities Monitoring (ADDM) Network in 2006 and 2008. This study included 8-year-old children living in ADDM Network study areas in 2006 or 2008, including 644 883 children under surveillance, of whom 6577 met surveillance ASD case status based on the DSM-IV-TR.

MAIN OUTCOMES AND MEASURES

Proportion of children meeting ADDM Network ASD criteria based on the DSM-IV-TR who also met DSM-5 criteria; overall prevalence of ASD using DSM-5 criteria.

RESULTS

Among the 6577 children classified by the ADDM Network as having ASD based on the DSM-IV-TR, 5339 (81.2%) met DSM-5 ASD criteria. This percentage was similar for boys and girls but higher for those with than without intellectual disability (86.6% and 72.5%, respectively; P < .001). A total of 304 children met DSM-5 ASD criteria but not current ADDM Network ASD case status. Based on these findings, ASD prevalence per 1000 for 2008 would have been 10.0 (95% CI, 9.6-10.3) using DSM-5 criteria compared with the reported prevalence based on DSM-IV-TR criteria of 11.3 (95% CI, 11.0-11.7).

CONCLUSIONS AND RELEVANCE

Autism spectrum disorder prevalence estimates will likely be lower under DSM-5 than under DSM-IV-TR diagnostic criteria, although this effect could be tempered by future adaptation of diagnostic practices and documentation of behaviors to fit the new criteria.

Video feedforward for rapid learning of a picture-based communication system

This study examined the efficacy of video self modeling (VSM) using feedforward, to teach various goals of a picture exchange communication system (PECS). The participants were two boys with autism and one man with Down syndrome. All three participants were non-verbal with no current functional system of communication; the two children had long histories of PECS failure. A series of replications, with different length baselines, was used to examine whether video self modeling could replace the PECS method of teaching to achieve the same goals. All three participants showed rapid learning of their target behavior when introduced to their self modeling videos, and effects generalized without the need for further intervention. We conclude that VSM, using feedforward, can provide a fast, simple way of teaching the use of a picture-based communication system without the need for prompts or intensive operant conditioning. VSM may provide an accessible, easy-to-use alternative to common methods of teaching augmentative and alternative communication systems.

The BTBR T+ tf/J mouse model for autism spectrum disorders-in search of biomarkers

Autism spectrum disorders (ASD) form a common group of neurodevelopmental disorders appearing to be under polygenic control, but also strongly influenced by multiple environmental factors. The brain mechanisms responsible for ASD are not understood and animal models paralleling related emotional and cognitive impairments may prove helpful in unraveling them. BTBR T+ tf/J (BTBR) mice display behaviors consistent with the three diagnostic categories for ASD. They show impaired social interaction and communication as well as increased repetitive behaviors. This review covers much of the data available to date on BTBR behavior, neuroanatomy and physiology in search for candidate biomarkers, which could both serve as diagnostic tools and help to design effective treatments for the behavioral symptoms of ASD.

Fractone-associated N-sulfated heparan sulfate shows reduced quantity in BTBR T+tf/J mice: a strong model of autism

BTBR T+tf/J (BTBR) mice show abnormal social, communicatory, and repetitive/stereotyped behaviors paralleling many of the symptoms of autism spectrum disorders. BTBR also show agenesis of the corpus callosum (CC) suggesting major perturbations of growth or guidance factors in the dorsal forebrain [1]. Heparan sulfate (HS) is a polysaccaride found in the brain and other animal tissues. It binds to a wide variety of ligands and through these ligands modulates a number of biological processes, including cell proliferation and differentiation, migration and guidance. It is aggregated on fractal-like structures (fractones) in the subventricular zone (SVZ), that may be visualized by laminin immunoreactivity (LAM-ir), as well as by HS immunoreactivity (HS-ir). We report that the lateral ventricles of BTBR mice were drastically reduced in area compared to C57BL/6J (B6) mice while the BTBR SVZ was significantly shorter than that of B6. In addition to much smaller fractones for BTBR, both HS and LAM-ir associated with fractones were significantly reduced in BTBR, and their anterior-posterior distributions were also altered. Finally, the ratio of HS to LAM in individual fractones was significantly higher in BTBR than in B6 mice. These data, in agreement with other findings linking HS to callosal development, suggest that variations in the quantity and distribution of HS in the SVZ of the lateral ventricles may be important modulators of the brain structural abnormalities of BTBR mice, and, potentially, contribute to the behavioral pathologies of these animals.

BTBR T+tf/J mice: autism-relevant behaviors and reduced fractone-associated heparan sulfate

BTBR T+tf/J (BTBR) mice have emerged as strong candidates to serve as models of a range of autism-relevant behaviors, showing deficiencies in social behaviors; reduced or unusual ultrasonic vocalizations in conspecific situations; and enhanced, repetitive self-grooming. Recent studies have described their behaviors in a seminatural visible burrow system (VBS); a Social Proximity Test in which avoidance of a conspecific is impossible; and in an object approach and investigation test evaluating attention to specific objects and potential stereotypies in the order of approaching/investigating objects. VBS results confirmed strong BTBR avoidance of conspecifics and in the Social Proximity Test, BTBR showed dramatic differences in several close-in behaviors, including specific avoidance of a nose-to-nose contact that may potentially be related to gaze-avoidance. Diazepam normalized social avoidance by BTBRs in a Three-Chamber Test, and some additional behaviors - but not nose to nose avoidance - in the Social Proximity Test. BTBR also showed higher levels of preference for particular objects, and higher levels of sequences investigating 3- or 4-objects in the same order. Heparan sulfate (HS) associated with fractal structures in the subventricular zone of the lateral ventricles was severely reduced in BTBR. HS may modulate the functions of a range of growth and guidance factors during development, and HS abnormalities are associated with relevant brain (callosal agenesis) and behavioral (reductions in sociality) changes; suggesting the value of examination of the dynamics of the HS system in the context of autism.

Increased secreted amyloid precursor protein-α (sAPPα) in severe autism: proposal of a specific, anabolic pathway and putative biomarker

Autism is a neurodevelopmental disorder characterized by deficits in verbal communication, social interactions, and the presence of repetitive, stereotyped and compulsive behaviors. Excessive early brain growth is found commonly in some patients and may contribute to disease phenotype. Reports of increased levels of brain-derived neurotrophic factor (BDNF) and other neurotrophic-like factors in autistic neonates suggest that enhanced anabolic activity in CNS mediates this overgrowth effect. We have shown previously that in a subset of patients with severe autism and aggression, plasma levels of the secreted amyloid-β (Aβ) precursor protein-alpha form (sAPPα) were significantly elevated relative to controls and patients with mild-to-moderate autism. Here we further tested the hypothesis that levels of sAPPα and sAPPβ (proteolytic cleavage products of APP by α- and β-secretase, respectively) are deranged in autism and may contribute to an anabolic environment leading to brain overgrowth. We measured plasma levels of sAPPα, sAPPβ, Aβ peptides and BDNF by corresponding ELISA in a well characterized set of subjects. We included for analysis 18 control, 6 mild-to-moderate, and 15 severely autistic patient plasma samples. We have observed that sAPPα levels are increased and BDNF levels decreased in the plasma of patients with severe autism as compared to controls. Further, we show that Aβ1-40, Aβ1-42, and sAPPβ levels are significantly decreased in the plasma of patients with severe autism. These findings do not extend to patients with mild-to-moderate autism, providing a biochemical correlate of phenotypic severity. Taken together, this study provides evidence that sAPPα levels are generally elevated in severe autism and suggests that these patients may have aberrant non-amyloidogenic processing of APP.

The neurochemical basis for the treatment of autism spectrum disorders and Fragile X Syndrome

Autism spectrum disorders (ASD) and Fragile X Syndrome (FXS) are neurodevelopmental disorders that share overlapping behavioral characteristics. While FXS is known to result from a specific genetic mutation, the causes of the majority of cases of ASD are unknown. Animal models of FXS have revealed new insight into the cellular and biochemical changes that occur in the central nervous system in this disorder, while human genetic studies on individuals with autism have identified sets of genes that may increase susceptibility to the disorder. Together these discoveries suggest overlapping biochemical characteristics and reveal new directions for the potential development of pharmacological therapies that might prove useful in the treatment of both FXS and ASD. In particular, delayed synaptic maturation, abnormal synaptic structure and/or function and alterations in intracellular signaling pathways have been linked to the pathogenesis of FXS and ASD. Aberrations in GABA(A) receptor ion channels and the G-protein coupled metabotropic glutamate and GABA(B) transmitter systems are also linked to both disorders and these receptors are currently at the forefront of preclinical and clinical research into treatments for both autism and Fragile X Syndrome.