High-throughput plasma proteomics reveals circulating biomarkers of interstitial lung disease and progressive pulmonary fibrosis in systemic sclerosis.

Abstract

This study aimed to identify plasma biomarkers associated with systemic sclerosis-related interstitial lung disease (SSc-ILD) and progressive pulmonary fibrosis (SSc-PPF) using an unbiased proteomic approach, and to assess their predictive value across independent cohorts. Plasma from 202 patients with SSc was analysed, including a discovery cohort (n = 45) and a replication cohort (n = 157) from 3 centres (Paris, Bordeaux, Leeds). Patients were stratified by ILD status (SSc without ILD [SSc-NoILD] vs SSc-ILD) and ILD progression (SSc with nonprogressive pulmonary fibrosis [SSc-NoPPF] vs SSc-PPF), with SSc-PPF defined according to INBUILD criteria. Mass spectrometry-based proteomics identified candidate biomarkers in the discovery cohort. Top candidates were evaluated by enzyme-linked immunosorbent assay (ELISA) in the replication cohort. Differential expression, pathway enrichment, and predictive performance analyses were performed. A total of 1507 proteins were quantified, of which 44 and 51 were associated with SSc-ILD and SSc-PPF, respectively. Five candidates progressed to ELISA validation, among which surfactant protein D (SP-D) and matrix metalloproteinase 8 (MMP-8) were successfully replicated. In the combined cohort, SP-D was elevated in SSc-ILD vs SSc-NoILD (17.36 ± 11.99 vs 9.49 ± 7.92 ng/mL; P < .0001). MMP-8 was higher in SSc-PPF vs SSc-NoPPF (17.67 ± 12.45 vs 10.77 ± 10.92 ng/mL; P < .001). Its prognostic value for PPF was further replicated in another cohort of 113 patients from Tokyo and Milan. In combined analyses, MMP-8 independently predicted SSc-PPF and improved performance when added to clinical variables. SP-D and MMP-8 emerge as candidate biomarkers for diagnosing SSc-ILD and predicting SSc-PPF, respectively. Their validation across multicentric cohorts supports their relevance for clinical risk stratification.