Identification of feature genes and key biological pathways in immune-mediated necrotizing myopathy: High-throughput sequencing and bioinformatics analysis
Background: Immune-mediated necrotizing myopathy (IMNM), a subgroup of idiopathic inflammatory myopathies (IIMs), is characterized by severe proximal muscle weakness and prominent necrotic fibers but no infiltration of inflammatory cells. IMNM pathogenesis is unclear. This study investigated key bio...
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Elsevier
2023-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037023001186 |
| _version_ | 1827577680374005760 |
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| author | Kai Chen Chun-yan Zhu Jia-ying Bai Feng Xiao Song Tan Qiao Zhou Li Zeng |
| author_facet | Kai Chen Chun-yan Zhu Jia-ying Bai Feng Xiao Song Tan Qiao Zhou Li Zeng |
| author_sort | Kai Chen |
| collection | DOAJ |
| description | Background: Immune-mediated necrotizing myopathy (IMNM), a subgroup of idiopathic inflammatory myopathies (IIMs), is characterized by severe proximal muscle weakness and prominent necrotic fibers but no infiltration of inflammatory cells. IMNM pathogenesis is unclear. This study investigated key biomarkers and potential pathways for IMNM using high-throughput sequencing and bioinformatics technology. Methods: RNA sequencing was conducted in 18 IMNM patients and 10 controls. A combination of weighted gene coexpression network analysis (WGCNA) and differentially expressed gene (DEG) analysis was conducted to identify IMNM-related DEGs. Feature genes were screened out by employing the proteinprotein interaction (PPI) network, support vector machine-recursive feature elimination (SVM-RFE), and least absolute shrinkage selection operator (LASSO). Quantitative real-time polymerase chain reaction (qRTPCR) was performed to verify their differential expression, and the receiver operating characteristic curve (ROC) was used to evaluate their diagnostic efficiency. Functional enrichment analysis was applied to reveal the hidden functions of feature genes. Furthermore, 28 immune cell abundance patterns in IMNM samples were measured. Results: We identified 193 IMNM-related DEGs that were aberrantly upregulated in the IMNM population and were closely associated with immune-inflammatory responses, regulation of skeletal and cardiac muscle contraction, and lipoprotein metabolism. With the help of the PPI network and the LASSO and SVM-RFE algorithms, three feature genes, LTK, MYBPH, and MYL4, were identified and further confirmed by qRTPCR. ROC curves among IMNM, dermatomyositis (DM), inclusion body myositis (IBM), and polymyositis (PM) samples validated the LTK and MYL4 genes as IMNM-specific feature markers. In addition, all three genes had a notable association with the autophagylysosome pathway and immune-inflammatory responses. Ultimately, IMNM displayed a marked immune-cell infiltrative microenvironment. The most significant correlation was found between CD4 T cells, CD8 T cells, macrophages, natural killer (NK) cells, and dendritic cells (DCs). Conclusions: LTK, MYBPH, and MYL4 were identified as potential key molecules for IMNM and are believed to play a role in the autophagylysosome pathway and muscle inflammation. |
| first_indexed | 2024-03-08T21:31:21Z |
| format | Article |
| id | doaj.art-838f52a104a74150bbfbbe4311c334c4 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-03-08T21:31:21Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
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| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-838f52a104a74150bbfbbe4311c334c42023-12-21T07:31:14ZengElsevierComputational and Structural Biotechnology Journal2001-03702023-01-012122282240Identification of feature genes and key biological pathways in immune-mediated necrotizing myopathy: High-throughput sequencing and bioinformatics analysisKai Chen0Chun-yan Zhu1Jia-ying Bai2Feng Xiao3Song Tan4Qiao Zhou5Li Zeng6Department of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, ChinaDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, ChinaDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, ChinaDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, ChinaDepartment of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China; Sichuan Provincial Key Laboratory for Human Disease Gene Study, Chengdu, ChinaDepartment of Rheumatology and Immunology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China; Clinical Immunology Translational Medicine Key Laboratory of Sichuan Province, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China,; Corresponding author at: Department of Rheumatology and Immunology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China.Department of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China; Corresponding author.Background: Immune-mediated necrotizing myopathy (IMNM), a subgroup of idiopathic inflammatory myopathies (IIMs), is characterized by severe proximal muscle weakness and prominent necrotic fibers but no infiltration of inflammatory cells. IMNM pathogenesis is unclear. This study investigated key biomarkers and potential pathways for IMNM using high-throughput sequencing and bioinformatics technology. Methods: RNA sequencing was conducted in 18 IMNM patients and 10 controls. A combination of weighted gene coexpression network analysis (WGCNA) and differentially expressed gene (DEG) analysis was conducted to identify IMNM-related DEGs. Feature genes were screened out by employing the proteinprotein interaction (PPI) network, support vector machine-recursive feature elimination (SVM-RFE), and least absolute shrinkage selection operator (LASSO). Quantitative real-time polymerase chain reaction (qRTPCR) was performed to verify their differential expression, and the receiver operating characteristic curve (ROC) was used to evaluate their diagnostic efficiency. Functional enrichment analysis was applied to reveal the hidden functions of feature genes. Furthermore, 28 immune cell abundance patterns in IMNM samples were measured. Results: We identified 193 IMNM-related DEGs that were aberrantly upregulated in the IMNM population and were closely associated with immune-inflammatory responses, regulation of skeletal and cardiac muscle contraction, and lipoprotein metabolism. With the help of the PPI network and the LASSO and SVM-RFE algorithms, three feature genes, LTK, MYBPH, and MYL4, were identified and further confirmed by qRTPCR. ROC curves among IMNM, dermatomyositis (DM), inclusion body myositis (IBM), and polymyositis (PM) samples validated the LTK and MYL4 genes as IMNM-specific feature markers. In addition, all three genes had a notable association with the autophagylysosome pathway and immune-inflammatory responses. Ultimately, IMNM displayed a marked immune-cell infiltrative microenvironment. The most significant correlation was found between CD4 T cells, CD8 T cells, macrophages, natural killer (NK) cells, and dendritic cells (DCs). Conclusions: LTK, MYBPH, and MYL4 were identified as potential key molecules for IMNM and are believed to play a role in the autophagylysosome pathway and muscle inflammation.http://www.sciencedirect.com/science/article/pii/S2001037023001186IMNMRNA sequencingBiomarkersImmune cell infiltrationAutophay-lysosome pathway |
| spellingShingle | Kai Chen Chun-yan Zhu Jia-ying Bai Feng Xiao Song Tan Qiao Zhou Li Zeng Identification of feature genes and key biological pathways in immune-mediated necrotizing myopathy: High-throughput sequencing and bioinformatics analysis Computational and Structural Biotechnology Journal IMNM RNA sequencing Biomarkers Immune cell infiltration Autophay-lysosome pathway |
| title | Identification of feature genes and key biological pathways in immune-mediated necrotizing myopathy: High-throughput sequencing and bioinformatics analysis |
| title_full | Identification of feature genes and key biological pathways in immune-mediated necrotizing myopathy: High-throughput sequencing and bioinformatics analysis |
| title_fullStr | Identification of feature genes and key biological pathways in immune-mediated necrotizing myopathy: High-throughput sequencing and bioinformatics analysis |
| title_full_unstemmed | Identification of feature genes and key biological pathways in immune-mediated necrotizing myopathy: High-throughput sequencing and bioinformatics analysis |
| title_short | Identification of feature genes and key biological pathways in immune-mediated necrotizing myopathy: High-throughput sequencing and bioinformatics analysis |
| title_sort | identification of feature genes and key biological pathways in immune mediated necrotizing myopathy high throughput sequencing and bioinformatics analysis |
| topic | IMNM RNA sequencing Biomarkers Immune cell infiltration Autophay-lysosome pathway |
| url | http://www.sciencedirect.com/science/article/pii/S2001037023001186 |
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