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
BACKGROUND
Subcortical regions are widely implicated in the pathological mechanisms and treatment of schizophrenia, and accumulating evidence, including our prior findings, suggests that subcortical functional dysconnectivity is closely associated with treatment response. Accordingly, the present study aimed to examine the relationship between the subcortical functional connectivity (FC) and treatment outcomes in schizophrenia using multivariate analytical approaches and machine learning algorithms.
METHODS
One hundred and nineteen individuals with first-episode schizophrenia were recruited for this study. All patients underwent MRI scanning and completed assessments with the Positive and Negative Syndrome Scale (PANSS) at baseline and at follow-up after 12 weeks of antipsychotic medication. We employed partial least squares analysis to explore the multivariate associations between changes in subcortical FC (∆FC) and changes in symptom severity (∆PANSS). In addition, a machine learning algorithm was used to predict the antipsychotic treatment outcome based on the distinctive subcortical FC pattern at baseline.
RESULTS
We identified a distinctive subcortical FC pattern dominated by the striatum that was associated with overall treatment outcomes in first-episode schizophrenia. Furthermore, the reduction in PANSS total scores predicted using baseline subcortical FC patterns was positively correlated with the actual reduction in PANSS total scores following antipsychotic treatment.
CONCLUSION
These results indicate that the distinctive subcortical FC pattern holds promise as a biomarker for schizophrenia, supporting individualized treatment approaches and facilitating early intervention to improve clinical outcomes.
C. Hou, Huan Huang, Sisi Jiang et al.· Schizophrenia Research· 0 citations
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