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

Yingying Hong; Jiawen Wu; Yang Sun; Shenghai Zhang; Yi Lu; Yinghong Ji

doi:10.7717/peerj.15054

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

PeerJ. 2023 Mar 23:11:e15054. doi: 10.7717/peerj.15054. eCollection 2023.

Authors

Yingying Hong¹, Jiawen Wu¹, Yang Sun¹, Shenghai Zhang¹, Yi Lu¹, Yinghong Ji¹

Affiliation

¹ Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.

Abstract

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.

Keywords: Age-related cataract; Bioinformatics; Enrichment analysis; ceRNA network; lncRNA.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Cluster Analysis
Computational Biology
Genes, Tumor Suppressor*
Genes, cdc*
Humans
Intracellular Signaling Peptides and Proteins
Membrane Proteins

Substances

SPRY2 protein, human
Membrane Proteins
Intracellular Signaling Peptides and Proteins

Grants and funding

This work was supported by the National Natural Science Foundation of China (Grant No. 82070942). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.