Development of a monoclonal antibody-based competitive ELISA as a surrogate assay for detecting neutralizing anti-interferon gamma autoantibodies in adult-onset immunodeficiency

Neutralizing anti-interferon gamma autoantibodies (nAIGAs) play a pivotal role in the pathogenesis of adult-onset immunodeficiency (AOID), predisposing affected individuals to severe opportunistic infections. Current detection of nAIGAs relies on cell-based assays requiring flow cytometric analysis, which limits routine clinical settings. Notably, nAIGAs recognizing the B27 epitope of interferon gamma (IFN-γ) exhibit strong neutralizing activity, underscoring the need for practical, epitope-specific detection methods for routine diagnostic. This study aimed to develop and validate a competitive enzyme-linked immunosorbent assay (cELISA) as a surrogate assay for detecting B27 epitope-targeting nAIGAs in plasma samples from patients with AOID. Plasma samples from patients with AOID (n = 40) and healthy controls (n = 40) were initially screened for AIGAs using an indirect ELISA. Neutralizing activity was confirmed using a cell-based assay measuring MHC class II expression on IFN-γ-stimulated THP-1 cells. The cELISA was subsequently developed and optimized to detect nAIGAs specific to the B27 epitope. ROC curve analysis was performed to assess the diagnostic performance of the assay. All AOID samples with detectable levels of AIGAs showed percentage inhibition above the cut-off in the cell-based assay, confirming the neutralizing activity of AIGAs. The developed cELISA detected nAIGAs in 36 of 40 AOID samples, with no false-positive results observed among healthy controls. ROC curve analysis indicated excellent diagnostic performance, yielding an area under curves (AUC) of 0.9684. Taken together, our findings indicate that the developed cELISA serves as a surrogate assay for detecting nAIGAs targeting the B27 epitope of IFN-γ. This assay represents a practical and scalable tool for AOID screening and may facilitate broader applications in clinical diagnostics.