Abstract

Identification of the antigens associated with antibodies is vital to understanding immune responses in the context of infection, autoimmunity, and cancer. Discovering antigens at a proteome scale could enable broader identification of antigens that are responsible for generating an immune response or driving a disease state. Although targeted tests for known antigens can be straightforward, discovering antigens at a proteome scale using protein and peptide arrays is time consuming and expensive. We leverage Serum Epitope Repertoire Analysis (SERA), an assay based on a random bacterial display peptide library coupled with next generation sequencing (NGS), to power the development of Protein-based Immunome Wide Association Study (PIWAS). PIWAS uses proteome-based signals to discover candidate antibody-antigen epitopes that are significantly elevated in a subset of cases compared to controls. After demonstrating statistical power relative to the magnitude and prevalence of effect in synthetic data, we apply PIWAS to systemic lupus erythematosus (SLE, n=31) and observe known autoantigens, Smith and Ribosomal protein P, within the 22 highest scoring candidate protein antigens across the entire human proteome. We validate the magnitude and location of the SLE specific signal against the Smith family of proteins using a cohort of patients who are positive by predicate anti-Sm tests. To test the generalizability of the method in an additional autoimmune disease, we identified and validated autoantigenic signals to SSB, CENPA, and keratin proteins in a cohort of individuals with Sjogren’s syndrome (n=91). Collectively, these results suggest that PIWAS provides a powerful new tool to discover disease-associated serological antigens within any known proteome.

Highlights

  • Antibodies present in human specimens serve as the primary analyte and disease biomarker for a broad group of infectious and autoimmune diseases

  • Both systemic lupus erythematosus (SLE) and anti-Smith cohorts yielded Proteinbased Immunome Wide Association Study (PIWAS) value distributions with longer tails when analyzed against the entire human proteome when compared to those of healthy controls (Figures 2C)

  • We demonstrate the utility of a general and scalable methodology to identify serological antigens within arbitrary proteomes using Protein-based Immunome Wide Association Studies (PIWAS)

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Summary

Introduction

Antibodies present in human specimens serve as the primary analyte and disease biomarker for a broad group of infectious (bacterial, viral, fungal, and parasitic) and autoimmune diseases. Hundreds of distinct antibody-detecting immunoassays have been developed to diagnose human disease using blood derived specimens. The development of high-throughput sequencing technologies has enabled sequencing of numerous proteomes from diverse organisms. Methods for antigen discovery within any given proteome remain relatively low throughput. The serological analysis of expression cDNA libraries (SEREX) method has been applied frequently to identify a variety of antigens, but high-quality cDNA library construction remains technically challenging and time consuming [1,2,3]. Entire human and pathogen derived proteomes can be segmented into overlapping peptides, and displayed on phage or solid-phase arrays and probed with serum [4,5,6]. The limited molecular diversity of array based libraries can reduce antibody detection sensitivity and hinder successful mapping of peptide motifs to specific proteome antigens [7]. A general, scalable approach to identify serological antigens within arbitrary proteomes is needed

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