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Single-cell Analysis of Subcutaneous Fat Reveals Pro-fibrotic Cells that Correlate with Visceral Adiposity in HIV

GSE243957 Homo sapiens (human) Single-cell RNA-seq 108 samples Submitted 2024/05/22 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 108 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
108 samples: 38 × Adipose Tissue, HIV+preDM, vs 36 × Adipose Tissue, HIV+NonDM, vs 34 × Adipose Tissue, HIV+DM,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
Single-Cell Analysis of Subcutaneous Fat Reveals Profibrotic Cells That Correlate With Visceral Adiposity in HIVThe Journal of clinical endocrinology and metabolism · 2024
Summary (written by the submitters)
Cardiometabolic diseases are common in persons with HIV (PWH) on antiretroviral therapy (ART), which has been attributed to preferential lipid storage in visceral adipose tissue (VAT) compared with subcutaneous adipose tissue (SAT). However, the relationship of SAT-specific cellular and molecular programs with VAT volume is poorly understood in PWH.
Read the full summary ↓
We characterized SAT cell-type specific composition and transcriptional programs that are associated with greater VAT volume in PWH on contemporary ART. We enrolled PWH on long-term ART with a spectrum of metabolic health.We enrolled PWH on long-term ART with a spectrum of metabolic health. Ninety-two participants underwent SAT biopsy for bulk RNA sequencing and 43 had single-cell RNA sequencing. Computed tomography quantified VAT volume and insulin resistance was calculated using HOMA2-IR. VAT volume was associated with HOMA2-IR (p<0.001). Higher proportions of SAT intermediate macrophages (IMs), myofibroblasts, and MYOC+ fibroblasts were associated with greater VAT volume using partial Spearman’s correlation adjusting for age, sex, and body mass index (r =0.34-0.49, p<0.05 for all). Whole SAT transcriptomics showed PWH with greater VAT volume have increased expression of extracellular matrix (ECM)- and inflammation-associated genes, and reduced expression of lipolysis- and fatty acid metabolism-associated genes. In PWH, greater VAT volume is associated with higher proportion of SAT IMs and fibroblasts, and a SAT ECM and inflammatory transcriptome, which is similar to findings in HIV-negative persons with obesity. These data identify SAT cell-type specific changes associated with VAT volume in PWH that could underlie the high rates of cardiometabolic diseases in PWH, though additional longitudinal studies are needed to define directionality and mechanisms.
Published in
Single-Cell Analysis of Subcutaneous Fat Reveals Profibrotic Cells That Correlate With Visceral Adiposity in HIV
Bailin SS, Gabriel CL, Gangula RD et al. · The Journal of clinical endocrinology and metabolism 2024 · PMID 38820087 · doi:10.1210/clinem/dgae369
This dataset
Open GSE243957 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 GSE243957_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 PRJNA1020791 and SRA study SRP463058. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38820087) ↗
Study design
38 × Adipose Tissue, HIV+preDM, vs 36 × Adipose Tissue, HIV+NonDM, vs 34 × Adipose Tissue, HIV+DM,

Supports a between-group comparison across 108 samples.

How we read this: 3 replicated groups read from 108 sample titles; they account for 108 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

+ 68 more — browse all 108 samples with per-sample file links →

Datasets on a similar topic

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