Exploration of Mutated Genes and Prediction of Potential Biomarkers for Childhood-Onset Schizophrenia Using an Integrated Bioinformatic Analysis

Abstract

Childhood-onset schizophrenia (COS) is an unusual severe neurodevelopmental disorder of unknown etiology. In this study, we aimed to survey the missense variants in new cases of COS and also identify possible pathology biomarkers for COS. We found one list of mutated genes such as TTN, MUC12, and MUC2, which are the candidates to be involved in the etiology of COS. Next, we used WGSNA to predict COS disease-related genes and identified differential DNA methylation among COS disease groups, COS dangerous groups, and normal groups and found eight methylation sites that can be used as the diagnostic biomarkers. A total of six key genes are obtained through the intersection analysis between weighted correlation network analysis (WGCNA) mode, methylation-related genes, and differentially expressed genes (DGenes). These genes may play important roles in the progression of COS and serve as the potential biomarkers for future diagnosis. Our results might help to design the molecule or gene-targeted drugs for COS.