The clinical high-risk (CHR) state identifies individuals at elevated risk for psychosis, yet neurobiological markers of vulnerability remain incompletely characterized, particularly in African populations. Functional Network Area and Topography Analysis (FUNCATA) quantifies individualized network size and spatial organization, addressing limitations of group-average parcellations. Prior studies in schizophrenia identified dorsal attention network (DAN) enlargement and topographic abnormalities. We applied FUNCATA to a Kenyan CHR cohort to examine whether similar alterations are detectable. Twenty-four healthy controls and 63 CHR participants (ages 18-26) underwent resting-state fMRI in Nairobi. Individualized functional networks were derived using template matching. Network size and Topographic Abnormality Index (TAI) were compared between groups using ANCOVA. Associations with symptom dimensions (BPRS-derived principal components), global functioning, cognition, and longitudinal symptom trajectories were examined. CHR participants demonstrated modest left-lateralized DAN enlargement (d = 0.61) and reduced salience network (SAL) size (d = 0.50). More robust effects emerged for TAI, with significantly elevated spatial abnormalities across multiple networks, most prominently the DAN (d = 1.18), default mode network (d = 0.91) and cingulo-opercular network (d = 0.80). Larger left DAN size was associated with longitudinal worsening of general psychopathology, while SAL size was associated with unusual thought processing and role functioning. TAI measures showed limited associations with clinical outcomes after correction. These results suggest that functional network enlargement and spatial reorganization are detectable in CHR individuals within a non-Western cohort. DAN enlargement and widespread topographic abnormalities may represent early neurobiological features of psychosis vulnerability. TAI appears particularly sensitive to spatial deviations and may serve as a promising biomarker for risk stratification and longitudinal monitoring.
D. Mamah, ShingShiun Chen, Michael P. Harms et al.· NeuroImage: Clinical· 0 citations
Abstract Background and Hypothesis Sleep disturbance is a well-established risk factor for suicide, though few studies to date have examined whether sleep disturbance contributes to suicide risk among individuals at clinical high risk for psychosis (CHR). The current study addressed this gap in the literature. We hypothesized that sleep disturbance would have a unique relationship with suicidal ideation/attempts when accounting for other variables in the model. We also hypothesized that the interaction between sleep disturbance/attenuated positive symptoms and sleep disturbance/stress would be related to suicidal ideation/attempts in CHR. Study Design The current study used data generated by the Accelerating Medicines Partnership® Schizophrenia Observational Study. The total sample included 1,048 participants (827 CHR and 221 community controls). Participants completed measures of suicidal ideation/attempts, attenuated positive symptoms, depressive symptoms, perceived stress, and sleep disturbance. Study Results Results supported a relationship between sleep disturbance and suicidal ideation/attempts in CHR, with participants who had lifetime ideation and attempts experiencing more sleep disturbance than those with no ideation or attempts. We also found small, but significant positive correlations between sleep disturbance and suicide risk in CHR. When accounting for other variables in the model, the effect of sleep disturbance remained significant for past month ideation, but not lifetime ideation or attempts. Both interaction models were non-significant. Conclusions Our findings highlight the potential value of sleep measures in early identification and treatment of suicide risk in CHR. Further research in this area is warranted.
H. Wastler, Aubrey M. Moe, Alexandra M Blouin et al.· Schizophrenia Bulletin Open· 0 citations
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