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Transcriptomic analysis after SARS-CoV-2 mRNA vaccination reveals a specific gene signature in low-responder hemodialysis patients

GSE265975 Homo sapiens (human) RNA-seq (gene expression) 100 samples Submitted 2024/10/09 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 100 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
100 samples: 28 conditions, mostly with about 4 replicates eachGroups 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 analysis after SARS-CoV-2 mRNA vaccination reveals a specific gene signature in low-responder hemodialysis patientsFrontiers in immunology · 2025
Summary (written by the submitters)
Individuals with comorbidities, such as chronic kidney disease and hemodialysis patients (HDP), are particularly susceptible to severe COVID-19 and to its complications. Furthermore, their immune response to vaccines is impaired, requiring tailored vaccination strategies. In this study, we investigated through transcriptomic profiling the immune response heterogeneity of HDP vaccinated with two doses of mRNA BNT162b2 vaccine.
Read the full summary ↓
Transcriptomic analyses were conducted in peripheral blood mononuclear cells (PBMC) collected from HDP and healthy controls (HC) before and 7 days after each dose. The HDP were stratified into high- and low-responders based on their humoral response after the second dose. Significant differences in gene expression related to B cell abundance and regulation, CD4 T cell proliferation, and inflammation pathways were observed at baseline and day 7 between HDP-low responders and HC, while the HDP high-responders displayed an intermediate expression profile for these genes. Results were consistent with the known immunologic alterations occurring in HDP cohorts related to lymphopenia, chronic inflammation, and dysregulated proliferation of CD4+. Our analyses identified an early transcriptional signature correlated with a diminished immune response in HDP low-responders, highlighting the importance of conducting a characterization of immunocompromised cohorts.
Published in
Transcriptomic analysis after SARS-CoV-2 mRNA vaccination reveals a specific gene signature in low-responder hemodialysis patients
Lucchesi S, Montesi G, Polvere J et al. · Frontiers in immunology 2025 · PMID 40370459 · doi:10.3389/fimmu.2025.1508659
This dataset
Open GSE265975 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 GSE265975_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 PRJNA1105077 and SRA study SRP504288. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40370459) ↗
Study design
28 conditions, mostly with about 4 replicates each
PAT21, HDP-high, d ×4 PAT22, HDP-high, d ×4 PAT23, HDP-low, d ×4 PAT26, HDP-high, d ×4 PAT27, HDP-high, d ×4 PAT32, HDP-high, d ×4 PAT33, HDP-high, d ×4 PAT35, HDP-low, d ×4 +21 more

Supports a between-group comparison across 99 samples.

How we read this: 28 replicated groups read from 100 sample titles; they account for 99 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

+ 60 more — browse all 100 samples with per-sample file links →

Datasets on a similar topic

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