Autism spectrum disorder reclassified: a second look at the 1980s Utah/UCLA Autism Epidemiologic Study

Children with Autism Spectrum Disorder and Abnormalities of Clinical EEG: A Qualitative Review

Over the last decade, the comorbidity between Autism Spectrum Disorder (ASD) and epilepsy has been widely demonstrated, and many hypotheses regarding the common neurobiological bases of these disorders have been put forward. A variable, but significant, prevalence of abnormalities on electroencephalogram (EEG) has been documented in non-epileptic children with ASD; therefore, several scientific studies have recently tried to demonstrate the role of these abnormalities as a possible biomarker of altered neural connectivity in ASD individuals. This narrative review intends to summarize the main findings of the recent scientific literature regarding abnormalities detected with standard EEG in children/adolescents with idiopathic ASD. Research using three different databases (PubMed, Scopus and Google Scholar) was conducted, resulting in the selection of 10 original articles. Despite an important lack of studies on preschoolers and a deep heterogeneity in results, some authors speculated on a possible association between EEG abnormalities and ASD characteristics, in particular, the severity of symptoms. Although this correlation needs to be more strongly elucidated, these findings may encourage future studies aimed at demonstrating the role of electrical brain abnormalities as an early biomarker of neural circuit alterations in ASD, highlighting the potential diagnostic, prognostic and therapeutic value of EEG in this field.

Defining in Detail and Evaluating Reliability of DSM-5 Criteria for Autism Spectrum Disorder (ASD) Among Children

This paper describes a process to define a comprehensive list of exemplars for seven core Diagnostic and Statistical Manual (DSM) diagnostic criteria for autism spectrum disorder (ASD), and report on interrater reliability in applying these exemplars to determine ASD case classification. Clinicians completed an iterative process to map specific exemplars from the CDC Autism and Developmental Disabilities Monitoring (ADDM) Network criteria for ASD surveillance, DSM-5 text, and diagnostic assessments to each of the core DSM-5 ASD criteria. Clinicians applied the diagnostic exemplars to child behavioral descriptions in existing evaluation records to establish initial reliability standards and then for blinded clinician review in one site (phase 1) and for two ADDM Network surveillance years (phase 2). Interrater reliability for each of the DSM-5 diagnostic categories and overall ASD classification was high (defined as very good .60-.79 to excellent ≥ .80 Kappa values) across sex, race/ethnicity, and cognitive levels for both phases. Classification of DSM-5 ASD by mapping specific exemplars from evaluation records by a diverse group of clinician raters is feasible and reliable. This framework provides confidence in the consistency of prevalence classifications of ASD and may be further applied to improve consistency of ASD diagnoses in clinical settings.

A machine learning-based diagnostic model for children with autism spectrum disorders complicated with intellectual disability

Background

Early detection of children with autism spectrum disorder (ASD) and comorbid intellectual disability (ID) can help in individualized intervention. Appropriate assessment and diagnostic tools are lacking in primary care. This study aims to explore the applicability of machine learning (ML) methods in diagnosing ASD comorbid ID compared with traditional regression models.

Method

From January 2017 to December 2021, 241 children with ASD, with an average age of 6.41 ± 1.96, diagnosed in the Developmental Behavior Department of the Children's Hospital Affiliated with the Medical College of Zhejiang University were included in the analysis. This study trained the traditional diagnostic models of Logistic regression (LR), Support Vector Machine (SVM), and two ensemble learning algorithms [Random Forest (RF) and XGBoost]. Socio-demographic and behavioral observation data were used to distinguish whether autistic children had combined ID. The hyperparameters adjustment uses grid search and 10-fold validation. The Boruta method is used to select variables. The model's performance was evaluated using discrimination, calibration, and decision curve analysis (DCA).

Result

Among 241 autistic children, 98 (40.66%) were ASD comorbid ID. The four diagnostic models can better distinguish whether autistic children are complicated with ID, and the accuracy of SVM is the highest (0.836); SVM and XGBoost have better accuracy (0.800, 0.838); LR has the best sensitivity (0.939), followed by SVM (0.952). Regarding specificity, SVM, RF, and XGBoost performed significantly higher than LR (0.355). The AUC of ML (SVM, 0.835 [95% CI: 0.747-0.944]; RF, 0.829 [95% CI: 0.738-0.920]; XGBoost, 0.845 [95% CI: 0.734-0.937]) is not different from traditional LR (0.858 [95% CI: 0.770-0.944]). Only SVM observed a good calibration degree. Regarding DCA, LR, and SVM have higher benefits in a wider threshold range.

Conclusion

Compared to the traditional regression model, ML model based on socio-demographic and behavioral observation data, especially SVM, has a better ability to distinguish whether autistic children are combined with ID.

IQ in Autism Spectrum Disorder: A Population-Based Birth Cohort Study

OBJECTIVES

We aimed to describe the intellectual ability and ratio of boys to girls with average or higher IQ within autism spectrum disorder (ASD) cases identified in a population-based birth cohort. We hypothesized that research-identified individuals with ASD would be more likely to have average or higher IQ, compared to clinically diagnosed ASD. We also hypothesized the male to female ratio would decrease as the definition of ASD broadened.

METHODS

ASD incident cases were identified from 31 220 subjects in a population-based birth cohort. Research-defined autism spectrum disorder, inclusive criteria (ASD-RI) was based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision, autistic disorder (AD), Asperger Disorder, and pervasive developmental disorder not otherwise specified criteria. Research-defined autism spectrum disorder, narrow criteria (ASD-RN) was a narrower definition based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision AD criteria. Clinical diagnoses of ASD were abstracted from medical and school records. Intellectual ability was based on the last IQ score or on documented diagnoses of intellectual disability if no scores available. Average or higher IQ was defined as IQ ≥86.

RESULTS

A total of 59.1% of those with ASD-RI (n = 890), 51.2% of those with ASD-RN (n = 453), and 42.8% of those with clinically diagnosed autism spectrum disorder (n = 187) had average or higher IQ. Within the ASD-RI and ASD-RN groups, boys were more likely than girls to have an average or higher IQ (62.0% vs 51.3% [P = .004] and 54.1% vs. 42.5% [P = .03], respectively).

CONCLUSION

Our data suggest that nearly half of individuals with ASD have average or higher IQ. Boys with ASD are more likely to have average or higher IQ than girls. Patients with ASD and higher IQ remain at risk for not being identified.

Sulforaphane treatment for autism spectrum disorder: A systematic review

Autism Spectrum Disorder (ASD) is defined as a neurodevelopmental condition characterized by social communication impairment, delayed development, social function deficit, and repetitive behaviors. The Center for Disease Control reports an increase in ASD diagnosis rates every year. This systematic review evaluated the use of sulforaphane (SFN) therapy as a potential treatment option for individuals with ASD. PubMed.gov, PubMed Central, Natural Medicines, BoardVitals, Google Scholar and Medline were searched for studies measuring the effects of SFN on behavior and cognitive function. All five clinical trials included in this systematic review showed a significant positive correlation between SFN use and ASD behavior and cognitive function. The current evidence shows with minimal side effects observed, SFN appears to be a safe and effective treatment option for treating ASD.

Objective Estimates of Direct-Medical Costs Among Persons Aged 3 to 38 Years With and Without Research-Defined Autism Spectrum Disorder Ascertained During Childhood: A Population-Based Birth-Cohort Study

OBJECTIVES

Accurate estimates of autism spectrum disorder (ASD)-associated medical costs are essential for predicting future care needs, allocating resources, identifying best practices, and modeling cost-effectiveness. Most existing studies have either employed subjective cost data or ascertained ASD using self-reported or International Classification of Diseases-coded diagnoses. Such ascertainment is especially problematic for identifying milder ASD among older individuals never diagnosed with ASD.

METHODS

This 1976 through 2000 population-based birth-cohort study was set in Olmsted County, Minnesota. ASD cases and age- and sex-matched unaffected controls were identified by applying uniform operational research criteria for ASD (using the guidelines of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, text revision) after rigorous review of provider-linked medical and public, private, or home school records available for all members from birth to a maximum age of 21 years. Medical cost estimates for the 901 case-control pairs used line-item provider-linked billing data (including all payers) from 2003 through 2014 (ages 3-38 years). Outpatient pharmaceutical costs were unavailable. Temporal changes in diagnostic criteria, clinical practice, public awareness, and access were addressed by separating analyses into 5-year age group and 4-year calendar period cells. Unadjusted and adjusted (age and age plus co-occurring conditions) cost estimates were provided for cases, controls, and case-control differences. Additional factors (co-occurring conditions, percentage hospitalized, intellectual disability) were investigated using unadjusted descriptive analyses.

RESULTS

Cell sample sizes ranged from 93 to 402 for age groups 3 through 19 years and from 45 to 395 for age groups 20 through 38 years. Unadjusted, age-adjusted, and fully adjusted medical costs were significantly higher for cases versus controls in 100% of cells for age groups 3 through 19 years and in 50% (unadjusted), 38% (age adjusted), and 12% (fully adjusted) of cells for age groups 20 through 38 years.

CONCLUSIONS

These unique estimates can help inform the construction of cost-effectiveness models; decisions by payers, providers, and policy makers; and predictions of lifetime costs.

Autism Spectrum Disorder: Incidence and Time Trends Over Two Decades in a Population-Based Birth Cohort

We retrospectively identified autism spectrum disorder (ASD) incident cases among 31,220 individuals in a population-based birth cohort based on signs and symptoms uniformly abstracted from medical and educational records. Inclusive and narrow research definitions of ASD (ASD-RI and ASD-RN, respectively) were explored, along with clinical diagnoses of ASD (ASD-C) obtained from the records. The incidence of ASD-RI, ASD-RN, and ASD-C increased significantly from 1985 to 1998, then ASD-RI and ASD-RN plateaued while the rate of ASD-C continued to increase during 1998-2004. The rising incidence of research-defined ASD may reflect improved recognition and documentation of ASD signs and symptoms. Although the frequency of threshold ASD symptoms stabilized, the rate of ASD-C continued to increase, narrowing the gap between clinical ascertainment and symptom documentation.

Mid-life social outcomes for a population-based sample of adults with ASD

Adults with autism spectrum disorders (ASD) fall short of social outcomes of non-ASD peers in mid-life, as documented by currently published research. The aim of the current study was to extend what is known about social functioning, employment, independent living, and use of social services by examining details of the current life status for a population-based sample of adults with ASD (mean age = 35.5 years, range = 22.2-51.4). We collected outcome data via direct assessment and informant report for 169 individuals. Three-fourths of the sample had cognitive abilities in the intellectually disabled range. Social functioning outcomes, as a single measure, mirror those reported previously for other samples, including samples with a high proportion of individuals with normal range intellectual abilities, with 20% achieving the most independent outcomes and 46% requiring high levels of support across most life areas. Participant subgroups who achieved maximal outcomes represented a range of social and intellectual abilities for several outcome metrics. Participants used high levels of public and private supports, yet specific areas of clear, unmet need were also identified. Autism Res 2018, 11: 142-152. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

This paper describes the social functioning outcomes for 169 adults with autism spectrum disorders in mid-life. Adult participants spanned the full range of functional and cognitive ability levels, with over 75% functioning in the cognitively impaired range. While summary descriptions of outcomes for this sample were similar to those reported for other groups of adults, this report provides detailed information regarding employment outcomes, social relationships, leisure activities, participation in the community, residential situations, public service use, and involvement with law enforcement.

Brief Report: The Prevalence of Neurofibromatosis Type 1 among Children with Autism Spectrum Disorder Identified by the Autism and Developmental Disabilities Monitoring Network

Neurofibromatosis type 1 (NF1) is an inherited neurocutaneous disorder associated with neurodevelopmental disorders including autism spectrum disorder (ASD). The frequency of ASD/NF1 co-occurrence has been subject to debate since the 1980s. This relationship was investigated in a large population-based sample of 8-year-old children identified with ASD (N = 12,271) by the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring (ADDM) Network. Twenty-two (1-in-558) children with ASD had diagnosed NF1, exceeding NF1 general population estimates by four to five fold. Children with ASD/NF1 versus ASD without NF1 were significantly less likely to receive a community-based ASD diagnosis (p = 0.04) and understand non-verbal communication (p = 0.001). These findings underscore the importance of including social-communication ability among relevant developmental concerns in children with NF1.

Investigation of Autism Spectrum Disorder and Autistic Traits in an Adolescent Sample with Anorexia Nervosa

This study aimed to examine the presence of Autism Spectrum Disorder (ASD) in a sample of female adolescents with Anorexia Nervosa (AN) during the acute phase of illness. We also compare the level of autistic traits, social perception skills and obsessive-compulsive symptoms in four groups: AN, ASD, and two gender- and age-matched control groups. Of the 30 AN participants, only three scored above the conventional ADOS-2 threshold for ASD. The AN participants were similar to their controls on autistic trait measures, and to the ASD group on obsessive-compulsive measures, and on theory of mind ability and affect recognition measures. Further longitudinal studies are needed in order to determine the association between these conditions.

Language Ability Predicts Cortical Structure and Covariance in Boys with Autism Spectrum Disorder

There is significant clinical heterogeneity in language and communication abilities of individuals with Autism Spectrum Disorders (ASD). However, no consistent pathology regarding the relationship of these abilities to brain structure has emerged. Recent developments in anatomical correlation-based approaches to map structural covariance networks (SCNs), combined with detailed behavioral characterization, offer an alternative for studying these relationships. In this study, such an approach was used to study the integrity of SCNs of cortical thickness and surface area associated with language and communication, in 46 high-functioning, school-age children with ASD compared with 50 matched, typically developing controls (all males) with IQ > 75. Findings showed that there was alteration of cortical structure and disruption of fronto-temporal cortical covariance in ASD compared with controls. Furthermore, in an analysis of a subset of ASD participants, alterations in both cortical structure and covariance were modulated by structural language ability of the participants, but not communicative function. These findings indicate that structural language abilities are related to altered fronto-temporal cortical covariance in ASD, much more than symptom severity or cognitive ability. They also support the importance of better characterizing ASD samples while studying brain structure and for better understanding individual differences in language and communication abilities in ASD.

Imaging Brain Development: Benefiting from Individual Variability

Human brain development is a complex process that evolves from early childhood to young adulthood. Major advances in brain imaging are increasingly being used to characterize the developing brain. These advances have further helped to elucidate the dynamic maturational processes that lead to the emergence of complex cognitive abilities in both typical and atypical development. However, conventional approaches involve categorical group comparison models and tend to disregard the role of widespread interindividual variability in brain development. This review highlights how this variability can inform our understanding of developmental processes. The latest studies in the field of brain development are reviewed, with a particular focus on the role of individual variability and the consequent heterogeneity in brain structural and functional development. This review also highlights how such heterogeneity might be utilized to inform our understanding of complex neuropsychiatric disorders and recommends the use of more dimensional approaches to study brain development.

Structural Gray Matter Differences During Childhood Development in Autism Spectrum Disorder: A Multimetric Approach

BACKGROUND

Autism spectrum disorder is a complex neurodevelopmental disorder characterized by impaired social interaction and communication, repetitive behaviors, and restricted interests. Gray matter differences linked to autism spectrum disorder have been studied using a variety of structural imaging methods, but yielded little consensus; the extent to which disparate results reflect differences in methodology or heterogeneity within autism spectrum disorder is not yet clear. Moreover, very few studies have examined gray matter changes as a function of age in autism spectrum disorder.

METHOD

A detailed investigation of gray matter structural development was performed via voxel-based morphometry, cortical thickness, and cortical surface area analyses in 38 autism spectrum disorder versus 46 typically developing children.

RESULTS

Relative to typically developing children, the autism spectrum disorder group showed gray matter increases most prominently in the frontal and temporal lobes (including regions such as medial frontal gyrus, Broca's area and posterior temporal cortex), as well as certain parietal and occipital subcortical regions. Gray matter decreases were found only near the temporoparietal junction. Subcortical gray matter increases were found in the putamen and caudate nucleus, while decreases were found in cerebellum. There were age-dependent GM differences in distributed regions including prefrontal cortex, primary sensorimotor cortex, and temporoparietal junction.

CONCLUSION

The results underline the distributed nature of gray matter structural differences in autism spectrum disorder and provide a more comprehensive characterization of autism spectrum disorder-related cortical and subcortical gray matter structural differences during childhood and adolescent development.

A description of medical conditions in adults with autism spectrum disorder: A follow-up of the 1980s Utah/UCLA Autism Epidemiologic Study

This study describes medical conditions experienced by a population-based cohort of adults with autism spectrum disorder whose significant developmental concerns were apparent during childhood. As part of a 25-year outcome study of autism spectrum disorder in adulthood, medical histories were collected on 92 participants (N = 69 males) who were first ascertained as children in the mid-1980s, 11 of whom were deceased at the time of follow-up. Questionnaires queried medical symptoms, disorders, hospitalizations, surgeries, and medication use. Median age at follow-up was 36 years (range: 23.5-50.5 years), and intellectual disability co-occurred in 62%. The most common medical conditions were seizures, obesity, insomnia, and constipation. The median number of medical conditions per person was 11. Increased medical comorbidity was associated with female gender (p = 0.01) and obesity (p = 0.03), but not intellectual disability (p = 0.79). Adults in this cohort of autism spectrum disorder first ascertained in the 1980s experience a high number of chronic medical conditions, regardless of intellectual ability. Understanding of these conditions commonly experienced should direct community-based and medical primary care for this population.

Psychiatric comorbidity and medication use in adults with autism spectrum disorder

The purpose of this study was to investigate comorbid psychiatric disorders and psychotropic medication use among adults with autism spectrum disorder (ASD) ascertained as children during a 1980's statewide Utah autism prevalence study (n = 129). Seventy-three individuals (56.6 %) met criteria for a current psychiatric disorder; 89 participants (69.0 %) met lifetime criteria for a psychiatric disorder. Caregivers reported a psychiatric diagnosis in 44 participants (34.1 %). Anxiety disorder had the highest current and lifetime prevalence (39.5 and 52.7 %, respectively). Participants with intellectual disability (n = 94, 72.8 %) were significantly less likely to have community-based diagnoses of anxiety (χ(2) = 5.37, p = 0.02) or depression (χ(2) = 13.18, p < 0.001) reported by caregivers. Seventy-six participants (58.9 %) were taking ≥1 psychotropic medication. Comorbid psychiatric disorders occur frequently in adults with ASD, though identifying these disorders poses a challenge in community settings. A greater understanding of the presentation of these conditions within this population will increase assessment validity and the potential for efficacious intervention.

Excess mortality and causes of death in autism spectrum disorders: a follow up of the 1980s Utah/UCLA autism epidemiologic study

This study's purpose was to investigate mortality among individuals with autism spectrum disorders (ASD) ascertained during a 1980s statewide autism prevalence study (n = 305) in relation to controls. Twenty-nine of these individuals (9.5 %) died by the time of follow up, representing a hazard rate ratio of 9.9 (95 % CI 5.7-17.2) in relation to population controls. Death certificates identified respiratory, cardiac, and epileptic events as the most common causes of death. The elevated mortality risk associated with ASD in the study cohort appeared related to the presence of comorbid medical conditions and intellectual disability rather than ASD itself suggesting the importance of coordinated medical care for this high risk sub-population of individuals with ASD.

Trends in Vocational Rehabilitation Services and Outcomes of Youth With Autism

As the number of adults with a diagnosis of autism continues to grow, attention is drawn to whether they receive adequate services and achieve satisfactory employment outcomes, compared with their peers with other disabilities. After examining data from the U.S. state vocational rehabilitation programs from the years 2006–2010, we found that youth with autism received similar levels of services and reported similar employment outcomes compared with their peers with other disabilities. However, these outcomes were modest, declining, and substantially different across states, regardless of the types of disabilities. We recommend continuous monitoring of services and outcomes of people with autism and other disabilities as a means to promote their economic self-sufficiency and inclusion in society.