GEO series

Multi-Omics Analysis of the Immunological State at Baseline and Following SARS-CoV-2 mRNA Vaccination in Lung Transplant Recipients

GSE288562 Homo sapiens (human) Single-cell RNA-seq 14 samples Submitted 2025/02/28 Platform GPL34281

At a glance

Single-cell RNA-seq · human · 14 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 14 samples: 14 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: Altered baseline immunological state and impaired immune response to SARS-CoV-2 mRNA vaccination in lung transplant recipientsCell reports. Medicine · 2025

Summary (written by the submitters)

Despite their remarkable success, the effectiveness of COVID-19 mRNA vaccines is notably diminished in organ transplant patients. Here, we employed a multi-omics approach to elucidate the immunological state at baseline and following SARS-CoV-2 mRNA vaccination of lung transplant (LTX) patients compared to healthy controls (HC). Our analysis revealed a baseline immune profile in LTX patients that mirrors the immune alterations observed in severe COVID-19 cases and sepsis.

Read the full summary ↓

This profile is characterized by: (i) elevated pro-inflammatory cytokines in plasma, notably high levels of EN-RAGE and IL-6; (ii) reduced expression of HLA-DR on blood monocytes and dendritic cells (DCs); (iii) diminished cytokine production by blood monocytes and DCs in response to toll-like receptor (TLR) activation; (iv) increased plasma concentrations of microbial products. In addition to these alterations, single-cell RNA-seq analysis revealed 4 transcriptionally distinct clusters of classical monocytes in HC, with a striking enrichment of a unique classical monocyte cluster in LTX patients, differing from the predominant classical monocytes in HC, marked by heightened expression of the S100A family and reduced expression of genes related to cytokine production and antigen presentation. Following vaccination, LTX patients displayed a reduced magnitude and breadth of binding and neutralizing antibody responses, and impaired memory B and T cell responses. Furthermore, there was a blunted innate immune response to vaccination, evidenced by decreased transcriptional signatures linked to antigen presentation, dendritic cell activation, interferon and monocytes at the single-cell level. Integrative multiscale, multiresponse network (MMRN) analysis revealed an inverse correlation between the distinctive baseline immunological state observed in LTX patients and the adaptive immune responses to vaccines. These findings underscore the distinct immunological profile of lung transplant recipients, providing insights into their immunosuppressed condition and reduced immune responses to vaccines.

Published in

Altered baseline immunological state and impaired immune response to SARS-CoV-2 mRNA vaccination in lung transplant recipients

Hu M, Oliveira APBN, Fang Z et al. · Cell reports. Medicine 2025 · PMID 40187358 · doi:10.1016/j.xcrm.2025.102050

This dataset

Open GSE288562 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 GSE288562_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 PRJNA1218445 and SRA study SRP561124. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40187358) ↗

Study design

14 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 14 sample titles: 14 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

GSM8769949 Batch1_Capture_a, GEX
GSM8769950 Batch1_Capture_a, ADT
GSM8769951 Batch1_Capture_b, GEX
GSM8769952 Batch1_Capture_b, ADT
GSM8769953 Batch1_Capture_c, GEX
GSM8769954 Batch1_Capture_c, ADT
GSM8769955 Batch1_Capture_d, GEX
GSM8769956 Batch1_Capture_d, ADT
GSM8769957 Batch1_Capture_e, GEX
GSM8769958 Batch1_Capture_e, ADT
GSM8769959 Batch2_Capture_f, GEX
GSM8769960 Batch2_Capture_f, ADT
GSM8769961 Batch2_Capture_g, GEX
GSM8769962 Batch2_Capture_g, ADT

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