Revealing differential psychotic symptoms in schizophrenia and bipolar I disorder by manifold learning and network analyses.

The field of psychiatry has encountered ongoing challenges in understanding the intricate nature of psychotic symptoms, particularly when they manifest in individuals diagnosed with bipolar disorder or schizophrenia. In this study, we employed manifold and network analyses to investigate whether the pattern of symptom occurrence differs between schizophrenia and bipolar I disorder. We analyzed data collected from 555 individuals, 282 of whom were diagnosed with schizophrenia-related disorders and 273 with bipolar I disorder. In the context of schizophrenia, negative symptoms, particularly avolition, were prominent with manifold and network analyses, identifying avolition as a high central symptom associated with clozapine use, patterns of deterioration, tendency toward remission, and illness severity. Conversely, bipolar I disorder exhibits discernible patterns where positive symptoms play a central role in network analysis. Unexpectedly, manifold analysis revealed two distinct clusters of patients, suggesting variability in psychotic symptom profiles within bipolar I disorder. In conclusion, schizophrenia and bipolar I disorder, while sharing psychotic symptoms, exhibit distinct co-occurrence patterns. Schizophrenia demonstrates negative symptoms, whereas bipolar I disorder exhibits a stronger interconnectivity of psychotic symptoms, highlighting the complexity of psychotic symptom patterns and their relevance for understanding psychiatric disorders. These findings highlight the complexity of psychotic symptom patterns and their relevance for understanding psychiatric disorders.