← BioTransfer GEO Dataset Finder
GEO series

Influenza virus exposure shapes the B cell response to influenza vaccination fifty years later

GSE283403 Homo sapiens (human) RNA-seq (gene expression) 90 samples Submitted 2025/02/28 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 90 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
90 samples: 90 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.
Paper
Early influenza virus exposure shapes the B cell response to influenza vaccination in individuals 50 years laterImmunity · 2025
Summary (written by the submitters)
Pre-existing immunity impacts vaccine responses to endemic respiratory viruses such as influenza, but directly connecting influenza infections early in life with immune responses decades later is difficult. However, H2N2 stopped circulating in the human population in 1968, creating the opportunity to directly evaluate the impact of early H2N2 exposure on vaccine responses 50 years later.
Read the full summary ↓
Here, we vaccinate individuals born before (H2 Exposed) or after (H2 Naïve) 1968 with an H2 HA DNA plasmid and/or a ferritin nanoparticle vaccine. H2 Exposed individuals generated a rapid B cell recall response that differed in potency, cross-reactivity, immunoglobulin repertoire, epitope targeting and phenotype from the de novo response in H2 Naïve individuals. Furthermore, vaccinating with a DNA versus a protein nanoparticle vaccine altered the response in H2 Naïve but not H2 Exposed individuals. This study clearly establishes and describes the life-long impact of influenza HA-specific memory B cells formed early in life on vaccine responses decades later.
Published in
Early influenza virus exposure shapes the B cell response to influenza vaccination in individuals 50 years later
Spangler A, Shimberg GD, Mantus GE et al. · Immunity 2025 · PMID 40023164 · doi:10.1016/j.immuni.2025.02.004
This dataset
Open GSE283403 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 GSE283403_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 PRJNA1193580 and SRA study SRP549079. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40023164) ↗
Study design
90 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 90 sample titles: 90 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

+ 50 more — browse all 90 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.