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Selective remodelling of the adipose niche in obesity and weight loss [snRNA-Seq]

GSE295708 Homo sapiens (human) Single-nucleus RNA-seq 18 samples Submitted 2025/06/19 Platform GPL30173
At a glance

Single-nucleus RNA-seq · human · 18 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Homo sapiens (human)
Samples
18 samples: 6 × SAT, Pooled Patients, Obese, vs 6 × SAT, Pooled Patients, Lean, vs 6 × SAT, Pooled Patients, Weight Loss,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
Selective remodelling of the adipose niche in obesity and weight lossNature · 2025
Summary (written by the submitters)
Weight loss significantly improves metabolic and cardiovascular health in people with obesity. Adipose tissue remodelling is central to these varied and important clinical effects. However surprisingly little is known about the underlying mechanisms, presenting a barrier to treatment advances. Here we report a spatially resolved single nucleus atlas (171,247 cells, 70 people) investigating the cell types, molecular events and regulatory factors that reshape human adipose tissues, and thus metabolic health, in obesity and therapeutic weight loss.
Read the full summary ↓
We discover selective vulnerability to senescence in metabolic, precursor and vascular cells and reveal senescence is potently reversed by weight loss. We define gene regulatory mechanisms and tissue signals that may drive a degenerative cycle of senescence, tissue injury and metabolic dysfunction. We find that weight loss reduces adipocyte hypertrophy and biomechanical constraint pathways, activating global metabolic flux and bioenergetic substrate cycles that may mediate systemic improvements in metabolic health. In the immune compartment, we demonstrate that weight loss represses obesity-induced macrophage infiltration but does not completely reverse activation, leaving these cells primed to trigger potential weight regain and worsen metabolic dysfunction. Throughout, we map cells to tissue niches to understand the collective determinants of tissue injury and recovery. Overall, our complementary single nucleus and spatial datasets offer unprecedented insights into the basis of obese adipose tissue dysfunction and its reversal by weight loss, and a key resource for mechanistic and therapeutic exploration.
Published in
Selective remodelling of the adipose niche in obesity and weight loss
Miranda AMA, McAllan L, Mazzei G et al. · Nature 2025 · PMID 40634602 · doi:10.1038/s41586-025-09233-2
This dataset
Open GSE295708 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 GSE295708_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1255645 and SRA study SRP581386. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40634602) ↗
Study design
6 × SAT, Pooled Patients, Obese, vs 6 × SAT, Pooled Patients, Lean, vs 6 × SAT, Pooled Patients, Weight Loss,

Supports a between-group comparison across 18 samples.

How we read this: 3 replicated groups read from 18 sample titles; they account for 18 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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