Limited Biomarker Potential for IgG Autoantibodies Reactive to Linear Epitopes in Systemic Lupus Erythematosus or Spondyloarthropathy.

Autor:	Bashar SJ; Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA., Zheng Z; Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA.; Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA., Mergaert AM; Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA.; Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA., Adyniec RR; Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA., Gupta S; Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA., Amjadi MF; Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA., McCoy SS; Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA., Newton MA; Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA.; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53726, USA., Shelef MA; Department of Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA.; William S. Middleton Memorial Veterans Hospital, Madison, WI 53705, USA.
Jazyk:	angličtina
Zdroj:	Antibodies (Basel, Switzerland) [Antibodies (Basel)] 2024 Oct 12; Vol. 13 (4). Date of Electronic Publication: 2024 Oct 12.
DOI:	10.3390/antib13040087
Abstrakt:	Background: Autoantibodies are commonly used as biomarkers in autoimmune diseases, but there are limitations. For example, autoantibody biomarkers have poor sensitivity or specificity in systemic lupus erythematosus and do not exist in the spondyloarthropathies, impairing diagnosis and treatment. While autoantibodies suitable for strong biomarkers may not exist in these conditions, another possibility is that technology has limited their discovery. The purpose of this study was to use a novel high-density peptide array that enables the evaluation of IgG binding to every possible linear antigen in the entire human peptidome, as well as a novel machine learning approach that incorporates ELISA validation predictability in order to discover autoantibodies that could be developed into sensitive and specific markers of lupus or spondyloarthropathy. Methods: We used a peptide array containing the human peptidome, several viral peptidomes, and key post-translational modifications (6 million peptides) to quantify IgG binding in lupus, spondyloarthropathy, rheumatoid arthritis, Sjögren's disease, and control sera. Using ELISA data for 70 peptides, we performed a random forest analysis that evaluated multiple array features to predict which peptides might be good biomarkers, as confirmed by ELISA. We validated the peptide prediction methodology in rheumatoid arthritis and COVID-19, conditions for which the antibody repertoire is well-understood, and then evaluated IgG binding by ELISA to peptides that we predicted would be highly bound specifically in lupus or spondyloarthropathy. Results: Our methodology performed well in validation studies, but peptides predicted to be highly and specifically bound in lupus or spondyloarthropathy could not be confirmed by ELISA. Conclusions: In a comprehensive evaluation of the entire human peptidome, highly sensitive and specific IgG autoantibodies were not identified in lupus or spondyloarthropathy. Thus, the pathogenesis of lupus and spondyloarthropathy may not depend upon unique autoantigens, and other types of molecules should be sought as optimal biomarkers in these conditions.
Databáze:	MEDLINE
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