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Mol Syst Biol. 2019 May 2;15(5):e8747. doi: 10.15252/msb.20188747.

Antibody Fab-Fc properties outperform titer in predictive models of SIV vaccine-induced protection.

Author information

1
Department of Computer Science, Dartmouth, Hanover, NH, USA.
2
Profectus BioSciences, Inc., Baltimore, MD, USA.
3
Thayer School of Engineering, Dartmouth, Hanover, NH, USA.
4
Advanced Bioscience Laboratories, Inc., Rockville, MD, USA.
5
Duke Human Vaccine Institute, Durham, NC, USA.
6
Department of Surgery, Duke University Medical Center, Durham, NC, USA.
7
Institute for Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA.
8
Duke University, Durham, NC, USA.
9
Harvard Medical School, Boston, MA, USA.
10
Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston, MA, USA.
11
Vaccine Research Center, NIAID, NIH, Bethesda, MD, USA.
12
Department of Computer Science, Dartmouth, Hanover, NH, USA cbk@cs.dartmouth.edu.

Abstract

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-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.

KEYWORDS:

HIV ; antibody effector function; biomarker identification; protection modeling; systems serology

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