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Critical care

Which immune genes drop in sepsis single-cell maps?

Tu X, Huang H, Xu S, et al. · Frontiers in pharmacology · 2023

Open access · cc by · source: Europe PMC

In GSE28750 (10 sepsis vs 20 controls), 61 DEGs and single-cell t-SNE (T/NK/monocyte/megakaryocyte/DC/B cells) pointed to seven T-cell hub genes; six of them were lower in sepsis, with animal assays as follow-up.

How this study connects

Role on claims

Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.

  • SupportsCritical Illnessconcept

    The composition difference is the durable finding; the specific gene list is not.

    Immune cell composition differs in sepsis, but small-sample transcriptomics identifies hub genes unreliably. Single-cell and microarray analysis found six t-SNE clusters and seven hub genes (CD28, CD3D, CD2, CD4, IL7R, LCK, CD3E), six of them reduced in sepsis — from ten sepsis arrays, where hub-gene algorithms overfit.

    Evidence for the claim as stated.

  • SupportsCritical Illnessconcept

    These studies subdivide critical illness with very different evidentiary weight. Macrophage activation-like syndrome is defined by a specific threshold and validated in a second cohort, while the sepsis transcriptomic clusters rest on ten arrays with algorithms the authors acknowledge overfit small public datasets.

    Evidence for the claim as stated.

Open questions

Tensions this paper is part of

From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.

  • Scope difference — different assays, populations, or outcomes

    These studies subdivide critical illness with very different evidentiary weight. Macrophage activation-like syndrome is defined by a specific threshold and validated in a second cohort, while the sepsis transcriptomic clusters rest on ten arrays with algorithms the authors acknowledge overfit small public datasets.

    Also on this tension

Study at a glance

Design
Computational / modelling — GEO GSE28750 bulk microarray (10 sepsis vs 20 controls) plus single-cell clustering, hub-gene network algorithms, and follow-up animal immunoassays
N
N=30 · GSE28750: 10 sepsis and 20 normal samples; 61 DEGs; 7 hub genes; plus in vivo animal validation assays
Population
Public human GEO sepsis vs control transcriptomes (GSE28750) with single-cell maps and animal immune-factor assays
Outcome
Differentially expressed and hub immune genes (CD28, CD3D, CD2, CD4, IL7R, LCK, CD3E) and immune-cell cluster shifts in sepsis

Structured fields used in claim comparison tables when every cited study has a complete layer.

Inspect source passages

Which immune genes drop in sepsis single-cell maps?

These passages occur verbatim in the stored paper text. They support the points listed below; they do not verify every statement in the explanation.

GSE28750 included 10 sepsis and 20 normal samples.

There was a total of 10 sepsis samples and 20 normal samples in GSE28750 dataset

61 DEGs were obtained with limma.

A total of 61 differentially expressed genes (DEGs) between sepsis samples and normal samples were obtained through the ‘limma’ package
Read passages in the original paper

Key findings

61 DEGs; after stricter microarray filters, 599 genes up and 599 down. Six t-SNE clusters. Seven hubs (CD28, CD3D, CD2, CD4, IL7R, LCK, CD3E); six (all but CD2 in the lower-expression list) were reduced in sepsis, with immune-cell composition differing from controls.

Methodology

Downloaded GEO data, called DEGs with limma on GSE28750, clustered single-cell profiles with Seurat t-SNE into six immune lineages, intersected immune genes, and ranked hubs with MCC/MNC/DMNC, then ran Western blot, flow, ELISA, and qPCR in animals.

Limitations

n=10 sepsis arrays cannot define treatment targets; hub-gene algorithms overfit small GEO sets, and animal assays do not prove the same network in human ICU sepsis.

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