Integrative Analysis Identified Key Schizophrenia Risk Factors from an Abnormal Behavior Mouse Gene Set

Abstract

Schizophrenia (SCZ) is a severe chronic psychiatric illness with heterogeneous symptoms. However, the pathogenesis of SCZ is unclear, and the number of well-defined SCZ risk factors is limited. We hypothesized that an abnormal behavior (AB) gene set verified by mouse model experiments can be used to better understand SCZ risks. In this work, we carried out an integrative bioinformatics analysis to study two types of risk genes that are either differentially expressed (DEGs) in the case-control study data or carry reported SCZ genetic variants (MUTs). Next, we used RNA-Seq expression data from the hippocampus (HIPPO) and dorsolateral prefrontal cortex (DLPFC) to define the key genes affected by different types (DEGs and MUTs) in different brain regions (DLPFC and HIPPO): DLPFC-kDEG, DLPFC-kMUT, HIPPO-kDEG, and HIPPO-kMUT. The four hub genes (SHANK1, SHANK2, DLG4, and NLGN3) of the biological functionally enriched terms were strongly linked to SCZ via gene co-expression network analysis. Then, we observed that specific spatial expressions of DLPFC-kMUT and HIPPO-kMUT were convergent in the early stages and divergent in the later stages of development. In addition, all four types of key genes showed significantly larger average protein–protein interaction degrees than the background. Comparing the different cell types, the expression of four types of key genes showed specificity in different dimensions. Together, our results offer new insights into potential risk factors and help us understand the complexity and regional heterogeneity of SCZ.

Epigenome-Wide Meta-Analysis Reveals Differential DNA Methylation Associated With Estimated Glomerular Filtration Rate Among African American Men With HIV

“… 35 Variants of the SHANK1 gene have been associated with a spectrum of neurodevelopmental disorders, and neurologic complications are reported to be highly prevalent among PWH and in CKD, irrespective of the cause. 36 , 37 , 38 , 39 This identified signal could be related to the development of neurologic diseases that are common among PWH and in CKD.…”

Multi-Omics for the Understanding of Brain Diseases

“…Concerning neuropsychiatric disorders, an integrative multi-omics analysis identified four categories of key genes involved in the pathogenesis of schizophrenia (SCZ), thus offering new insights to better understand the complexity and regional heterogeneity of SCZ [8]. Moreover, another study suggested that the disruption of DGCR8-dependent microRNA biogenesis is crucial for the 22q11.21 copy number variant (CNV) genes involved in psychiatric disorders for late fetal cortical development [9].…”