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pmid:37283588

Bioinformatics analysis of aging-related genes in thoracic aortic aneurysm and dissection.

Hong Wan · Danlingyi Liu · Bingqing Liu · Mengyao Sha · Wei Xia · Chang Liu

Frontiers in cardiovascular medicine · 2023 doi:10.3389/fcvm.2023.1089312

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Experiment

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Data

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Analysis

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title
Bioinformatics analysis of aging-related genes in thoracic aortic aneurysm and dissection.
doi
10.3389/fcvm.2023.1089312
pmid
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Hong Wan
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Danlingyi Liu
[2]
Bingqing Liu
[3]
Mengyao Sha
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Wei Xia
[5]
Chang Liu
journal
Frontiers in cardiovascular medicine
year
2023
abstract
Objective: Thoracic aortic aneurysm and dissection (TAAD) is a cardiovascular disease with a high mortality rate. Aging is an important risk factor for TAAD. This study explored the relationship between aging and TAAD and investigated the underlying mechanisms, which may contribute to the diagnosis and treatment of TAAD. Methods: Human aging genes were obtained from the Aging Atlas official website. Various datasets were downloaded from the GEO database:the human TAAD dataset GSE52093 were used for screening differentially expressed genes (DEGs); GSE137869, GSE102397 and GSE153434 were used as validation sets, and GSE9106 was used for diagnostic prediction of receiver operating characteristic (ROC) curves. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and protein-protein interaction (PPI) network analysis were used to screen differentially co-expressed genes from human aging genes and TAAD. Using five methods of the cytoHubba plugin in Cytoscape software (Degree, Closeness, EPC, MNC, Radiality), hub genes were identified from the differentially co-expressed genes. Single-cell RNA sequencing was used to verify the expression levels of hubgenes in different cell types of aortic tissue. ROC curves were used to further screen for diagnostic genes. Results: A total of 70 differentially co-expressed genes were screened from human aging genes and DEGs in human TAAD dataset GSE52093. GO enrichment analysis revealed that the DEGs played a major role in regulating DNA metabolism and damaged DNA binding. KEGG enrichment analysis revealed enrichment in the longevity regulating pathway, cellular senescence, and HIF-1 signaling pathway. GSEA indicated that the DEGs were concentrated in the cell cycle and aging-related p53 signaling pathway. The five identified hubgenes were MYC, IL6, HIF1A, ESR1, and PTGS2. Single-cell sequencing of the aging rat aorta showed that hubgenes were expressed differently in different types of cells in aortic tissue. Among these five hubgenes, HIF1A and PTGS2 were validated in the aging dataset GSE102397; MYC, HIF1A and ESR1 were validated in the TAAD dataset GSE153434. The combined area under the diagnostic ROC curve (AUC) values for the five hub genes were >0.7 in the testing and training sets of the dataset GSE9106. The combined AUC values of MYC and ESR1 were equal to the combin ed AUC values of the five hub genes. Conclusion: The HIF-1 signaling pathway may play an important role in TAAD and aging. MYC and ESR1 may have diagnostic value for aging-related TAAD.
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The area under the diagnostic ROC curve (AUC) showed that in the testing set the combined AUC of these five hubgenes was 0.812, while in the training set the combined AUC value was 0.731.
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A combined ROC with MYC and ESR1 that had individual AUC > 0.7 was then performed and the results were equal to the AUC value of the combined ROC of all five hub genes (Figure 6E).
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This study explored the relationship between aging and TAAD and investigated the underlying mechanisms, which may contribute to the diagnosis and treatment of TAAD.\nMethods: Human aging genes were obtained from the Aging Atlas official website. Various datasets were downloaded from the GEO database:the human TAAD dataset GSE52093 were used for screening differentially expressed genes (DEGs); GSE137869, GSE102397 and GSE153434 were used as validation sets, and GSE9106 was used for diagnostic prediction of receiver operating characteristic (ROC) curves. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and protein-protein interaction (PPI) network analysis were used to screen differentially co-expressed genes from human aging genes and TAAD. Using five methods of the cytoHubba plugin in Cytoscape software (Degree, Closeness, EPC, MNC, Radiality), hub genes were identified from the differentially co-expressed genes. 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Among these five hubgenes, HIF1A and PTGS2 were validated in the aging dataset GSE102397; MYC, HIF1A and ESR1 were validated in the TAAD dataset GSE153434. The combined area under the diagnostic ROC curve (AUC) values for the five hub genes were >0.7 in the testing and training sets of the dataset GSE9106. The combined AUC values of MYC and ESR1 were equal to the combin ed AUC values of the five hub genes.\nConclusion: The HIF-1 signaling pathway may play an important role in TAAD and aging. 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