Blood immunophenotyping identifies distinct kidney histopathology and outcomes in patients with lupus nephritis
Alice Horisberger, … , James A. Lederer, Deepak A. Rao
Alice Horisberger, … , James A. Lederer, Deepak A. Rao
Published June 19, 2025
Citation Information: J Clin Invest. 2025;135(16):e181034. https://doi.org/10.1172/JCI181034.
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Research Article Autoimmunity Immunology

Blood immunophenotyping identifies distinct kidney histopathology and outcomes in patients with lupus nephritis

Abstract

Lupus nephritis (LN) is a frequent manifestation of systemic lupus erythematosus, and fewer than half of patients achieve complete renal response with standard immunosuppressants. Identifying noninvasive, blood-based immune alterations associated with renal injury could aid therapeutic decisions. Here, we used mass cytometry immunophenotyping of peripheral blood mononuclear cells in 145 patients with biopsy-proven LN and 40 healthy controls to evaluate the heterogeneity of immune activation and identify correlates of renal parameters. Unbiased analysis identified 3 immunologically distinct groups of patients that were associated with different patterns of histopathology, renal cell infiltrates, urine proteomic profiles, and treatment response at 1 year. Patients with enriched circulating granzyme B+ T cells showed more active disease and increased numbers of activated CD8+ T cells in the kidney, yet they had the highest likelihood of treatment response. A second group characterized by a high type I interferon signature had a lower likelihood of response to therapy, while a third group appeared immunologically inactive but with chronic renal injuries. The major immunologic axes of variation could be distilled down to 5 simple cytometric parameters that recapitulate several clinical associations, highlighting the potential for blood immunoprofiling to translate to clinically useful noninvasive metrics to assess immune-mediated disease in LN.

Authors

Alice Horisberger, Alec Griffith, Joshua Keegan, Arnon Arazi, John Pulford, Ekaterina Murzin, Kaitlyn Howard, Brandon Hancock, Andrea Fava, Takanori Sasaki, Tusharkanti Ghosh, Jun Inamo, Rebecca Beuschel, Ye Cao, Katie Preisinger, Maria Gutierrez-Arcelus, Thomas M. Eisenhaure, Joel Guthridge, Paul J. Hoover, Maria Dall’Era, David Wofsy, Diane L. Kamen, Kenneth C. Kalunian, Richard Furie, Michael Belmont, Peter Izmirly, Robert Clancy, David Hildeman, E. Steve Woodle, William Apruzzese, Maureen A. McMahon, Jennifer Grossman, Jennifer L. Barnas, Fernanda Payan-Schober, Mariko Ishimori, Michael Weisman, Matthias Kretzler, Celine C. Berthier, Jeffrey B. Hodgin, Dawit S. Demeke, Chaim Putterman, Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Network, Michael B. Brenner, Jennifer H. Anolik, Soumya Raychaudhuri, Nir Hacohen, Judith A. James, Anne Davidson, Michelle A. Petri, Jill P. Buyon, Betty Diamond, Fan Zhang, James A. Lederer, Deepak A. Rao

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Figure 5

Blood-defined LN groups are associated with specific immune cell infiltration in the kidney and translate to urinary markers of inflammation.

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Blood-defined LN groups are associated with specific immune cell infiltr...
(A) Distribution of T cells and NK cells and selected gene expression by single-cell RNA-Seq analysis of kidney tissue from patients with LN (n = 101). (B) CNA of T-NK cells with blood-defined LN group G2 relative to others (G0 and G1) applied to paired kidney tissue samples. Cells in the UMAP are expanded (red) or depleted (blue) in patients with LN, if correlation passed FDR < 0.05. (C and D) Comparison of the proportions of CNA-identified granzyme B+ and a subset of granzyme K+ immune cell subsets, and CD4+ memory T cells in the kidney tissue (C), or IFN-I gene signature (21-gene list previously reported) in all immune cells from the kidney tissue (D), between blood-defined LN groups (G0: n = 19; G1: n = 40; G2: n = 42); *P < 0.05, **P < 0.01, ****P < 0.0001. (E) Comparison of each urine protein abundance between specified groups, as displayed by the performance of classification using the area under the curve (AUC). Dots colored pink passed FDR threshold of 0.10, and labels were assigned to the top associated proteins. Statistical significance was determined using Wilcoxon’s rank sum test.