Evolution of strain coverage by the multicomponent meningococcal serogroup B vaccine (4CMenB) in France.


Journal

Human vaccines & immunotherapeutics
ISSN: 2164-554X
Titre abrégé: Hum Vaccin Immunother
Pays: United States
ID NLM: 101572652

Informations de publication

Date de publication:
02 12 2021
Historique:
pubmed: 4 12 2021
medline: 19 4 2022
entrez: 3 12 2021
Statut: ppublish

Résumé

The 4CMenB, a protein-based vaccine, was licensed in Europe in 2013 against invasive meningococcal disease caused by serogroup B and is currently implemented in several countries although according to different national strategies. Isolate coverage estimation is required as vaccine-targeted antigens may vary among isolates over time. Several phenotypic and genotypic methods have been developed to predict strain coverage by scoring the expression and cross-reactivity of vaccine antigens using the Meningococcal Antigen Typing system (MATS), by the genetic correlation of alleles encoding these antigens and MATS expression data (gMATS) and by the Meningococcal Deduced Vaccine Antigen Reactivity (MenDeVAR). We applied these approaches on meningococcal B isolates in France and compared two epidemiological years, 2013-2014 and 2018-2019. A strong correlation was observed between MATS data that were generated for the year 2013-2014 and the gMATS data extracted from whole genome sequencing. gMATS and MenDeVAR were next used to compare the two years. Using gMATS, the overall coverage was 77.2% (lower limit (LL)-upper limit (UL) 66.7-87.7) and 70.7% (LL-UL 61.5-80.0) for the two years, respectively. The reduction in coverage between the two years is mainly driven by the reduction of alleles exactly matching the vaccine antigens. A high number of unpredictable isolates was observed using the MenDeVAR and was due to lack of MATS information for new or rare alleles in particular for the year 2018-2019. Our data underline the need of continuous surveillance of strain coverage and the importance of generating phenotypic MATS data to update the genetic approaches of prediction.

Identifiants

pubmed: 34856875
doi: 10.1080/21645515.2021.2004055
pmc: PMC8903912
doi:

Substances chimiques

Antigens, Bacterial 0
Meningococcal Vaccines 0
Vaccines, Combined 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5614-5622

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Auteurs

Eva Hong (E)

Institute Pasteur, Invasive Bacterial Infections Unit, Paris, France.

Aude Terrade (A)

Institute Pasteur, Invasive Bacterial Infections Unit, Paris, France.

Rita La Gaetana (R)

GSK, Siena, Italy.

Ala-Eddine Deghmane (AE)

Institute Pasteur, Invasive Bacterial Infections Unit, Paris, France.

Laura Serino (L)

GSK, Siena, Italy.

Muhamed-Kheir Taha (MK)

Institute Pasteur, Invasive Bacterial Infections Unit, Paris, France.

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Classifications MeSH