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A Guide to Generating and Using hiPSC Derived NPCs for the Study of Neurological Diseases
Published on: February 21, 2015
Comprehensive transcriptome analysis and lncRNA-miRNA-mRNA establishment of schizophrenia based on induced
Ningning Jia1, Xuyuan Yin2, Zhenhua Zhu2
1Research Center of Biological Psychiatry, Suzhou Guangji Hospital, Suzhou Medical College of Soochow University, Suzhou 215137, China; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China.
Background:
Schizophrenia (SCZ) is a complex and heterogeneous disorder with unclear underlying mechanisms. Identifying key gene diseases and constructing biological regulatory networks were beneficial in expanding our understanding of the pathogenesis of SCZ.
Methods:
We conducted whole transcriptome sequencing of induced pluripotent stem cells (iPSCs) derived from 5 SCZ patients and 5 healthy controls to analyze differences in mRNA and non-coding RNA expression profiles. Differentially expressed mRNAs (DE mRNAs) were explored for their functions and pathways, and lncRNA-miRNA-mRNA regulatory networks were constructed to understand post-transcriptional regulation mechanisms. Additionally, correlation analyses between competitive endogenous RNAs (ceRNAs), hub genes, and clinical phenotypes of SCZ patients (positive/negative and cognitive symptoms) were performed.
Results:
We identified 139 DE mRNAs, 154 lncRNAs, and 19 miRNAs. Significant enrichment of pathways related to apoptosis, inflammatory response, hypoxia, KRAS signaling, and IL6_JAK_STAT3 signaling were observed. Ten hub genes, CCK, CCNA1, CDH5, GATA2, GRPR, NPY, PRKG2, TLE6, ZEB1and ZEB2, were identified, of which ZEB1 and GATA2 were positively correlated with positive symptoms of SCZ, while CDH5 and GRPR were associated with memory. The ceRNA regulatory network (TPM1-AS/ADPGK-AS1/MIRLET7BHG-hsa-mir-3180/3180-3p-LRRC15/TUBA8 and MIRLET7BHG- hsa-mir-3187-3p- CCDC92/ TDRD6/ TMEM26/ ATP1A2) was established, which was also significantly associated with positive, negative and cognitive symptoms of SCZ.
Conclusions:
This study identified potential hub genes, pathways, and lncRNA-miRNA-mRNA regulatory networks in iPSCs that provide new insights into the molecular mechanisms of SCZ. The identified hub genes and ceRNA showed significant correlations with various clinical phenotypes of SCZ, offering potential biomarkers and therapeutic targets.
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