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A 5-transcript signature for discriminating viral and bacterial etiology in pediatric pneumonia

GSE261482 Homo sapiens (human) RNA-seq (gene expression) 177 samples Submitted 2024/12/09 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 177 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
177 samples: 177 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
A diagnostic host-specific transcriptome response for Mycoplasma pneumoniae pneumonia to guide pediatric patient treatmentNature communications · 2025
Summary (written by the submitters)
Pneumonia stands as the primary cause of death among children under five, with its onset attributed to a broad spectrum of microorganisms. Diagnosis poses an ongoing challenge, relying on clinical or microbiological criteria, often resulting in delayed and inaccurate treatment and unnecessary therapy. Our research focuses on identifying host transcriptomic biomarkers in the blood of children affected by viral and bacterial pneumonia, alongside healthy controls.
Read the full summary ↓
The main goal is to establish a gene-expression signature enhancing disease diagnosis and management. We conducted an analysis of a total of 192 whole blood samples, comprising 38 controls and 154 viral and bacterial pneumonia patients recruited through the EUCLIDS clinical network. Our investigation identified 5,486 differentially expressed genes (DEGs) when comparing blood RNA from pneumonia patients with healthy controls. Functional enrichment analysis highlighted pathways related to the immune system response, encompassing neutrophil degranulation, humoral immune response, and various inflammatory pathways. In the comparative analysis of gene expression between viral and bacterial pneumonia patients, we identified 272 DEGs. Gene set analysis revealed a significant difference in pathway enrichment for the immune response, contingent on the over-regulation of gene sets in viral or bacterial pneumonias. Furthermore, we identified a 5-transcript host signature specifically designed to distinguish between viral and bacterial pediatric pneumonia (FAM20A, BAG3, TDRD9, MXRA7 and KLF14; AUC: 0.95 [0.88–1.00]), pseudo-validated in a cohort including probable bacterial and viral patients (AUC: 0.87 [0.77–0.97]). This signature holds the potential to enhance the accuracy of previously described general transcript-based signatures for viral and bacterial infections.
Published in
A diagnostic host-specific transcriptome response for Mycoplasma pneumoniae pneumonia to guide pediatric patient treatment
Viz-Lasheras S, Gómez-Carballa A, Bello X et al. · Nature communications 2025 · PMID 39809748 · doi:10.1038/s41467-025-55932-9
This dataset
Open GSE261482 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 GSE261482_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 PRJNA1087273 and SRA study SRP494984. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39809748) ↗
Study design
177 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 177 sample titles: 177 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

+ 137 more — browse all 177 samples with per-sample file links →

Datasets on a similar topic

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