Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network
Objective. This study aimed to investigate the molecular regulatory mechanisms underpinning Duchenne muscular dystrophy (DMD). Methods. Using microarray data, differentially expressed long noncoding RNAs (DELs) and DMD-related differentially expressed mRNAs (DEMs) were screened based on the comparat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Hindawi - Cambridge University Press
2022-01-01
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| Series: | Genetics Research |
| Online Access: | http://dx.doi.org/10.1155/2022/8548804 |
| _version_ | 1797977085844652032 |
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| author | Bing Xu Chunlei Zheng |
| author_facet | Bing Xu Chunlei Zheng |
| author_sort | Bing Xu |
| collection | DOAJ |
| description | Objective. This study aimed to investigate the molecular regulatory mechanisms underpinning Duchenne muscular dystrophy (DMD). Methods. Using microarray data, differentially expressed long noncoding RNAs (DELs) and DMD-related differentially expressed mRNAs (DEMs) were screened based on the comparative toxicogenomics database, using a cutoff of |log2 fold change| > 1 and false discovery rate (FDR) < 0.05. Then, protein-protein interaction (PPI), coexpression network of lncRNA-mRNA, and DMD-related lncRNA-mRNA pathway networks were constructed, and functional analyses of the genes in the network were performed. Finally, the proportions of immune cells infiltrating the muscle tissues in DMD were analyzed, and the correlation between the immune cells and expression of the DELs/DEMs was studied. Results. A total of 46 DELs and 313 DMD-related DEMs were identified. The PPI network revealed STAT1, VEGFA, and CCL2 to be the top three hub genes. The DMD-related lncRNA-mRNA pathway network comprising two pathways, nine DELs, and nine DMD-related DEMs showed that PYCARD, RIPK2, and CASP1 were significantly enriched in the NOD-like receptor signaling pathway, whereas MAP2K2, LUM, RPS6, PDCD4, TWIST1, and HIF1A were significantly enriched with proteoglycans in cancers. The nine DELs in this network were DBET, MBNL1-AS1, MIR29B2CHG, CCDC18-AS1, FAM111A-DT, GAS5, LINC01290, ATP2B1-AS1, and PSMB8-AS1. Conclusion. The nine DMD-related DEMs and DELs identified in this study may play important roles in the occurrence and progression of DMD through the two pathways of the NOD-like receptor signaling pathway and proteoglycans in cancers. |
| first_indexed | 2024-04-11T05:01:20Z |
| format | Article |
| id | doaj.art-cf0c28a460a14ffd82293ae9beff11af |
| institution | Directory Open Access Journal |
| issn | 1469-5073 |
| language | English |
| last_indexed | 2024-04-11T05:01:20Z |
| publishDate | 2022-01-01 |
| publisher | Hindawi - Cambridge University Press |
| record_format | Article |
| series | Genetics Research |
| spelling | doaj.art-cf0c28a460a14ffd82293ae9beff11af2022-12-26T01:12:14ZengHindawi - Cambridge University PressGenetics Research1469-50732022-01-01202210.1155/2022/8548804Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway NetworkBing Xu0Chunlei Zheng1Department of PediatricsDepartment of OrthopedicsObjective. This study aimed to investigate the molecular regulatory mechanisms underpinning Duchenne muscular dystrophy (DMD). Methods. Using microarray data, differentially expressed long noncoding RNAs (DELs) and DMD-related differentially expressed mRNAs (DEMs) were screened based on the comparative toxicogenomics database, using a cutoff of |log2 fold change| > 1 and false discovery rate (FDR) < 0.05. Then, protein-protein interaction (PPI), coexpression network of lncRNA-mRNA, and DMD-related lncRNA-mRNA pathway networks were constructed, and functional analyses of the genes in the network were performed. Finally, the proportions of immune cells infiltrating the muscle tissues in DMD were analyzed, and the correlation between the immune cells and expression of the DELs/DEMs was studied. Results. A total of 46 DELs and 313 DMD-related DEMs were identified. The PPI network revealed STAT1, VEGFA, and CCL2 to be the top three hub genes. The DMD-related lncRNA-mRNA pathway network comprising two pathways, nine DELs, and nine DMD-related DEMs showed that PYCARD, RIPK2, and CASP1 were significantly enriched in the NOD-like receptor signaling pathway, whereas MAP2K2, LUM, RPS6, PDCD4, TWIST1, and HIF1A were significantly enriched with proteoglycans in cancers. The nine DELs in this network were DBET, MBNL1-AS1, MIR29B2CHG, CCDC18-AS1, FAM111A-DT, GAS5, LINC01290, ATP2B1-AS1, and PSMB8-AS1. Conclusion. The nine DMD-related DEMs and DELs identified in this study may play important roles in the occurrence and progression of DMD through the two pathways of the NOD-like receptor signaling pathway and proteoglycans in cancers.http://dx.doi.org/10.1155/2022/8548804 |
| spellingShingle | Bing Xu Chunlei Zheng Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network Genetics Research |
| title | Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network |
| title_full | Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network |
| title_fullStr | Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network |
| title_full_unstemmed | Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network |
| title_short | Analysis of Long Noncoding RNAs-Related Regulatory Mechanisms in Duchenne Muscular Dystrophy Using a Disease-Related lncRNA-mRNA Pathway Network |
| title_sort | analysis of long noncoding rnas related regulatory mechanisms in duchenne muscular dystrophy using a disease related lncrna mrna pathway network |
| url | http://dx.doi.org/10.1155/2022/8548804 |
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