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Dynamics of gene expression profiling by RNA-Seq and identification of high-risk patients for severe COVID-19 [RNA-Seq]

GSE212861 Homo sapiens (human) RNA-seq (gene expression) 93 samples Submitted 2024/12/31 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 93 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
93 samples: 31 conditions, mostly in duplicateGroups 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
Dynamics of Gene Expression Profiling and Identification of High-Risk Patients for Severe COVID-19Biomedicines · 2023
Summary (written by the submitters)
The clinical manifestations of SARS-Co-2 infection vary widely, from asymptomatic infection to the development of acute respiratory distress syndrome (ARDS) and death. The host response elicited by SARS-CoV-2 plays a key role in determining the clinical outcome. We hypothesized that determining the dynamic whole blood transcriptomic profile of adult patients hospitalized for COVID-19 and characterizing the subgroup that develops severe disease and ARDS would broaden our understanding of the heterogeneity in clinical outcomes.
Read the full summary ↓
We recruited 60 hospitalized patients with microbiology-confirmed COVID-19, among whom 19 developed ARDS. Peripheral blood was collected using PAXGene RNA tubes within 24 hours of admission and at day 7. There were 2150 differently expressed genes in patients with ARDS at baseline, and 1963 at day 7. We found a dysregulated inflammatory response in COVID-19 ARDS patients, with an increased expression of genes related to pro-inflammatory molecules and neutrophil and macrophage activation at admission, in addition to the loss of immune regulation. This led in turn to a higher expression of genes related to reactive oxygen species, protein polyubiquitination, and metalloproteinases in latter stages. Some of the most significant differences in gene expression found between patients with and without ARDS corresponded to long non-coding RNA involved in epigenetic control.
Published in
Dynamics of Gene Expression Profiling and Identification of High-Risk Patients for Severe COVID-19
Rombauts A, Bódalo Torruella M, Abelenda-Alonso G et al. · Biomedicines 2023 · PMID 37239019 · doi:10.3390/biomedicines11051348
This dataset
Open GSE212861 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 GSE212861_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 PRJNA877667 and SRA study SRP396106. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 37239019) ↗
Study design
31 conditions, mostly in duplicate
4_D ×2 5_D ×2 6_D ×2 7_D ×2 14_D ×2 15_D ×2 18_D ×2 21_D ×2 +54 more

Supports a between-group comparison across 62 samples.

How we read this: 31 replicated groups read from 93 sample titles; they account for 62 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

+ 53 more — browse all 93 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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