Use of Antibody Structural Information in Disease Prediction Models Reveals Antigen Specific B Cell Receptor Sequences in Bulk Repertoire Data

Abstract

Convergent antibodies are highly similar antibodies elicited in multiple individuals in response to the same antigen. Convergent antibodies provide insight into shared immunological responses and show great promise as diagnostic biomarkers. They have typically been identified using methods that consider the amino acid sequence of the third complementarity-determining region (CDR3) of immunoglobulin heavy chain (IgH). In this study, we extend the definition of convergent antibodies to use structural information about the three IgH CDR regions (CDR1-3). We benchmark the performance of both definitions of convergence by their ability to predict disease status from bulk IgH sequencing data for two different diseases (HIV infection and food sensitization). We show that using predicted structural information outperforms prior approaches for the prediction of food sensitization status and performs on par for HIV infection status. Additionally, the structurally convergent antibody groups driving HIV prediction are from known HIV binders. Thus, the use of structural information allows for the identification of antigen specific antibody groups from bulk IgH sequencing data.