(6ag) Discovery of Disease-Specific Antibody Biomarkers and Their Targets

Discovery of biologic molecules specific to a diseased state, or biomarkers, can lead to diagnostic development, therapeutic target identification, and improved understanding of disease pathogenesis.  Antibodies remain an attractive class of biomarkers given their amplification by the immune system, stability, and current clinical use.  While the antibody repertoire represents a rich source for biomarker discovery, it has been difficult to impartially identify which molecules from this repertoire are associated with disease.  This work demonstrates three molecular discovery processes centered on the utility of bacterial-displayed peptide libraries and fluorescence activated cell sorting (FACS) for identifying novel antibody biomarkers.  We applied these methods to identify candidate molecular diagnostics for pre-eclampsia (PE), a condition with unknown etiology that affects 5-8% of pregnancies.  Previously characterized autoantibodies that bind the angiotensin II type 1 (AT1) receptor in PE patients [1][2] are difficult to detect, vary in prevalence amongst studies, and most importantly, lack specificity.  Thus, we sought to identify additional PE-specific antibody biomarkers.

Applying three quantitative screening strategies against a set of PE and healthy outcome pregnancies (HOP) identified unique disease-specific peptides from a 15 amino acid peptide library.  With a two-color screening method, we used antibody fractions enriched from plasma to isolate significantly PE cross-reactive and specific peptides distinct from the AT1 receptor epitope.  We used a panel of these antibody-detecting peptides to train and validate an Adaptive Boosting classification algorithm that achieved 80% diagnostic accuracy [3].  In a second screen, the library underwent sequential enrichment for PE antibody (immunoglobulin G) binding followed by removal of HOP antibody binding peptides against unprocessed, diluted plasma.  This screen more closely replicated the native environment for the antibody binding interaction and yielded a strong consensus motif.  Directed evolution expanded this motif for which BLAST searches identified a number of environmental antigens and human proteins that shared similarities.  Importantly, by evaluating antibody binding activity of bacterial-displayed 15-mer fragments from the strongest candidates, we linked this motif to a region of a common viral antigen (VA) and a human G protein-coupled receptor (hGPCRa).  Furthermore, we verified that the synthesized VA fragment efficiently blocked antibody binding to the hGPCRa fragment and to HEK293T cells expressing the full length protein.  Thus, this method enabled unbiased identification of a disease-specific antibody and characterization of its targets.  In a third method, we combined library screening with next-generation sequencing to profile the antibody repertoire of four individual PE patients and four HOP and identify motifs present amongst these PE. 

This work demonstrates that we can now probe the antibody repertoire using unbiased screening of bacterial-displayed peptide libraries to identify new markers of disease.  These disease-specific antibody-detecting peptide reagents can be used for molecular diagnostics and/or characterizing antibody target(s), potentially elucidating novel therapeutic targets.  Building upon this work, we can investigate how the antibody repertoire changes with age or after exposure to a particular virus or environmental factor.

[1]  Wallukat, G. et al. Patients with Preeclampsia Develop Agonistic Autoantibodies against the Angiotensin AT1 Receptor. The Journal of Clinical Investigation 103,945–952 (1999).

[2] Zhou, C. C. et al. Angiotensin Receptor Agonistic Autoantibodies Induce Pre-eclampsia in Pregnant Mice. Nature Medicine 14,855–862 (2008).

[3] Elliott, S.E. et al. Characterization of Antibody Specificities Associated with Preeclampsia. Hypertension 63,1086-1093 (2014).