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Detailed delineation of the immune response to COVID-19 mRNA vaccination via high-temporal frequency blood transcriptomics [third]

GSE281864 Homo sapiens (human) RNA-seq (gene expression) 193 samples Submitted 2025/01/14 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 193 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
193 samples: 193 samples, each with a distinct title — no replicated groupsGroups 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)
mRNA vaccines have played a crucial role in combating the COVID-19 pandemic, but the long-term dynamics of immune responses to repeated vaccination remain poorly understood. In this study, we extend our previous work on first and second dose responses by characterizing the immune signatures elicited by a third dose of COVID-19 mRNA vaccines.
Read the full summary ↓
Using high-resolution temporal profiling of blood transcriptomes, we analyzed samples collected daily for 9 days post-vaccination across all three doses. We observed distinct patterns of gene expression related to interferon responses, inflammation, erythroid cell signatures, and plasmablast activity. While the first dose elicited a modest response primarily characterized by interferon signaling, the second dose induced a robust, polyfunctional response. Surprisingly, the third dose, administered months later, showed a response pattern that shared similarities with both previous doses but also exhibited unique features. The interferon response following the third dose mirrored the timing of the first dose, peaking on day 2, but matched the amplitude of the second dose. Notably, we observed a progressive amplification of the plasmablast response across the three doses, with an earlier peak (day 4) compared to other vaccines, potentially a unique feature of mRNA vaccines. These findings provide crucial insights into how the immune system adapts to repeated mRNA vaccination over extended periods. They demonstrate that the heightened responsiveness induced by initial doses is maintained months later, suggesting effective immune memory. Our results contribute to a more comprehensive understanding of mRNA vaccine-induced immunity, with implications for optimizing booster strategies and developing next-generation vaccines.
This dataset
Open GSE281864 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 GSE281864_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 PRJNA1186068. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
193 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 193 sample titles: 193 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

+ 153 more — browse all 193 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.