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Several biological changes are associated with increased risk or imminent onset of psychosis, but no single marker is currently accurate enough to diagnose or predict onset on its own in clinical practice. Multiple systems show alterations before and around first-episode psychosis, eg., immune/inflammatory markers, brain structure and function, electrophysiology, neurotransmitters, and cognition.

Current work focuses on multidimensional risk signatures (combining clinical, cognitive, immune, EEG, and imaging data) rather than one standalone biomarker. Peripheral immune / inflammatory markers: Individuals at clinical high risk (CHR) and early psychosis show altered serum cytokines and immune markers (e.g.

IL6, IL10, VEGF, chemokines, complement proteins) compared with controls. In a large CHR cohort, higher VEGF and an elevated IL10/IL6 ratio modestly predicted later transition to psychosis, suggesting dysregulated inflammatory balance and possibly increased blood–brain barrier permeability.

Antipsychoticnaïve firstepisode psychosis samples show elevated plasma inflammatory molecules (e.g. TNFα, CCL2, CCL4, CCL11) that correlate with CSF inflammatory markers and glutamatergic neuro-metabolites, pointing to a neuroinflammatory subtype.

Brain imaging markers: Structural MRI and longitudinal imaging indicate aberrant brain developmental trajectories predating illness, with gray matter volume reductions in regions such as temporal and frontal cortices in CHR and firstepisode samples. Functional imaging shows altered activation and connectivity in salience and sociocognitive networks (e.g. anterior insula, anterior cingulate, temporoparietal regions), which seem to differ between risk states, firstepisode, and controls.

Multimodal imaging integrated with clinical and cognitive data can modestly improve prediction of which CHR individuals will transition, though accuracy remains below what is needed for routine individuallevel use. Electrophysiological (EEG/ERP) markers: Eventrelated potentials such as mismatch negativity (MMN) and P300 are consistently reduced or delayed in schizophrenia and firstepisode psychosis, and abnormalities are already detectable in some atrisk individuals and relatives.

P300 latency and amplitude disturbances, and MMN deficits, have “highly suggestive” or replicated evidence as biomarkers linked to transition risk, cognitive impairment, and gray matter loss. Sensory gating markers (e.g. P50 suppression), gammaband connectivity, and restingstate EEG source measures can distinguish CHR, firstepisode, and controls, and may stratify different psychosis stages.

Neurochemical and neurotransmitter markers: Magnetic resonance spectroscopy in antipsychoticnaïve firstepisode psychosis finds elevated glutamate/Glx in regions such as the dorsal caudate, correlating with plasma and CSF inflammatory molecules. These findings support models where microglial activation and glutamatergic dysregulation contribute to synaptic/neuronal loss and symptom emergence in a subset of patients.

Cognitive and social-cognitive markers: Broad cognitive deficits (processing speed, verbal memory, working memory, executive functions) are already present at first episode, with larger impairments predicting worse functional outcome. In CHR and early psychosis, poorer attention/processing speed and executive function at baseline predict lower global functioning over followup, making them candidate prognostic markers rather than specific onset markers.

Social cognition deficits (e.g. theory of mind, emotion recognition) are also evident early and relate to functional prognosis but are not specific enough to uniquely signal imminent transition. Current clinical reality: Individually, immune markers, EEG indices, imaging features, or cognitive scores show only modest predictive value (AUCs often in the 0.6 range or lower) for transition from CHR to psychosis.

The most promising direction is integrating multiple biomarker dimensions with clinical highrisk assessments (e.g. CAARMS, SIPS) to refine risk estimates and tailor preventive interventions, but this is still largely researchstage. References Byrne, J.F., Monagn, D., Murphy, J., Healy, C., Focking, M., Cannon, M. & Cotter, D.R. (2023, October 28).

Prognostic Models Predicting Transition to Psychotic Disorder Using Blood-Based Biomarkers: A Systematic Review and Critical Appraisal. Translational Psychiatry. Cadenhead, K.S., Mirzakhanian, H., Achim, C., Reyes-Madrigal, F. & de la Fuente-Sandoval, C. (2023, December 12). 264:39-48.

Peripheral and Central Biomarkers Associated with Inflammation in Antipsychotic Naïve First Episode Psychosis: Pilot Studies. Schizophrenia Research. Fuentes-Claramonte, P., Estrade, A., Solanes, A., Ramella-Cravaro, V., Garcia-Leon, M.A., et al. (2024, August 30). 5(1).

Biomarkers for Psychosis: Are We There Yet? Umbrella Review of 1478 Biomarkers. Schizophrenia Bulletin Open. Lee, H.S. & Kim, J.S. (2022, January 2). Implication of Electrophysiological Biomarkers in Psychosis: Focusing on Diagnosis and Treatment Response.

Journal of Personalized Medicine. Mondelli, V., Blackman, G., Kempton, M.J., Pollak, T.A., Iyegbe, C., et al. (2023, May). 110:290-296. Serum Immune Markers and Transition to Psychosis in Individuals at Clinical High Risk. Brain, Behavior, and Immunity.

Tusconi, M. & Dursun, S.M. (2025, April 21). 16: 1591274. Editorial: Neuroimaging in Psychiatry 2023: Schizophrenia. Frontiers in Psychiatry. Zhang, T.H., Xu, L.H., Tang, X.C., Wei, Y.Y., Hu, Y.G., et al. (2023, November 14). Comprehensive Review of Multidimentional Biomarkers in the Shanghai At Risk for Psychosis (SHARP) Program for Early Psychosis Identification.

Psychiatry and Clinical Neurosciences Reports.

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