Biomarkers for Pulmonary Vascular Remodeling in Systemic Sclerosis: A Pathophysiological Approach

Abstract

Pulmonary arterial hypertension (PAH) is a severe complication of systemic sclerosis (SSc) associated with high morbidity and mortality. There are several biomarkers of SSc-PAH, reflecting endothelial physiology, inflammation, immune activation, extracellular matrix, metabolic changes, or cardiac involvement. Biomarkers associated with diagnosis, disease severity and progression have been identified, however, very few have been tested in a prospective setting. Some antinuclear antibodies such as nucleosome antibodies (NUC), anti-centromere antibodies (CENP-A/B) and anti-U3-ribonucleoprotein (anti-U3-RNP) are associated with PAH while anti-U1-ribonucleoprotein (anti-U1-RNP) is associated with a reduced PAH risk. Anti-endothelin receptor and angiotensin-1 receptor antibodies might be good markers of SSc-PAH and progression of pulmonary vasculopathy. Regarding the markers reflecting immune activation and inflammation, there are many inconsistent results. CXCL-4 was associated with SSc progression including PAH and lung fibrosis. Growth differentiation factor (GDF)-15 was associated with PAH and mortality but is not specific for SSc. Among the metabolites, kynurenine was identified as diagnostic marker for PAH, however, its pathologic role in the disease is unclear. Endostatin, an angiostatic factor, was associated with heart failure and poor prognosis. Established heart related markers, such as N-terminal fragment of A-type natriuretic peptide/brain natriuretic peptide (NT-proANP, NT-proBNP) or troponin I/T are elevated in SSc-PAH but are not specific for the right ventricle and may be increased to the same extent in left heart disease. Taken together, there is no universal specific biomarker for SSc-PAH, however, there is a pattern of markers that is strongly associated with a risk of vascular complications in SSc patients. Further comprehensive, multicenter and prospective studies are warranted to develop reliable algorithms for detection and prognosis of SSc-PAH.