Improved prognosis prediction of idiopathic pulmonary arterial hypertension using targeted plasma proteomics in disease management

Abstract Background Idiopathic pulmonary arterial hypertension (IPAH), a special subgroup of PAH with unclear etiology, is characterized by rapid progression and poor prognosis underscoring the need for optimization of IPAH management and the accurate prediction of prognosis. However, it is disappointing that specific plasma biomarkers for IPAH management and prognosis are lacking in clinical practice. Up to date, the plasma biomarkers used for assessment of IPAH severity and prognosis are relied solely on indicators such as N-terminal prohormone of brain natriuretic peptide, or brain natriuretic peptide, which could reflect cardiac function but fail to promptly response to the dynamic change of disease condition due to the complexity of IPAH pathogenesis. Purpose We evaluated the prognostic value of plasma proteins in addition to current clinical predictors for prognosis prediction of IPAH. Methods Olink Immune-Response panel was used to measure 92 plasma proteins in a prospective IPAH cohort with 169 patients and a mean follow-up period of 2.4 ± 0.9 years. Six machine learning methods were used to construct predictive models, including plasma proteins-based Olink models, clinical parameters-based clinical models, and integrative models. Results A total of 18 proteins showed differential expression between patients with or without adverse clinical outcomes. Three proteins (STC1, CXADR, and IL6) were strongly correlated with clinical indicators of IPAH severity and their concentrations showed upward trends along with increased risk stratification. Elevated levels of STC1, CXADR, and IL6 are all associated with an increased risk of adverse clinical events, indicated by survival analysis, restricted cubic splines, and multivariable Cox regression analysis (STC1 HR=3.474, 95%CI: 1.129-10.692, P=0.030; CXADR: HR=1.602, 95%CI: 1.074-2.387, P=0.021; IL6: HR=1.883, 95%CI: 1.376-2.576, P<0.001). The inclusion of these three proteins into the predictive model could significantly increase the predictive power on the basis of the clinical model (AUC: 0.746 vs 0.626). Conclusions High levels of STC1, CXADR, and IL6 in plasma were associated with severe clinical phenotype and increased risk of adverse clinical events in patients with IPAH. These plasma proteins could significantly improve the prognostic performance of pre-existing clinical models, facilitating the clinical management of IPAH patients.The predictive efficient of models