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Single-cell transcriptomic analysis of PBMCs from IgAN patients

GSE285335 Homo sapiens (human) Single-cell RNA-seq 26 samples Submitted 2026/01/21 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 26 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
26 samples: 11 × Patients-Early_group# vs 9 × Healthy_group# vs 6 × Patients-Late_group#Groups 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
Chromatin accessibility of circulating CD8⁺ T cells differentiates disease severity in IgA nephropathyScientific reports · 2025
Summary (written by the submitters)
IgA nephropathy (IgAN), the most common primary glomerulonephritis, is a significant cause of chronic kidney disease. While previous studies have highlighted the role of immune cells in IgAN development, the disease’s heterogeneous clinical presentation and prognosis have hindered a comprehensive understanding of its specific pathogenesis.
Read the full summary ↓
This study aimed to identify circulating immune cell subsets linked to the progression of IgAN. Peripheral blood samples were obtained from 9 healthy controls and 17 biopsy-proven IgAN patients, and stratified into early- and late-stage groups based on their estimated glomerular filtration rate (eGFR) at the time of blood sampling. To characterize IgAN-specific immune cell profiles and underlying regulatory mechanisms, single-cell RNA sequencing was conducted to observe distinct immune cell profiles and transcriptomic differences between the IgAN groups. Notably, CD8+ T cells, particularly IL-7Rαlow effector memory, exhibited a significant correlation with the disease progression. Trajectory analysis highlighted distinct CD8+ T-cell developmental patterns, with the early-stage group showing unique enrichment of memory CD8+ T cells. Gene expression profiling of CD8+ T-cell clusters indicated differences in activation and differentiation, emphasizing the critical role of CD8+ T cells in IgAN progression. In contrast, CD4+ T cells and B cells exhibited limited correlation with disease progression. The present transcriptome profiling underscores the prognostic significance of CD8+ T-cell subpopulations in IgAN progression. The findings highlight their potential as therapeutic targets and offers novel insights into the role of circulating immune cells in the progression of IgAN.
Published in
Chromatin accessibility of circulating CD8⁺ T cells differentiates disease severity in IgA nephropathy
Kim G, Lee S, Lee S et al. · Scientific reports 2025 · PMID 41466033 · doi:10.1038/s41598-025-31213-9
This dataset
Open GSE285335 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 GSE285335_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1202919 and SRA study SRP553783. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41466033) ↗
Study design
11 × Patients-Early_group# vs 9 × Healthy_group# vs 6 × Patients-Late_group#

Supports a case/control comparison: 17 samples read as cases, 9 as controls.

How we read this: 3 replicated groups read from 26 sample titles; they account for 26 of them. 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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