Identification of differentially expressed and methylated genes and construction of a co-expression network in age-related macular degeneration

Liang, Gaohua; Ma, Wenhao; Luo, Yanni; Yin, Jiayang; Hao, Lili; Zhong, Jingxiang

doi:10.21037/atm-21-7043

Cited by 6 publications

(5 citation statements)

References 40 publications

(34 reference statements)

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“…Among these genes, activation of ERK1 /2 and CREB showed protection function for human RPEs from H 2 O 2 -induced oxidative damage ( 36 ). AR was proved to be a hub gene during the pathogenesis of AMD ( 37 ). These results provide further insights into the biological processes and potential roles regulated by the 12 hub genes.…”

Section: Resultsmentioning

confidence: 99%

The transcriptome profile of RPE cells by the fullerenol against hydrogen peroxide stress

Yao²,

Xu³

et al. 2022

Front. Med.

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Age-related macular degeneration (AMD) causes central vision impairment with increased incidence. In the pathogenesis of AMD, reactive oxygen species (ROS) are associated with RPE cell apoptosis. H2O2 is an oxidative toxicant and is used to establish the AMD in vitro model. However, the mechanisms of ROS in H2O2-induced AMD are still unclear. Fullerenol, a promising antioxidant of nanomaterials, protects RPE cells from ROS attack. In addition to working as a scavenger, little is known about the antioxidant mechanism of fullerenol in RPE cells. In this study, transcriptome sequencing was performed to examine the global changes in mRNA transcripts induced by H2O2 in human ARPE-19 cells. Moreover, we comprehensively investigated the protective effects of fullerenol against H2O2-induced oxidative injury by RNA sequencing. Gene Ontology enrichment analysis showed that those pathways related to the release of positive regulation of DNA-templated transcription and negative regulation of apoptotic process were affected. Finally, we found that 12 hub genes were related to the oxidative-protection function of fullerenol. In summary, H2O2 affected these hub genes and signaling pathways to regulate the senescence of RPE cells. Moreover, fullerenol is a potent nanomaterial that protects the RPE and would be a promising approach for AMD prevention.

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Section: Resultsmentioning

confidence: 99%

The transcriptome profile of RPE cells by the fullerenol against hydrogen peroxide stress

Yao²,

Xu³

et al. 2022

Front. Med.

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“…They observed that the expression of FSTL1 was higher in AMD compared to the normal control group. Niu et al also investigated the potential involvement of FSTL1 in the pathogenesis of PDR by analyzing vitreous uid and proliferative membrane samples from PDR patients 30,31 . These ndings align with our results.…”

Section: Discussionmentioning

confidence: 99%

Identification of key biomarkers in Diabetic retinopathy and age-related macular degeneration by integrated bioinformatics analysis

Feng,

Gao

2024

Preprint

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Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are the main causes of visual impairment in individuals aged 50 and above globally. Interestingly, there is a complex relationship between DR and AMD, although the specific mechanisms connecting them are not yet fully understood. This study aims to identify common gene signatures and uncover potential molecular mechanisms involved in the development of both DR and AMD. The gene expression profiles of GSE160306 and GSE29801 were obtained from the Gene Expression Omnibus (GEO) database to analyze the differences in gene expression between AMD, DR, and healthy samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the clusterProfiler package in R. The protein-protein interaction (PPI) network was constructed using the STRING database and Cytoscape software. Additionally, meaningful hub genes were identified through machine-learning algorithms. Receiver operating characteristic (ROC) analyses were conducted to assess the diagnostic value of the differentially expressed genes (DEGs) for DR and AMD. Overall, a total of 5 DEGs (C5, KRAS, FSTL1, KCNV2, and PILRB) were identified, and further analysis revealed key pathways, gene modules, and co-expression networks associated with DR and AMD.

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“…In this study, we analyzed the gene expression of genes in the RPE/choroid tissues, aiming to identify hub genes in AMD patients. In contrast to previous research ( Li et al, 2022 ; Liang et al, 2022 ; Wang et al, 2022 ), our approach utilized three gene expression profiles comprising 55 AMD samples and 138 control samples. Two of these datasets were used to identify DEGs, whereas the third dataset was used to analyze key gene network modules through the WGCNA.…”

Section: Discussionmentioning

confidence: 99%

“…Systematic network analyses based on gene expression profiles can assist in identifying key genes and disease-related pathways. Traditional analyses of AMD have focused primarily on differentially expressed genes (DEGs), with limited knowledge regarding their co-expression patterns ( Li et al, 2022 ; Liang et al, 2022 ; Wang et al, 2022 ). Weighted gene co-expression network analysis (WGCNA) has been widely used to explore key modules and hub genes for the identification of candidate biomarkers and therapeutic targets in diseases like cancers and neuropsychiatric disorders ( Li et al, 2018 ; Jo et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

“…Weighted gene co-expression network analysis (WGCNA) has been widely used to explore key modules and hub genes for the identification of candidate biomarkers and therapeutic targets in diseases like cancers and neuropsychiatric disorders ( Li et al, 2018 ; Jo et al, 2023 ). Only few studies used the WGCNA to uncover the co-expression network characteristics in AMD ( Liang et al, 2022 ; Han and He, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

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Identification of the CDH18 gene associated with age-related macular degeneration using weighted gene co-expression network analysis

Liu,

Tan,

Liu

et al. 2024

Front. Genet.

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Purpose: Age-related macular degeneration (AMD) is a chronic and progressive macular degenerative disease that culminates in a gradual deterioration of central vision. Despite its prevalence, the key biomarkers for AMD have not yet been fully elucidated. In this study, we aimed to efficiently identify biomarkers crucial for diagnosing AMD.Methods: Three datasets pertaining to retinal pigment epithelium (RPE)/choroid tissues associated with AMD were selected from the GEO database. The GSE50195 dataset was utilized to conduct weighted gene co-expression network analysis (WGCNA) for identifying module genes linked to AMD. KEGG and GO enrichment analyses were subsequently conducted on these module genes. GSE29801 and GSE135092 datasets were subjected to differential expression analysis to pinpoint the DEGs intersecting with the module genes. Subsequently, wet AMD (wAMD) and dry AMD (dAMD) mouse models were developed, from which RPE/choroid tissues were harvested to validate the hub genes via RT-qPCR and Western blot.Results: Using the WGCNA, we selected the “antiquewhite4” module (r = 0.91 and p = 7e-07), which contains a total of 325 genes. Through the intersection of module genes with DEGs, nine hub genes were identified. Pathways involved in complement and coagulation cascades, ECM–receptor interactions, unsaturated fatty acid biosynthesis, and fatty acid elongation play important roles in AMD. Notably, CDH18 demonstrated notable variance across all three datasets. Post validation using RT-qPCR experiments revealed a significant downregulation of CDH18 in both dAMD and wAMD. EGLN3 was expressed at low levels in wAMD. In dAMD, EYA2, LTB, and PODXL were significantly downregulated, whereas APOC1 was notably upregulated. Western blot confirmed that CDH18 was lowly expressed in dAMD and wAMD mouse models.Conclusion: CDH18 was identified as the key gene involved in the pathogenesis of AMD. An imbalance of the complement and coagulation cascades is a potential mechanism of AMD. This study provides a novel idea for diagnosing and treating AMD in the future.

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Identification of differentially expressed and methylated genes and construction of a co-expression network in age-related macular degeneration

Cited by 6 publications

References 40 publications

The transcriptome profile of RPE cells by the fullerenol against hydrogen peroxide stress

The transcriptome profile of RPE cells by the fullerenol against hydrogen peroxide stress

Identification of key biomarkers in Diabetic retinopathy and age-related macular degeneration by integrated bioinformatics analysis

Identification of the CDH18 gene associated with age-related macular degeneration using weighted gene co-expression network analysis

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