Publication
Title
Transcriptome profiling in blood before and after hepatitis B vaccination shows significant differences in gene expression between responders and non-responders
Author
Abstract
Introduction: As the hepatitis B virus is widely spread and responsible for considerable morbidity and mortality, WHO recommends vaccination from infancy to reduce acute infection and chronic carriers. However, current subunit vaccines are not 100% efficacious and leave 5-10% of recipients unprotected. Methods: To evaluate immune responses after Engerix-B vaccination, we determined, using mRNA-sequencing, whole blood early gene expression signatures before, at day 3 and day 7 after the first dose and correlated this with the resulting antibody titer after two vaccine doses. Results: Our results indicate that immune related genes are differentially expressed in responders mostly at day 3 and in non-responders mostly at day 7. The most remarkable difference between responders and non-responders were the differentially expressed genes before vaccination. The granulin precursor gene (GRN) was significantly downregulated in responders while upregulated in non-responders at day 0. Furthermore, absolute granulocytes numbers were significantly higher in non-responders at day 0. Conclusion: The non-responders already showed an activated state of the immune system before vaccination. Furthermore, after vaccination, they exhibited a delayed and partial immune response in comparison to the responders. Our data may indicate that the baseline and untriggered immune system can influence the response upon hepatitis B vaccination. (C) 2018 Elsevier Ltd. All rights reserved.
Language
English
Source (journal)
Vaccine / International Society for Vaccines. - Amsterdam
Publication
Amsterdam : 2018
ISSN
0264-410X
DOI
10.1016/J.VACCINE.2018.09.001
Volume/pages
36 :42 (2018) , p. 6282-6289
ISI
000447479200005
Pubmed ID
30205979
Full text (Publisher's DOI)
Full text (open access)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
Predicting Immune responses by Modeling immunoSequencing data (PIMS).
Development of immunoinformatics tools for the discovery of T-cell epitope recognition rules.
Translational and Transdisciplinary research in Modeling Infectious Diseases (TransMID).
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 09.11.2018
Last edited 02.10.2024
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