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A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis

Objective: The primary study aim was to identify long non-coding RNA (lncRNA) abnormalities associated with ultra-high-risk (UHR) for psychosis based on a weighted gene co-expression network analysis. Methods: UHR patients were screened by the structured interview for prodromal syndromes (SIPS). We...

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Autores principales: Ren, Yan, Li, Wei, Liu, Sha, Li, Zhi, Wang, Jiaying, Yang, Hong, Xu, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769947/
https://www.ncbi.nlm.nih.gov/pubmed/33384626
http://dx.doi.org/10.3389/fpsyt.2020.580307
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author Ren, Yan
Li, Wei
Liu, Sha
Li, Zhi
Wang, Jiaying
Yang, Hong
Xu, Yong
author_facet Ren, Yan
Li, Wei
Liu, Sha
Li, Zhi
Wang, Jiaying
Yang, Hong
Xu, Yong
author_sort Ren, Yan
collection PubMed
description Objective: The primary study aim was to identify long non-coding RNA (lncRNA) abnormalities associated with ultra-high-risk (UHR) for psychosis based on a weighted gene co-expression network analysis. Methods: UHR patients were screened by the structured interview for prodromal syndromes (SIPS). We performed a WGCNA analysis on lncRNA and mRNA microarray profiles generated from the peripheral blood samples in 14 treatment-seeking patients with UHR who never received psychiatric medication and 18 demographically matched typically developing controls. Gene Ontology (GO) analysis and canonical correlation analysis were then applied to reveal functions and correlation between lncRNAs and mRNAs. Results: The lncRNAs were organized into co-expressed modules by WGCNA, two modules of which were strongly associated with UHR. The mRNA networks were constructed and two disease-associated mRNA modules were identified. A functional enrichment analysis showed that mRNAs were highly enriched for immune regulation and inflammation. Moreover, a significant correlation between lncRNAs and mRNAs were verified by a canonical correlation analysis. Conclusion: We identified novel lncRNA modules related to UHR. These results contribute to our understanding of the molecular basis of UHR from the perspective of systems biology and provide a theoretical basis for early intervention in the assumed development of schizophrenia.
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spelling pubmed-77699472020-12-30 A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis Ren, Yan Li, Wei Liu, Sha Li, Zhi Wang, Jiaying Yang, Hong Xu, Yong Front Psychiatry Psychiatry Objective: The primary study aim was to identify long non-coding RNA (lncRNA) abnormalities associated with ultra-high-risk (UHR) for psychosis based on a weighted gene co-expression network analysis. Methods: UHR patients were screened by the structured interview for prodromal syndromes (SIPS). We performed a WGCNA analysis on lncRNA and mRNA microarray profiles generated from the peripheral blood samples in 14 treatment-seeking patients with UHR who never received psychiatric medication and 18 demographically matched typically developing controls. Gene Ontology (GO) analysis and canonical correlation analysis were then applied to reveal functions and correlation between lncRNAs and mRNAs. Results: The lncRNAs were organized into co-expressed modules by WGCNA, two modules of which were strongly associated with UHR. The mRNA networks were constructed and two disease-associated mRNA modules were identified. A functional enrichment analysis showed that mRNAs were highly enriched for immune regulation and inflammation. Moreover, a significant correlation between lncRNAs and mRNAs were verified by a canonical correlation analysis. Conclusion: We identified novel lncRNA modules related to UHR. These results contribute to our understanding of the molecular basis of UHR from the perspective of systems biology and provide a theoretical basis for early intervention in the assumed development of schizophrenia. Frontiers Media S.A. 2020-12-15 /pmc/articles/PMC7769947/ /pubmed/33384626 http://dx.doi.org/10.3389/fpsyt.2020.580307 Text en Copyright © 2020 Ren, Li, Liu, Li, Wang, Yang and Xu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Ren, Yan
Li, Wei
Liu, Sha
Li, Zhi
Wang, Jiaying
Yang, Hong
Xu, Yong
A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis
title A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis
title_full A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis
title_fullStr A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis
title_full_unstemmed A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis
title_short A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis
title_sort weighted gene co-expression network analysis reveals lncrna abnormalities in the peripheral blood associated with ultra-high-risk for psychosis
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769947/
https://www.ncbi.nlm.nih.gov/pubmed/33384626
http://dx.doi.org/10.3389/fpsyt.2020.580307
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