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pmid:36059547
MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus.
Xiang-Wen Meng · Zhi-Luo Cheng · Zhi-Yuan Lu · Ya-Nan Tan · Xiao-Yi Jia · Min Zhang
Frontiers in immunology · 2022 doi:10.3389/fimmu.2022.978851
Paper
complete
Experiment
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Data
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Analysis
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Execution
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Complete file
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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.\nMethods: 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.\nResults: 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.\nConclusion: 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.", "claims": [{"id": "claim-method", "statement": "Differences between two groups of continuous non-normally distributed variables were analyzed using the Mann‒Whitney U test (Wilcoxon rank sum test). The Kruskal‒Wallis test was used for comparison of variables among multiple groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36059547", "locator": "sections[10] \"Statistical analysis\" paragraph 2", "quote": "Differences between two groups of continuous non-normally distributed variables were analyzed using the Mann‒Whitney U test (Wilcoxon rank sum test). The Kruskal‒Wallis test was used for comparison of variables among multiple groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: GEO database (http://www.ncbi.nlm.nih.gov/geo/). The accession number(s) can be found in the article. Resulting data are available through Supplementary Material , and other reasonable requests can be obtained from the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36059547", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: GEO database (http://www.ncbi.nlm.nih.gov/geo/). The accession number(s) can be found in the article. Resulting data are available through Supplementary Material , and other reasonable requests can be obtained from the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36059547", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Our study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Our study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36059547"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE100163"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE100163"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36059547", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2022.978851", "sha256": "sha256:37a21766dcc814c26005906a24fc9efe3a53344dc154d59cfc5bf631e6a20974", "bytes": 54384, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2022.978851", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9433551", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE100163", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100163", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE100163", "version": null, "note": "Publicly available datasets were analyzed in this study. 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