Objective: To identify novel biomarkers for diagnosis and prediction of active eosinophilic granulomatosis with polyangiitis (EGPA) through data-independent acquisition (DIA) analysis.
Methods: Plasma from 11 EGPA patients and 10 healthy controls (HCs) were analyzed through DIA to identify potential biomarkers. The results were validated in 32 EGPA patients, 24 disease controls (DCs), and 20 HCs using enzyme-linked immunosorbent assay (ELISA). The receiver operating characteristic (ROC) curve was used to assess the diagnostic value of candidate biomarkers.
Results: Thirty-five differentially expressed proteins (DEPs) (24 upregulated and 11 downregulated) were screened between EGPA and HC groups. Five proteins, including serine proteinase inhibitor A3 (SERPINA3), alpha-fibrinogen (FGA), alpha-1 acid glycoprotein 1(AGP1), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), and serum amyloid A1 (SAA1), were significantly upregulated in EGPA compared with HCs. Apart from SAA1, all proteins were also higher in EGPA patients compared with DCs. Furthermore, a panel of SERPINA3 and SAA1 exhibited potential diagnostic value for EGPA with an area under the curve (AUC) of 0.953, while a panel of SERPINA3, FGA, AGP1, and ITIH3 showed good discriminative power to differentiate EGPA from DCs with AUC of 0.926. Moreover, SERPINA3, FGA, and AGP levels were significantly higher in active EGPA and correlated well with disease activity. A combination of SERPINA3 and AGP1 exhibited an excellent AUC of 0.918 for disease activity assessment.
Conclusion: SERPINA3, FGA, AGP1, ITIH3 and SAA1 were identified as potential biomarkers for EGPA diagnosis and disease activity assessment. Among them, as a single biomarker, SERPINA3 has the best diagnostic performance.
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