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Pulmonary fibrosis after COVID-19 is characterized by airway abnormalities and elevated club cell secretory protein-16

GSE308611 Homo sapiens (human) Single-cell RNA-seq 34 samples Submitted 2026/01/28 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 34 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
34 samples
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.
Summary (written by the submitters)
Prior studies testing biomarkers of residual lung abnormalities after COVID-19 are limited by sampling within the first year after acute COVID-19 illness and lack of external validation of findings. In three independent, international, racially and ethnically diverse prospective cohorts of survivors of moderate to critical COVID-19, we systematically tested 18 circulating biomarkers of inflammation, aging, endothelial activation, pulmonary epithelial function, fibrosis, and fibrinolysis.
Read the full summary ↓
We found that only higher club-cell secretory protein-16 (CC16) levels are consistently associated with persistent fibrotic lung abnormalities in cross-sectional and longitudinal analyses for up to 3 years after acute COVID-19. Histopathological and single-cell RNA sequencing analyses of transbronchial biopsies of fibrotic lung abnormalities in COVID-19 survivors sampled between 3 and 4 years after acute illness and of COVID-19 lung explants suggest that circulating CC16 reflects underlying deranged pulmonary epithelial progenitor proliferation and anomalous CC16/MUC5B-related pro-fibrotic signaling in the distal airways. CC16 should be investigated further as a potential blood biomarker that may facilitate screening of COVID-19 survivors for pulmonary fibrosis and its progression.
This dataset
Open GSE308611 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 GSE308611_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 PRJNA1331709 and SRA study SRP622479. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

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