ReviewNature reviews. Rheumatology2015
Immune cell profiling to guide therapeutic decisions in rheumatic diseases.
Review in Nature reviews. Rheumatology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed.
- Immune cell annotation in the single-cell studies: technologies, challenges, and integrative solutions.Immunologic research · 2026Review
- Hypergraph representations of single-cell RNA sequencing data for improved cell clustering.Bioinformatics (Oxford, England) · 2026Article
- A novel Slide-seq based image processing software to identify gene expression at the single cell level.Journal of pathology informatics · 2024Article
- Increasing Signal Intensity of Fluorescent Oligo-Labeled Antibodies to Enable Combination Multiplexing.Bioconjugate chemistry · 2024Article
- Increasing Signal Intensity of Fluorescent Oligo-Labeled Antibodies to Enable Combination Multiplexing.bioRxiv : the preprint server for biology · 2024Article
- Single-Cell Analysis of Patients with Axial Spondyloarthritis After Anti-TNFα Treatment: Experimental Data and Review of the Literature.Clinical reviews in allergy & immunology · 2023Review
- PD-1Cancers · 2023Article
- Techniques for Profiling the Cellular Immune Response and Their Implications for Interventional Oncology.Cancers · 2022Review
- Precision medicine in rheumatoid arthritis.Best practice & research. Clinical rheumatology · 2022Review
- CD127 imprints functional heterogeneity to diversify monocyte responses in inflammatory diseases.The Journal of experimental medicine · 2022Article
- Fibroblast pathology in inflammatory diseases.The Journal of clinical investigation · 2021Review
- Gray platelet syndrome: immunity goes awry.Blood · 2020Article
- Immune monitoring using mass cytometry and related high-dimensional imaging approaches.Nature reviews. Rheumatology · 2020Review
- Autoimmune antibodies correlate with immune checkpoint therapy-induced toxicities.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Using the Immunophenotype to Predict Response to Biologic Drugs in Rheumatoid Arthritis.Journal of personalized medicine · 2019Review
- The rise of peripheral T helper cells in autoimmune disease.Nature reviews. Rheumatology · 2019Article
- Insights into rheumatic diseases from next-generation sequencing.Nature reviews. Rheumatology · 2019Review
- Characterization of a Subset of Patients With Rheumatoid Arthritis for Whom Current Management Strategies are Inadequate.ACR open rheumatology · 2019Article
- Review
- Lymphocyte innateness defined by transcriptional states reflects a balance between proliferation and effector functions.Nature communications · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Biomarkers are needed to guide treatment decisions for patients with rheumatic diseases. Although the phenotypic and functional analysis of immune cells is an appealing strategy for understanding immune-mediated disease processes, immune cell profiling currently has no role in clinical rheumatology. New technologies, including mass cytometry, gene expression profiling by RNA sequencing (RNA-seq) and multiplexed functional assays, enable the analysis of immune cell function with unprecedented detail and promise not only a deeper understanding of pathogenesis, but also the discovery of novel biomarkers. The large and complex data sets generated by these technologies--big data--require specialized approaches for analysis and visualization of results. Standardization of assays and definition of the range of normal values are additional challenges when translating these novel approaches into clinical practice. In this Review, we discuss technological advances in the high-dimensional analysis of immune cells and consider how these developments might support the discovery of predictive biomarkers to benefit the practice of rheumatology and improve patient care.
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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.