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Expansion of profibrotic monocyte-derived alveolar macrophages in patients with persistent respiratory symptoms and radiographic abnormalities after COVID-19 [PASC]

GSE232627 Homo sapiens (human) Single-cell RNA-seq 30 samples Submitted 2024/05/12 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 30 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
30 samples: 28 distinct titles, 2 of them repeatedGroups 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
Profibrotic monocyte-derived alveolar macrophages are expanded in patients with persistent respiratory symptoms and radiographic abnormalities after COVID-19Nature immunology · 2024
Summary (written by the submitters)
As many as 10–30% of the nearly 750 million survivors of COVID-19 develop persistent symptoms that define the post-acute sequelae of COVID-19 (PASC) syndrome. To understand the molecular basis of this syndrome, we combined a machine learning based analysis of lung computed tomography (CT) with flow cytometry and single cell RNA-sequencing analysis of bronchoalveolar lavage fluid and nasal curettage samples in a cohort of thirty-five patients with respiratory symptoms and radiographic abnormalities more than 90 days after infection with COVID-19.
Read the full summary ↓
CT images from patients with PASC revealed primarily fibrotic abnormalities involving 73 +/- 28% of the lung, most of which improved on subsequent imaging. The presence of profibrotic monocyte-derived alveolar macrophages in BAL fluid was significantly associated with increased levels of alveolar cytokines and fibrotic abnormalities on CT. Persistent infection with SARS-CoV-2 was identified in 6 patients and secondary bacterial or viral infections in two others. These findings suggest persistent alveolar inflammation characterized by the ongoing recruitment of monocyte derived alveolar macrophages is associated with fibrotic CT changes in some COVID-19 survivors with implications for diagnosis and therapy.
Published in
Profibrotic monocyte-derived alveolar macrophages are expanded in patients with persistent respiratory symptoms and radiographic abnormalities after COVID-19
Bailey JI, Puritz CH, Senkow KJ et al. · Nature immunology 2024 · PMID 39367123 · doi:10.1038/s41590-024-01975-x
This dataset
Open GSE232627 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 GSE232627_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 PRJNA973049. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39367123) ↗
Study design
28 distinct titles, 2 of them repeated
Library_5D ×2 Library_6A ×2

How we read this: Read from 30 sample titles: 28 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
Datasets on a similar topic

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