Patterns of Autoantibody Expression in Multiple Sclerosis and Systemic Lupus Erythematosus Unveiled Through the Development of an Autoantigen Discovery Technology

Abstract

The human body contains over 290 quintillion (1018) antibodies that circulate the blood and express extensive diversity in binding pathogens, allergens, or even self-proteins. Characterizing the antibody repertoire is useful for understanding pathogen response, cancer development, and autoimmune diseases. Current technologies have enabled the characterization of a subset of antibodies expressed in health and disease; however, continued technological advances may enable a more complete characterization of human antibody repertoires and an understanding of their contributions to pathogen protection, cancer surveillance, and autoimmune disease development. In this work, I describe the development of The Antigenome Platform for improved antibody discovery. This Platform is a high-throughput assay comprised of large-fragment cDNA libraries, a phage-display and serum antibody screening technology, and a robust bioinformatics analysis pipeline. The work described herein extends prior methodology through the development of a rigorous procedure for cDNA library preparation that allows the display of in-frame human cDNA fragments that are up to 250 amino acids. I applied this technology in the context of autoimmune diseases; therefore, human transcripts were used for cDNA library generation. Moreover, this platform assesses antibody binding to targets across approximately 90% of the human genome, allowing for an agnostic and robust evaluation of autoantibodies.The Antigenome Platform was applied to the study of two autoimmune diseases: Multiple sclerosis (MS) and Systemic Lupus Erythematosus (SLE). MS is a debilitating autoimmune disease of the central nervous system (CNS), which is characterized by demyelination and axonal injury and is often preceded by a demyelinating event called clinically isolated syndrome (CIS). Despite the importance of B cells and autoantibodies in MS pathology, their target specificities remain largely unknown. Therefore, I employed the Antigenome Platform for an agnostic and comprehensive evaluation of autoantibodies in MS. Toward this goal, I assayed serum samples from both placebo and treated MS patients enrolled in the REFLEX clinical trial, which assessed the effects of interferon beta-1a (Rebif®) on the conversion from CIS to MS. Serum autoantibodies from MS patients significantly and reproducibly enriched for known and novel protein targets; 166 targets were selected by >10% of patients’ sera. Further, 10 autoantibody biomarkers predicted conversion from CIS to MS, and 17 predicted patient responses to interferon beta-1a therapy. These findings indicate the existence of widespread autoantibody production in MS and provide novel biomarkers for continued study and prediction of disease progression. Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by a wide array of clinical and immunologic features, including abundant production of autoantibodies, especially to components of the cell nucleus. The marked heterogeneity among SLE patients hinders research, our understanding of the disease, therapeutic development, and clinical trial success. As a result, there is great interest in biomarkers for distinguishing subtypes or clusters of SLE patients. Previous studies have identified four clusters of SLE patients based on patterns of autoantibody expression to 10-20 common target antigens. Since SLE patients are known to express autoantibodies to a much larger number of self-antigens (roughly 200 targets have been identified), I sought to further define SLE clusters with more comprehensive autoantibody profiles to improve and understand the molecular basis of clustering. The work described herein focused on serum samples from four SLE patient clusters defined by the expression of 13 autoantibodies. In a prior analysis, Cluster 1 patients exhibited positivity for antibodies to Ro60/Ro52/La; Cluster 2 patients exhibited positivity for antibodies to nucleosome/SmRNP/DNA/RNPA; Cluster 3 patients exhibited positivity for antibodies to beta2GP1/aCL-IgG/IgM; and Cluster 4 patients were negative for all 13 tested autoantibodies. Since it is a challenge to cluster some patients according to these criteria (i.e., some patients exhibit autoantibody profiles matching more than one cluster) and there are no known biomarkers for Cluster 4 patients, I employed the Antigenome Platform for the discovery of additional autoantibodies associated with each cluster. I identified patterns of 88, 49, 10, and 24 autoantibodies associated with four SLE clusters, which includes autoantibodies for the subgroup previously defined by a lack of common SLE autoantibodies. While clinicians and researchers generally focus on determining the specificities and function of anti-nuclear antibodies in SLE, my findings of anti-cytoplasmic antibodies call attention to the potential importance of cytoplasmic antigens in SLE disease. I further report autoantibodies targeting the kidney-enhanced cell surface protein, BCAM, in a cluster of patients associated with nephritis. By discovering new autoantigens, this study provides the basis for novel serological assays to improve understanding of autoantibody clustering and its impact on disease expression and outcome. The work described herein collectively provides a methodology for improved antigen target discovery that can be applied to the study of autoimmune disease, cancer, viral infection, and other applications. I have applied this technology to study the autoimmune diseases MS and SLE and have identified several autoantibody targets that shed light on each disease and provide potential biomarkers for precision-medicine approaches.