ArticleAnnals of translational medicine2020
Identification of the tubulointerstitial infiltrating immune cell landscape and immune marker related molecular patterns in lupus nephritis using bioinformatics analysis.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- C1QB-Mediated Immunopathology in a Murine Malaria Model: A Multi-Omics Validation for Diagnostic and Therapeutic Targeting.International journal of molecular sciences · 2026Article
- Identification of differentially expressed immune-related genes in patients with systemic lupus erythematosus and the development of a hub gene-based diagnostic model.European journal of medical research · 2025Article
- Recognition of differently expressed genes and DNA methylation markers in patients with Lupus nephritis.Journal of translational internal medicine · 2024Article
- Applying 12 machine learning algorithms and Non-negative Matrix Factorization for robust prediction of lupus nephritis.Frontiers in immunology · 2024Article
- The Role of the Oxidative State and Innate Immunity Mediated by TLR7 and TLR9 in Lupus Nephritis.International journal of molecular sciences · 2023Review
- Title: Bioinformatic Identification of Genes Involved in Diabetic Nephropathy Fibrosis and their Clinical Relevance.Biochemical genetics · 2023Article
- Mechanisms and modeling of wound repair in the intestinal epithelium.Tissue barriers · 2023Review
- Integrative analyses of biomarkers and pathways for diabetic nephropathy.Frontiers in genetics · 2023Article
- Identification of driver genes in lupus nephritis based on comprehensive bioinformatics and machine learning.Frontiers in immunology · 2023Article
- Spine‑specific downregulation of LAPTM5 expression promotes the progression and spinal metastasis of estrogen receptor‑positive breast cancer by activating glutamine‑dependent mTOR signaling.International journal of oncology · 2022Article
- NR4A2 may be a potential diagnostic biomarker for myocardial infarction: A comprehensive bioinformatics analysis and experimental validation.Frontiers in immunology · 2022Article
- Application of weighted co-expression network analysis and machine learning to identify the pathological mechanism of Alzheimer's disease.Frontiers in aging neuroscience · 2022Article
- Identification of Feature Autophagy-Related Genes and DNA Methylation Profiles in Systemic Lupus Erythematosus Patients.Medical science monitor : international medical journal of experimental and clinical research · 2021Article
- Exploration of Potential Integrated Models of N6-Methyladenosine Immunity in Systemic Lupus Erythematosus by Bioinformatic Analyses.Frontiers in immunology · 2021Article
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9 authors.
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Abstract
backgroundSystemic lupus erythematosus (SLE) is a multisystem autoimmune disease that commonly affects the kidneys. Research into markers that can predict the prognosis of tubulointerstitial lupus nephritis (LN) has been impeded by the lack of well-designed studies.
methodsIn this study, we selected and merged 3 sets of renal biopsy tubulointerstitial data from GSE32591, GSE69438, and GSE127797, including 95 LN and 15 living healthy donors. CIBERSORTx was utilized for differentially infiltrating immune cell (DIIC) analysis. Weighted Gene Co-Expression network analysis (WGCNA) was employed to explore differentially expressed gene (DEG) related modules. Combined WGCNA hub genes and protein-protein interaction (PPI) validation was used for immune marker identification. Lastly, unsupervised clustering was carried out to validate the correlation between these markers and clinical characteristics.
resultsOur findings unveiled TYROBP, C1QB, LAPTM5, CTSS, PTPRC as the 5 immune markers, which were negatively correlated with glomerular filtration rate (GFR). Specifically, the expression levels of TYROBP and C1QB were significantly different between proliferative LN (PLN) and membranous LN (MLN). Unsupervised clustering could aggregate LN by these immune marker expression spectrums.
conclusionsThis study is the first to identify infiltrating immune cells and associated molecular patterns in the tubulointerstitium of LN by utilizing bioinformatics methods. These findings contribute to a better understanding of the mechanisms behind LN, and promote more precise diagnosis.
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