ArticleFrontiers in immunology2022
The shared biomarkers and pathways of systemic lupus erythematosus and metabolic syndrome analyzed by bioinformatics combining machine learning algorithm and single-cell sequencing analysis.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.
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Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.
- Research progress on the application of single-cell sequencing in autoimmune diseases.Genes and immunity · 2023Pooled it
- [Explore the potential diagnostic markers of primary Sjögren syndrome by bioinformatics combined with machine learning].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2026Article
- Progress in the Application of Machine Learning in the Field of Single-Cell and Spatial Transcriptomics.Genes · 2026Review
- Disease-specific crosstalk of Alistipes with lipoprotein profiles in overweight individuals at high cardiometabolic risk.Scientific reports · 2026Article
- Oxidative stress-associated genes TPPP3 and VEGFA in COPD revealed by bulk and single-cell sequencing analysis.Scientific reports · 2026Article
- Immunopathogenesis of accelerated atherosclerosis in systemic lupus erythematosus: from innate and adaptive dysregulation to clinical implications.Frontiers in immunology · 2026Review
- Decoding vascular calcification-neutrophil signature in pathogenesis of chronic IgA nephropathy: evidence from artificial intelligence-driven multi-omics andFrontiers in physiology · 2026Article
- A neuron-distributed DEK integrates ac4C modification and neuroinflammation in pathogenesis of Parkinson disease: evidence from Mendelian randomization, multi-omics andFrontiers in neuroscience · 2026Article
- The microbiota-systemic lupus erythematosus axis: mechanisms, diagnostics, and therapeutic frontiers.Frontiers in immunology · 2026Review
- Targeting TKT-associated immunometabolic remodeling attenuates experimental lupus nephritis and NET-related inflammation.Frontiers in cell and developmental biology · 2026Article
- Associations of inflammation-related hematological profile with the early-stages of cardiovascular-kidney-metabolic syndrome and the mediating role of body composition: evidence from the China National Health Survey.Diabetology & metabolic syndrome · 2025Article
- The molecular complexity of deep vein thrombosis was preliminarily explored based on the ceRNA network, scRNA-seq and AlphaFold 2.BMC medical genomics · 2025Article
- Unveiling Molecular Mechanisms Underlying Obesity-Associated Systemic Lupus Erythematosus.Endocrinology, diabetes & metabolism · 2025Review
- Mendelian Randomization and Machine Learning Reveal Immune Cell and Gene Drivers in Systemic Lupus Erythematosus.Brain and behavior · 2025Article
- ITGB2 and ICAM3 predict increased survival of sepsis with decreased intercellular communication in cytotoxic CD8+ T cells.Scientific reports · 2025Article
- Bioinformatics analysis to identify key invasion related genes and construct a prognostic model for glioblastoma.Scientific reports · 2025Article
- Exploring mitochondrial and ferroptotic mechanisms for systemic lupus erythematosus biomarker identification and therapy.Scientific reports · 2025Article
- Macrophages Unmasked: Their Pivotal Role in Driving Atherosclerosis in Systemic Lupus Erythematosus.Clinical reviews in allergy & immunology · 2025Review
- Knowledge, attitudes, and practices toward biologics among systemic lupus erythematosus patients: a cross-sectional study.Frontiers in public health · 2025Article
- Identification and validation of prognostic genes associated with T-cell exhaustion and macrophage polarization in breast cancer.Frontiers in endocrinology · 2025Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Systemic lupus erythematosus (SLE) is one of the most prevalent systemic autoimmune diseases, and metabolic syndrome (MetS) is the most common metabolic disorder that contains hypertension, dyslipidemia, and obesity. Despite clinical evidence suggested potential associations between SLE and MetS, the underlying pathogenesis is yet unclear. Methods: The microarray data sets of SLE and MetS were obtained from the Gene Expression Omnibus (GEO) database. To identify the shared genes between SLE and MetS, the Differentially Expressed Genes (DEGs) analysis and the weighted gene co-expression network analysis (WGCNA) were conducted. Then, the GO and KEGG analyses were performed, and the protein-protein interaction (PPI) network was constructed. Next, Random Forest and LASSO algorithms were used to screen shared hub genes, and a diagnostic model was built using the machine learning technique XG-Boost. Subsequently, CIBERSORT and GSVA were used to estimate the correlation between shared hub genes and immune infiltration as well as metabolic pathways. Finally, the significant hub genes were verified using single-cell RNA sequencing (scRNA-seq) data. Results: Using limma and WGCNA, we identified 153 shared feature genes, which were enriched in immune- and metabolic-related pathways. Further, 20 shared hub genes were screened and successfully used to build a prognostic model. Those shared hub genes were associated with immunological and metabolic processes in peripheral blood. The scRNA-seq results verified that Conclusion: This study identified shared hub genes and constructed an effective diagnostic model in SLE and MetS.
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