From neuroinflammation to neural inference: computational psychiatry meets precision medicine

Psychosis spectrum disorders exhibit substantial clinical variability, necessitating novel frameworks that transcend traditional symptomatic classification. While polygenic risk accounts for significant heritability, the precise mechanisms translating genetic vulnerability into clinical illness remain elusive. An increasingly compelling hypothesis suggests that immune-related abnormalities link genetic risk with environmental stressors to precipitate neural dysfunction. This review integrates neuroimmunology and computational psychiatry to advance mechanism-driven precision medicine by connecting specific molecular dysfunctions to high-level information processing deficits. We synthesize evidence demonstrating that genetic and environmental risks converge on immune pathways-particularly microglial dysfunction and aberrant synaptic pruning. Functionally, we propose this pathology drives fundamental information processing errors, including maladaptive prior beliefs and reduced sensory precision. Here we highlight the necessity of multi-modal biomarkers and real-time digital phenotyping to stratify patients based on underlying neuro-immune endotypes. Finally, we address the critical challenge of algorithmic bias, emphasizing that proactive, standards-based strategies are required to ensure computational models are equitable and generalizable across diverse global populations. This integrated roadmap offers a path toward a truly personalized, biologically grounded psychiatry.