Summary: A new study shows that autism symptom severity, rather than a formal diagnosis, aligns with shared brain-connectivity patterns across children diagnosed with autism or ADHD. Stronger autistic traits were linked to heightened connectivity between frontoparietal and default-mode networks, regions central to social cognition and executive functions.
These connectivity differences also mapped onto gene-expression profiles tied to neural development, suggesting a shared biological mechanism. The findings support a shift toward dimensional, neurobiologically informed approaches to understanding neurodevelopmental conditions.
Key Facts
- Symptom-Based Brain Patterns: Autism severity predicted brain-connectivity differences regardless of whether a child had ASD or ADHD.
- Gene Expression Overlap: Connectivity changes mirrored expression of neural-development genes associated with both conditions.
- Supports Dimensional Models: Results strengthen the case for transdiagnostic, biology-driven frameworks in neurodevelopmental research.
Source: Child Mind Institute
A new study published in Molecular Psychiatry reveals that the biological underpinnings of autism and ADHD may transcend traditional diagnostic boundaries.
While there is increasing appreciation that ADHD and autism often co-occur, the underlying shared biological features have remained largely unknown.
Researchers from the Child Mind Institute and collaborating institutions discovered that autism symptom severity, rather than diagnostic classification, corresponds to distinct patterns of brain connectivity and related gene expression in children diagnosed with either autism spectrum disorder (ASD) or attention-deficit/hyperactivity disorder (ADHD).
This finding supports an evolving clinical and research landscape that aims to better define the roots of neurodevelopmental co-occurrences.
The study, led by Adriana Di Martino, MD, Founding Director of the Autism Center at the Child Mind Institute and Senior Research Scientist, examined brain connectivity using resting-state functional MRI in 166 verbal children aged 6–12 diagnosed with autism or ADHD (without autism).
The team discovered that more severe autism symptoms were associated with increased connectivity between nodes of the frontoparietal (FP) and default-mode (DM) networks, which are known to be essential for social cognition and executive functions.
In typical development, this connectivity decreases with maturation to support functional specialization, so these findings point to a locus of atypical maturation in children with more severe autistic symptoms.
This pattern was observed across all children, regardless of their diagnostic classification, and overlapped with expression maps of genes — particularly those involved in neural development — previously implicated in both autism and ADHD.
“We see in the clinic that some children with ADHD share symptoms qualitatively similar to those observed in autism, even if they do not fully meet the diagnostic criteria for ASD,” says Dr. Adriana Di Martino.
“By focusing on shared brain–gene expression patterns linked to autism symptoms across both ASD and ADHD, we can point towards a shared biological basis of these clinical observations. Our findings provide a more nuanced, dimensional understanding of neurodevelopmental conditions.”
The researchers were able to find this overlap between patterns of connectivity and gene expression by using a novel integrative approach that combines state-of the-art neuroimaging with in silico spatial transcriptomic analysis — a computational method that maps the connectivity patterns observed in participants against existing databases of where genes are expressed in the brain. This approach may be useful for future development of biomarkers associated with these neurodevelopmental conditions.
Key findings include:
- Autism symptom severity is associated with similar patterns of brain connectivity in children with a diagnosis of ASD, and at least a subset of those with ADHD who do not present with a clear diagnosis of autism
- Connectivity differences aligned with brain expression of genes involved in neural development
- The study findings that shared clinical presentations are linked to shared genetic mechanisms between autism and ADHD
- Mechanisms involved in functional network maturation may play a significant role in the development of autistic symptoms in children diagnosed with ASD, and at least a subset of those diagnosed with ADHD
- Findings support the importance of both dimensional and categorical models of neurodevelopmental conditions
- This study will shape future research for biomarkers associated with both conditions, as well as models of vulnerability for autism symptom severity
Implications for Clinical Practice and Research:
The findings suggest that focusing on specific symptom dimensions and their biological correlates may lead to more precise recognition and treatment approaches tailored to individual neural profiles.
The results support a growing movement in psychiatry toward dimensional, transdiagnostic, and data-driven models of mental health. This approach has also been championed by the Child Mind Institute through its Healthy Brain Network, a landmark initiative that enables families to receive no-cost diagnostic assessments — and provides researchers with neuroimaging and phenotypic data from thousands of children.
Key Questions Answered:
A: Autism symptom severity — not diagnostic label — mapped onto distinct brain connectivity patterns shared across ASD and ADHD.
A: Stronger connectivity between the frontoparietal and default-mode networks tracked with more severe autistic symptoms.
A: Yes. The patterns overlapped with expression of genes involved in neural development, previously implicated in both autism and ADHD.
About this Autism, genetics, and ADHD research news
Author: Media Office
Source: Child Mind Institute
Contact: Media Office – Child Mind Institute
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Connectome-based symptom mapping and in silico related gene expression in children with autism and/or attention-deficit/hyperactivity disorder” by Adriana Di Martino et al. Molecular Psychiatry
Abstract
Connectome-based symptom mapping and in silico related gene expression in children with autism and/or attention-deficit/hyperactivity disorder
Clinical, neuroimaging and genomics evidence have increasingly underscored a degree of overlap between autism and attention-deficit/hyperactivity disorder (ADHD).
This study explores the specific contribution of their core symptoms to shared biology in N = 166 verbal children (6–12 years) with rigorously-established primary diagnoses of either autism or ADHD (without autism).
We investigated the associations between inter-individual differences in low motion whole-brain intrinsic functional connectivity (iFC) and dimensional measures of autism and ADHD symptoms indexed by clinician-based observation and parent interview, respectively.
Additionally, we explored their linked gene expression patterns in silico. Whole-brain multivariate distance matrix regression revealed a transdiagnostic association between autism severity and iFC of two nodes primarily on the left hemisphere: the middle frontal gyrus of the frontoparietal network and the posterior cingulate cortex of the default mode network.
Across children, the greater the iFC between these nodes, the more severe the autism symptoms, even after controlling for ADHD ratings.
Results from secondary segregation analyses were consistent with primary findings, underscoring the significance of internetwork iFC for autism symptom severity across diagnoses.
No statistically significant brain-behavior relationships were observed for ADHD symptoms.
Genetic enrichment analyses of the iFC maps associated with autism symptoms implicated genes known to: (i) have greater rate of variance in autism and ADHD, and (ii) be involved in neuron projections, suggesting shared genetic mechanisms for this specific brain-clinical phenotype.
These findings underscore the relevance of transdiagnostic dimensional approaches in linking clinically-defined and observation-based phenomena to shared presentations at the macroscale circuit- and genomic-levels across diagnoses.
