Publication
Title
Transcriptomic profiling of different responder types in adults after a Priorix® vaccination
Author
Abstract
Thanks to the recommendation of a combined Measles/Mumps/Rubella (MMR) vaccine, like Priorix®, these childhood diseases are less common now. This is beneficial to limit the spread of these diseases and work towards their elimination. However, the measles, mumps and rubella antibody titers show a large variability in short- and long-term immunity. The recent outbreaks worldwide of measles and mumps and previous studies, which mostly focused on only one of the three virus responses, illustrate that there is a clear need for better understanding the immune responses after vaccination. Our healthy cohort was already primed with the MMR antigens in their childhood. In this study, the adult volunteers received one Priorix® vaccine dose at day 0. First, we defined 4 different groups of responders, based on their antibody titers’ evolution over 4 time points (Day 0, 21, 150 and 365). This showed a high variability within and between individuals. Second, we determined transcriptome profiles using 3′mRNA sequencing at day 0, 3 and 7. Using two analytical approaches, “one response group per time point” and “a time comparison per response group”, we correlated the short-term gene expression profiles to the different response groups. In general, the list of differentially expressed genes is limited, however, most of them are clearly immune-related and upregulated at day 3 and 7, compared to the baseline day 0. Depending on the specific response group there are overlapping signatures for two of the three viruses. Antibody titers and transcriptomics data showed that an additional Priorix vaccination does not facilitate an equal immune response against the 3 viruses or among different vaccine recipients.
Language
English
Source (journal)
Vaccine / International Society for Vaccines. - Amsterdam
Publication
Amsterdam : 2020
ISSN
0264-410X
DOI
10.1016/J.VACCINE.2020.03.004
Volume/pages
38 :16 (2020) , p. 3218-3226
ISI
000525317600008
Pubmed ID
32165045
Full text (Publisher's DOI)
Full text (open access)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
GENOMED - Genomics in Medicine.
Predicting Immune responses by Modeling immunoSequencing data (PIMS).
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 07.04.2020
Last edited 17.12.2024
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