Conclusions
Proteomic markers are used to improve the diagnosis and prognosis of PH but, as demonstrated here, can be altered in genetically unique populations such as individuals with Down syndrome. This further suggests that clinical biomarkers should be evaluated in unique groups with the development of population-specific nomograms.
Objective
To evaluate the performance of pulmonary hypertension (PH) biomarkers in children with Down syndrome, an independent risk factor for PH, in whom biomarker performance may differ compared with other populations. Study design: Serum endostatin, interleukin (IL)-1 receptor 1 (ST2), galectin-3, N-terminal pro hormone B-natriuretic peptide (NT-proBNP), IL-6, and hepatoma-derived growth factor (HDGF) were measured in subjects with Down syndrome and PH (n = 29), subjects with Down syndrome and resolved PH (n = 13), subjects with Down syndrome without PH (n = 49), and subjects without Down syndrome with World Symposium on Pulmonary Hypertension group I pulmonary arterial hypertension (no Down syndrome PH group; n = 173). Each biomarker was assessed to discriminate PH in Down syndrome. A classification tree was created to distinguish PH from resolved PH and no PH in children with Down syndrome.
Results
Endostatin, galectin-3, HDGF, and ST2 were elevated in subjects with Down syndrome regardless of PH status. Not all markers differed between subjects with Down syndrome and PH and subjects with Down syndrome and resolved PH. NT-proBNP and IL-6 levels were similar in the Down syndrome with PH group and the no Down syndrome PH group. A classification tree identified NT-proBNP and galectin-3 as the best markers for sequentially distinguishing PH, resolved PH, and no PH in subjects with Down syndrome. Conclusions: Proteomic markers are used to improve the diagnosis and prognosis of PH but, as demonstrated here, can be altered in genetically unique populations such as individuals with Down syndrome. This further suggests that clinical biomarkers should be evaluated in unique groups with the development of population-specific nomograms.