Structural hierarchy of autism spectrum disorder symptoms: an integrative framework

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

Integrating "Lumpers" versus "Splitters" Perspectives: Toward a Hierarchical Dimensional Taxonomy of Eating Disorders from Clinician Ratings

This study describes a hierarchical dimensional model of eating-disorder (ED) classification based on the Hierarchical Taxonomy of Psychopathology (HiTOP). Participants were community-recruited adults with an ED (N=252; 81.9% female). We used a modified version of Goldberg's (2006) method, which involved sequentially extracting latent factors using exploratory structural equation modeling, resulting in a 10-factor hierarchical-dimensional model. Dimensions predicted 92.4% and 58.7% of the variance in recovery outcomes at six-month and one-year, respectively. Compared to other illness indicators (e.g., DSM diagnoses, dimensional ED impairment scores, weight/shape overvaluation, and DSM ED severity specifiers), hierarchical dimensions predicted .88 to 334 times more variance in ED behaviors at baseline and 1.95 to 80.8 times more variance in psychiatric impairment at one-year follow-up. Results suggest that reducing within-disorder heterogeneity for EDs within the broader context of internalizing symptoms provides a powerful framework from which to predict outcomes and understand symptoms experienced by those with EDs.

More than the sum of its parts: Merging network psychometrics and network neuroscience with application in autism

Network approaches that investigate the interaction between symptoms and behaviours have opened new ways of understanding psychological phenomena in health and disorder in recent years. In parallel, network approaches that characterise the interaction between brain regions have become the dominant approach in neuroimaging research. In this paper, we introduce a methodology for combining network psychometrics and network neuroscience. This approach utilises the information from the psychometric network to obtain neural correlates that are associated with each node in the psychometric network (network-based regression). Moreover, we combine the behavioural variables and their neural correlates in a joint network to characterise their interactions. We illustrate the approach by highlighting the interaction between the triad of autistic traits and their resting-state functional connectivity associations. To this end, we utilise data from 172 male autistic participants (10–21 years) from the autism brain data exchange (ABIDE, ABIDE-II) that completed resting-state fMRI and were assessed using the autism diagnostic interview (ADI-R). Our results indicate that the network-based regression approach can uncover both unique and shared neural correlates of behavioural measures. For instance, our example analysis indicates that the overlap between communication and social difficulties is not reflected in the overlap between their functional brain correlates.

The article introduces a method to combine common practices in network psychometrics and network neuroimaging. Namely, we use the unique variance in behavioural measures as regressors to identify unique neural correlates. This enables the description of brain-level and behavioural-level data into a joint network while keeping the dimensionality of the results manageable and interpretable. We illustrate this approach by showing the network of autistic traits and their correlates in resting-state functional connectivity.

Mapping features of pathological exercise using hierarchical-dimensional modeling

OBJECTIVE

Pathological exercise is common among those with eating disorders and has typically been characterized as excessive, compulsive, or compensatory in nature. Little is known about how pathological exercise is associated with other eating disorder behaviors or personality traits, or whether these associations differ between men and women.

METHOD

We used hierarchical dimensional modeling in three samples, including college women (N = 205), women with eating psychopathology (N = 268), and college men (N = 235), to examine latent associations between pathological exercise and eating disorder psychopathology, namely compulsivity, emotion regulation, and body dissatisfaction.

RESULTS

Using Goldberg's (2006) "bass-ackwards" method, we identified separate 10-factor solutions (women) or an 11-factor solution (men). A distinct muscle building factor arose in the three-factor solution for men, and it also notably arose in the six- and eight-factor solutions for community and college women, respectively, highlighting an important understudied motivation factor in both healthy and pathological exercise. Each solution accounted for 64.8% (college women), 51.9% (women with eating psychopathology), and 43.9% (college men) of the variance in excessive exercise, respectively.

DISCUSSION

Findings indicate that pathological exercise is associated with different psychological traits (e.g., poor emotion regulation, compulsivity) across populations, and such differences may necessitate unique treatment approaches tailored accordingly.

Dimensions of Autistic Traits Rated by Parents of Children and Adolescents with Suspected Autism Spectrum Disorders

To examine the factor structure of autism spectrum disorder (ASD) and the psychometric properties of the German Symptom Checklist for Autism Spectrum Disorders (SCL-ASD). Data were collected from 312 clinical referrals with suspected ASD (2–18 years). Confirmatory factor analyses and analyses of reliability, convergent and divergent validity were performed. A bifactor model with one general ASD factor and two specific factors (interaction-communication; restricted, repetitive behaviors) provided an adequate data fit. Internal consistencies of the SCL-ASD subscales and the total scale were > .70. Correlations with measures of ASD traits were higher than correlations with measures of externalizing and internalizing symptoms. The results support a factor structure consistent with DSM-5/ICD-11 criteria. The SCL-ASD has sound psychometric properties.

Annual Research Review: Looking back to look forward - changes in the concept of autism and implications for future research

The concept of autism is a significant contribution from child psychiatry that has entered wider culture and public consciousness, and has evolved significantly over the last four decades. Taking a rather personal retrospective, reflecting on our own time in autism research, this review explores changes in the concept of autism and the implications of these for future research. We focus on seven major changes in how autism is thought of, operationalised, and recognised: (1) from a narrow definition to wide diagnostic criteria; (2) from a rare to a relatively common condition, although probably still under-recognised in women; (3) from something affecting children, to a lifelong condition; (4) from something discreet and distinct, to a dimensional view; (5) from one thing to many 'autisms', and a compound or 'fractionable' condition; (6) from a focus on 'pure' autism, to recognition that complexity and comorbidity is the norm; and finally, (7) from conceptualising autism purely as a 'developmental disorder', to recognising a neurodiversity perspective, operationalised in participatory research models. We conclude with some challenges for the field and suggestions for areas currently neglected in autism research.

Quantifying the Optimal Structure of the Autism Phenotype: A Comprehensive Comparison of Dimensional, Categorical, and Hybrid Models

OBJECTIVE

The two primary-seemingly contradictory-strategies for classifying child psychiatric syndromes are categorical and dimensional; conceptual ambiguities appear to be greatest for polythetic syndromes such as autism spectrum disorder (ASD). Recently, a compelling alternative has emerged that integrates both categorical and dimensional approaches (ie, a hybrid model), thanks to the increasing sophistication of analytic procedures. This study aimed to quantify the optimal phenotypic structure of ASD by comprehensively comparing categorical, dimensional, and hybrid models.

METHOD

The sample comprised 3,825 youth, who were consecutive referrals to a university developmental disabilities or child psychiatric outpatient clinic. Caregivers completed the Child and Adolescent Symptom Inventory-4R (CASI-4R), which includes an ASD symptom rating scale. A series of latent class analyses, exploratory and confirmatory factor analyses, and factor mixture analyses was conducted. Replication analyses were conducted in an independent sample (N = 2,503) of children referred for outpatient evaluation.

RESULTS

Based on comparison of 44 different models, results indicated that the ASD symptom phenotype is best conceptualized as multidimensional versus a categorical or categorical-dimensional hybrid construct. ASD symptoms were best characterized as falling along three dimensions (ie, social interaction, communication, and repetitive behavior) on the CASI-4R.

CONCLUSION

Findings reveal an optimal structure with which to characterize the ASD phenotype using a single, parent-report measure, supporting the presence of multiple correlated symptom dimensions that traverse formal diagnostic boundaries and quantify the heterogeneity of ASD. These findings inform understanding of how neurodevelopmental disorders can extend beyond discrete categories of development and represent continuously distributed traits across the range of human behaviors.

Autism severity, co-occurring psychopathology, and intellectual functioning predict supportive school services for youth with autism spectrum disorder

Supportive school services are a primary service modality for youth with autism spectrum disorder. Autism spectrum disorder, as well as co-occurring psychiatric symptoms and low intellectual abilities, interfere with academic achievement and therefore influence decisions about school services. Therefore, we examined the association of parent, teacher, and clinician ratings of autism spectrum disorder and co-occurring psychiatric symptom severity and intellectual functioning with school services. In total, 283 youth with autism spectrum disorder were assessed with clinical evaluation via the Autism Diagnostic Observation Schedule and parent and teacher versions of the CASI-4R ( Child and Adolescent Symptom Inventory). Full Scale Intelligence Quotient scores were obtained from case records. Clinical and teacher evaluations of autism spectrum disorder severity predicted services and were more strongly associated with school services than parent ratings. Teacher ratings were only associated with common school services (e.g. speech/language therapy, occupational therapy, and/or social skills training) frequency at medium and high levels of clinician-rated autism spectrum disorder severity. Higher IQ and parent-rated externalizing symptoms predicted lower likelihood of receiving school services, whereas internalizing symptoms were not predictive of school services. Autism spectrum disorder symptoms may overshadow externalizing and internalizing symptoms when considering school service supports. Results highlight the importance of evaluating autism spectrum disorder severity via multiple sources, especially in cases of unclear symptom presentation, when examining correlates of school services for youth with autism spectrum disorder.

Neuroinflammation in preterm babies and autism spectrum disorders

Genetic anomalies have a role in autism spectrum disorders (ASD). Each genetic factor is responsible for a small fraction of cases. Environment factors, like preterm delivery, have an important role in ASD. Preterm infants have a 10-fold higher risk of developing ASD. Preterm birth is often associated with maternal/fetal inflammation, leading to a fetal/neonatal inflammatory syndrome. There are demonstrated experimental links between fetal inflammation and the later development of behavioral symptoms consistent with ASD. Preterm infants have deficits in connectivity. Most ASD genes encode synaptic proteins, suggesting that ASD are connectivity pathologies. Microglia are essential for normal synaptogenesis. Microglia are diverted from homeostatic functions towards inflammatory phenotypes during perinatal inflammation, impairing synaptogenesis. Preterm infants with ASD have a different phenotype from term born peers. Our original hypothesis is that exposure to inflammation in preterm infants, combined with at risk genetic background, deregulates brain development leading to ASD.