Whole transcriptome analysis reveals dysregulation of molecular networks in schizophrenia.

Abstract

To characterize the regulatory relationships between different types of transcripts and the altered molecular networks in schizophrenia (SCZ), we performed a whole transcriptome study by quantifying mRNAs, long noncoding RNAs (lncRNAs), miRNAs, and circular RNAs (circRNAs) in the same individuals simultaneously. A total of 807 dysregulated genes showed differential expression in SCZ cases compared with controls. Network-based analysis revealed dysregulation of molecular networks in SCZ. Finally, integration of the transcriptome data with published data identified promising SCZ candidate genes. Our study reveals that dysregulated molecular networks and regulatory relationships between different types of transcript may have a role in SCZ.

• Authors: Jinfeng Yang, Qing Long, Yunqiao Zhang, Yilin Liu, Jie Wu, Xinling Zhao, Xu You, Xiaoyan Li, Jiewei Liu, Zhaowei Teng, Yong Zeng, Xiong-Jian Luo
• Journal: Asian journal of psychiatry (Asian J Psychiatr) Vol. 85 Pg. 103649 (Jul 2023) ISSN: 1876-2026 [Electronic] Netherlands
• PMID: 37267675 (Publication Type: Journal Article)
• Copyright: Copyright © 2023 Elsevier B.V. All rights reserved.

Chemical References

• MicroRNAs
• RNA, Messenger

Topics

• Humans
• Schizophrenia (genetics)
• Gene Regulatory Networks
• MicroRNAs (genetics, metabolism)
• Gene Expression Profiling
• RNA, Messenger (metabolism)