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dc.contributor.authorPittala, S.
dc.contributor.authorBagley, K.
dc.contributor.authorSchwartz, J.A.
dc.date.accessioned2019-09-13T14:49:28Z
dc.date.available2019-09-13T14:49:28Z
dc.date.issued2019
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85065559828&doi=10.15252%2fmsb.20188747&partnerID=40&md5=067c7d5d4ec264dc04a1f07f5e5780ad
dc.identifier.urihttp://hdl.handle.net/10713/10554
dc.description.abstractCharacterizing the antigen-binding and innate immune-recruiting properties of the humoral response offers the chance to obtain deeper insights into mechanisms of protection than revealed by measuring only overall antibody titer. Here, a high-throughput, multiplexed Fab-Fc Array was employed to profile rhesus macaques vaccinated with a gp120-CD4 fusion protein in combination with different genetically encoded adjuvants, and subsequently subjected to multiple heterologous simian immunodeficiency virus (SIV) challenges. Systems analyses modeling protection and adjuvant differences using Fab-Fc Array measurements revealed a set of correlates yielding strong and robust predictive performance, while models based on measurements of response magnitude alone exhibited significantly inferior performance. At the same time, rendering Fab-Fc measurements mathematically independent of titer had relatively little impact on predictive performance. Similar analyses for a distinct SIV vaccine study also showed that Fab-Fc measurements performed significantly better than titer. These results suggest that predictive modeling with measurements of antibody properties can provide detailed correlates with robust predictive power, suggest directions for vaccine improvement, and potentially enable discovery of mechanistic associations. Copyright 2019 The Authors. Published under the terms of the CC BY 4.0 licenseen_US
dc.description.sponsorshipThese studies were supported by the Bill and Melinda Gates Foundation (OPP1032817, OPP1146996, and OPP1114729) and the HHS|National Institutes of Health (NIH) National Institute of Allergy and Infectious Disease and National Institute of General Medical Sciences (R37 AI080289, R01 AI102291, R01 AI131975, P01 AI120756, R01 AI102660, R44 AI074334, R44 AI102702, and R44 AI091567), and HHSN272201100016C.en_US
dc.description.urihttps://doi.org/10.15252/msb.20188747en_US
dc.language.isoen-USen_US
dc.publisherBlackwell Publishing Ltden_US
dc.relation.ispartofMolecular Systems Biology
dc.subjectantibody effector functionen_US
dc.subjectbiomarker identificationen_US
dc.subjectHIVen_US
dc.subjectprotection modelingen_US
dc.subjectsystems serologyen_US
dc.titleAntibody Fab-Fc properties outperform titer in predictive models of SIV vaccine-induced protectionen_US
dc.typeArticleen_US
dc.identifier.doi10.15252/msb.20188747
dc.identifier.pmid31048360


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