Autism interest intensity in early childhood associates with executive functioning but not reward sensitivity or anxiety symptoms

Autism Spectrum Disorder and BRIEF-P: A Review and Meta-Analysis

BACKGROUND

This research can facilitate the development of early detection tools for ASD by identifying specific patterns of deficits in executive functioning, validating the use of the BRIEF-P as a detection tool, and complementing information obtained from other evaluation instruments (Autism Diagnostic Interview-ADI-and Autism Diagnostic Observation Schedule-ADOS).

AIMS

To gain knowledge of the application and usefulness of the BRIEF-P in the evaluation of executive functions (EFs) in people with ASD in the early years of the life cycle.

METHOD

In order to systematically examine this hypothesis, a meta-analysis was conducted to identify the executive profile (strengths and weaknesses) of children with ASD. Out of a total of 161,773 potentially eligible published articles from different databases, 13 appropriate articles were revised and 4 articles were selected. Studies that were included evaluated samples involving individuals with ASD aged 2 to 8 years and were published in English or Spanish during the period of 2012-2022.

RESULTS

The executive profile obtained from the application of the BRIEF-P in individuals with ASD was analyzed. It was identified that children with ASD, compared to typically developing children, show significantly clinical scores on the flexibility, inhibition, and global executive functioning scales. The results support the hypothesis of an executive deficit, with flexibility and inhibition being diagnostic markers for early and prompt identification of autism.

CONCLUSIONS AND DISCUSSION

The results confirm deficits in flexibility, although they are not conclusive. This may be due to aspects related to methodology, whereby the studies (i) include very large and heterogeneous age groups, (ii) do not discriminate based on the level of competence, and (iii) use instruments for evaluating executive functions that are not validated or adapted for people with ASD. Another reason is the lack of consensus in the very operational definition of the executive functions construct, with the studies focusing mainly on the cold dimension while ignoring the hot dimension. From the perspective of therapeutic and treatment implications, executive dysfunction can impact adaptive skills in daily life and consequently the person's autonomy.

Categorizing and identifying preferred interests in autistic toddlers

Preferred interests are characteristic of autism spectrum disorder and are reported by parents starting at an early age. However, limited research has explored the presentation of preferred interests in toddlerhood. Previous literature suggests that both the intensity and type of preferred interests held by autistic individuals differ from those held by peers with developmental delay and no diagnosis and that autistic interests are more unusual in nature. While preferred interests are seen in typical child development, previous research suggests that the presence of preferred interests in children with no diagnosis declines with age. Literature also indicates that the sex and cognitive ability of autistic children influences preferred interests. Identification of early preferred interests commonly held by autistic toddlers could serve as a useful clinical indicator of future diagnosis. This article explored whether diagnostic group, age, sex, and cognitive ability predict the likelihood that parents reported preferred interests in children aged 12-36 months with diagnoses of autism, developmental delay, and those with no diagnosis. Additionally, we explored potential diagnostic group differences in interest type. Results suggest that diagnostic group, but not age, sex, or cognitive ability, predicts the likelihood that parents report preferred interests. No differences in the type of interests among diagnostic groups were identified. These results support the use of preferred interests as an early sign of autism but suggest that interest type may not be a helpful clinical indicator of autism in toddlerhood.

Brain-phenotype predictions can survive across diverse real-world data

Recent work suggests that machine learning models predicting psychiatric treatment outcomes based on clinical data may fail when applied to unharmonized samples. Neuroimaging predictive models offer the opportunity to incorporate neurobiological information, which may be more robust to dataset shifts. Yet, among the minority of neuroimaging studies that undertake any form of external validation, there is a notable lack of attention to generalization across dataset-specific idiosyncrasies. Research settings, by design, remove the between-site variations that real-world and, eventually, clinical applications demand. Here, we rigorously test the ability of a range of predictive models to generalize across three diverse, unharmonized samples: the Philadelphia Neurodevelopmental Cohort (n=1291), the Healthy Brain Network (n=1110), and the Human Connectome Project in Development (n=428). These datasets have high inter-dataset heterogeneity, encompassing substantial variations in age distribution, sex, racial and ethnic minority representation, recruitment geography, clinical symptom burdens, fMRI tasks, sequences, and behavioral measures. We demonstrate that reproducible and generalizable brain-behavior associations can be realized across diverse dataset features with sample sizes in the hundreds. Results indicate the potential of functional connectivity-based predictive models to be robust despite substantial inter-dataset variability. Notably, for the HCPD and HBN datasets, the best predictions were not from training and testing in the same dataset (i.e., cross-validation) but across datasets. This result suggests that training on diverse data may improve prediction in specific cases. Overall, this work provides a critical foundation for future work evaluating the generalizability of neuroimaging predictive models in real-world scenarios and clinical settings.