MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus
BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease that involves multiple organs. However, the current SLE-related biomarkers still lack sufficient sensitivity, specificity and predictive power for clinical application. Thus, it is significant to explore new immune-related biomark...
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.978851/full |
| _version_ | 1818486878049927168 |
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| author | Xiang-Wen Meng Zhi-Luo Cheng Zhi-Yuan Lu Ya-Nan Tan Xiao-Yi Jia Xiao-Yi Jia Xiao-Yi Jia Min Zhang |
| author_facet | Xiang-Wen Meng Zhi-Luo Cheng Zhi-Yuan Lu Ya-Nan Tan Xiao-Yi Jia Xiao-Yi Jia Xiao-Yi Jia Min Zhang |
| author_sort | Xiang-Wen Meng |
| collection | DOAJ |
| description | BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease that involves multiple organs. However, the current SLE-related biomarkers still lack sufficient sensitivity, specificity and predictive power for clinical application. Thus, it is significant to explore new immune-related biomarkers for SLE diagnosis and development.MethodsWe obtained seven SLE gene expression profile microarrays (GSE121239/11907/81622/65391/100163/45291/49454) from the GEO database. First, differentially expressed genes (DEGs) were screened using GEO2R, and SLE biomarkers were screened by performing WGCNA, Random Forest, SVM-REF, correlation with SLEDAI and differential gene analysis. Receiver operating characteristic curves (ROCs) and AUC values were used to determine the clinical value. The expression level of the biomarker was verified by RT‒qPCR. Subsequently, functional enrichment analysis was utilized to identify biomarker-associated pathways. ssGSEA, CIBERSORT, xCell and ImmuCellAI algorithms were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Finally, the transcriptional regulatory network of the biomarker was constructed, and the corresponding therapeutic drugs were predicted.ResultsMultiple algorithms were screened together for a unique marker gene, MX2, and expression analysis of multiple datasets revealed that MX2 was highly expressed in SLE compared to the normal group (all P < 0.05), with the same trend validated by RT‒qPCR (P = 0.026). Functional enrichment analysis identified the main pathway of MX2 promotion in SLE as the NOD-like receptor signaling pathway (NES=2.492, P < 0.001, etc.). Immuno-infiltration analysis showed that MX2 was closely associated with neutrophils, and single-cell and transcriptomic data revealed that MX2 was specifically expressed in neutrophils. The NOD-like receptor signaling pathway was also remarkably correlated with neutrophils (r >0.3, P < 0.001, etc.). Most of the MX2-related interacting proteins were associated with SLE, and potential transcription factors of MX2 and its related genes were also significantly associated with the immune response.ConclusionOur study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE. It activates the NOD-like receptor signaling pathway and promotes neutrophil infiltration to aggravate SLE. |
| first_indexed | 2024-12-10T16:29:03Z |
| format | Article |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-12-10T16:29:03Z |
| publishDate | 2022-08-01 |
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| spelling | doaj.art-6889b05afcd94849b35617ae81ab74482022-12-22T01:41:34ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-08-011310.3389/fimmu.2022.978851978851MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosusXiang-Wen Meng0Zhi-Luo Cheng1Zhi-Yuan Lu2Ya-Nan Tan3Xiao-Yi Jia4Xiao-Yi Jia5Xiao-Yi Jia6Min Zhang7School of Pharmacy, Anhui University of Chinese Medicine, Hefei, ChinaSchool of Pharmacy, Anhui University of Chinese Medicine, Hefei, ChinaSchool of Pharmacy, Anhui University of Chinese Medicine, Hefei, ChinaSchool of Pharmacy, Anhui University of Chinese Medicine, Hefei, ChinaSchool of Pharmacy, Anhui University of Chinese Medicine, Hefei, ChinaAnhui Province Key Laboratory of Chinese Medicinal Formula, Hefei, ChinaAnhui Province Key Laboratory of Research and Development of Chinese Medicine, Hefei, ChinaDepartment of Rheumatology and Immunology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, ChinaBackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease that involves multiple organs. However, the current SLE-related biomarkers still lack sufficient sensitivity, specificity and predictive power for clinical application. Thus, it is significant to explore new immune-related biomarkers for SLE diagnosis and development.MethodsWe obtained seven SLE gene expression profile microarrays (GSE121239/11907/81622/65391/100163/45291/49454) from the GEO database. First, differentially expressed genes (DEGs) were screened using GEO2R, and SLE biomarkers were screened by performing WGCNA, Random Forest, SVM-REF, correlation with SLEDAI and differential gene analysis. Receiver operating characteristic curves (ROCs) and AUC values were used to determine the clinical value. The expression level of the biomarker was verified by RT‒qPCR. Subsequently, functional enrichment analysis was utilized to identify biomarker-associated pathways. ssGSEA, CIBERSORT, xCell and ImmuCellAI algorithms were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Finally, the transcriptional regulatory network of the biomarker was constructed, and the corresponding therapeutic drugs were predicted.ResultsMultiple algorithms were screened together for a unique marker gene, MX2, and expression analysis of multiple datasets revealed that MX2 was highly expressed in SLE compared to the normal group (all P < 0.05), with the same trend validated by RT‒qPCR (P = 0.026). Functional enrichment analysis identified the main pathway of MX2 promotion in SLE as the NOD-like receptor signaling pathway (NES=2.492, P < 0.001, etc.). Immuno-infiltration analysis showed that MX2 was closely associated with neutrophils, and single-cell and transcriptomic data revealed that MX2 was specifically expressed in neutrophils. The NOD-like receptor signaling pathway was also remarkably correlated with neutrophils (r >0.3, P < 0.001, etc.). Most of the MX2-related interacting proteins were associated with SLE, and potential transcription factors of MX2 and its related genes were also significantly associated with the immune response.ConclusionOur study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE. It activates the NOD-like receptor signaling pathway and promotes neutrophil infiltration to aggravate SLE.https://www.frontiersin.org/articles/10.3389/fimmu.2022.978851/fullsystemic lupus erythematosusMX2machine learningbiomarkerimmune infiltration |
| spellingShingle | Xiang-Wen Meng Zhi-Luo Cheng Zhi-Yuan Lu Ya-Nan Tan Xiao-Yi Jia Xiao-Yi Jia Xiao-Yi Jia Min Zhang MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus Frontiers in Immunology systemic lupus erythematosus MX2 machine learning biomarker immune infiltration |
| title | MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus |
| title_full | MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus |
| title_fullStr | MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus |
| title_full_unstemmed | MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus |
| title_short | MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus |
| title_sort | mx2 identification and systematic mechanistic analysis of a novel immune related biomarker for systemic lupus erythematosus |
| topic | systemic lupus erythematosus MX2 machine learning biomarker immune infiltration |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.978851/full |
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