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Spatio-temporal interaction of immune and renal cells determines glomerular crescent formation in autoimmune kidney disease

GSE303481 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2025/08/19 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
15 samples: 15 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Spatiotemporal interaction of immune and renal cells controls glomerular crescent formation in autoimmune kidney diseaseNature immunology · 2025
Summary (written by the submitters)
Rapidly progressive glomerulonephritis (RPGN) is the most aggressive group of autoimmune kidney disease with the worst prognosis. Anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis, anti-glomerular basement membrane (anti-GBM) and lupus nephritis are the most common causes of RPGN and are characterized by the formation of glomerular crescents and infiltration of leukocytes that eventually lead to glomerulosclerosis and kidney failure.
Read the full summary ↓
In this work, we used high-resolution spatial transcriptomics of 32 ANCA, 19 lupus nephritis, 6 anti-GBM, and 6 control patients to understand how intercellular signaling between immune and renal tissue cells leads to renal inflammation and glomerular injury. Using 3,218,210 immune and kidney cells, we observed that the biological pathways involved in the sequence of glomerular crescent formation are similar across the diseases. While innate immune cells infiltrated the glomerular compartment relatively early, later increases in adaptive immune cells were largely restricted to the periglomerular regions. These changes in immune cells temporally correlated with increases in glomerular parietal epithelial (PEC) and fibrotic mesangial cells, suggesting disease-relevant functional signaling between these immune and renal cells. Cell communication analysis revealed early disease PDGF signaling from epithelial and mesangial cells to PECs, causing their activation and proliferation. At later stages, TGF-β signaling from macrophages, T cells, epithelial cells, and mesangial cells to PECs triggered the expression of extracellular matrix components resulting in glomerulosclerosis. Our results highlight a spatio-temporally conserved progression into glomerular crescents and sclerosis for ANCA, lupus nephritis, and anti-GBM disease, which is driven by consecutive PDGF and TGF-β signaling to PECs.
Published in
Spatiotemporal interaction of immune and renal cells controls glomerular crescent formation in autoimmune kidney disease
Sultana Z, Khatri R, Yousefi B et al. · Nature immunology 2025 · PMID 41028563 · doi:10.1038/s41590-025-02291-8
This dataset
Open GSE303481 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE303481_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1295503 and SRA study SRP603076. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41028563) ↗
Study design
15 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 11 samples read as cases, 4 as controls.

How we read this: Read from 15 sample titles: 15 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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