The role of blood-based biomarkers in advancing personalized therapy of schizophrenia

ABSTRACT

Introduction: The discovery of potential biomarkers to improve the clinical management of schizophrenia has received considerable attention. While blood-based markers of this mental disorder have particular appeal, due to their accessibility as part of routine clinical sample collection, the discovery of such peripheral markers however faces specific challenges. It is becoming increasingly clear that the identification of clinically useful biomarker profiles will require integrative analysis across data modalities, to untangle systems-wide etiological mechanisms.

Areas covered: In this review, the authors focus on multivariate integration of high-dimensional data sources, aimed at the characterization of schizophrenia patients at the individual subject level. The authors present current advances of multi-omics integration in schizophrenia research and discuss computational strategies towards this goal.

Expert commentary: Integrative analysis approaches may have to initially focus on individual biological systems of high etiological plausibility. This may help to capture the likely complex structure of etiological mechanisms across data modalities and to take advantage of powerful machine learning methods. The rate at which such methods can learn the etiological complexity from multi-modal data will likely be a bottleneck for development of clinically useful biomarker signatures.

KEYWORDS:

• Blood-based
• biomarker
• schizophrenia
• multi-omics

Declaration of Interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This study was supported by the Deutsche Forschungsgemeinschaft (DFG), SCHW 1768/1-1.