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 4

Blood-defined LN groups are associated with renal pathology and outcome.

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Blood-defined LN groups are associated with renal pathology and outcome....
(A) Comparison of NIH renal activity index between blood-defined LN groups (G0: n = 20; G1: n = 40; G2: n = 40; LN groups were defined using K-means clustering based on blood immunophenotyping). Statistical significance was determined using the Kruskal-Wallis test with Dunn’s multiple comparisons. (B) Heatmap showing Spearman’s correlation coefficients between LN groups (one-versus-rest) and NIH renal activity/chronicity subscores (G0: n = 18; G1: n = 33; G2: n = 30). Adjusted significance levels are indicated (FDR < 0.05 and < 0.1). (C) Multivariable models evaluating one-versus-rest group associations with activity index (linear model) and proliferative class (logistic regression; reference = membranous class), adjusting for demographic factors (age, sex, ethnicity, and race), history of previous biopsy, and prednisone dose. (D) Comparison of NIH renal chronicity index between LN groups (G0: n = 20; G1: n = 40; G2: n = 40), with statistical significance determined by the Kruskal-Wallis test with Dunn’s multiple comparisons. *P < 0.05, **P < 0.01, ***P < 0.001. (E) Multivariable model testing one-versus-rest group associations with chronicity index (linear model), adjusting for demographic variables, history of previous biopsy, and prednisone dose. (F) Multivariable model testing one-versus-rest group associations with complete renal response at 52 weeks (non-complete vs. complete response), adjusting for demographic variables, history of previous biopsy, and prednisone dose. (G) Univariate model evaluating group associations with complete renal response at 52 weeks in patients treated with MMF throughout the study.