Comprehensive Data Integration Approach to Assess Immune Responses and Correlates of RTS,S/AS01-Mediated Protection From Malaria Infection in Controlled Human Malaria Infection Trials
RTS,S/AS01 (GSK) is the world’s first malaria vaccine. However, despite initial efficacy of almost 70% over the first 6 months of follow-up, efficacy waned over time. A deeper understanding of the immune features that contribute to RTS,S/AS01-mediated protection could be beneficial for further vacci...
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Frontiers Media S.A.
2021-06-01
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| Series: | Frontiers in Big Data |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fdata.2021.672460/full |
| _version_ | 1819101247244861440 |
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| author | William Chad Young Lindsay N. Carpp Sidhartha Chaudhury Jason A. Regules Elke S. Bergmann-Leitner Christian Ockenhouse Ulrike Wille-Reece Allan C. deCamp Ellis Hughes Celia Mahoney Suresh Pallikkuth Savita Pahwa S. Moses Dennison S. Moses Dennison S. Moses Dennison Sarah V. Mudrak Sarah V. Mudrak Sarah V. Mudrak S. Munir Alam S. Munir Alam S. Munir Alam Kelly E. Seaton Kelly E. Seaton Kelly E. Seaton Rachel L. Spreng Rachel L. Spreng Rachel L. Spreng Jon Fallon Ashlin Michell Fernando Ulloa-Montoya Margherita Coccia Erik Jongert Galit Alter Georgia D. Tomaras Georgia D. Tomaras Georgia D. Tomaras Raphael Gottardo |
| author_facet | William Chad Young Lindsay N. Carpp Sidhartha Chaudhury Jason A. Regules Elke S. Bergmann-Leitner Christian Ockenhouse Ulrike Wille-Reece Allan C. deCamp Ellis Hughes Celia Mahoney Suresh Pallikkuth Savita Pahwa S. Moses Dennison S. Moses Dennison S. Moses Dennison Sarah V. Mudrak Sarah V. Mudrak Sarah V. Mudrak S. Munir Alam S. Munir Alam S. Munir Alam Kelly E. Seaton Kelly E. Seaton Kelly E. Seaton Rachel L. Spreng Rachel L. Spreng Rachel L. Spreng Jon Fallon Ashlin Michell Fernando Ulloa-Montoya Margherita Coccia Erik Jongert Galit Alter Georgia D. Tomaras Georgia D. Tomaras Georgia D. Tomaras Raphael Gottardo |
| author_sort | William Chad Young |
| collection | DOAJ |
| description | RTS,S/AS01 (GSK) is the world’s first malaria vaccine. However, despite initial efficacy of almost 70% over the first 6 months of follow-up, efficacy waned over time. A deeper understanding of the immune features that contribute to RTS,S/AS01-mediated protection could be beneficial for further vaccine development. In two recent controlled human malaria infection (CHMI) trials of the RTS,S/AS01 vaccine in malaria-naïve adults, MAL068 and MAL071, vaccine efficacy against patent parasitemia ranged from 44% to 87% across studies and arms (each study included a standard RTS,S/AS01 arm with three vaccine doses delivered in four-week-intervals, as well as an alternative arm with a modified version of this regimen). In each trial, RTS,S/AS01 immunogenicity was interrogated using a broad range of immunological assays, assessing cellular and humoral immune parameters as well as gene expression. Here, we used a predictive modeling framework to identify immune biomarkers measured at day-of-challenge that could predict sterile protection against malaria infection. Using cross-validation on MAL068 data (either the standard RTS,S/AS01 arm alone, or across both the standard RTS,S/AS01 arm and the alternative arm), top-performing univariate models identified variables related to Fc effector functions and titer of antibodies that bind to the central repeat region (NANP6) of CSP as the most predictive variables; all NANP6-related variables consistently associated with protection. In cross-study prediction analyses of MAL071 outcomes (the standard RTS,S/AS01 arm), top-performing univariate models again identified variables related to Fc effector functions of NANP6-targeting antibodies as highly predictive. We found little benefit–with this dataset–in terms of improved prediction accuracy in bivariate models vs. univariate models. These findings await validation in children living in malaria-endemic regions, and in vaccinees administered a fourth RTS,S/AS01 dose. Our findings support a “quality as well as quantity” hypothesis for RTS,S/AS01-elicited antibodies against NANP6, implying that malaria vaccine clinical trials should assess both titer and Fc effector functions of anti-NANP6 antibodies. |
| first_indexed | 2024-12-22T01:15:38Z |
| format | Article |
| id | doaj.art-3a278326c7e94b59825dbc56352b388d |
| institution | Directory Open Access Journal |
| issn | 2624-909X |
| language | English |
| last_indexed | 2024-12-22T01:15:38Z |
| publishDate | 2021-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Big Data |
| spelling | doaj.art-3a278326c7e94b59825dbc56352b388d2022-12-21T18:43:53ZengFrontiers Media S.A.Frontiers in Big Data2624-909X2021-06-01410.3389/fdata.2021.672460672460Comprehensive Data Integration Approach to Assess Immune Responses and Correlates of RTS,S/AS01-Mediated Protection From Malaria Infection in Controlled Human Malaria Infection TrialsWilliam Chad Young0Lindsay N. Carpp1Sidhartha Chaudhury2Jason A. Regules3Elke S. Bergmann-Leitner4Christian Ockenhouse5Ulrike Wille-Reece6Allan C. deCamp7Ellis Hughes8Celia Mahoney9Suresh Pallikkuth10Savita Pahwa11S. Moses Dennison12S. Moses Dennison13S. Moses Dennison14Sarah V. Mudrak15Sarah V. Mudrak16Sarah V. Mudrak17S. Munir Alam18S. Munir Alam19S. Munir Alam20Kelly E. Seaton21Kelly E. Seaton22Kelly E. Seaton23Rachel L. Spreng24Rachel L. Spreng25Rachel L. Spreng26Jon Fallon27Ashlin Michell28Fernando Ulloa-Montoya29Margherita Coccia30Erik Jongert31Galit Alter32Georgia D. Tomaras33Georgia D. Tomaras34Georgia D. Tomaras35Raphael Gottardo36Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United StatesVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United StatesMalaria Biologics Branch, Walter Reed Army Institute of Research, Silver Spring, MD, United StatesMalaria Biologics Branch, Walter Reed Army Institute of Research, Silver Spring, MD, United StatesMalaria Biologics Branch, Walter Reed Army Institute of Research, Silver Spring, MD, United StatesPATH Malaria Vaccine Initiative, Washington, DC, United StatesPATH Malaria Vaccine Initiative, Washington, DC, United StatesVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United StatesVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United StatesVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United StatesDepartment of Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL, United StatesDepartment of Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL, United StatesCenter for Human Systems Immunology, Duke University, Durham, NC, United StatesDepartments of Surgery, Immunology, and Molecular Genetics and Microbiology, Duke University, Durham, NC, United StatesDuke Human Vaccine Institute, Duke University, Durham, NC, United StatesCenter for Human Systems Immunology, Duke University, Durham, NC, United StatesDepartments of Surgery, Immunology, and Molecular Genetics and Microbiology, Duke University, Durham, NC, United StatesDuke Human Vaccine Institute, Duke University, Durham, NC, United StatesCenter for Human Systems Immunology, Duke University, Durham, NC, United StatesDuke Human Vaccine Institute, Duke University, Durham, NC, United StatesDepartment of Pathology, Duke University, Durham, NC, United StatesCenter for Human Systems Immunology, Duke University, Durham, NC, United StatesDepartments of Surgery, Immunology, and Molecular Genetics and Microbiology, Duke University, Durham, NC, United StatesDuke Human Vaccine Institute, Duke University, Durham, NC, United StatesCenter for Human Systems Immunology, Duke University, Durham, NC, United StatesDepartments of Surgery, Immunology, and Molecular Genetics and Microbiology, Duke University, Durham, NC, United StatesDuke Human Vaccine Institute, Duke University, Durham, NC, United StatesRagon Institute of MGH, MIT, and Harvard, Cambridge, MA, United StatesRagon Institute of MGH, MIT, and Harvard, Cambridge, MA, United States0GSK, Rixensart, Belgium0GSK, Rixensart, Belgium0GSK, Rixensart, BelgiumRagon Institute of MGH, MIT, and Harvard, Cambridge, MA, United StatesCenter for Human Systems Immunology, Duke University, Durham, NC, United StatesDepartments of Surgery, Immunology, and Molecular Genetics and Microbiology, Duke University, Durham, NC, United StatesDuke Human Vaccine Institute, Duke University, Durham, NC, United StatesVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United StatesRTS,S/AS01 (GSK) is the world’s first malaria vaccine. However, despite initial efficacy of almost 70% over the first 6 months of follow-up, efficacy waned over time. A deeper understanding of the immune features that contribute to RTS,S/AS01-mediated protection could be beneficial for further vaccine development. In two recent controlled human malaria infection (CHMI) trials of the RTS,S/AS01 vaccine in malaria-naïve adults, MAL068 and MAL071, vaccine efficacy against patent parasitemia ranged from 44% to 87% across studies and arms (each study included a standard RTS,S/AS01 arm with three vaccine doses delivered in four-week-intervals, as well as an alternative arm with a modified version of this regimen). In each trial, RTS,S/AS01 immunogenicity was interrogated using a broad range of immunological assays, assessing cellular and humoral immune parameters as well as gene expression. Here, we used a predictive modeling framework to identify immune biomarkers measured at day-of-challenge that could predict sterile protection against malaria infection. Using cross-validation on MAL068 data (either the standard RTS,S/AS01 arm alone, or across both the standard RTS,S/AS01 arm and the alternative arm), top-performing univariate models identified variables related to Fc effector functions and titer of antibodies that bind to the central repeat region (NANP6) of CSP as the most predictive variables; all NANP6-related variables consistently associated with protection. In cross-study prediction analyses of MAL071 outcomes (the standard RTS,S/AS01 arm), top-performing univariate models again identified variables related to Fc effector functions of NANP6-targeting antibodies as highly predictive. We found little benefit–with this dataset–in terms of improved prediction accuracy in bivariate models vs. univariate models. These findings await validation in children living in malaria-endemic regions, and in vaccinees administered a fourth RTS,S/AS01 dose. Our findings support a “quality as well as quantity” hypothesis for RTS,S/AS01-elicited antibodies against NANP6, implying that malaria vaccine clinical trials should assess both titer and Fc effector functions of anti-NANP6 antibodies.https://www.frontiersin.org/articles/10.3389/fdata.2021.672460/fullcorrelates of protectionimmune responsemalariavaccinemachine learning |
| spellingShingle | William Chad Young Lindsay N. Carpp Sidhartha Chaudhury Jason A. Regules Elke S. Bergmann-Leitner Christian Ockenhouse Ulrike Wille-Reece Allan C. deCamp Ellis Hughes Celia Mahoney Suresh Pallikkuth Savita Pahwa S. Moses Dennison S. Moses Dennison S. Moses Dennison Sarah V. Mudrak Sarah V. Mudrak Sarah V. Mudrak S. Munir Alam S. Munir Alam S. Munir Alam Kelly E. Seaton Kelly E. Seaton Kelly E. Seaton Rachel L. Spreng Rachel L. Spreng Rachel L. Spreng Jon Fallon Ashlin Michell Fernando Ulloa-Montoya Margherita Coccia Erik Jongert Galit Alter Georgia D. Tomaras Georgia D. Tomaras Georgia D. Tomaras Raphael Gottardo Comprehensive Data Integration Approach to Assess Immune Responses and Correlates of RTS,S/AS01-Mediated Protection From Malaria Infection in Controlled Human Malaria Infection Trials Frontiers in Big Data correlates of protection immune response malaria vaccine machine learning |
| title | Comprehensive Data Integration Approach to Assess Immune Responses and Correlates of RTS,S/AS01-Mediated Protection From Malaria Infection in Controlled Human Malaria Infection Trials |
| title_full | Comprehensive Data Integration Approach to Assess Immune Responses and Correlates of RTS,S/AS01-Mediated Protection From Malaria Infection in Controlled Human Malaria Infection Trials |
| title_fullStr | Comprehensive Data Integration Approach to Assess Immune Responses and Correlates of RTS,S/AS01-Mediated Protection From Malaria Infection in Controlled Human Malaria Infection Trials |
| title_full_unstemmed | Comprehensive Data Integration Approach to Assess Immune Responses and Correlates of RTS,S/AS01-Mediated Protection From Malaria Infection in Controlled Human Malaria Infection Trials |
| title_short | Comprehensive Data Integration Approach to Assess Immune Responses and Correlates of RTS,S/AS01-Mediated Protection From Malaria Infection in Controlled Human Malaria Infection Trials |
| title_sort | comprehensive data integration approach to assess immune responses and correlates of rts s as01 mediated protection from malaria infection in controlled human malaria infection trials |
| topic | correlates of protection immune response malaria vaccine machine learning |
| url | https://www.frontiersin.org/articles/10.3389/fdata.2021.672460/full |
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