ReviewFrontiers in immunology2022
Lessons From Transcriptome Analysis of Autoimmune Diseases.
Review 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 8 papers.
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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.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Immunomodulation by bepirovirsen may induce killing of infected hepatocytes (B-Together study).Hepatology international · 2026Trial
- Innate immune transcriptomic remodeling across clinical stages of bovine leukemia virus infection.Virus genes · 2026Article
- Article
- Complement contributes to ICI-triggered sialadenitis and predicts ICI efficacy.Cancer immunology, immunotherapy : CII · 2026Article
- Unique transcriptomic profile of peripheral blood monocytes in rheumatoid arthritis-associated interstitial lung disease.Rheumatology (Oxford, England) · 2025Article
- T-cell and autoantibody profiling for primary immune regulatory disorders.The Journal of allergy and clinical immunology · 2025Article
- A nosology of immune diseases from deep immunophenotyping.Nature reviews. Rheumatology · 2024Article
- Advanced methods and novel biomarkers in autoimmune diseases ‑ a review of the recent years progress in systemic lupus erythematosus.Frontiers in medicine · 2023Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Various immune cell types, including monocytes, macrophages, and adaptive immune T and B cells, play major roles in inflammation in systemic autoimmune diseases. However, the precise contribution of these cells to autoimmunity remains elusive. Transcriptome analysis has added a new dimension to biology and medicine. It enables us to observe the dynamics of gene expression in different cell types in patients with diverse diseases as well as in healthy individuals, which cannot be achieved with genomic information alone. In this review, we summarize how transcriptome analysis has improved our understanding of the pathological roles of immune cells in autoimmune diseases with a focus on the ImmuNexUT database we reported. We will also discuss the common experimental and analytical design of transcriptome analyses. Recently, single-cell RNA-seq analysis has provided atlases of infiltrating immune cells, such as pro-inflammatory monocytes and macrophages, peripheral helper T cells, and age or autoimmune-associated B cells in various autoimmune disease lesions. With the integration of genomic data, expression quantitative trait locus (eQTL) analysis can help identify candidate causal genes and immune cells. Finally, we also mention how the information obtained from these analyses can be used practically to predict patient prognosis.
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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 Socratic graph.