ReviewNature reviews. Immunology2024
Single-cell analysis in rheumatic and allergic diseases: insights for clinical practice.
Review in Nature reviews. Immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Platelet-derived serotonin epigenetically programs macrophage alternative activation to orchestrate type 2 airway inflammation.Cellular & molecular immunology · 2026Article
- Cellular crosstalk and signaling networks in the rheumatoid arthritis synovial microenvironment.Journal of translational medicine · 2026Review
- Current Overview of Multi-omics Analyses in Microscopic Polyangiitis and Granulomatosis with Polyangiitis.Internal medicine (Tokyo, Japan) · 2026Review
- Targeting the synovial engine: next-generation engineered immune cells to eradicate pathogenic FLS in rheumatoid arthritis, with safety-first, selective designs.Frontiers in immunology · 2026Review
- Cross-disease immune cells atlas reveals the similarities and differences of cell characteristics and interactions in rheumatic diseases.Frontiers in medicine · 2026Article
- Decoding Cellular Stress States for Toxicology Using Single-Cell Transcriptomics.bioRxiv : the preprint server for biology · 2025Article
- Single-cell analysis reveals immune cell abnormalities underlying the clinical heterogeneity of patients with systemic sclerosis.Nature communications · 2025Article
- Spatial transcriptomics in autoimmune rheumatic disease: potential clinical applications and perspectives.Inflammation and regeneration · 2025Review
- Mendelian Randomization Combined with Single-Cell Transcriptome Analysis Reveals the Role of the Key Gene PCLAF in the Pathogenesis of Atopic Dermatitis.Clinical, cosmetic and investigational dermatology · 2025Article
- Bridging Gaps and Charting Future Directions in Vasculitis.Journal of clinical medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since the advent of single-cell RNA sequencing (scRNA-seq) methodology, single-cell analysis has become a powerful tool for exploration of cellular networks and dysregulated immune responses in disease pathogenesis. Advanced bioinformatics tools have enabled the combined analysis of scRNA-seq data and information on various cell properties, such as cell surface molecular profiles, chromatin accessibility and spatial information, leading to a deeper understanding of pathology. This Review provides an overview of the achievements in single-cell analysis applied to clinical samples of rheumatic and allergic diseases, including rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis, allergic airway diseases and atopic dermatitis, with an expanded scope beyond peripheral blood cells to include local diseased tissues. Despite the valuable insights that single-cell analysis has provided into disease pathogenesis, challenges remain in translating single-cell findings into clinical practice and developing personalized treatment strategies. Beyond understanding the atlas of cellular diversity, we discuss the application of data obtained in each study to clinical practice, with a focus on identifying biomarkers and therapeutic targets.
Indexed as
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.