ArticleLupus science & medicine2023
Molecular endotypes of type 1 and type 2 SLE.
Article in Lupus science & medicine, 2023. 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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Who cites it
8 citing papers in PubMed.
- Article
- Applications of artificial intelligence in systemic lupus erythematosus: integrating multi-omics data for precision medicine.Frontiers in immunology · 2026Review
- M5542, a bifunctional fusion protein targeting CD80, CD86, and OX40L that modulates excessive T-cell activity: a preclinical proof-of-concept study.Frontiers in immunology · 2026Article
- Neutrophil Extracellular Traps in Systemic Lupus Erythematosus: Pathogenic Mechanisms, Crosstalk with Oxidative Stress, and Antioxidant Therapeutic Potential.Antioxidants (Basel, Switzerland) · 2025Review
- Pain in systemic lupus erythematosus: emerging insights and paradigms.Nature reviews. Rheumatology · 2025Review
- Artificial Intelligence in Rheumatology: Quo Vadis?Mediterranean journal of rheumatology · 2025Article
- Unlocking therapeutic potential: Targeting lymphocyte activation Gene-3 (LAG-3) with fibrinogen-like protein 1 (FGL1) in systemic lupus erythematosus.Journal of translational autoimmunity · 2024Review
- Clinical and Serologic Phenotyping and Damage Indices in Patients With Systemic Lupus Erythematosus With and Without Fibromyalgia.ACR open rheumatology · 2024Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo character the molecular landscape of patients with type 1 and type 2 SLE by analysing gene expression profiles from peripheral blood.
methodsFull transcriptomic RNA sequencing was carried out on whole blood samples from 18 subjects with SLE selected by the presence of manifestations typical of type 1 and type 2 SLE. The top 5000 row variance genes were analysed by Multiscale Embedded Gene Co-expression Network Analysis to generate gene co-expression modules that were functionally annotated and correlated with various demographic traits, clinical features and laboratory measures.
resultsExpression of specific gene co-expression modules correlated with individual features of type 1 and type 2 SLE and also effectively segregated samples from patients with type 1 SLE from those with type 2 SLE. Unique type 1 SLE enrichment included interferon, monocytes, T cells, cell cycle and neurotransmitter pathways, whereas unique type 2 SLE enrichment included B cells and metabolic and neuromuscular pathways. Gene co-expression modules of patients with type 2 SLE were identified in subsets of previously reported patients with inactive SLE and idiopathic fibromyalgia (FM) and also identified subsets of patients with active SLE with a greater frequency of severe fatigue.
conclusionGene co-expression analysis successfully identified unique transcriptional patterns that segregate type 1 SLE from type 2 SLE and further identified type 2 molecular features in patients with inactive SLE or FM and with active SLE with severe fatigue.
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