Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia

Abstract

Background: There is evidence suggesting neuropsychiatric disorders share genomic, cognitive and clinical features. Here, we ask if autism-spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD) and schizophrenia share neuroanatomical variations.

Methods: First, we used measures of cortical anatomy to estimate spatial overlap of neuroanatomical variation using univariate methods. Next, we developed a novel methodology to determine whether cortical deficits specifically target or are "enriched" within functional resting-state networks.

Results: We found cortical anomalies were preferentially enriched across functional networks rather than clustering spatially. Specifically, cortical thickness showed significant enrichment between patients with ASD and those with ADHD in the default mode network, between patients with ASD and those with schizophrenia in the frontoparietal and limbic networks, and between patients with ADHD and those with schizophrenia in the ventral attention network. Networks enriched in cortical thickness anomalies were also strongly represented in functional MRI results (Neurosynth; r = 0.64, p = 0.032).

Limitations: We did not account for variable symptom dimensions and severity in patient populations, and our cross-sectional design prevented longitudinal analyses of developmental trajectories.

Conclusion: These findings suggest that common deficits across neuropsychiatric disorders cannot simply be characterized as arising out of local changes in cortical grey matter, but rather as entities of both local and systemic alterations targeting brain networks.

Fig. 1

Graphical representation of network-set enrichment analysis (NSEA) using 2 hypothetical disorders and corresponding arrays. In both disorders, vertices are ordered using the ranking metric described: −log(p value) × sign(Cohen d), derived from case–control meta-analysis statistics within each disorder. Examining the enrichment score (ES) curves of the default mode network across Disorders A and B: A shows an initially decreasing ES due to default mode network vertices lacking enrichment (clustering) near the top of the ranked list, whereas B shows increasing ES due to highly enriched arrangement in ranked list L near the top.

Fig. 2

Cross-disorder comparisons and combined meta-analysis. (A) Distribution of Cohen d effects across single- and combined-disorder analyses. (B) Meta-analysis of combined-disorder effects (all 3) relative to healthy controls. Colour bars indicate the direction of effect (Cohen d), with warmer colours (red) indicating increased cortical thickness/surface area (CT/SA) and cooler colours (blue) indicating decreased CT/SA compared with controls. Significance levels after false-discovery rate (FDR) correction (or lack thereof) are noted in the second panels. ADHD = attention-deficit/hyperactivity disorder; ASD = autism-spectrum disorder; SCZ = schizophrenia.

Fig. 3

Conjunction analysis examining overlap between disorders by thresholding p values to the top 20%, 15%, 10% and 5% significant vertices within each disorder for (A) cortical thickness, with p value thresholds as follows: p = 0.004 at 20%, p = 0.002 at 15%, and p < 0.001 at both the 10% and 5% thresholds for patients with autism-spectrum disorders (ASD); p = 0.07 at 20%, p = 0.06 at 15%, p = 0.040 at 10% and p = 0.023 at the 5% threshold for patients with attention-deficit/hyperactivity disorder (ADHD); and p < 0.001 at all thresholds for patients with schizophrenia (SCZ), and (B) surface area, with p value thresholds as follows: ASD p = 0.20 at 20%, p = 0.14 at 15%, p = 0.09 at 10% and p = 0.032 at the 5% threshold for patients with ASD; p = 0.12 at 20%, p = 0.09 at 15%, p = 0.05 at 10% and p = 0.028 at the 5% threshold for patients with ADHD; and p < 0.001 at all thresholds for patients with schizophrenia.

Fig. 4

Assessing cross-modal homology comparing structural MRI to Neurosynth functional MRI (fMRI) findings at the network level. (A) Network-set enrichment analysis (NSEA) applied to single-disorder analyses for cortical thickness (CT) and surface area (SA), with Neurosynth comparisons. The Y axis indicates the normalized enrichment score (NES) for all meta-analysis results. Venn diagrams show networks that were significantly enriched across disorders. Correlations of Venn diagrams between CT and Neurosynth was significant (r = 0.64, p = 0.032), whereas the correlation between SA and Neurosynth was not significant (r = −0.48, p = 0.11). (B) The NSEA applied to combined disorder analyses and was compared with Neurosynth results. (C) Examining the dorsal attention SA network ES curves between patients with autism-spectrum disorder (ASD) and schizophrenia (SCZ). The Y axis indicates ES, and the X axis indicates ranked vertices from both hemispheres.