Integrative metabolomics-genomics analysis identifies key networks in a stem cell-based model of schizophrenia.

Abstract

Schizophrenia is a neuropsychiatric disorder, caused by a combination of genetic and environmental factors. Recently, metabolomic studies based on patients’ biofluids and post-mortem brain specimens have revealed altered levels of distinct metabolites between healthy individuals and patients with schizophrenia (SCZ). However, a putative link between dysregulated metabolites and distorted neurodevelopment has not been assessed and access to patients’ material is restricted. In this study, we aimed to investigate a presumed correlation between transcriptomics and metabolomics in a SCZ model using patient-derived induced pluripotent stem cells (iPSCs). iPSCs were differentiated towards cortical neurons and samples were collected longitudinally at defined developmental stages, such as neuroepithelium, radial glia, young and mature neurons. Samples were subsequently analyzed by bulk RNA-sequencing and targeted metabolomics. The transcriptomic analysis revealed dysregulations in several extracellular matrix-related genes in the SCZ samples observed in early neurogenesis, including members of the collagen superfamily. At the metabolic level, several lipid and amino acid discrepancies were correlated to the SCZ phenotype. By employing a novel in silico analysis, we correlated the transcriptome with the metabolome through the generation of integrative networks. The network comparison between SCZ and healthy controls revealed a number of consistently affected pathways in SCZ, related to early stages of cortical development, indicating abnormalities in membrane composition, lipid homeostasis and amino acid imbalances. Ultimately, our study suggests a novel approach of correlating in vitro metabolic and transcriptomic data obtained from a patient-derived iPSC model. This type of analysis will offer novel insights in cellular and genetic mechanisms underlying the pathogenesis of complex neuropsychiatric disorders, such as schizophrenia.