Probing Autism and ADHD subtypes using cortical signatures of the T1w/T2w-ratio and morphometry

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental conditions that share genetic etiology and frequently co-occur. Given this comorbidity and the well-established clinical heterogeneity within both conditions, identifying individuals with similar brain signatures may be valuable for predicting clinical outcomes and tailoring treatment strategies. Cortical myelination is a prominent developmental process, and its disruption is one of the candidate mechanisms for both disorders. Yet, no studies have attempted to identify subtypes based on T1w/T2w-ratio, a magnetic resonance imaging (MRI) based proxy for intracortical myelin. Moreover, cortical variability likely arises from numerous biological pathways, and multimodal approaches can effectively integrate several cortical metrics by fusing them into a single network. We analyzed data from 310 youths aged 2.6-23.6 years, obtained from the Province of Ontario Neurodevelopmental (POND) Network consisting of individuals diagnosed with ASD (n=136), ADHD (n=100), and typically developing (TD) individuals (n=74). We first tested for differences in cortical microstructure between diagnostic categories and controls, as assessed by the T1w/T2w-ratio. We then performed unimodal (T1w/T2w-ratio) and multimodal (T1w/T2w-ratio, cortical thickness, and surface area) spectral clustering to identify diagnostic-blind subgroups. As hypothesized, we did not find statistically significant case-control differences in T1w/T2w-ratio. Unimodal clustering mostly isolated single individual- or minority clusters, driven by image quality and intensity outliers. Multimodal clustering suggested three distinct subgroups, which transcended diagnostic boundaries, showing distinct cortical patterns but similar clinical and cognitive profiles. T1w/T2w-ratio features were the most relevant for demarcation, followed by surface area. While there do not appear to be considerable differences at the diagnostic group level, multimodal clustering using the T1w/T2w-ratio holds promise for identifying biologically similar subsets among individuals with neurodevelopmental conditions.