Background/Purpose: Systemic sclerosis (SSc) is a connective tissue disease (CTD) characterized by fibrosis, vascular complications, and inflammation affecting both skin and internal organs. Diagnosis of SSc is difficult due to the complexity of manifestations and overlap with other autoimmune (AI) diseases. Clinical classification criteria including SSc-specific autoantibodies have been developed, but disease manifestations are often advanced once patients fulfill these criteria. In addition, heterogeneity in clinical presentation, internal organ involvement, and rate of disease progression make counseling and management of each individual patient challenging. The ImmunoSignature(IMS) Technology has shown promise as a new diagnostic platform for both chronic and infectious diseases. The goal of this study was to identify specific antibody signatures that differentiate SSc patients from healthy individuals and those with other AI, as well as those SSc patients with and without particular internal organ complications.

Methods: Plasma samples from a study population of 876 subjects were evaluated; the cohort was comprised of SSc (n=301), dermatomyositis (DM) (396), mixed and undifferentiated CTD (31), polymyositis (14), systemic lupus erythematosus (8), other AI (42), and healthy controls (84). All met validated classification criteria for each specific disease. An IMS assay was used to detect plasma antibodies bound to an array of ~126,000 unique peptides. Peptide sequences were designed to broadly sample chemical space thus providing a library of diverse epitope mimetics for antibodies to selectively bind. Features most discriminating SSc contrasts were identified using a t-test. Support vector machine classifiers were trained and assessed by 100 iterations of 5-fold cross validation.

Results: Cross-validated estimates of classification performance are provided in Table 1. One classifier distinguished SSc patients from healthy donors. Additional classifiers differentiated SSc from other AI diseases or from DM in particular. Finally, SSc patients that suffered from interstitial lung disease (ILD), renal crisis, or gastric antral vascular ectasia (GAVE) within a year of their blood draw could be distinguished from those SSc patients who did not. Up to 10,000 peptides whose antibody-binding characteristics differentiated health status groups were used as inputs to these classifiers.

Conclusion: Reproducible binding patterns produced by peripheral-blood antibody repertoires on a mimetic-peptide microarray can differentiate SSc from healthy donors and from other AI diseases. In addition, distinctive signatures were established for SSc patients with internal organ complications including ILD, renal crisis, and GAVE. This suggests that the IMS technology may be instrumental in the development of both new diagnostic and prognostic tests for SSc.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/immunosignature-technology-differentiates-patients-with-systemic-sclerosis-and-internal-organ-involvement/