An ECNP-led global biomarkers mapping project across anxiety, depression and psychosis disorders: an umbrella systematic review

Introduction

Over the past decades, biomarker research in mental disorders has expanded rapidly, spanning genetic, molecular, neuroimaging, and behavioral domains. Biomarkers objectively measure indicators of biological processes or responses to exposures or interventions, and have transformed other areas of medicine by enabling early diagnosis, risk stratification, and treatment selection. In psychiatry, however, translation into clinical practice remains limited. This gap reflects several challenges, including heterogeneity of biomarkers across levels of analysis, lack of standardized frameworks for evaluating their clinical utility, and limited statistical power in many studies due to small sample sizes and fragmented research efforts.[1-3]

Aims

To address the challenges, we will be performing an umbrella systematic review, aiming to comprehensively synthesize the evidence on biomarkers associated with susceptibility, diagnosis, prognosis, treatment response, and monitoring in anxiety, depression, psychosis, and transdiagnostic populations. A central objective is to map these biomarkers within a unified translational framework to evaluate their readiness for clinical implementation.

Methods

The review follows PRISMA guidelines. A preliminary search was conducted in PubMed, Web of Science, PsycINFO, Cochrane Library, and EMBASE. In addition, ongoing pre-registrations from PROSPERO were also searched. Eligibility criteria were defined using the PICO framework. The population (P) includes human participants with anxiety, depression, or psychosis across the lifespan. The intervention (I) comprises biomarkers across multiple domains, including genetic, epigenetic, peripheral (e.g., inflammatory or hormonal), electrophysiological, neuroimaging, neuropathological, and behavioral task-based measures. The comparator (C) includes healthy controls, lower-risk groups, or within-sample comparisons where applicable. The outcomes (O) includes clinically relevant endpoints such as susceptibility/risk, diagnosis, prognosis, treatment response, and longitudinal monitoring. Biomarkers will be classified along four dimensions: (1) level of analysis (molecular to social), (2) context of use (diagnostic, prognostic, predictive, monitoring), (3) clinical scope (disorder-specific vs transdiagnostic), and (4) stage of validation (discovery to clinical implementation), enabling comparison across heterogeneous evidence within a unified translational framework.

Results

A preliminary search identified 871 records in PubMed, 1,183 in Web of Science, 2,374 in Embase, and 666 in PsycINFO, suggesting the existence of a large body of literature on biomarkers in mental disorders. These studies spanned multiple domains, with a predominance in neuroimaging and inflammatory biomarkers. In parallel, a preliminary search of the PROSPERO registry revealed a substantial number of ongoing or pre-registered systematic reviews, including 364 in anxiety, 622 in depression, and 104 in psychosis. These preliminary findings highlight the rapid expansion of the evidence base alongside a high level of ongoing synthesis activity across diagnostic domains. Full screening and reviewing of the literature is undergoing, thus, more detailed results will be presented at the conference.

Conclusions

Current biomarker research in psychiatry is characterized by substantial heterogeneity. Integrating biomarkers across levels of analysis and aligning them with specific contexts of use may improve their translational potential. Addressing limitations such as limited statistical power and fragmented evidence will be critical for advancing clinically actionable biomarkers and supporting precision psychiatry across diagnostic boundaries.

References

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