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Whole blood transcriptomics characterize molecular phenotypes of pulmonary Mycobacterium avium complex disease

GSE288604 Homo sapiens (human) RNA-seq (gene expression) 200 samples Submitted 2025/12/08 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 200 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
200 samples: 100 × Patient before treatment with guideline based therapy vs 100 × Patient 1 month after treatment with guideline based therapyGroups 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
Transcriptomic profiling in Mycobacterium avium complex pulmonary disease identifies clusters linked to disease severity and neutrophil activationAmerican journal of respiratory and critical care medicine · 2026
Summary (written by the submitters)
Pulmonary Mycobacterium avium complex (MAC) disease shows a range of clinical phenotypes and responses to treatment. While Th1 immunity and neutrophils have been implicated in its pathogenesis, the precise mechanisms remain unclear. Furthermore, comprehensive gene expression analysis in this context are scarce. This study aimed to elucidate the heterogeneity of pulmonary MAC disease by gene expression profiling of whole blood cells.
Read the full summary ↓
Unsupervised cluster analysis was performed on whole blood gene expression data at 0M. In addition, we also evaluated the variation in gene expression profiles of whole blood cells before (0M) and after starting treatment (1M) with guideline based therapy (GBT; azithromycin [AZM]/clarithromycin [CAM]+ethambutol [EB]+rifampicin [RFP]).
Published in
Transcriptomic profiling in Mycobacterium avium complex pulmonary disease identifies clusters linked to disease severity and neutrophil activation
Sakai C, Nonaka M, Matsuyama M et al. · American journal of respiratory and critical care medicine 2026 · PMID 41086411 · doi:10.1164/rccm.202503-0665OC
This dataset
Open GSE288604 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 GSE288604_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 PRJNA1218673 and SRA study SRP561318. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41086411) ↗
Study design
100 × Patient before treatment with guideline based therapy vs 100 × Patient 1 month after treatment with guideline based therapy

Supports a between-group comparison across 200 samples.

How we read this: 2 replicated groups read from 200 sample titles; they account for 200 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

+ 160 more — browse all 200 samples with per-sample file links →

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.