SciLifeLab
Browse

File(s) not publicly available

Reason: The data contains transcriptomic and personal data that cannot be completely anonymized.

Modulation of innate immune response to mRNA vaccination after SARS-CoV-2 infection or sequential vaccination in humans

dataset
posted on 2024-05-17, 07:47 authored by Rodrigo ArcoverdeRodrigo Arcoverde, Fredrika HellgrenFredrika Hellgren, Gustav Joas

### General information


This is a dataset record for the research paper "Modulation of innate immune response to mRNA vaccination after SARS-CoV-2 infection or sequential vaccination in humans" led by professor Karin Loré (Karolinska Institutet) and her research group.


Author(s): Hellgren F, Rosdahl A, Arcoverde Cerveira R, Lenart K, Ols S, Gwon Y-D, Joas G, Kurt S, Delis A-M, Evander M, Normark J, Ahlm C, Forsell M, Cajander S, Loré K


Corresponding author: Karin Loré, Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institutet, Visionsgatan 4, BioClinicum J7:30, Karolinska University Hospital, 171 64 Stockholm, Sweden.

Contact e-mail: karin.lore@ki.se

Github code repo: https://github.com/rodrigarc/orebro_study/

DOI: https://doi.org/10.1172/jci.insight.175401

This readme file was last updated: 2024-04-22


The dataset is available upon reasonable request through the corresponding author.


### Cohort description


The repository contains metadata for the 30 study participants recruited among health-care workers at the University hospital of Örebro, Sweden. At the start of the study, 14 individuals had a previous Covid-19 infection and 16 were infection naïve. Among the infection naïve group, 75% were female (12 out of 16 participants), with a mean age of 41 years, ranging from 25 to 66 years. In the group with previous Covid-19 infection, 71.4% were female (10 out of 14 participants), with a mean age of 44.6 years, spanning from 29 to 63 years. Study participants were sampled adjacent to each vaccine dose according to the schedule shown in Fig. 1A.


For a more detailed overview of the baseline characteristics please see Table 1 attached in the manuscript.


### Dataset description


Antibody titers measured by ELISA, Percentages of Immunophenotyping of studied cell subsets, and serum protein measurements were compiled into Excel sheets and fully anonymized. This data was provided as supplemental material with the original article.

RNA-sequencing data: RNA-seq analysis of 99 samples was performed using Illumina sequencing. Preprocessing of FASTQ raw reads was done with the nf-core/rnaseq v3.8 pipeline, with results saved in TSV format. The human genome was appended with vaccine and SARS-CoV-2 related genes prior to read alignment using STAR and gene expression quantification with Salmon.


Keywords: mRNA vaccines, innate immunity, Covid-19, coronavirus, vaccine

Funding

This study has been funded by Knut and Alice Wallenberg Foundation, the Swedish Research Council (Vetenskapsrådet), the Regional Research Council Mid-Sweden, and graduate student fellowships from Karolinska Institutet. None of the funders had influence on the study design, data collection, analysis and interpretation, or on the writing of the article. We thank all study participants as well as the research staff at USÖ. In particular, we thank the research nurses at Clinical Research Center, USÖ, for their work in contributing to the study and data collection and the staff at the Clinical Epidemiology and Biostatistics Unit (Research Laboratory), USÖ, for their contributions to sample preparation and analysis. We thank Mireia Rocavert Barranco, Dillon Lim, and Kristoffer Johansson for contributions to sample handling and ELISA at Karolinska Institutet. We thank the SciLifeLab plasma proteomics core facilities in Stockholm and Uppsala for assistance with performing cytokine Luminex/OLINK assays and Spike MSD assays, respectively. We thank the Bioinformatics and Expression core facility at Karolinska Institute for sample preparation and sequencing in the transcriptomic analyses. Computation, data handling, and storage of RNA-Seq data were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) partially funded by the Swedish Research Council through grant agreements no. 2022-06725 and no. 2018-05973.

History

Publisher

Karolinska Institutet

Access request email

karin.lore@ki.se

Contact email

karin.lore@ki.se

Usage metrics

    Karin Loré research group

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC