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Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease

Diabetic kidney disease (DKD) has become the major contributor to end-stage renal disease with high incidence and mortality. The functional roles and exact mechanisms of long noncoding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) network in DKD are still largely unknown. This study sough...

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Autores principales: Wang, Ya, Tan, Jie, Xu, Cheng, Wu, Hongyan, Zhang, Youshan, Xiong, Ying, Yi, Cunjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183707/
https://www.ncbi.nlm.nih.gov/pubmed/34087849
http://dx.doi.org/10.1097/MD.0000000000026062
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author Wang, Ya
Tan, Jie
Xu, Cheng
Wu, Hongyan
Zhang, Youshan
Xiong, Ying
Yi, Cunjian
author_facet Wang, Ya
Tan, Jie
Xu, Cheng
Wu, Hongyan
Zhang, Youshan
Xiong, Ying
Yi, Cunjian
author_sort Wang, Ya
collection PubMed
description Diabetic kidney disease (DKD) has become the major contributor to end-stage renal disease with high incidence and mortality. The functional roles and exact mechanisms of long noncoding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) network in DKD are still largely unknown. This study sought to discover novel potential biomarkers and ceRNA network for DKD. The candidate differentially expressed genes (DEGs), lncRNAs and microRNAs (miRNAs) in human glomerular and tubular tissues derived from Gene Expression Omnibus database were systematically selected and analyzed. Functional enrichment analysis and protein-protein interaction network analysis were conducted to identify hub genes and reveal their regulatory mechanisms involved in DKD. Following this, the integrated ceRNA network was constructed by bioinformatics methods. A total of 164 DEGs, 6 lncRNAs and 18 miRNAs correlated with DKD were finally filtered and identified. It is noteworthy that the global lncRNA-associated ceRNA network related to DKD was constructed, among which lnc-HIST2H2AA4-1, VCAN-AS1 and MAGI2-AS1 were identified as the 3 key lncRNAs, and VCAN, FN1, CCL2, and KNG1 were identified as the predominant genes. Consistent with that observed in the training set, 3 of the key genes also showed significant differences in the 2 validation datasets. Integrating with functional enrichment analysis results, these key genes in the ceRNA network were mainly enriched in the immune and inflammation-related pathways. This study first identified key lncRNAs, miRNAs and their targets, and further revealed a global view of lncRNA-associated ceRNA network involved in DKD by using whole gene transcripts analysis.
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spelling pubmed-81837072021-06-07 Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease Wang, Ya Tan, Jie Xu, Cheng Wu, Hongyan Zhang, Youshan Xiong, Ying Yi, Cunjian Medicine (Baltimore) 4300 Diabetic kidney disease (DKD) has become the major contributor to end-stage renal disease with high incidence and mortality. The functional roles and exact mechanisms of long noncoding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) network in DKD are still largely unknown. This study sought to discover novel potential biomarkers and ceRNA network for DKD. The candidate differentially expressed genes (DEGs), lncRNAs and microRNAs (miRNAs) in human glomerular and tubular tissues derived from Gene Expression Omnibus database were systematically selected and analyzed. Functional enrichment analysis and protein-protein interaction network analysis were conducted to identify hub genes and reveal their regulatory mechanisms involved in DKD. Following this, the integrated ceRNA network was constructed by bioinformatics methods. A total of 164 DEGs, 6 lncRNAs and 18 miRNAs correlated with DKD were finally filtered and identified. It is noteworthy that the global lncRNA-associated ceRNA network related to DKD was constructed, among which lnc-HIST2H2AA4-1, VCAN-AS1 and MAGI2-AS1 were identified as the 3 key lncRNAs, and VCAN, FN1, CCL2, and KNG1 were identified as the predominant genes. Consistent with that observed in the training set, 3 of the key genes also showed significant differences in the 2 validation datasets. Integrating with functional enrichment analysis results, these key genes in the ceRNA network were mainly enriched in the immune and inflammation-related pathways. This study first identified key lncRNAs, miRNAs and their targets, and further revealed a global view of lncRNA-associated ceRNA network involved in DKD by using whole gene transcripts analysis. Lippincott Williams & Wilkins 2021-06-04 /pmc/articles/PMC8183707/ /pubmed/34087849 http://dx.doi.org/10.1097/MD.0000000000026062 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle 4300
Wang, Ya
Tan, Jie
Xu, Cheng
Wu, Hongyan
Zhang, Youshan
Xiong, Ying
Yi, Cunjian
Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease
title Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease
title_full Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease
title_fullStr Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease
title_full_unstemmed Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease
title_short Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease
title_sort identification and construction of lncrna-associated cerna network in diabetic kidney disease
topic 4300
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183707/
https://www.ncbi.nlm.nih.gov/pubmed/34087849
http://dx.doi.org/10.1097/MD.0000000000026062
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