Broad immune activation underlies shared set point signatures for vaccine responsiveness in healthy individuals and disease activity in patients with lupus

Basic information
Cell
53,201
Sample
20

Technology
10X Genomics
CITE-seq
Omics
scRNA-seq,CITE-seq
Source
PBMCs

Dataset ID
32094927
Platform
Illumina HiSeq 2500
Species
Human
Disease
Healthy/vaccine
Age range
21 - 62
Update date
2024-09-24
Summary

Responses to vaccination and to diseases vary widely across individuals, which may be partly due to baseline immune variations. Identifying such baseline predictors of immune responses and their biological basis is of broad interest, given their potential importance for cancer immunotherapy, disease outcomes, vaccination and infection responses. Here we uncover baseline blood transcriptional signatures predictive of antibody responses to both influenza and yellow fever vaccinations in healthy subjects. These same signatures evaluated at clinical quiescence are correlated with disease activity in patients with systemic lupus erythematosus with plasmablast-associated flares. CITE-seq profiling of 82 surface proteins and transcriptomes of 53,201 single cells from healthy high and low influenza vaccination responders revealed that our signatures reflect the extent of activation in a plasmacytoid dendritic cell–type I IFN–T/B lymphocyte network. Our findings raise the prospect that modulating such immune baseline states may improve vaccine responsiveness and mitigate undesirable autoimmune disease activity.

Overall design

Researchers identified baseline blood transcriptional signatures that predict antibody responses to influenza and yellow fever vaccinations. These signatures, linked to a plasmacytoid dendritic cell–type I IFN–T/B lymphocyte network, also correlate with disease activity in systemic lupus erythematosus. Their findings suggest modulating these immune states could improve vaccine responses and mitigate autoimmune activity.

Contributors

Yuri Kotliarov†, Rachel Sparks†, John S. Tsang✉️

Contact

john.tsang@nih.gov (John S. Tsang)

snRNA-Seq
Sample nameSample titleDiseaseGenderAgeSourceTreatmentTechnologyPlatformOmicsSample IDDataset IDAction
No data available