Sir’TAuria Hilliard
Research Subjects
Research Interests
Sir’TAuria Hilliard has a total of 22 co-authors. Here are the top co-authors by number of shared publications:
- Aaron W. Deal
Center for Human Systems Immunology
1 shared publication - Alexander J. Carnacchi
Center for Human Systems Immunology
1 shared publication - C. Richter King
Center for Vaccine Innovation and Access, PATH, Washington, DC, USA
1 shared publication - Elizabeth Feeney
Center for Human Systems Immunology
1 shared publication - Erik Jongert
GSK, Rixensart, Belgium
1 shared publication - Georgia D. Tomaras
Departments of Surgery and Integrative Immunobiology, Center for Human Systems Immunology, Duke University, Durham, USA
1 shared publication
Latest Publications
- Open Access
- 8 October 2024
- Published by American Society for Clinical Investigation in JCI Insight
- Vol. 9 (19)
Identification of RTS,S/AS01 vaccine–induced humoral biomarkers predictive of protection against controlled human malaria infection
BACKGROUND: The mechanism(s) responsible for the efficacy of WHO-recommended malaria vaccine RTS,S/AS01 are not completely understood. We previously identified RTS,S vaccine–induced Plasmodium falciparum circumsporozoite protein–specific (PfCSP-specific) antibody measures associated with protection from controlled human malaria infection (CHMI). Here, we tested the protection-predicting capability of these measures in independent CHMI studies. METHODS: Vaccine-induced total serum antibody (immunoglobulins, Igs) and subclass antibody (IgG1 and IgG3) responses were measured by biolayer interferometry and the binding antibody multiplex assay, respectively. Immune responses were compared between protected and nonprotected vaccinees using univariate and multivariate logistic regression. RESULTS: Blinded prediction analysis showed that 5 antibody binding measures, including magnitude-avidity composite of serum Ig specific for PfCSP, major NANP repeats and N-terminal junction, and PfCSP- and NANP-specific IgG1 subclass magnitude, had good prediction accuracy (area under the receiver operating characteristic curves [ROC AUC] > 0.7) in at least 1 trial. Furthermore, univariate analysis showed a significant association between these antibody measures and protection (odds ratios 2.6–3.1). Multivariate modeling of combined data from 3 RTS,S CHMI trials identified the combination of IgG1 NANP binding magnitude plus serum NANP and N-junction Ig binding magnitude-avidity composite as the best predictor of protection (95% confidence interval for ROC AUC 0.693–0.834). CONCLUSION: These results reinforce our previous findings and provide a tool for predicting protection in future trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT03162614, NCT03824236, NCT01366534, and NCT01857869. FUNDING: This study was supported by Bill & Melinda Gates Foundation’s Global Health-Discovery Collaboratory grants (INV-008612 and INV-043419) to GDT.
- 8 October 2024
- Published by American Society for Clinical Investigation in JCI Insight
- Vol. 9 (19)
Open AccessIdentification of RTS,S/AS01 vaccine–induced humoral biomarkers predictive of protection against controlled human malaria infection
BACKGROUND: The mechanism(s) responsible for the efficacy of WHO-recommended malaria vaccine RTS,S/AS01 are not completely understood. We previously identified RTS,S vaccine–induced Plasmodium falciparum circumsporozoite protein–specific (PfCSP-specific) antibody measures associated with protection from controlled human malaria infection (CHMI). Here, we tested the protection-predicting capability of these measures in independent CHMI studies. METHODS: Vaccine-induced total serum antibody (immunoglobulins, Igs) and subclass antibody (IgG1 and IgG3) responses were measured by biolayer interferometry and the binding antibody multiplex assay, respectively. Immune responses were compared between protected and nonprotected vaccinees using univariate and multivariate logistic regression. RESULTS: Blinded prediction analysis showed that 5 antibody binding measures, including magnitude-avidity composite of serum Ig specific for PfCSP, major NANP repeats and N-terminal junction, and PfCSP- and NANP-specific IgG1 subclass magnitude, had good prediction accuracy (area under the receiver operating characteristic curves [ROC AUC] > 0.7) in at least 1 trial. Furthermore, univariate analysis showed a significant association between these antibody measures and protection (odds ratios 2.6–3.1). Multivariate modeling of combined data from 3 RTS,S CHMI trials identified the combination of IgG1 NANP binding magnitude plus serum NANP and N-junction Ig binding magnitude-avidity composite as the best predictor of protection (95% confidence interval for ROC AUC 0.693–0.834). CONCLUSION: These results reinforce our previous findings and provide a tool for predicting protection in future trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT03162614, NCT03824236, NCT01366534, and NCT01857869. FUNDING: This study was supported by Bill & Melinda Gates Foundation’s Global Health-Discovery Collaboratory grants (INV-008612 and INV-043419) to GDT.