ArticleThe British journal of dermatology2021
Modular gene analysis reveals distinct molecular signatures for subsets of patients with cutaneous lupus erythematosus.
Article in The British journal of dermatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- Artificial intelligence-enabled precision medicine for inflammatory skin diseases.The Journal of investigative dermatology · 2026Review
- Focus on Interferon Signature in Cutaneous Lupus Erythematosus: Novel Therapies From Better Understanding of the Pathogenesis.Journal of immunology research · 2025Review
- Identification of a shared gene signature and biological mechanism between diabetic foot ulcers and cutaneous lupus erythemnatosus by transcriptomic analysis.Frontiers in physiology · 2024Article
- Gene Expression and Autoantibody Analysis Revealing Distinct Ancestry-Specific Profiles Associated With Response to Rituximab in Refractory Systemic Lupus Erythematosus.Arthritis & rheumatology (Hoboken, N.J.) · 2023Article
- Recent advances in cutaneous lupus.Journal of autoimmunity · 2022Review
- Machine learning reveals distinct gene signature profiles in lesional and nonlesional regions of inflammatory skin diseases.Science advances · 2022Article
- Influence of Socio-Demographic Factors in Patients With Cutaneous Lupus Erythematosus.Frontiers in medicine · 2022Review
- The Genetic Landscape of Cutaneous Lupus Erythematosus.Frontiers in medicine · 2022Review
- B Cell Signatures Distinguish Cutaneous Lupus Erythematosus Subtypes and the Presence of Systemic Disease Activity.Frontiers in immunology · 2021Article
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8 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundCutaneous lupus erythematosus (CLE) is a heterogeneous autoimmune disease with clinical sequelae such as itching, dyspigmentation and scarring.
objectivesWe applied a previously described modular analysis approach to assess the molecular heterogeneity of patients with CLE.
methodsWhole-blood transcriptomes of RNA sequencing data from a racially and ethnically diverse group of patients with CLE (n = 62) were used to calculate gene co-expression module scores. An unsupervised cluster analysis and k-means clustering based on these module scores were then performed. We used Fisher's exact tests and Kruskal-Wallis tests to compare characteristics between patient clusters.
resultsSix unique clusters of patients with CLE were identified from the cluster analysis. We observed that seven inflammation modules were elevated in two clusters of patients with CLE. Additionally, these clusters were characterized by interferon, neutrophil and cell-death signatures, suggesting that interferon-related proteins, neutrophils and cell-death processes could be driving the inflammatory response in these subgroups. Three different clusters had a predominant T-cell signature, which were supported by lymphocyte counts.
conclusionsOur data support a diverse molecular profile in CLE that further adds to the clinical variations of this skin disease, and may affect disease course and treatment selection. Future studies with a larger and diverse cohort of patients with CLE are warranted to confirm these findings.
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