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Biomarkers for Predicting Clinical Deterioration in Schizophrenia-Spectrum Disorders: A Systematic Review
Valerio Ricci1, Alessandro Sarni1,2, Marialuigia Barresi1,2
1San Luigi Gonzaga Hospital, University of Turin, Regione Gonzole, 10, 10043 Orbassano, Italy.
Brain Sciences
|June 26, 2026
Summary
Objective neurobiological tools are needed to predict psychotic relapse in schizophrenia. This review found neurophysiological and inflammatory markers, like mismatch negativity and interleukin-6, show promise for monitoring, but no single biomarker is currently accurate enough for clinical use.
Area of Science:
- Neuroscience
- Psychiatry
- Biomarker Research
Background:
- Psychotic relapse is common in schizophrenia-spectrum disorders, leading to disability and hospitalizations.
- Current relapse management relies on symptom monitoring, lacking objective neurobiological tools for personalized treatment decisions.
Purpose of the Study:
- To systematically review evidence on neurophysiological, blood-based, molecular, neuroimaging, and digital biomarkers for predicting relapse in schizophrenia-spectrum disorders.
- To identify the most promising biomarkers for potential clinical implementation in relapse management.
Main Methods:
- Systematic review of longitudinal biomarker studies following PRISMA 2020 guidelines.
- Searched five databases through March 2026, assessing study quality using Newcastle-Ottawa Scale and PROBAST.
- Narrative synthesis of findings from 21 included studies across different illness stages.
Main Results:
- Mismatch negativity and P300 event-related potentials showed consistent associations with relapse risk.
- Inflammatory (interleukin-6, C-reactive protein) and neuroendocrine (cortisol awakening response) markers predicted poor treatment response.
- Peripheral gene expression (TCF4 network) and digital phenotyping showed potential but require further development; neuroimaging did not outperform clinical variables.
Conclusions:
- No single biomarker currently achieves sufficient accuracy for routine clinical implementation in relapse prediction.
- Neurophysiological (mismatch negativity) and inflammatory markers are the most tractable candidates for monitoring protocols.
- A combination of mismatch negativity and interleukin-6/cortisol awakening response shows promise for pilot implementation in specialized settings.
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