Identification of serum exosome proteins in systemic sclerosis with interstitial lung disease by aptamer proteomics

A major unmet need for Systemic Sclerosis (SSc) clinical management is the absence of well validated biomarkers for early diagnosis of SSc-associated interstitial lung disease (SSc-ILD). The objective of this study was to identify proteins contained within serum exosomes that may serve as potential biomarkers to differentiate patients with Diffuse SSc without SSc-ILD from patients with Diffuse SSc with SSc-ILD employing aptamer-based proteomics. Serum exosomes were isolated from two cohorts of patients. The first cohort included 15 patients with Diffuse SSc without SSc-ILD and 14 patients with Diffuse SSc with SSc-ILD and the second cohort included 12 patients with Diffuse SSc with SSc-ILD and 12 patients with Diffuse SSc without SSc-ILD. SOMAscan aptamer proteomics was performed with the first cohort and quantified the concentration levels of 1,305 proteins. Significant associations of differentially elevated or reduced proteins (p < 0.05 |FC|>1.2) discriminating between the two SSc clinical subsets were assessed. Validation of the results obtained from the proteomics analysis of the first cohort was performed with the second cohort. The aptamer proteomic analysis identified 29 proteins increased and 9 proteins decreased in SSc with SSc-ILD as compared to SSc without SSc-ILD. Principal component analysis using the 20 most significantly differentially expressed proteins resulted in excellent separation of the two SSc clinical subsets. Most of the differentially increased proteins converged around enhanced inflammatory responses, immune cell activation, cell death, and abnormal vascular functions and several of them displayed a highly significant correlation with the CO Diffusion Capacity Levels. Aptamer proteomic analysis of circulating exosomes from patients with Diffuse SSc with and without SSc-ILD identified several biologically plausible biomarkers that may be of value to differentiate these two SSc clinical subsets.