GEO series

Immune-cell signatures of persistent inflammation-immunosuppression and catabolism syndrome

GSE217906 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2025/01/23 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 16 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 16 samples: 6 conditions, mostly in duplicateGroups 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: Immune-cell signatures of persistent inflammation, immunosuppression, and catabolism syndrome after sepsisMed (New York, N.Y.) · 2025

Summary (written by the submitters)

Sepsis is a debilitating disease with a worldwide prevalence. An increasing number of patients with sepsis, especially aged patients, suffer from chronic critical illness and develop persistent inflammation-immunosuppression and catabolism syndrome (PICS). Here, we profiled peripheral blood mononuclear cells in four patients with PICS, two patients with acute sepsis, and three healthy controls using single-cell RNA sequencing and systematic analyses.

Read the full summary ↓

We found that gene expression patterns and developmental routes in distinct immune cell populations exhibited notable differences between patients with PICS, patients with acute sepsis, and healthy controls.

Published in

Immune-cell signatures of persistent inflammation, immunosuppression, and catabolism syndrome after sepsis

Sun XF, Luo WC, Huang SQ et al. · Med (New York, N.Y.) 2025 · PMID 39824181 · doi:10.1016/j.medj.2024.12.003

This dataset

Open GSE217906 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 GSE217906_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 PRJNA901378 and SRA study SRP407793. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39824181) ↗

Study design

6 conditions, mostly in duplicate

HC ×5 Sepsis ×3 PD ×2 PA ×2 AS ×2 PICS ×2

Supports a between-group comparison across 16 samples.

How we read this: 6 replicated groups read from 16 sample titles; they account for 16 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

GSM6729707 PD-01 PD
GSM6729708 PD-02 PD
GSM6729709 PA-01 PA
GSM6729710 PA-02 PA
GSM6729711 AS-01 AS
GSM6729712 AS-02 AS
GSM6729713 HC-01 HC
GSM6729714 HC-02 HC
GSM6729715 HC-03 HC
GSM8217322 PICS5 PICS
GSM8217323 Sepsis4 Sepsis
GSM8217324 Sepsis2 Sepsis
GSM8217325 Sepsis3 Sepsis
GSM8217326 HC3 HC
GSM8217327 HC5 HC
GSM8217328 PICS3 PICS

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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.