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Discovery of kidney disease targets using multimodal human podocyte injury models

GSE302890 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/04/02 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 24 conditions, mostly in duplicateGroups 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
Discovery of kidney disease targets using multimodal human podocyte injury modelsStem cell reports · 2026
Summary (written by the submitters)
Podocyte injury is a hallmark of chronic kidney disease (CKD), but whether different injury signals perturb unified or distinct molecular targets remains unclear. Using human induced pluripotent stem cell (hiPSC)-derived podocytes, we modeled cellular injury via exposure to diabetic, inflammatory, chemical toxin, biomechanical, and infectious stressors.
Read the full summary ↓
Transcriptomic analysis revealed both shared and unique changes in gene expression across injury modes. While drug-induced injuries triggered broader transcriptional responses, conserved pathways related to lysosome function, RNA metabolism, and immune activation were identified across models. Importantly, we discovered that NEU1, CD82, ABI3BP, and ADAM17 as targets of human podocyte injury. We confirmed enrichment of these targets in kidney disease patient biopsies, underscoring their in vivo relevance and potential as therapeutic targets. These findings highlight the value of human-relevant experimental models and provide insight into podocyte injury responses, offering a framework for future precision medicine approaches.
Published in
Discovery of kidney disease targets using multimodal human podocyte injury models
Barreto AD, Jiang B, Burt MA et al. · Stem cell reports 2026 · PMID 41932339 · doi:10.1016/j.stemcr.2026.102868
This dataset
Open GSE302890 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 GSE302890_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 PRJNA1292765 and SRA study SRP601502. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41932339) ↗
Study design
24 conditions, mostly in duplicate
AO9_S23_L ×2 AO8_S22_L ×2 MB34_S25_L ×2 AO4_S18_L ×2 AO3_S17_L ×2 AO17_S21_L ×2 AO14_S19_L ×2 AO16_S20_L ×2 +16 more

Supports a between-group comparison across 48 samples.

How we read this: 24 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.