← BioTransfer GEO Dataset Finder
GEO series

Fructose specifically exacerbates pathogenic-Th17 cell differentiation and autoimmune diseases through ROS-EGFR signal

GSE285450 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/09/29 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 18 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.
Summary (written by the submitters)
Th17 cells are quite heterogeneous, with pathogenic roles in autoimmunity and non-pathogenic roles in maintaining tissue homeostasis. Although efforts have been made to study genetic and cellular factors in regulating Th17 cell differentiation, little is known about the role of environmental factors and their underlying mechanisms. Here, we revealed that high-fructose intake selectively enhanced the differentiation and function of IL1b+IL-6+IL-23-induced pathogenic Th17 cells (pTh17), without affecting TGFb1+IL-6-induced non-pTh17 cells, and exacerbated autoimmune diseases models.
Read the full summary ↓
Notably, fructose enhanced both aerobic glycolysis and OXPHOS activity in pTh17 cells, leading to increased ROS production and subsequently promoting their differentiation. N-acetyl cysteine (NAC), a ROS scavenger, specifically impaired pTh17 cell immunity and mitigated autoimmune disease under high-fructose consumption. Mechanistically, ROS accumulation resulted in higher EGFR expression and activation, which subsequently translocated in nucleus to bind with STAT3, enhancing its transcriptional activity of CNS6 and CNS9 regions of Rorc. Taking together, we illustrated a previously unrecognized mechanism underlying the adverse effects of high-fructose intake in pTh17 cell-related pathologies and diseases.
This dataset
Open GSE285450 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 GSE285450_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 PRJNA1203650 and SRA study SRP554112. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 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 18 sample titles: 18 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
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.