Cargando…

ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics

BACKGROUND: The aim of this study is to investigate the genetic and epigenetic mechanisms involved in the pathogenesis of age-related cataract (ARC). METHODS: We obtained the transcriptome datafile of th ree ARC samples and three healthy, age-matched samples and used differential expression analyses...

Descripción completa

Detalles Bibliográficos
Autores principales: Hong, Yingying, Wu, Jiawen, Sun, Yang, Zhang, Shenghai, Lu, Yi, Ji, Yinghong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10040182/
https://www.ncbi.nlm.nih.gov/pubmed/36987450
http://dx.doi.org/10.7717/peerj.15054
_version_ 1784912426769055744
author Hong, Yingying
Wu, Jiawen
Sun, Yang
Zhang, Shenghai
Lu, Yi
Ji, Yinghong
author_facet Hong, Yingying
Wu, Jiawen
Sun, Yang
Zhang, Shenghai
Lu, Yi
Ji, Yinghong
author_sort Hong, Yingying
collection PubMed
description BACKGROUND: The aim of this study is to investigate the genetic and epigenetic mechanisms involved in the pathogenesis of age-related cataract (ARC). METHODS: We obtained the transcriptome datafile of th ree ARC samples and three healthy, age-matched samples and used differential expression analyses to identify the differentially expressed genes (DEGs). The differential lncRNA-associated competing endogenous (ceRNA) network, and the protein-protein network (PPI) were constructed using Cytoscape and STRING. Cluster analyses were performed to identify the underlying molecular mechanisms of the hub genes affecting ARC progression. To verify the immune status of the ARC patients, immune-associated analyses were also conducted. RESULTS: The PPI network identified the FOXO1 gene as the hub gene with the highest score, as calculated by the Maximal Clique Centrality (MCC) algorithm. The ceRNA network identified lncRNAs H19, XIST, TTTY14, and MEG3 and hub genes FOXO1, NOTCH3, CDK6, SPRY2, and CA2 as playing key roles in regulating the pathogenesis of ARC. Additionally, the identified hub genes showed no significant correlation with an immune response but were highly correlated with cell metabolism, including cysteine, methionine, and galactose. DISCUSSION: The findings of this study may provide clues toward ARC pathogenic mechanisms and may be of significance for future therapeutic research.
format Online
Article
Text
id pubmed-10040182
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher PeerJ Inc.
record_format MEDLINE/PubMed
spelling pubmed-100401822023-03-27 ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics Hong, Yingying Wu, Jiawen Sun, Yang Zhang, Shenghai Lu, Yi Ji, Yinghong PeerJ Bioinformatics BACKGROUND: The aim of this study is to investigate the genetic and epigenetic mechanisms involved in the pathogenesis of age-related cataract (ARC). METHODS: We obtained the transcriptome datafile of th ree ARC samples and three healthy, age-matched samples and used differential expression analyses to identify the differentially expressed genes (DEGs). The differential lncRNA-associated competing endogenous (ceRNA) network, and the protein-protein network (PPI) were constructed using Cytoscape and STRING. Cluster analyses were performed to identify the underlying molecular mechanisms of the hub genes affecting ARC progression. To verify the immune status of the ARC patients, immune-associated analyses were also conducted. RESULTS: The PPI network identified the FOXO1 gene as the hub gene with the highest score, as calculated by the Maximal Clique Centrality (MCC) algorithm. The ceRNA network identified lncRNAs H19, XIST, TTTY14, and MEG3 and hub genes FOXO1, NOTCH3, CDK6, SPRY2, and CA2 as playing key roles in regulating the pathogenesis of ARC. Additionally, the identified hub genes showed no significant correlation with an immune response but were highly correlated with cell metabolism, including cysteine, methionine, and galactose. DISCUSSION: The findings of this study may provide clues toward ARC pathogenic mechanisms and may be of significance for future therapeutic research. PeerJ Inc. 2023-03-23 /pmc/articles/PMC10040182/ /pubmed/36987450 http://dx.doi.org/10.7717/peerj.15054 Text en ©2023 Hong et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Hong, Yingying
Wu, Jiawen
Sun, Yang
Zhang, Shenghai
Lu, Yi
Ji, Yinghong
ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics
title ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics
title_full ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics
title_fullStr ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics
title_full_unstemmed ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics
title_short ceRNA network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics
title_sort cerna network construction and identification of hub genes as novel therapeutic targets for age-related cataracts using bioinformatics
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10040182/
https://www.ncbi.nlm.nih.gov/pubmed/36987450
http://dx.doi.org/10.7717/peerj.15054
work_keys_str_mv AT hongyingying cernanetworkconstructionandidentificationofhubgenesasnoveltherapeutictargetsforagerelatedcataractsusingbioinformatics
AT wujiawen cernanetworkconstructionandidentificationofhubgenesasnoveltherapeutictargetsforagerelatedcataractsusingbioinformatics
AT sunyang cernanetworkconstructionandidentificationofhubgenesasnoveltherapeutictargetsforagerelatedcataractsusingbioinformatics
AT zhangshenghai cernanetworkconstructionandidentificationofhubgenesasnoveltherapeutictargetsforagerelatedcataractsusingbioinformatics
AT luyi cernanetworkconstructionandidentificationofhubgenesasnoveltherapeutictargetsforagerelatedcataractsusingbioinformatics
AT jiyinghong cernanetworkconstructionandidentificationofhubgenesasnoveltherapeutictargetsforagerelatedcataractsusingbioinformatics