Validation of disease-specific biomarkers for the early detection of bronchopulmonary dysplasia.

OBJECTIVE: To demonstrate and validate the improvement of current risk stratification for bronchopulmonary dysplasia (BPD) early after birth by plasma protein markers (sialic acid-binding Ig-like lectin 14 (SIGLEC-14), basal cell adhesion molecule (BCAM), angiopoietin-like 3 protein (ANGPTL-3)) in extremely premature infants. METHODS AND RESULTS: Proteome screening in first-week-of-life plasma samples of n = 52 preterm infants <32 weeks gestational age (GA) on two proteomic platforms (SomaLogic®, Olink-Proteomics®) confirmed three biomarkers with significant predictive power: BCAM, SIGLEC-14, and ANGPTL-3. We demonstrate high sensitivity (0.92) and specificity (0.86) under consideration of GA, show the proteins' critical contribution to the predictive power of known clinical risk factors, e.g., birth weight and GA, and predicted the duration of mechanical ventilation, oxygen supplementation, as well as neonatal intensive care stay. We confirmed significant predictive power for BPD cases when switching to a clinically applicable method (enzyme-linked immunosorbent assay) in an independent sample set (n = 25, p < 0.001) and demonstrated disease specificity in different cohorts of neonatal and adult lung disease. CONCLUSION: While successfully addressing typical challenges of clinical biomarker studies, we demonstrated the potential of BCAM, SIGLEC-14, and ANGPTL-3 to inform future clinical decision making in the preterm infant at risk for BPD. TRIAL REGISTRATION: Deutsches Register Klinische Studien (DRKS) No. 00004600; https://www.drks.de . IMPACT: The urgent need for biomarkers that enable early decision making and personalized monitoring strategies in preterm infants with BPD is challenged by targeted marker analyses, cohort size, and disease heterogeneity. We demonstrate the potential of the plasma proteins BCAM, SIGLEC-14, and ANGPTL-3 to identify infants with BPD early after birth while improving the predictive power of clinical variables, confirming the robustness toward proteome assays and proving disease specificity. Our comprehensive analysis enables a phase-III clinical trial that allows full implementation of the biomarkers into clinical routine to enable early risk stratification in preterms with BPD.

In silico numerical simulation of ventilator settings during high-frequency ventilation in preterm infants.

OBJECTIVE: Despite the routine use of antenatal steroids, exogenous surfactants, and different noninvasive ventilation methods, many extremely low gestational age neonates, preterm, and term infants eventually require invasive ventilation. In addition to prematurity, mechanical ventilation itself can induce ventilator-induced lung injury leading to lifelong pulmonary sequelae. Besides conventional mechanical ventilation, high-frequency oscillatory ventilation (HFOV) with tidal volumes below dead space and high ventilation frequencies is used either as a primary or rescue therapy in severe neonatal respiratory failure. METHODS AND RESULTS: Applying a high-resolution computational lung modeling technique in a preterm infant, we studied three different high-frequency ventilation settings as well as conventional ventilation (CV) settings. Evaluating the computed oxygen delivery (OD) and lung mechanics (LM) we outline for the first time how changing ventilator settings from CV to HFOV lead to significant improvements in OD and LM. CONCLUSION: This personalized "digital twin" strategy advances our general knowledge of protective ventilation strategies in neonatal care and can support decisions on various modes of ventilatory therapy at high frequencies.

Gas exchange mechanisms in preterm infants on HFOV - a computational approach.

High-frequency oscillatory ventilation (HFOV) is a commonly used therapy applied to neonates requiring ventilatory support during their first weeks of life. Despite its wide application, the underlying gas exchange mechanisms promoting the success of HVOF in neonatal care are not fully understood until today. In this work, a highly resolved computational lung model, derived from Magnetic Resonance Imaging (MRI) and Infant Lung Function Testing (ILFT), is used to reveal the reason for highly efficient gas exchange during HFOV, in the preterm infant. In total we detected six mechanisms that facilitate gas exchange during HFOV: (i) turbulent vortices in large airways; (ii) asymmetric in- and expiratory flow profiles; (iii) radial mixing in main bronchi; (iv) laminar flow in higher generations of the respiratory tract; (v) pendelluft; (vi) direct ventilation of central alveoli. The illustration of six specific gas transport phenomena during HFOV in preterm infants advances general knowledge on protective ventilation in neonatal care and can support decisions on various modes of ventilatory therapy at high frequencies.