Background Classification and treatment decisions in lupus nephritis (LN) are largely based on renal histology. Single-cell RNA sequencing (scRNAseq) analysis may accurately differentiate types of renal involvement at the transcriptomic level, and better inform treatment decisions and prognosis.

Methods scRNAseq was performed on kidney and non-lesional skin tissue collected from 20 SLE patients undergoing a clinically indicated renal biopsy. Cell types were determined using principal component analysis and t-distributed stochastic neighbor embedding (tSNE) plotting, resulting in the definitive identification of keratinocytes, tubular cells, mesangial cells, fibroblasts, endothelial cells, and leukocytes.

Results LN patients expressed upregulated IFN response genes in both their tubular cells and keratinocytes. This IFN response signature in tubular cells predicted poor response to therapy 6 months post-biopsy. Tubular cells of non-responder patients also expressed upregulated extracellular matrix proteins and fibrotic markers (figure 1A and 1B). Using logistic regression analysis, a 4-gene tubular fibrosis score was created and able to predict response to treatment with an area under curve of 0.9 (figure 1C). Keratinocytes of non-responders also upregulated certain extracellular matrix genes and this response was not observed in peripheral blood mononuclear cells. Differential expression analysis between histology classes indicated an upregulation of IFN and TNF signaling in the tubular cells of patients with proliferative LN compared with membranous.

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Abstract 300 Figure 1

A fibrotic gene signature as a potential prognostic marker for patients non-responsive to treatment. A) MA plot of differential expression analysis performed between tubular cells of patients responsive (n=13) or non-responsive to treatment (n=5). Significantly differentially expressed genes are colored in red. B) Pathway enrichment analysis of genes identified as upregulated in patients non-responsive to treatment. -Log10(p-value) of each pathway is shown for both keratinocytes and tubular cells colored from least significant (black) to most significant (red). Log2 fold change in gene expression between patients non-responsive to treatment compared with patients responsive to treatment in each pathway is indicated for tubular cells from smallest (grey) to highest (orange). C) Receiver operating characteristic curve of the logistic regression equation of differentially expressed fibrotic genes, COL1A2, COL1A1, COL14A1, COL5A2, with area under the curve (AUC) indicated.

Conclusions scRNAseq from 2–10 mm of renal biopsy tissue in SLE can differentiate between the different classes of LN, and provide important insights into potential pathogenic mechanisms. Further, changes in the skin of LN patients can provide a useful source of biomarkers and may reflect important information concerning concurrent kidney pathological events.

Funding Source(s): This work was supported by the Accelerating Medicines Partnership (AMP) in Rheumatoid Arthritis and Lupus Network. AMP is a public-private partnership (AbbVie, Arthritis Foundation, Bristol-Myers Squibb, Foundation for the National Institutes of Health, Lupus Foundation of America, Lupus Research Alliance, Merck Sharp and Dohme, National Institute of Allergy and Infectious Diseases, National Institute of Arthritis and Musculoskeletal and Skin Diseases, Pfizer, Rheumatology Research Foundation, Sanofi, and Takeda Pharmaceuticals) created to develop new ways of identifying and validating promising biological targets for diagnostics and drug development. Funding was provided through grants from the National Institutes of Health (UH2-AR067676, UH2-AR067677, UH2-AR067679, UH2-AR067681, UH2-AR067685, UH2-AR067688, UH2-AR067689, UH2-AR067690, UH2-AR067691, UH2-AR067694, and UM2-AR067678).