Mass spectrometry-based autoimmune profiling reveals predictive autoantigens in idiopathic pulmonary fibrosis

Abstract

Autoimmunity plays a role in certain types of lung fibrosis, notably connective tissue disease-associated interstitial lung disease (CTD-ILD). In idiopathic pulmonary fibrosis (IPF), an incurable and fatal lung disease, diagnosis typically requires clinical exclusion of autoimmunity. However, autoantibodies of unknown significance have been detected in IPF patients. We conducted computational analysis of B cell transcriptomes in published transcriptomics datasets and developed a proteomic Differential Antigen Capture (DAC) assay that captures plasma antibodies followed by affinity purification of lung proteins coupled to mass spectrometry. We analyzed antibody capture in two independent cohorts of IPF and CTL-ILD patients over two disease progression time points. Our findings revealed significant upregulation of specific immunoglobulins with V-segment bias in IPF across multiple cohorts. We identified a predictive autoimmune signature linked to reduced transplant-free survival in IPF, persisting over time. Notably, autoantibodies against thrombospondin-1 were associated with decreased survival, suggesting their potential as predictive biomarkers.