bioRxivSystems BiologyPreprint
A transcriptional patient map of systemic lupus erythematosus reveals disease-related multicellular immune programs conserved between blood and kidney
José Liñares-BlancoiD, Philipp Sven Lars SchäferiD, Leoni ZimmermanniD, Ricardo Melo FerreiraiD, Daniel Toro DomingueziD, Pedro Carmona‐SáeziD, Jovan TanevskiiD, Marta Eugenia Alarcón-RiquelmeiD, Michael T. EadoniD, Ricardo O. Ramirez FloresiD, Julio Sáez-RodrígueziD
- Citations
- 1
Abstract
Systemic lupus erythematosus (SLE) shows marked clinical and molecular heterogeneity, yet patient stratification often relies on gene expression signatures lacking multicellular context. Here we construct a transcriptional patient map of SLE by analyzing 1,167 total samples (783 SLE, 384 healthy controls) across different resolutions, including single-cell and bulk blood as well as spatially resolved kidney tissue transcriptomes. Using an unsupervised approach we inferred patient-level transcriptomic immune programs from two independent single-cell RNA sequencing cohorts of peripheral blood mononuclear cells (PBMCs), capturing both differences between SLE and health as well as within-SLE heterogeneity. Specifically, we identified four conserved programs comprising two multicellular inflammatory programs driven by interferon and TNF/NFkB activity across immune cells, and two cell type-specific programs reflecting CD8 T cell cytotoxicity and a CD4 T cell naive-to-effector state. Functional analysis of these programs revealed a rewiring of both cell-to-cell interactions and task allocation across cell types during disease activation. In addition, mapping these programs onto an external longitudinal blood transcriptomic cohort predicted flare risk and identified candidate blood protein biomarkers detectable by proteomics. Finally, we showed that these blood programs were enriched in immune-infiltrated glomerular regions from kidney biopsies of individuals with lupus nephritis using spatially resolved transcriptomic data, thereby linking systemic immune programs to local tissue pathology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/721379v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1e75f00org.highwire.dtl.DTLVardef@10e0a63org.highwire.dtl.DTLVardef@cc194forg.highwire.dtl.DTLVardef@191b4d2_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: scRNA-seq
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- research focus: clustering
- research focus: differential expression
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: statistical model
- approach: machine learning (classical)
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