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Network analysis of depressive and anxiety symptoms in schizophrenia: Revealing central symptoms and suicide risk
Yue Wu1, Jingsong Ma2, Yuyin Zhang1
1Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background:
Depressive and anxiety symptoms are highly prevalent in schizophrenia, substantially contributing to disease burden and suicide risk. However, their complex interrelationships remain poorly understood, limiting the development of targeted interventions. This study was the first to apply network analysis to investigate the network structure of depressive and anxiety symptoms specifically in individuals with schizophrenia, aiming to uncover precise therapeutic targets.
Methods:
In a large-scale cross-sectional study of 19,326 individuals with schizophrenia, depressive and anxiety symptoms were assessed using the PHQ-9 and GAD-7. A Gaussian Graphical Model was constructed to map symptom networks, with analyses of centrality, bridge symptoms, community detection, and pathways linking symptoms to suicide ideation. Network stability and gender differences were also examined.
Results:
"Guilt", "Uncontrollable Worry", and "Sad Mood" were the most central symptoms, driving overall symptom severity. "Feeling Afraid", "Irritability", and "Sad Mood" were key bridge symptoms linking depressive and anxiety clusters. Notably, "Guilt", "Motor Retardation", and "Feeling Afraid" showed the strongest direct connections to "suicide ideation", highlighting their potential as intervention targets. Three symptom communities were identified: anxiety (GAD-7 items), core depressive (PHQ-1-5), and severe affective-cognitive (PHQ-6-9). The network demonstrated acceptable stability, moderate predictability, and no significant gender differences.
Conclusions:
This study provided the first network-based characterization of depressive and anxiety symptoms specifically in individuals with schizophrenia uncovering a novel symptom structure, identifying "Guilt", "Uncontrollable Worry", and "Feeling Afraid" as pivotal targets for reducing affective comorbidities and suicide risk. These findings provided a data-driven framework for precision psychiatry, paving the way for tailored interventions to improve clinical outcomes in schizophrenia.
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