Assessment of functioning in ADHD according to World Health Organization standards: First revision of the International Classification of Functioning, Disability and Health Core Sets.

AIM: To conduct the first revision of the World Health Organization International Classification of Functioning, Disability and Health (ICF) Core Sets for attention-deficit/hyperactivity disorder (ADHD). METHOD: A Delphi-like method was used, integrating evidence from stakeholder feedback and developing and piloting the ADHD ICF Core Set platform to inform revisions to the ADHD Core Sets. RESULTS: A total of 27 second-level ICF codes were added to the comprehensive ADHD Core Set: body functions of temperament and personality, and basic sensory functions; activities and participation in terms of learning to read and write, spoken communication, community life, religion and spirituality, education, economy, and human rights; environmental factors for domestic animals; and several societal services. The revised comprehensive Core Set contains 98 ICF codes: 18 body function codes; 47 activities and participation codes; and 33 environmental factor codes. Extensive changes were also made to the age-appropriate brief Core Sets to allow their independent use in research and clinical practice. INTERPRETATION: Although substantially expanded, the revised ICF Core Sets better reflect the lived experience of individuals with ADHD and clinical implementation preferences than the initial sets. We recommend further feasibility and validation studies of these Core Sets with the goal of optimizing their acceptance and practicability, and strengthening their evidence base.

Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium.

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

From Symptomatology to Functioning - Applying the ICF to Autism Measures to Facilitate Neurodiversity-Affirmative Data Harmonization.

PURPOSE: A considerable number of screening and diagnostic tools for autism exist, but variability in these measures presents challenges to data harmonization and the comparability and generalizability of findings. At the same time, there is a movement away from autism symptomatology to stances that capture heterogeneity and appreciate diversity. The International Classification of Functioning, Disability and Health (ICF) provides a classification system that can support content harmonization of different screening and diagnostic tools for autism while enabling the translation of diagnostic information into functioning. METHOD: Here we linked commonly used screening and diagnostic measures within the field of autism to the ICF to facilitate the unification of data obtained from these measures. RESULTS: As expected, screening and diagnostic measures primarily focus on body functions and activities and participation domains of the ICF, and much less on environmental factors, reflecting biomedical and adaptive behavior operationalizations of autism derived from diagnostic manuals. CONCLUSION: By translating symptomology-based information to the continuous and diagnostically neutral view of functioning, the ICF linking presented here may provide a means to harmonize measures of autism characteristics while enabling diagnostic information to be re-examined through a more neurodiversity-affirmative lens.

Associations between Elemental Metabolic Dynamics and Default Mode Network Functional Connectivity Are Altered in Autism.

Autism is a neurodevelopmental condition associated with atypical social communication, cognitive, and sensory faculties. Recent advances in exposure biology suggest that biomarkers of elemental uptake and metabolism measured in hair samples can yield an effective signal predictive of autism diagnosis. Here, we investigated if elemental biomarkers in hair were associated with functional connectivity in regions of the default mode network (DMN) previously linked to autism. In a study sample which included twin pairs with concordant and discordant diagnoses for autism, our analysis of hair samples and neuroimaging data supported two general findings. First, independent of autism diagnosis, we found a broad pattern of association between elemental biomarkers and functional connectivity in the DMN, which primarily involved dynamics in zinc metabolism. Second, we found that associations between the DMN and elemental biomarkers, particularly involving phosphorus, calcium, manganese, and magnesium, differed significantly in autistic participants from control participants. In sum, these findings suggest that functional dynamics in elemental metabolism relate broadly to persistent patterns of functional connectivity in the DMN, and that these associations are altered in the emergence of autism.

Deciduous tooth biomarkers reveal atypical fetal inflammatory regulation in autism spectrum disorder.

Atypical regulation of inflammation has been proposed in the etiology of autism spectrum disorder (ASD); however, measuring the temporal profile of fetal inflammation associated with future ASD diagnosis has not been possible. Here, we present a method to generate approximately daily profiles of prenatal and early childhood inflammation as measured by developmentally archived C-reactive protein (CRP) in incremental layers of deciduous tooth dentin. In our discovery population, a group of Swedish twins, we found heightened inflammation in the third trimester in children with future ASD diagnosis relative to controls (n = 66; 14 ASD cases; critical window: -90 to -50 days before birth). In our replication study, in the US, we observed a similar increase in CRP in ASD cases during the third trimester (n = 47; 23 ASD cases; -128 to -21 days before birth). Our results indicate that the third trimester is a critical period of atypical fetal inflammatory regulation in ASD.

Elemental Dynamics in Hair Accurately Predict Future Autism Spectrum Disorder Diagnosis: An International Multi-Center Study.

Autism spectrum disorder (ASD) is a neurodevelopmental condition diagnosed in approximately 2% of children. Reliance on the emergence of clinically observable behavioral patterns only delays the mean age of diagnosis to approximately 4 years. However, neural pathways critical to language and social functions develop during infancy, and current diagnostic protocols miss the age when therapy would be most effective. We developed non-invasive ASD biomarkers using mass spectrometry analyses of elemental metabolism in single hair strands, coupled with machine learning. We undertook a national prospective study in Japan, where hair samples were collected at 1 month and clinical diagnosis was undertaken at 4 years. Next, we analyzed a national sample of Swedish twins and, in our third study, participants from a specialist ASD center in the US. In a blinded analysis, a predictive algorithm detected ASD risk as early as 1 month with 96.4% sensitivity, 75.4% specificity, and 81.4% accuracy (n = 486; 175 cases). These findings emphasize that the dynamics in elemental metabolism are systemically dysregulated in autism, and these signatures can be detected and leveraged in hair samples to predict the emergence of ASD as early as 1 month of age.

Behavioral and biological divergence in monozygotic twin pairs discordant for autism phenotypes: A systematic review.

Background: Non-shared environment (NSE) effects account for around one-third of the etiology of autism spectrum disorder (ASD). However, the knowledge of mechanisms and phenotypic profiles associated with NSE in ASD is scarce. Methods: A systematic search was conducted using Embase, MEDLINE, and PsycINFO for studies published in English between 1990 and August 2020 using co-twin control design to compare behavioral and biological phenotypes among monozygotic (MZ) twin pairs concordant/discordant for ASD, clinical autism symptoms, or autistic traits. Risk of bias was assessed through a modified Newcastle-Ottawa Scale. Results: Twenty six articles were included. Differential DNA methylation and gene expression were found among ASD discordant twins; however, genetic results were inconsistent. Neurological disorders and early medical events were associated with ASD and autistic traits, while no within pair differences were found for minor physical anomalies or head circumference. Structural and functional brain imaging studies and research on social and other cognitive/behavioral functions were inconclusive. Risk of bias assessment found that all studies used the same exposure (or outcome) measures to collect data for participants and most used either secure health-related records or structured interviews for ascertainment of exposure; however, only a handful of studies representative of the population from which they were drawn. Formal assessment of risk of publication bias (i.e., funnel plot) was not possible. Conclusions: Our results suggest that NSE in ASD could be associated with heterogeneous postzygotic genetic mechanisms and manifest as a range of biological and behavioral phenotypes. Extant findings were limited by relatively few studies, small sample sizes, and methodological diversity. More research is needed on co-occurring biological and behavioral phenotypes using a consistent format for designing, analyzing, and reporting MZ ASD discordant twin studies in order to further examine the role of NSE in the etiology of ASD.