SERPINA3, FGA, AGP1, ITIH3 and SAA1 as novel biomarkers for eosinophilic granulomatosis with polyangiitis diagnosis and activity assessment

Abstract

Abstract Objective The objective of this study was to identify novel biomarkers for diagnosis and prediction of active eosinophilic granulomatosis with polyangiitis (EGPA) through data-independent acquisition (DIA) analysis. Methods Plasma samples from 11 EGPA patients and 10 healthy controls (HCs) were analysed through DIA to identify potential biomarkers. The results were validated in 32 EGPA patients, 24 disease controls (DCs), and 20 HCs using 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 the 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 for differentiating EGPA from DCs, with an 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 had the best diagnostic performance.