While cystic fibrosis (CF) lung disease is characterized by persistent inflammation and infections, and chronic inflammatory diseases are often accompanied by autoimmunity, autooimmune reactivity in CF has not been studied in depth. In this work, we undertook an unbiased approach to explore the systemic autoantibody repertoire in CF. Our results show higher levels of several new autoantibodies in the blood of people with CF (PwCF) compared to control subjects. Some of these are IgA autoantibodies targeting neutrophil components or autoantigens linked to neutrophil-mediated tissue damage in CF. We also found that PwCF with higher systemic IgM autoantibody levels have lower prevalence of S. aureus infection. On the other hand, IgM autoantibody levels in S. aureus-infected PwCF correlate with lung disease severity. Diabetic PwCF have significantly higher levels of IgA autoantibodies in their circulation compared to nondiabetic PwCF, and several of their IgM autoantibodies are associated with worse lung disease. In contrast, in nondiabetic PwCF blood levels of IgA autoantibodies correlate with lung disease. We have also identified other autoantibodies in CF that are associated with P. aeruginosa airway infection. In summary, we have identified several new autoantibodies and associations of autoantibody signatures with specific clinical features in CF.

Autoantibody profiling was performed using an existing autoantigen microarray platform developed at the University of Texas Southwestern Medical Center Microarray Core. This platform has the capacity to display a large number of antigens found in human serum or plasma samples on a bio-chip and thereby serves as a high-multiplex screening method for the determination of autoantibody specificities. In this study, we designed an autoantigen microarray that contains 117 autoantigens. The protein array chips coated with these autoantigens were used for profiling four isotypes of autoantibodies – IgG, IgM, IgA and IgE – in human serum samples obtained from healthy control subjects and people diagnosed with cystic fibrosis, rheumatoid arthritis and systemic lupus erythematosus. The fluorescent signal of fluorescently labelled secondary antibodies was acquired with Genepix 7.0 software. The background signals were subtracted and signal normalized to internal controls for IgG, IgM, IgE and IgA. The final valie for each autoantibody was expressed as antibody score which is calculated based on the normalized signal intensity (NSI) and the signal-to-noise ratio (SNR) using the formula: Ab-score = log₂(NSI*SNR + 1).

The normalized and unit variance-scaled Ab-score values were used to generate heat maps, organized by unsupervised hierarchical co-clustering using Cluster and Treeview software. In the heat maps, values were centered by rows, each row represents an autoantibody and each column represents a sample (human serum sample). In parallel with the above-described antigen array analysis, a whole-chip citrullination was also performed to create a corresponding array with the same 117 autoantigens but all modified by citrullination. A protein citrullination kit was used to produce corresponding citrullinated arrays. Antigens that had been immobilized to the array chip were incubated with a mixture of human recombinant PAD enzymes (PAD 1,2,3,4,6) to produce citrullinated antigens. The quality of citrullination was confirmed by antibody-based detection of citrullination. Autoantibody reactivities against citrullinates autoantigens were measured in the sera the same way as with the non-citrullinated autoantigens described.