Evaluation of miRNA Expression Profiles in Schizophrenia Using Principal-Component Analysis-Based Unsupervised Feature Extraction Method.

Abstract

Schizophrenia (SZ) is a disease that causes mental disability and affects 1% of the total population in the world. Our aim was to identify new molecular targets that would help to diagnose and treat these patients. The GSE54578 microRNA expression profile was downloaded from the Gene Expression Omnibus database that consists of peripheral blood samples of 15 first-onset SZ patients and 15 healthy controls. Principal-component analysis-based unsupervised feature extraction (FE), protein-protein interaction network, and pathway enrichment were performed, and microRNA (miRNA)-hub gene network was established. A set of seven miRNA (hsa-miR-373-5p, hsa-miR-199a-3p, hsa-miR-22-5p, hsa-miR-4711-3p, hsa-miR-3157-3p, hsa-miR-542-5p, and hsa-miR-3615) could successfully discriminate SZ patients from healthy controls with high accuracy. We identified two miRNAs (hsa-miR-373-5p and hsa-miR-199a-3p) as a signature that mostly related to SZ. These miRNAs could be potential novel biomarkers and could contribute to the clinical treatment of this disease.