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MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus

BACKGROUND: Systemic 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 bioma...

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Autores principales: Meng, Xiang-Wen, Cheng, Zhi-Luo, Lu, Zhi-Yuan, Tan, Ya-Nan, Jia, Xiao-Yi, Zhang, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9433551/
https://www.ncbi.nlm.nih.gov/pubmed/36059547
http://dx.doi.org/10.3389/fimmu.2022.978851
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author Meng, Xiang-Wen
Cheng, Zhi-Luo
Lu, Zhi-Yuan
Tan, Ya-Nan
Jia, Xiao-Yi
Zhang, Min
author_facet Meng, Xiang-Wen
Cheng, Zhi-Luo
Lu, Zhi-Yuan
Tan, Ya-Nan
Jia, Xiao-Yi
Zhang, Min
author_sort Meng, Xiang-Wen
collection PubMed
description BACKGROUND: Systemic 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. METHODS: We 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. RESULTS: Multiple 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. CONCLUSION: Our 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.
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spelling pubmed-94335512022-09-02 MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus Meng, Xiang-Wen Cheng, Zhi-Luo Lu, Zhi-Yuan Tan, Ya-Nan Jia, Xiao-Yi Zhang, Min Front Immunol Immunology BACKGROUND: Systemic 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. METHODS: We 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. RESULTS: Multiple 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. CONCLUSION: Our 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. Frontiers Media S.A. 2022-08-18 /pmc/articles/PMC9433551/ /pubmed/36059547 http://dx.doi.org/10.3389/fimmu.2022.978851 Text en Copyright © 2022 Meng, Cheng, Lu, Tan, Jia and Zhang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Meng, Xiang-Wen
Cheng, Zhi-Luo
Lu, Zhi-Yuan
Tan, Ya-Nan
Jia, Xiao-Yi
Zhang, Min
MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus
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 Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9433551/
https://www.ncbi.nlm.nih.gov/pubmed/36059547
http://dx.doi.org/10.3389/fimmu.2022.978851
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