Multi-omics data integration methods and their applications in psychiatric disorders

Sathyanarayanan, Anita;Mueller, Tamara T.;Ali Moni, Mohammad;Schueler, Katja;Baune, Bernhard T.;Lio, Pietro;Mehta, Divya;Baune, Bernhard T;Dierssen, Mara;Ebert, Bjarke;Fabbri, Chiara;Fusar-Poli, Paolo;Gennarelli, Massimo;Harmer, Catherine;Howes, Oliver D.;Janzing, Joost G. E.;Lio, Pietro;Maron, Eduard;Mehta, Divya;Minelli, Alessandra;Nonell, Lara;Pisanu, Claudia;Potier, Marie-Claude;Rybakowski, Filip;Serretti, Alessandro;Squassina, Alessio;Stacey, David;van Westrhenen, Roos;Xicota, Laura

2023-01-01

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Abstract

combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and ma-chine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treat-ment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current chal-lenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry. (c) 2023 Elsevier B.V. and ECNP. All rights reserved.