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Affective and non-affective psychoses exhibit heterogeneous clinical presentation, neurobiological underpinnings, and treatment response. This special issue integrates multimodal findings to examine overlapping and distinct neural substrates in the psychosis spectrum. In this context, longitudinal designs appear essential to observe the developmental trajectory of patients and advance real-world precision psychiatry. Interestingly, gray matter changes in psychotic patients point toward the possibility of differential developmental trajectories in insular subregions between affective and non-affective psychosis. Moreover, white matter abnormalities shared by schizophrenia and bipolar disorder, as revealed by diffusion tensor imaging studies, might indicate common neural mechanisms affecting cognitive and behavioral functions across both conditions. Beyond these neuroimaging findings, stratification approaches based on immune-inflammatory profiles may further characterize biologically distinct subgroups, with immune-neurobiological interactions potentially contributing to illness trajectories. Finally, machine learning techniques, integrating clinical and neuroimaging data in a multimodal approach, emerged as promising tools for predicting critical outcomes, such as suicide, enabling earlier and more targeted interventions. The evidence presented in this special issue underscores the complexity of psychotic disorders and the need for multimodal approaches. Future research will be essential to improve predictive tools and refine biomarker integration.