ArticleComputational and structural biotechnology journal2026
SLECA: A Single-Cell Atlas of Systemic Lupus Erythematosus Enabling Rare-Cell Discovery Using Graph Transformer.
Article in Computational and structural biotechnology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- A transcriptional patient map of systemic lupus erythematosus reveals disease-related multicellular immune programs conserved between blood and kidney.bioRxiv : the preprint server for biology · 2026Article
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6 authors.
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Abstract
Systemic lupus erythematosus (SLE) is a complex autoimmune disease with multisystem involvement and marked interpatient heterogeneity. This heterogeneity has hindered precise characterization of the immune dysregulatory mechanisms underlying the disease. While rare immune cell populations are increasingly recognized as critical drivers of disease pathogenesis and progression, the lack of sufficiently powered, comprehensive single-cell transcriptomic resources has limited their systematic identification and characterization. To address this gap, we present SLECA, the first large-scale single-cell RNA sequencing atlas of SLE, together with a novel graph-transformer framework for the interpretable discovery and analysis of disease-relevant rare-cell populations. SLECA integrates 366 samples with standardized clinical and biological metadata, providing an atlas of SLE with a unified analytical framework. Through scalable integration and systematic analysis, SLECA resolves 54 distinct cell types, including rare populations of potential disease relevance. Notably, we identify double-negative T cells (DNTs) as a disease-expanded population whose abundance correlates with clinical severity. In silico perturbation analyses predict shifts in DNT-cell states following perturbation of JUN and EGR1, suggesting potential regulatory roles in DNT-cell transcriptional programs.
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