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Single-cell Transcriptomics Reveal Signatures of Altered B cell Response and T cell Senescence in Geriatric Non-responders to COVID-19 mRNA Vaccination

GSE300265 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2026/03/20 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
12 samples: 6 × PBMC, Covid Vaccine, Responde vs 6 × PBMC, Covid Vaccine, Non-respondeGroups 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
Single-cell transcriptomics reveal altered B cell responses and T cell senescence in geriatric non-responders to COVID-19 mRNA vaccinationiScience · 2026
Summary (written by the submitters)
The immune response to COVID-19 vaccines is diminished in older individuals. To understand the underlying immunobiology, we analyzed single-cell RNA-seq data from PBMCs of SARS-CoV-2 naïve nursing home residents with varying humoral responses following BNT162b2 vaccination and validated via flow cytometry. Responders (>4500 AU/mL anti-spike titers) showed enrichment for naïve B cell (IGHD, BACH2, CD22) and naïve CD4 T cell and early Tfh-related genes (CCR7, TCF7, LEF1, IL6ST, TGFBR2).
Read the full summary ↓
Non-responders (<20 AU/mL) displayed elevated markers of T cell senescence (KLRG1, CCL4, CCL5, IL32), immune exhaustion (PD-1), and inflammation (TNF-α, IFN-γ). Flow cytometry revealed reduced CD4 T and B cell frequencies but higher CD8 T and NK cells in non-responders. Despite reduced B cell frequency, non-responders upregulated plasma B cell genes (PRDM1, XPB1, IRF4), suggesting dysregulated B cell differentiation. Our findings point to impaired lymphocyte responses and increased immunosenescence in non-responders, emphasizing the need for enhanced vaccine strategies in aging populations.
Published in
Single-cell transcriptomics reveal altered B cell responses and T cell senescence in geriatric non-responders to COVID-19 mRNA vaccination
Ismail J, Tamilselvan B, Rubsamen M et al. · iScience 2026 · PMID 42095075 · doi:10.1016/j.isci.2026.115730
This dataset
Open GSE300265 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 GSE300265_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1279990 and SRA study SRP593321. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42095075) ↗
Study design
6 × PBMC, Covid Vaccine, Responde vs 6 × PBMC, Covid Vaccine, Non-responde

Supports a between-group comparison across 12 samples.

How we read this: 2 replicated groups read from 12 sample titles; they account for 12 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
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