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RNAseq data of CD20+CD38++ and other B cell subsets sorted from healthy donors

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posted on 2020-02-23, 05:18 authored by Andrew Martins, Lela Kardava, Susan Moir, John TsangJohn Tsang
The purpose of this experiment was to determine the transcriptional differences between CD19+CD20+CD38++ B cells and the total CD19+CD20+ B cell fraction in healthy human donors.

This data can be used to reproduce the results reported in Extended Data Figure 7 for the associated article.

This item is a part of the collection: https://doi.org/10.35092/yhjc.c.4753772

If you use our data (including CITE-seq data) or code for your work please cite the following publication:
Kotliarov, Y., Sparks, R. et al. Broad immune activation underlies shared set point signatures for vaccine responsiveness in healthy individuals and disease activity in patients with lupus. Nat. Med. DOI: https://doi.org/10.1038/s41591-020-0769-8 (2020)

Abstract
Responses to vaccination and to diseases vary widely across individuals, which may be partly due to baseline immune variations. Identifying such baseline predictors and their biological basis are 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 systemic lupus erythematosus patients 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 activities.

General contact: John Tsang (john.tsang@nih.gov)
Questions about software/code: Yuri Kotliarov (yuri.kotliarov@nih.gov)

Funding

Funded by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases (NIAID) and NIH Institutes supporting the Center for Human Immunology (CHI), National Institutes of Health, Bethesda, MD, USA

1ZIAAI001152 (NIAID)

1ZICAI001226 (NIH CHI)

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  • AI - National Institute of Allergy and Infectious Diseases (NIAID)

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  • Yes

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I confirm there is no human identifiable information in this dataset.

  • Yes

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