Open AccessAntibody Fab‐Fc properties outperform titer in predictive models of SIV vaccine‐induced protection
Author(s) -
Pittala Srivamshi,
Bagley Kenneth,
Schwartz Jennifer A,
Brown Eric P,
Weiner Joshua A,
Prado Ilia J,
Zhang Wenlei,
Xu Rong,
OtaSetlik Ayuko,
Pal Ranajit,
Shen Xiaoying,
Beck Charles,
Ferrari Guido,
Lewis George K,
LaBranche Celia C,
Montefiori David C,
Tomaras Georgia D,
Alter Galit,
Roederer Mario,
Fouts Timothy R,
Ackerman Margaret E,
BaileyKellogg Chris
Publication year - 2019
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.15252/msb.20188747
Subject(s) - library science , operations research , computer science , engineering
Characterizing 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‐ CD 4 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.