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

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.