Cross-Diagnosis Structural Correlates of Autistic-Like Social Communication Differences

Abstract

Social communication differences are seen in autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive–compulsive disorder (OCD), but the brain mechanisms contributing to these differences remain largely unknown. To address this gap, we used a data-driven and diagnosis-agnostic approach to discover brain correlates of social communication differences in ASD, ADHD, and OCD, and subgroups of individuals who share similar patterns of brain-behavior associations. A machine learning pipeline (regression clustering) was used to discover the pattern of association between structural brain measures (volume, surface area, and cortical thickness) and social communication abilities. Participants (n = 416) included children with a diagnosis of ASD (n = 192, age = 12.0[5.6], 19% female), ADHD (n = 109, age = 11.1[4.1], 18% female), or OCD (n = 50, age = 12.3[4.2], 42% female), and typically developing controls (n = 65, age = 11.6[7.1], 48% female). The analyses revealed (1) associations with social communication abilities in distributed cortical and subcortical networks implicated in social behaviors, language, attention, memory, and executive functions, and (2) three data-driven, diagnosis-agnostic subgroups based on the patterns of association in the above networks. Our results suggest that different brain networks may contribute to social communication differences in subgroups that are not diagnosis-specific.

Shared and Distinct Patterns of Functional Connectivity to Emotional Faces in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder Children

“…Finally, our brain-behaviour correlations reinforce this idea as symptom severity on diagnosis-specific measures correlate strongly with metrics of brain network connectivity. Given the growing body of literature highlighting shared underlying neurobiology among NDDs using data-driven methods ( Kushki et al, 2019 , 2021 ; Choi et al, 2020 ; Vandewouw et al, 2021 ), these approaches may facilitate an understanding of the similarities and individual differences among these disorders, without reliance on diagnostic categories. In terms of intervention, diagnostic status may be an inadequate indicator of the broader needs of children with NDDs and not fully capture behavioural and cognitive sequalae ( Kushki et al, 2019 ; Astle et al, 2021 ).…”

“…In terms of intervention, diagnostic status may be an inadequate indicator of the broader needs of children with NDDs and not fully capture behavioural and cognitive sequalae ( Kushki et al, 2019 ; Astle et al, 2021 ). Thus, taking a transdiagnostic child needs-based approach rather than focus on diagnosis-specific primary deficits may better serve to support children with NDDs ( Astle and Fletcher-Watson, 2020 ; Astle et al, 2021 ; Kushki et al, 2021 ).…”

Editorial: Precision medicine approaches for heterogeneous conditions such as autism spectrum disorders (The need for a biomarker exploration phase in clinical trials - Phase 2m)

“…The Research Domain Criteria (RDoC) initiative at the National Institute for Mental Health ( 43 ) focuses on specific behavioral or cognitive domains within psychiatric or neurodevelopmental diagnoses and may be more tractable for research that spans methods. In support of this, data-driven brain imaging studies have found that brain networks contribute to social communication in a manner that is not diagnosis specific ( 44 ). Furthermore, recent studies of the structure of ASD symptoms have suggested four or more distinct social communication dimensions and five separate restricted/repetitive behavior subdomains ( 45 – 49 ).…”

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data

“…9,10 To disentangle these findings, a shift from traditional case-control designs to data-driven approaches, which transcend diagnostic boundaries to identify groups that are homogeneous in their neurobiology, is necessary. An emerging body of literature using data-driven approaches supports the idea that the diagnostic categories of ASD, ADHD, and OCD are not associated with unique underlying neurobiological mechanisms 27,28 and often do not predict treatment outcome. 29 This motivates the need for the discovery of homogeneous groups that can accelerate the development of targeted and personalized treatment approaches, interventions, supports, and accommodations that fit the diverse profiles of strengths and needs of children with neurodevelopmental conditions.…”

“…To this end, several studies have used measures of brain function or structure to identify transdiagnostic subgroups of neurodevelopmental conditions, consistently demonstrating a misalignment between data-driven groupings and existing diagnostic categories. 9,10,12,27,28,[30][31][32] The first contribution of this article is to characterize the heterogeneity across neurodevelopmental conditions by identifying cross-diagnosis subgroups of children and adolescents with and without neurodevelopmental conditions using measures of integration and segregation of the functional connectome.…”