Search

Mounting evidence has shown disrupted brain network architecture across the psychosis spectrum. However, whether these changes relate to the development of psychosis is unclear. Here, we used graph theoretical analysis to investigate longitudinal changes in resting-state brain networks in samples of 72 subjects at clinical high risk (including 8 cases who converted to full psychosis) and 48 healthy controls drawn from the North American Prodrome Longitudinal Study (NAPLS) consortium. We observed progressive reduction in global efficiency (P = 0.006) and increase in network diversity (P = 0.001) in converters compared with non-converters and controls. More refined analysis separating nodes into nine key brain networks demonstrated that these alterations were primarily driven by progressively diminished local efficiency in the default-mode network (P = 0.004) and progressively enhanced node diversity across all networks (P < 0.05). The change rates of network efficiency and network diversity were significantly correlated (P = 0.003), suggesting these changes may reflect shared underlying neural mechanisms. In addition, change rates of global efficiency and node diversity were significantly correlated with change rate of cortical thinning in the prefrontal cortex in converters (P < 0.03) and could be predicted by visuospatial memory scores at baseline (P < 0.04). These results provide preliminary evidence for longitudinal reconfiguration of resting-state brain networks during psychosis development and suggest that decreased network efficiency, reflecting an increase in path length between nodes, and increased network diversity, reflecting a decrease in the consistency of functional network organization, are implicated in the progression to full psychosis.

Disorganization, presenting as impairment in thought, language and goal-directed behavior, is a core multidimensional syndrome of psychotic disorders. This study examined whether scalable computational measures of spoken language, and smartphone usage pattern, could serve as digital biomarkers of clinical disorganization symptoms.We examined in a longitudinal cohort of adults with a psychotic disorder, the associations between clinical measures of disorganization and computational measures of 1) spoken language derived from monthly, semi-structured, recorded clinical interviews; and 2) smartphone usage pattern derived via passive sensing technologies over the month prior to the interview. The language features included speech quantity, rate, fluency, and semantic regularity. The smartphone features included data missingness and phone usage during sleep time. The clinical measures consisted of the Positive and Negative Symptom Scale (PANSS) conceptual disorganization, difficulty in abstract thinking, and poor attention, items. Mixed linear regression analyses were used to estimate both fixed and random effects.Greater severity of clinical symptoms of conceptual disorganization was associated with greater verbosity and more disfluent speech. Greater severity of conceptual disorganization was also associated with greater missingness of smartphone data, and greater smartphone usage during sleep time. While the observed associations were significant across the group, there was also significant variation between individuals.The findings suggest that digital measures of speech disfluency may serve as scalable markers of conceptual disorganization. The findings warrant further investigation into the use of recorded interviews and passive sensing technologies to assist in the characterization and tracking of psychotic illness.

In a recent prospective longitudinal neuroimaging study, clinical high-risk (CHR) individuals who later developed full-blown psychosis showed an accelerated rate of gray matter thinning in superior and medial prefrontal cortex (PFC) and expansion of the ventricular system after applying a stringent correction for multiple comparisons. Although cortical and subcortical volume loss and enlarged ventricles are well characterized structural brain abnormalities among patients with schizophrenia, no prior study has evaluated whether these progressive changes of neuroanatomical indicators are linked in time prior to onset of psychosis. Therefore, we investigated the relationship between the changes in cortical gray matter thickness and ventricular volume using the longitudinal neuroimaging data from the North American Prodrome Longitudinal Study at the whole-brain level. The results showed that ventricular expansion is linked in time to progressive reduction of gray matter, rather than to structural changes in proximal subcortical regions, in a broadly distributed set of cortical regions among CHR youth, including superior, medial, lateral, and inferior PFC, superior temporal gyrus, and parietal cortices. In contrast, healthy controls did not show the same pattern of associations. The main findings were further replicated using a third assessment wave of MRI scans in a subset of study participants who were followed for an additional year. These findings suggest that the gray matter regions exhibiting aberrant rates of thinning in relation to psychosis risk are not limited to the PFC regions that survived the statistical threshold in our primary study, but also extend to other cortical regions previously implicated in schizophrenia.

Several magnetic resonance imaging studies have reported reductions in hippocampal volume in patients with psychosis. It is unclear whether structural abnormalities predate illness onset. We conducted a detailed, systematic literature search for studies reporting hippocampal volume in subjects with clinical high-risk, compared to healthy controls. The overall sample size comprised 1429 subjects. Meta-analysis revealed no difference for left, but a small, albeit significant, difference for right hippocampal volume, such that clinical high-risk patients had slightly smaller hippocampal volume than healthy controls (g=0.24, p=0.0418). Meta-regression indicated a moderating effect of manual tracing approach, due to one outlying site. The small difference on the right side did not remain significant (g=0.14, 95%CI=[-0.03-0.32], p=0.11) after removal of this outlier. This meta-analysis suggests that there is no reduction in hippocampal volume before transition to psychosis and hippocampal volume cannot be used as a biomarker in clinical high-risk individuals.

Highlights • Discriminatory experiences are associated with thinner cortex across time. • Age, gender, and race/ethnicity significantly moderate these associations. • Results persist in healthy subjects and those at clinical high risk for psychosis. • Cortical thickness partially mediates links between discrimination and anxiety., Individuals face discrimination based on characteristics including race/ethnicity, gender, age, and disability. Discriminatory experiences (DE) are associated with poor psychological health in the general population and with worse outcomes among individuals at clinical high risk for psychosis (CHR). Though the brain is sensitive to stress, and brain structural change is a well-documented precursor to psychosis, potential relationships between DE and brain structure among CHR or healthy individuals are not known. This report assessed whether lifetime DE are associated with cortical thinning and clinical outcomes across time, after controlling for discrimination-related demographic factors among CHR individuals who ultimately do (N = 57) and do not convert to psychosis (N = 451), and healthy comparison (N = 208) participants in the North American Prodrome Longitudinal Study 2. Results indicate that DE are associated with thinner cortex across time in several cortical areas. Thickness in several right hemisphere regions partially mediates associations between DE and subsequent anxiety symptoms, but not attenuated positive symptoms of psychosis. This report provides the first evidence to date of an association between DE and brain structure in both CHR and healthy comparison individuals. Results also suggest that thinner cortex across time in areas linked with DE may partially explain associations between DE and cross-diagnostic indicators of psychological distress.