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Adipose tissue gene expression profiling in women with overweight or obesity following early vs. late time-restricted eating

GSE287198 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2025/09/22 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 30 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
30 samples: 30 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
Impact of Intended Isocaloric Early versus Late Time-Restricted Eating on Plasma Lipidome in Women with Overweight or Obesity: Secondary Analysis of the ChronoFast TrialAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
Summary (written by the submitters)
Time-restricted eating (TRE) is a promising strategy to prevent obesity and type 2 diabetes, but data on its effects on adipose tissue metabolism are limited. Therefore, we conducted a crossover study examined 31 women with overweight or obesity who followed both a two-week early TRE (eTRE) and a two-week late TRE (lTRE). Gene expression profiles in subcutaneous adipose tissue collected after both TRE interventions were compared using RNA sequencing.
Read the full summary ↓
These data provide a first insight into the remodelling of the human adipose tissue transcriptome by the eating timing during TRE, warranting consideration in future dietary research and recommendations.
Published in
Impact of Intended Isocaloric Early versus Late Time-Restricted Eating on Plasma Lipidome in Women with Overweight or Obesity: Secondary Analysis of the ChronoFast Trial
Szekely K, Gerl MJ, Peters B et al. · Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2026 · PMID 41186047 · doi:10.1002/advs.202507149
This dataset
Open GSE287198 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 GSE287198_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 PRJNA1211586 and SRA study SRP557948. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41186047) ↗
Study design
30 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 30 sample titles: 30 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

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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.