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Adverse proinflammatory responses in the kidney after FGF23 administration in murine kidney disease models

GSE272289 Mus musculus (mouse) RNA-seq (gene expression) 38 samples Submitted 2025/07/15 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 38 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
Mus musculus (mouse)
Samples
38 samples: 10 conditions, mostly with about 4 replicates eachGroups 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
The renal response to FGF23 shifts from phosphaturia toward inflammation in kidney diseaseJournal of cell communication and signaling · 2026
Summary (written by the submitters)
FGF23 is a biomarker associated with morbidity and mortality, but controversies remain if a causative link exists between FGF23 excess and adverse renal consequences in chronic kidney disease (CKD). Here, we investigated renal FGF23 signaling in kidney disease models in mice, with a focus on adverse pro-inflammatory effects assessed in bulk transcriptomes.
Published in
The renal response to FGF23 shifts from phosphaturia toward inflammation in kidney disease
Moor MB, Burmakin M, Levin A et al. · Journal of cell communication and signaling 2026 · PMID 41744000 · doi:10.1002/ccs3.70061
This dataset
Open GSE272289 in finder → Find more mouse 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 GSE272289_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 PRJNA1136028 and SRA study SRP520004. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41744000) ↗
Study design
10 conditions, mostly with about 4 replicates each
kidneyNTS_control.vehicle ×4 kidneyNTS_antiGBM.vehicle ×4 kidneyAdria_control.vehicle ×4 kidneyAdria_adriamycin.vehicle ×4 kidneyAdria_control.FGF23 ×4 kidneyAdria_adriamycin.FGF23 ×4 PCKS_adenine_vehicle ×4 PCKS_adenine_FGF23 ×4 +2 more

Supports a between-group comparison across 38 samples.

How we read this: 10 replicated groups read from 38 sample titles; they account for 38 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
Datasets on a similar topic

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