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Whole transcriptome analysis reveals dysregulation of molecular networks in schizophrenia.

Authors :
Yang J
Long Q
Zhang Y
Liu Y
Wu J
Zhao X
You X
Li X
Liu J
Teng Z
Zeng Y
Luo XJ
Source :
Asian journal of psychiatry [Asian J Psychiatr] 2023 Jul; Vol. 85, pp. 103649. Date of Electronic Publication: 2023 May 24.
Publication Year :
2023

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.<br />Competing Interests: Declaration of Competing Interest The authors declare no competing interests.<br /> (Copyright © 2023 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1876-2026
Volume :
85
Database :
MEDLINE
Journal :
Asian journal of psychiatry
Publication Type :
Academic Journal
Accession number :
37267675
Full Text :
https://doi.org/10.1016/j.ajp.2023.103649