← BioTransfer GEO Dataset Finder
GEO series

Adipose tissue biology and effect of weight loss in women with lipedema

GSE274137 Homo sapiens (human) RNA-seq (gene expression) 34 samples Submitted 2024/10/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 34 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
34 samples: 34 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
Adipose Tissue Biology and Effect of Weight Loss in Women With LipedemaDiabetes · 2025
Summary (written by the submitters)
Lipedema is a lipodystrophic disease characterized by marked increases in lower-body subcutaneous adipose tissue, anecdotally reported to: i) increase inflammation and fibrosis and impair microvascular and lymphatic circulation in the affected adipose tissue, ii) reduce risk of developing obesity-related cardiometabolic abnormalities; and iii) be resistant to diet-induced weight loss.
Read the full summary ↓
To further our understanding of lipedema, we examined body composition, metabolic health and adipose tissue bology in women with obesity and lipedema (Obese-LIP) at baseline and following ~9% diet-induced weight loss. At baseline, people with Obese-LIP had ~23% greater leg fat mass, ~11% lower android-to-gynoid ratio and ~54% greater insulin sensitivity compared to women matched on age, body mass index and whole-body fat mass. In the Obese-LIP group, total and proinflammatory macrophage content and expression of inflammation and fibrosis-related genes were greater while lymph/angiogenesis-related genes were lower in subcutaneous femoral compared to abdominal adipose tissue. Diet-induced weight loss improved insulin sensitivity and decreased total fat mass due to similar reductions in abdominal and leg fat masses, with minimal effect on markers of adipose tissue inflammation/fibrosis and lymph/angiogenesis. Our study provides important insights into the pathophysiology of lipedema and suggests diet-induced weight loss should be the cornerstone therapy in people with Obese-LIP.
Published in
Adipose Tissue Biology and Effect of Weight Loss in Women With Lipedema
Cifarelli V, Smith GI, Gonzalez-Nieves S et al. · Diabetes 2025 · PMID 39652636 · doi:10.2337/db24-0890
This dataset
Open GSE274137 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 GSE274137_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 PRJNA1145083 and SRA study SRP524658. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39652636) ↗
Study design
34 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 34 sample titles: 34 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 human 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.