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Characterization of rubella-specific humoral immunity following two doses of MMR vaccine using proteome microarray technology

INTRODUCTION//BACKGROUND: The lack of standardization of the currently used commercial anti-rubella IgG antibody assays leads to frequent misinterpretation of results for samples with low/equivocal antibody concentration. The use of alternative approaches in rubella serology could add new informatio...

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Detalles Bibliográficos
Autores principales: Haralambieva, Iana H., Gibson, Michael J., Kennedy, Richard B., Ovsyannikova, Inna G., Warner, Nathaniel D., Grill, Diane E., Poland, Gregory A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690594/
https://www.ncbi.nlm.nih.gov/pubmed/29145521
http://dx.doi.org/10.1371/journal.pone.0188149
Descripción
Sumario:INTRODUCTION//BACKGROUND: The lack of standardization of the currently used commercial anti-rubella IgG antibody assays leads to frequent misinterpretation of results for samples with low/equivocal antibody concentration. The use of alternative approaches in rubella serology could add new information leading to a fuller understanding of rubella protective immunity and neutralizing antibody response after vaccination. METHODS: We applied microarray technology to measure antibodies to all rubella virus proteins in 75 high and 75 low rubella virus-specific antibody responders after two MMR vaccine doses. These data were used in multivariate penalized logistic regression modeling of rubella-specific neutralizing antibody response after vaccination. RESULTS: We measured antibodies to all rubella virus structural proteins (i.e., the glycoproteins E1 and E2 and the capsid C protein) and to the non-structural protein P150. Antibody levels to each of these proteins were: correlated with the neutralizing antibody titer (p<0.006); demonstrated differences between the high and the low antibody responder groups (p<0.008); and were components of the model associated with/predictive of vaccine-induced rubella virus-specific neutralizing antibody titers (misclassification error = 0.2). CONCLUSION: Our study supports the use of this new technology, as well as the use of antibody profiles/patterns (rather than single antibody measures) as biomarkers of neutralizing antibody response and correlates of protective immunity in rubella virus serology.