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Gene Expression Profiling Identifies Potential Biomarkers for Vaso-Occlusive Episodes in Sickle Cell Disease

GSE291257 Homo sapiens (human) RNA-seq (gene expression) 414 samples Submitted 2025/11/26 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 414 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
414 samples: 37 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.
Summary (written by the submitters)
Vaso-occlusive episodes (VOE) or acute pain events, involving complex interactions between sickle erythrocytes and other blood cells, are a hallmark symptom of sickle cell disease (SCD). In this study, we analyzed changes in peripheral blood transcriptomes between steady state and VOE in individuals with SCD. We followed a cohort of 174 individuals with SCD with or without chronic pain and collected peripheral blood at clinic visits (steady state) and during hospitalizations (VOE).
Read the full summary ↓
We performed RNA-Seq profiling of CD45+ leukocytes and CD71+ erythroid cells. Pathways linked to complement activation, coagulation, and IL6-JAK-STAT3 signaling were enriched at VOE in the CD45+ cells. Contrastingly, the CD71+ cells showed an enrichment of pathways related to the cell cycle such as mTORC1 signaling and the G2M checkpoint. Expression of four genes—FAM20A, IL1B, MS4A4A, and SERPINB2—were elevated during VOE compared to steady state in a majority of patients.
This dataset
Open GSE291257 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 GSE291257_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 PRJNA1228642 and SRA study SRP566522. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
37 conditions, mostly in duplicate
CD45+cells-Steady-State-ID ×141 CD71+cells-Steady-State-ID ×122 CD45+cells-VOE-ID ×19 CD71+cells-Follow-Up-ID ×16 CD45+cells-Follow-Up-ID ×15 CD71+cells-VOE-ID ×12 CD45+cells-VOE-ID194 ×5 CD71+cells-VOE-ID194 ×5 +30 more

Supports a between-group comparison across 399 samples.

How we read this: 37 replicated groups read from the first 400 of 414 sample titles; they account for 399 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

+ 374 more — browse all 414 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.