Background: Lupus nephritis (LN) is a severe complication of systemic lupus erythematosus (SLE), affecting up to 60% of patients [1]. Despite treatment advances, 10–30% of LN patients progress to ESRD within a decade [2]. The disease’s etiopathogenic complexity highlights the need for better classification and understanding of its pathophysiology. Genetic profiling and omics technologies offer potential for improved patient stratification [3]. Transcriptomic analysis of serial kidney biopsies has shown dynamic gene expression changes linked to clinical treatment responses, providing insights for targeted therapies [4]. Spatial transcriptomic integrates tissue morphology with cellular interactions and location-specific gene expression, providing comprehensive molecular insights while preserving histological architecture.

Objectives: To perform omic spatial analysis on a series of kidney biopsies from LN patients, aimig to analyze and characterize the transcriptomic and protein profiles pathways of immune cells and resident kidney cells within the distinct structural and functional compartments of LN kidney tissue.

Methods: Paraffin embedded kidney biopsies from 20 patients at flare time and after treatment were used for spatial omics analysis. Patients were classified in responders or non-responders following the American College of Rheumatology (ACR) response criteria for proliferative and membranous renal disease in SLE clinical trials.From each, we selected six regions of interest (ROIs) containing 12 areas of interest (AOIs) were selected, focusing on active glomerular and tubular regions as identified by the Vall d’Hebron renal pathology team. AOIs were characterized using immunofluorescence markers: CD45+ (immune cells), CD31- (mesangial cells)/+ (endothelial cells), and PanCK+ (tubular cells). GeoMx Digital Spatial Profiling (DSP) technology was employed to analyze RNA probes, and the data underwent quality control and processing via NanoString’s Spatial Data Analysis Services.

Results: Of the 20 patients treated with MMF therapy, 11 patients (55%) achieved complete response. Among them, eight underwent a second biopsy after one year of treatment. Immune cells in kidney biopsies were predominantly located in tubular regions, with plasmacytoid dendritic cells, natural killer cells, and macrophages being the most abundant during flare. A trend towards an increased presence of macrophages was observed in kidney biopsies of non-responders (p=0.057). Over time, non-responders exhibited higher expression of genes associated with immune activation and pathways related to integrins, plexin-B, and T-cell receptor signaling. In contrast, responders showed upregulation of genes linked to RNA repair and pathways related to RNA polymerase and splicing factors, suggesting enhanced transcriptional recovery. In mesangial cells, repeat biopsies highlighted a significant upregulation of inflammatory pathways in non-responders, including NF-κB, AP-1(-like), and interferon pathways. These pathways often synergize to regulate gene expression in response to pro-inflammatory cytokines such us TNF-α and IL-1β, with interferon signaling further amplifying NF-κB activation. Conversely, tubular regions of non-responder kidney tissues exhibited upregulated pathways related to T-cell receptor signaling. Protein spatial analysis confirmed the importance of immune activation and the interferon pathway by revealing significant differences between responders and non-responders. In immune cell regions, non-responders exhibited overexpression of CD14, IL-1α, CD27, TIM-3, STAT1, IL-15RA, and TMS1, while STING protein was abundantly present in endothelial cell regions.

Conclusion: Our findings highlight the critical role of cellular interactions between immune cells, mesangial cells, and tubular cells in perpetuating inflammation in LN kidney tissue. The significant upregulation of inflammatory pathways, particularly T-cell activation, interferon signaling, and NF-κB pathways, was maintained between the first and second biopsies in non-responder patients.

REFERENCES: [1] Anders HJ, Saxena R, Zhao MH, Parodis I, Salmon JE, Mohan C. Lupus nephritis. Nat Rev Dis Primer. 2020;6(1):7.

[2] Pryor KP, Barbhaiya M, Costenbader KH, Feldman CH. Disparities in lupus and lupus nephritis care and outcomes among US Medicaid beneficiaries. Rheum Dis Clin North Am. 2021;47(1):41–53.

[3] Arazi A, Rao DA, Berthier CC, Davidson A, Liu Y, Hoover PJ, et al. The immune cell landscape in kidneys of patients with lupus nephritis. Nat Immunol. 2019;20(7):902–14.

[4] Parikh SV, Malvar A, Song H, Shapiro J, Mejia-Vilet JM, Ayoub I, et al. Molecular profiling of kidney compartments from serial biopsies differentiate treatment responders from non-responders in lupus nephritis. Kidney Int. 2022;102(4):845–65.

Acknowledgements: NIL.

Disclosure of Interests: None declared.

© The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.