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NNMT promotes tubular senescence and fibrosis in chronic kidney disease (db/m and db/db mice kidney)

GSE283610 Mus musculus (mouse) RNA-seq (gene expression) 17 samples Submitted 2025/11/20 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 17 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
17 samples: 9 × kidney, db/db vs 8 × kidney, db/mGroups 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
NNMT inhibition counteracts tubular senescence and fibrosis in early stages of chronic kidney diseaseCell reports · 2026
Summary (written by the submitters)
Diabetic kidney disease is the leading cause of chronic kidney disease. db/db mice, which carry a deletion mutation resulting in a dysfunctional leptin receptor, exhibit hyperphagia, obesity, and elevated insulin levels, making them a widely used preclinical model of diabetic kidney disease. At 16 weeks of age, db/db mice showed enriched transcriptomic signatures of cellular senescence in their kidneys compared to control db/m mice.
Published in
NNMT inhibition counteracts tubular senescence and fibrosis in early stages of chronic kidney disease
Chanvillard L, Lantermans HC, Wall C et al. · Cell reports 2026 · PMID 41543936 · doi:10.1016/j.celrep.2025.116823
This dataset
Open GSE283610 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 GSE283610_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 PRJNA1194610 and SRA study SRP549639. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41543936) ↗
Study design
9 × kidney, db/db vs 8 × kidney, db/m

Supports a between-group comparison across 17 samples.

How we read this: 2 replicated groups read from 17 sample titles; they account for 17 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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