Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction

Abstract

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Fig. 1. Overall strategy for Schizophrenia Omics research.

Genomics is highlighted in the center as most integrative omics approaches are genome-first. Pairwise interactions are shown by lines connecting different omics.

Fig. 2. Examples of integrative Omics studies on Schizophrenia.

Eight recent reports were included as representative (two examples in each of those four categories) to demonstrate the usefulness of integrative Omics studies on schizophrenia (SCZ) research for pathogenesis (1), disease classification (2), risk prediction (3), and precise intervention (4). For each study, we briefly summarized the Omics data and the integrative methods used, and then highlighted the key SCZ findings identified by their application. eQTL expression quantitative trait locus, CMC CommonMind Consortium, DLPFC dorsolateral prefrontal cortex, GWAS genome-wide association study, MHC the major histocompatibility complex, cQTL chromatin quantitative trait locus, fMRI functional magnetic resonance imaging, PET positron emission tomography, SPECT single photon emission computed tomography, FSA functional striatal abnormalities, PRS polygenic risk score, ELC early-life complications, co-eQTL co-expression quantitative trait loci, Cmap The Connectivity Map.