← BioTransfer GEO Dataset Finder
GEO series

Longitudinal monitoring of Type 1 Diabetes progression to disease onset

GSE299709 Mus musculus (mouse) RNA-seq (gene expression) 120 samples Submitted 2025/12/21 Platform GPL34328Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 120 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
120 samples: 120 samples, each with a distinct title — no replicated groupsGroups 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
Longitudinal monitoring of type 1 diabetes progression to disease onsetScience advances · 2026
Summary (written by the submitters)
Preventing autoimmune type 1 diabetes (T1D) necessitates improved monitoring for disease progression prior to symptom onset. Current diagnostic methods assess circulating autoantibodies, C-peptide levels, or dysglycemia, yet these approaches fail to identify β cell destruction preceding glucose dysregulation. Herein, a subcutaneous microporous scaffold is employed as an immunological niche (IN), which provides a non-vital accessible tissue reflecting many immune changes occurring in the pancreas.
Read the full summary ↓
RNA sequencing analysis of the IN successfully delineates at-risk from non-risk groups, as well as disease progressors from non-progressors at six weeks of age in the NOD mouse model. Within progressors, we identify disease five to seven weeks prior to disease onset. Collectively, disease occurring in a poorly accessible site can be identified early by sampling a distant non-vital tissue, indicating the systemic nature of the disease and informing the timing of disease modifying therapies to halt or delay the progression of T1D.
Published in
Longitudinal monitoring of type 1 diabetes progression to disease onset
King JL, Roy J, Urie RR et al. · Science advances 2026 · PMID 41604487 · doi:10.1126/sciadv.adw8946
This dataset
Open GSE299709 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 GSE299709_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 PRJNA1276107 and SRA study SRP591713. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41604487) ↗
Study design
120 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 120 sample titles: 120 distinct titles with little repetition. 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

+ 80 more — browse all 120 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.