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Preterm Birth Increases Susceptibility to Hyperglycemia-Induced Kidney Injury with Sex-Specific Differences in Structural and Molecular Responses

GSE319377 Mus musculus (mouse) RNA-seq (gene expression) 14 samples Submitted 2026/05/05 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 14 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
14 samples: 4 × Female term non-diabetic (T-ND), RNAseq, vs 4 × Female term diabetic (T-D), RNAseq, vs 3 × Female preterm non-diabetic (PT-ND), RNAseq, vs 3 × Female preterm diabetic (PT-D), RNAseq,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
Preterm Birth Increases Susceptibility to Hyperglycemia-Induced Kidney Injury With Sex-Specific Differences in Structural and Molecular ResponsesEndocrinology, diabetes & metabolism · 2026
Summary (written by the submitters)
Background: Preterm birth increases the long-term risk of diabetes and chronic kidney disease (CKD), yet its impact on diabetic kidney disease (DKD) is unclear. We previously showed that male preterm mice with diabetes develop early features of DKD, including reduced podocyte density, decreased renin expression, activation of angiogenesis pathways, and impaired endothelial–podocyte signaling.
Read the full summary ↓
Here, we examine whether preterm birth similarly accelerates DKD progression in female mice and compare structural and transcriptomic outcomes in the females to the prior male cohort to assess sex-specific differences. Methods: Preterm mice were delivered by Cesarean section at 19 days post conception (dpc) and term mice at 20 dpc. Hyperglycemia was induced at 6 weeks with streptozotocin to generate term-diabetic (T-D) and preterm-diabetic (PT-D) groups; controls were term-nondiabetic (T-ND) and preterm-nondiabetic (PT-ND). Body weight and glucose were monitored, and kidneys were analyzed at 18 weeks using histologic, stereologic, imaging, and transcriptomic methods. Results: Compared with T-ND females, PT-D females showed higher albuminuria, more atubular glomeruli, reduced proximal tubule (PT) fraction, and pro-fibrotic gene activation. Compared to T-D females, PT-D females had higher blood urea nitrogen (BUN) levels and reduced PT fraction. This was associated with activation of pathways associated with the vasculature and suppression of mitochondrial metabolism gene pathways, along with Notch signaling alterations. Sex differences included a lower PT fraction in preterm females than males and fewer atubular glomeruli in PT-D females than PT-D males. Renin expression was lower in PT-D than T-D in males only. When comparing PT-D to T-D across sexes, 582 differentially expressed genes were unique to females. Notch signaling was upregulated in both male and female PT-D mice compared to T-D. Conclusion: Preterm birth increases susceptibility to kidney injury in females after exposure to hyperglycemia. However, preterm females with hyperglycemia are more resistant to kidney damage than males.
Published in
Preterm Birth Increases Susceptibility to Hyperglycemia-Induced Kidney Injury With Sex-Specific Differences in Structural and Molecular Responses
Dailey RK, Cwiek A, Hamil LC et al. · Endocrinology, diabetes & metabolism 2026 · PMID 42008787 · doi:10.1002/edm2.70223
This dataset
Open GSE319377 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 GSE319377_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 PRJNA1423191 and SRA study SRP676797. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42008787) ↗
Study design
4 × Female term non-diabetic (T-ND), RNAseq, vs 4 × Female term diabetic (T-D), RNAseq, vs 3 × Female preterm non-diabetic (PT-ND), RNAseq, vs 3 × Female preterm diabetic (PT-D), RNAseq,

Supports a between-group comparison across 14 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 14 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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