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Propionate and butyrate counteract renal damage and progression to chronic kidney disease

GSE221506 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/05/02 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 6 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
Propionate and butyrate counteract renal damage and progression to chronic kidney diseaseNephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
Summary (written by the submitters)
Background: Short-chain fatty acids (SCFAs), mainly acetate, propionate and butyrate, are produced by gut microbiota through fermentation of complex carbohydrates that cannot be digested by the human host. They affect gut health and can contribute at the distal level to the pathophysiology of several diseases, including renal pathologies.
Read the full summary ↓
Methods: SCFA levels were measured in chronic kidney disease (CKD) patients (n = 54) at different stages of the disease and associations with renal function and inflammation parameters were examined. The impact of propionate and butyrate in pathways triggered in tubular cells under inflammatory conditions was analysed using genome-wide expression assays. Finally, a pre-clinical mouse model of folic acid-induced transition from acute kidney injury to CKD was used to analyse the preventive and therapeutic potential of these microbial metabolites in the development of CKD. Results: Faecal levels of propionate and butyrate in CKD patients gradually reduce as the disease progresses, and do so in close association with established clinical parameters for serum creatinine, blood urea nitrogen and the estimated glomerular filtration rate. Propionate and butyrate jointly downregulated the expression of 103 genes related to inflammatory processes and immune system activation triggered by TNF-α in tubular cells. In vivo, the administration of propionate and butyrate, either before or soon after injury, respectively prevented and slowed the progression of damage. This was indicated by a decrease in renal injury markers, the expression of pro-inflammatory and pro-fibrotic markers, and recovery of renal function over the long term. Conclusions: Propionate and butyrate levels are associated with a progressive loss of renal function in CKD patients. Early administration of these SCFAs prevents disease advancement in a pre-clinical model of acute renal damage, demonstrating their therapeutic potential independently of the gut microbiota.
Published in
Propionate and butyrate counteract renal damage and progression to chronic kidney disease
Corte-Iglesias V, Saiz ML, Andrade-Lopez AC et al. · Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 2024 · PMID 38794880 · doi:10.1093/ndt/gfae118
This dataset
Open GSE221506 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 GSE221506_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 PRJNA914704 and SRA study SRP414283. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38794880) ↗
Study design
6 conditions, mostly in duplicate
CONTROL ×2 BUTN ×2 PRTN ×2 TNBU ×2 TNF ×2 TNP ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 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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