Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model
Objective: By using bioinformatics analysis, abnormal methylated differentially expressed genes (MDEGs) in Kawasaki disease (KD) were identified and a random forest diagnostic model for KD was established. Methods: The expression (GSE18606, GSE68004, GSE73461) and methylation (GSE109430) profiles wa...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844022031930 |
| _version_ | 1811190899636436992 |
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| author | Hongxiao Sun Changying Liu Xu Zhang Panpan Liu Zhanhui Du Gang Luo Silin Pan |
| author_facet | Hongxiao Sun Changying Liu Xu Zhang Panpan Liu Zhanhui Du Gang Luo Silin Pan |
| author_sort | Hongxiao Sun |
| collection | DOAJ |
| description | Objective: By using bioinformatics analysis, abnormal methylated differentially expressed genes (MDEGs) in Kawasaki disease (KD) were identified and a random forest diagnostic model for KD was established. Methods: The expression (GSE18606, GSE68004, GSE73461) and methylation (GSE109430) profiles was retrieved and download from Gene Expression Omnibus (GEO). We conducted enrichment analyses by using R software. In addition, we constructed a protein interaction network, and obtained 6 hub genes. We used expression profiles GSE100154 from GEO to verify the hub genes. Finally, we constructed a diagnostic model based on random forest. Results: We got a total of 55 MDEGs (43 hyper-methylated, low-expressing genes and 12 hypo-methylated, high-expressed genes). Six hub genes (CD2, IL2RB, IL7R, CD177, IL1RN, and MYL9) were identified by Cytoscape software. The area under curve (AUC) of the six hub genes was from 0.745 to 0.898, and the combined AUC was 0.967. The random forest diagnostic model showed that AUC was 0.901. Conclusion: The identification of 6 new hub genes improves our understanding of the molecular mechanism of KD, and the established model can be employed for accurate diagnosis and provide evidence for clinical diagnosis. |
| first_indexed | 2024-04-11T14:58:04Z |
| format | Article |
| id | doaj.art-37899c78922d46f296fd64bb52e1d328 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-11T14:58:04Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-37899c78922d46f296fd64bb52e1d3282022-12-22T04:17:05ZengElsevierHeliyon2405-84402022-11-01811e11905Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic modelHongxiao Sun0Changying Liu1Xu Zhang2Panpan Liu3Zhanhui Du4Gang Luo5Silin Pan6Heart Center, Women and Children’s Hospital, Qingdao University, 266034 Qingdao, ChinaRehabilitation Medicine Department, Women and Children’s Hospital, Qingdao University, 266034 Qingdao, ChinaAnesthesiology Department, Women and Children’s Hospital, Qingdao University, 266034 Qingdao, ChinaHeart Center, Women and Children’s Hospital, Qingdao University, 266034 Qingdao, ChinaHeart Center, Women and Children’s Hospital, Qingdao University, 266034 Qingdao, ChinaHeart Center, Women and Children’s Hospital, Qingdao University, 266034 Qingdao, ChinaHeart Center, Women and Children’s Hospital, Qingdao University, 266034 Qingdao, China; Corresponding author.Objective: By using bioinformatics analysis, abnormal methylated differentially expressed genes (MDEGs) in Kawasaki disease (KD) were identified and a random forest diagnostic model for KD was established. Methods: The expression (GSE18606, GSE68004, GSE73461) and methylation (GSE109430) profiles was retrieved and download from Gene Expression Omnibus (GEO). We conducted enrichment analyses by using R software. In addition, we constructed a protein interaction network, and obtained 6 hub genes. We used expression profiles GSE100154 from GEO to verify the hub genes. Finally, we constructed a diagnostic model based on random forest. Results: We got a total of 55 MDEGs (43 hyper-methylated, low-expressing genes and 12 hypo-methylated, high-expressed genes). Six hub genes (CD2, IL2RB, IL7R, CD177, IL1RN, and MYL9) were identified by Cytoscape software. The area under curve (AUC) of the six hub genes was from 0.745 to 0.898, and the combined AUC was 0.967. The random forest diagnostic model showed that AUC was 0.901. Conclusion: The identification of 6 new hub genes improves our understanding of the molecular mechanism of KD, and the established model can be employed for accurate diagnosis and provide evidence for clinical diagnosis.http://www.sciencedirect.com/science/article/pii/S2405844022031930Differentially expressed genesGene expression omnibusKawasaki diseaseProtein-protein interaction networkRandom forest |
| spellingShingle | Hongxiao Sun Changying Liu Xu Zhang Panpan Liu Zhanhui Du Gang Luo Silin Pan Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model Heliyon Differentially expressed genes Gene expression omnibus Kawasaki disease Protein-protein interaction network Random forest |
| title | Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model |
| title_full | Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model |
| title_fullStr | Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model |
| title_full_unstemmed | Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model |
| title_short | Using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of Kawasaki disease and construct diagnostic model |
| title_sort | using bioinformatics analysis to screen abnormal methylated differentially expressed hub genes of kawasaki disease and construct diagnostic model |
| topic | Differentially expressed genes Gene expression omnibus Kawasaki disease Protein-protein interaction network Random forest |
| url | http://www.sciencedirect.com/science/article/pii/S2405844022031930 |
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