Predictive values of clinical data,molecular biomarkers, and echocardiographic measurements in preterm infants with bronchopulmonary dysplasia

Longitudinal evaluation of hemodynamic blood and echocardiographic biomarkers for the prediction of BPD and BPD-related pulmonary hypertension in very-low-birth-weight preterm infants

Very-low-birth-weight infants (VLBW, < 1500 g) are at risk of developing bronchopulmonary dysplasia (BPD) and are at risk for BPD-related pulmonary hypertension (PH). The longitudinal measurement of innovative blood and echocardiographic biomarkers might allow for a risk stratification of these infants. A prospective single-center cohort study was conducted between 01/2021 and 06/2023. Inclusion criteria were the combination of a birth weight < 1500 g and a gestational age (GA) ≤ 30/0 weeks. Assessment timepoints: T1 (day 7), T2 (day 28), and T3 (at 36 weeks post-menstrual age, PMA). Overall, 71 preterm infants were included for final analysis. The Zlog-transformed NTproBNPZlog (at T1 AUC 0.772; p = 0.019; at T2 AUC 0.874, p = 0.002), and endothelin-1 (ET1, at T1 AUC 0.789, p = 0.013) were identified as an early predictive biomarker for BPD/death in the univariate analysis. Additionally, echocardiographic markers of ventricular function and PH at T1 were predictive for BPD/death in the univariate analysis, with the highest predictivity found for the tricuspid annular plane systolic excursion-TAPSE (AUC 0.748, p = 0.016) and the pulmonary artery acceleration time to right ventricular ejection time (PAAT/RVET; AUC 0.744, p = 0.043). Regarding predictability of mortality alone NTroBNPZlog (at T1 AUC 0.973, p = 0.000), and CA125 (at T1 AUC 0.747, p = 0.008) were identified as potential predictors, as well as TAPSE (AUC 0.926, p = 0.000), and PAAT/RVET (AUC 0.985, p = 0.000) Several biomarkers including ET-1 (at T1 AUC 0.893, p = 0.000), TAPSE (AUC 0.974, p = 0.000), and PAAT/RVET (AUC 1.0, p = 0.000) at T1 were identified as univariate predictors for BPD-PH. In the multivariate analysis, no biomarker was identified as an independent predictor of the primary endpoint.

CONCLUSION

Mainly at an early stage of postnatal neonatal care in VLBW preterm infants, several biomarkers were found to be associated with the combined endpoint BPD/death and BPD-PH. New candidates of blood biomarkers (NTproBNPZlog, ET-1, and CA125) and echocardiographic markers (TAPSE, PAAT/RVET) might serve as innovative predictors for BPD, BPD-PH, and adverse outcomes in VBLW infants.

WHAT IS KNOWN

• VLBW infants are at risk for the development of BPD and BPD-related PH, which both are main contributors for short and long-term morbidity and mortality. Several studies in the past focused on the evaluation of circulating blood biomarkers and biomarkers from echocardiographic assessment of these infants. But to date, there is still a lack on longitudinal prospective studies especially in VLBW infants.

WHAT IS NEW

• For the first time, this set of selected blood biomarkers (with the first description of Zlog-transformed NTproBNP and CA125 in preterm infants) and several echocardiographic markers were analyzed in a prospective longitudinal study from birth until 36 weeks post menstrual age in VLBW infants. Our data help clinicians to identify preterm infants at risk for BPD, BPD-PH and death and to offer new candidates of biomarkers. This might help to facilitate decision making and guidance of therapy in these highly vulnerable patients.

Recent progress in neonatal hyperoxic lung injury

With the progress in neonatal intensive care, there has been an increase in the survival rates of premature infants. However, this has also led to an increased incidence of neonatal hyperoxia lung injury and bronchopulmonary dysplasia (BPD), whose pathogenesis is believed to be influenced by various prenatal and postnatal factors, although the exact mechanisms remain unclear. Recent studies suggest that multiple mechanisms might be involved in neonatal hyperoxic lung injury and BPD, with sex also possibly playing an important role, and numerous drugs have been proposed and shown promise for improving the treatment outcomes of hyperoxic lung injury. Therefore, this paper aims to analyze and summarize sex differences in neonatal hyperoxic lung injury, potential pathogenesis and treatment progress to provide new ideas for basic and clinical research in this field.

Patent ductus arteriosus and the association between lung ultrasound score and bronchopulmonary dysplasia: a secondary analysis of a prospective study

Moderate-to-large patent ductus arteriosus (PDA) has been linked to increased risk of bronchopulmonary dysplasia (BPD), while lung ultrasound score (LUS) has been demonstrated to accurately predict BPD. We aimed to investigate the correlation of LUS as a marker of interstitial pulmonary edema and the severity of the ductal shunt in predicting future BPD development in very preterm infants. This secondary analysis of a prospective study recruited preterm infants with gestational age < 30 weeks. LUS on postnatal days 7 and 14, and echocardiographic data [PDA diameter and left atrium-to-aortic root ratio (LA/Ao)] near LUS acquisition were collected. Correlation coefficient, logistics regression analysis, and the area under the receiver operating characteristic (AUROC) procedure were used. A statistically significant and positive correlation existed between LUS and PDA diameter (ρ = 0.415, ρ = 0.581, and p < 0.001) and LA/Ao (ρ = 0.502, ρ = 0.743, and p < 0.001) at postnatal days 7 and 14, respectively, and the correlations of LUS and echocardiographic data were generally stronger in the non-BPD group. In the prediction of BPD, LUS incorporating echocardiographic data at postnatal days 7 obtained significantly higher predictive performance compared to LUS alone (AUROC 0.878 [95% CI 0.801-0.932] vs. AUROC 0.793 [95% CI 0.706-0.865]; Delong test, p = 0.013).

CONCLUSIONS

There is a statistically significant correlation between LUS and echocardiographic data, suggesting their potential role as early predictors for respiratory outcomes in very preterm infants.

WHAT IS KNOWN

• Lung ultrasound score (LUS) has shown good reliability in predicting bronchopulmonary dysplasia (BPD) development. • Some echocardiographic data that characterized ventricular function was reported to be used to predict severe BPD.

WHAT IS NEW

• There is a positive and statistically significant correlation between LUS and echocardiographic data at postnatal days 7 and 14. • The integrated use of LUS and echocardiographic data may have potential value in predicting BPD.

Identification of potential biomarkers in the peripheral blood of neonates with bronchopulmonary dysplasia using WGCNA and machine learning algorithms

Bronchopulmonary dysplasia (BPD) is often seen as a pulmonary complication of extreme preterm birth, resulting in persistent respiratory symptoms and diminished lung function. Unfortunately, current diagnostic and treatment options for this condition are insufficient. Hence, this study aimed to identify potential biomarkers in the peripheral blood of neonates affected by BPD. The Gene Expression Omnibus provided the expression dataset GSE32472 for BPD. Initially, using this database, we identified differentially expressed genes (DEGs) in GSE32472. Subsequently, we conducted gene set enrichment analysis on the DEGs and employed weighted gene co-expression network analysis (WGCNA) to screen the most relevant modules for BPD. We then mapped the DEGs to the WGCNA module genes, resulting in a gene intersection. We conducted detailed functional enrichment analyses on these overlapping genes. To identify hub genes, we used 3 machine learning algorithms, including SVM-RFE, LASSO, and Random Forest. We constructed a diagnostic nomogram model for predicting BPD based on the hub genes. Additionally, we carried out transcription factor analysis to predict the regulatory mechanisms and identify drugs associated with these biomarkers. We used differential analysis to obtain 470 DEGs and conducted WGCNA analysis to identify 1351 significant genes. The intersection of these 2 approaches yielded 273 common genes. Using machine learning algorithms, we identified CYYR1, GALNT14, and OLAH as potential biomarkers for BPD. Moreover, we predicted flunisolide, budesonide, and beclomethasone as potential anti-BPD drugs. The genes CYYR1, GALNT14, and OLAH have the potential to serve as diagnostic biomarkers for BPD. This may prove beneficial in clinical diagnosis and prevention of BPD.