White Matter Connectivity in Youth at Risk for Serious Mental Illness: A Longitudinal Analysis

Magnetic resonance advanced imaging analysis in adolescents: cortical thickness study to identify attenuated psychosis syndrome

PURPOSE

Psychosis is a symptom common to several mental illnesses and a defining feature of schizophrenia spectrum disorders, whose onset typically occurs in adolescence. Neuroradiological studies have reported evidence of brain structural abnormalities in patients with overt psychosis. However, early identification of brain structural changes in young subjects at risk for developing psychosis (such as those with Attenuated Psychosis Syndrome -APS) is currently lacking.

METHODS

Brain 3D T1-weighted and 64 directions diffusion-weighted images were acquired on 55 help-seeking adolescents (12-17 years old) with psychiatric disorders who referred to our Institute. Patients were divided into three groups: non-APS (n = 20), APS (n = 20), and Early-Onset Psychosis (n = 15). Cortical thickness was calculated from T1w images, and Tract-Based Spatial Statistics analysis was performed to study the distribution of white matter fractional anisotropy and all diffusivity metrics. A thorough neuropsychological test battery was adopted to investigate cognitive performance in several domains.

RESULTS

In patients with Attenuated Psychotic Syndrome, the left superior frontal gyrus was significantly thinner compared to patients with non-APS (p = 0.048), and their right medial orbitofrontal cortex thickness was associated with lower working memory scores (p = 0.0025, r = -0.668 for the working memory index and p = 0.001, r = -0.738 for the digit span). Early-Onset Psychosis patients showed thinner left pars triangularis compared to non-APS individuals (p = 0.024), and their left pars orbitalis was associated with impaired performance at the symbol search test (p = 0.005, r = -0.726). No differences in diffusivity along main tracts were found between sub-groups (p > 0.05).

CONCLUSION

This study showed specific associations between structural imaging features and cognitive performance in patients with APS. Characterizing this disorder using neuroimaging could reveal useful information that may aid in the development and evaluation of preventive strategies in these individuals.

Brain connectomes in youth at risk for serious mental illness: an exploratory analysis

BACKGROUND

Identifying early biomarkers of serious mental illness (SMI)-such as changes in brain structure and function-can aid in early diagnosis and treatment. Whole brain structural and functional connectomes were investigated in youth at risk for SMI.

METHODS

Participants were classified as healthy controls (HC; n = 33), familial risk for serious mental illness (stage 0; n = 31), mild symptoms (stage 1a; n = 37), attenuated syndromes (stage 1b; n = 61), or discrete disorder (transition; n = 9) based on clinical assessments. Imaging data was collected from two sites. Graph-theory based analysis was performed on the connectivity matrix constructed from whole-brain white matter fibers derived from constrained spherical deconvolution of the diffusion tensor imaging (DTI) scans, and from the correlations between brain regions measured with resting state functional magnetic resonance imaging (fMRI) data.

RESULTS

Linear mixed effects analysis and analysis of covariance revealed no significant differences between groups in global or nodal metrics after correction for multiple comparisons. A follow up machine learning analysis broadly supported the findings. Several non-overlapping frontal and temporal network differences were identified in the structural and functional connectomes before corrections.

CONCLUSIONS

Results suggest significant brain connectome changes in youth at transdiagnostic risk may not be evident before illness onset.

Subcortical Brain Morphometry Differences between Adults with Autism Spectrum Disorder and Schizophrenia

Autism spectrum disorder (ASD) and schizophrenia (SZ) are neuropsychiatric disorders that overlap in symptoms associated with social-cognitive impairment. Subcortical structures play a significant role in cognitive and social-emotional behaviors and their abnormalities are associated with neuropsychiatric conditions. This exploratory study utilized ABIDE II/COBRE MRI and corresponding phenotypic datasets to compare subcortical volumes of adults with ASD (n = 29), SZ (n = 51) and age and gender matched neurotypicals (NT). We examined the association between subcortical volumes and select behavioral measures to determine whether core symptomatology of disorders could be explained by subcortical association patterns. We observed volume differences in ASD (viz., left pallidum, left thalamus, left accumbens, right amygdala) but not in SZ compared to their respective NT controls, reflecting morphometric changes specific to one of the disorder groups. However, left hippocampus and amygdala volumes were implicated in both disorders. A disorder-specific negative correlation (r = −0.39, p = 0.038) was found between left-amygdala and scores on the Social Responsiveness Scale (SRS) Social-Cognition in ASD, and a positive association (r = 0.29, p = 0.039) between full scale IQ (FIQ) and right caudate in SZ. Significant correlations between behavior measures and subcortical volumes were observed in NT groups (ASD-NT range; r = −0.53 to −0.52, p = 0.002 to 0.004, SZ-NT range; r = −0.41 to −0.32, p = 0.007 to 0.021) that were non-significant in the disorder groups. The overlap of subcortical volumes implicated in ASD and SZ may reflect common neurological mechanisms. Furthermore, the difference in correlation patterns between disorder and NT groups may suggest dysfunctional connectivity with cascading effects unique to each disorder and a potential role for IQ in mediating behavior and brain circuits.