Altered expression of mRNA profiles in blood of early-onset schizophrenia
Copyright policy )Altered expression of mRNA profiles in blood of early-onset schizophrenia
AbstractTo identify gene expression abnormalities in schizophrenia (SZ), we generated whole-genome gene expression profiles using microarrays on peripheral blood mononuclear cells (PBMCs) from 18 early-onset SZ cases and 12 controls. We detected 84 transcripts differentially expressed by diagnostic status, with 82 genes being upregulated and 2 downregulated. We identified two SZ associated gene coexpression modules (green and red), including 446 genes . The green module is positively correlated with SZ, encompassing predominantly up-regulated genes in SZ; while the red module was negatively correlated with disease status, involving mostly nominally down-regulated genes in SZ. The olfactory transduction pathway was the most enriched pathways for the genes within the two modules. The expression levels of several hub genes, including AKT1, BRCA1, CCDC134, UBD and ZIC2 were validated using real-time quantitative PCR. Our findings indicate that mRNA coexpression abnormalities may serve as a promising mechanism underlying the development of SZ.
- Shanxi Medical University China (People's Republic of)
- National Institute of Mental Health United States
- National Institutes of Health United States
- National Institute of Health Pakistan
- McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA United States
Male, Adolescent, Gene Expression Profiling, Reproducibility of Results, Article, Gene Expression Regulation, Case-Control Studies, Schizophrenia, Cluster Analysis, Humans, Female, Gene Regulatory Networks, RNA, Messenger, Age of Onset, Child, Transcriptome
Male, Adolescent, Gene Expression Profiling, Reproducibility of Results, Article, Gene Expression Regulation, Case-Control Studies, Schizophrenia, Cluster Analysis, Humans, Female, Gene Regulatory Networks, RNA, Messenger, Age of Onset, Child, Transcriptome
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