Humoral Fingerprinting of Immune Responses: 'Super-Resolution', High-Dimensional Serology

Abstract

In a recent study, Chung et al. report the development of a high-dimensional approach to assess humoral responses to immune perturbation that goes beyond antibody neutralization and titers. This approach enables the identification of potentially novel correlates and mechanisms of protective immunity to HIV vaccination, thus offering a glimpse of how dense phenotyping of serological responses coupled with bioinformatics analysis could lead to much-sought-after markers of protective vaccination responses.

Figure 1. Constructing and comparing correlation networks across groups of human subjects

Here nodes denote antibody features (e.g., binding affinity to certain antigens) and an edge between a pair of nodes denotes statistically significant correlation between the two features among individuals in a particular group (depicted here are good vs. poor responders to vaccination.) The two correlation networks depicted here have both shared and distinct edges, such as the edge between features A and B where a significant correlation can be detected in the good responder group (blue subjects), but not in the poor responder group (red subjects). The presence of significant correlation (or connection) between features A and B as well as between C and D in the good-responder network bridges the green and orange subnetworks, which are disconnected in the poor-responder network. Since different sources of noise can contribute to correlation strength among variables, quantitative analyses are needed to formally assess whether an observed difference in correlation between two nodes is statistically significant (see refs. [5,6] for further details and references to analysis approaches.)