LSC - 2024 - Fetal lung growth as a tool to predict the risk for respiratory infections and asthma early in life

<bold>Background:</bold> Respiratory diseases, such as infections and asthma, are major health burdens in childhood (Eder W et al. N Engl J Med 2006;355:2226-35). Markers predicting an increased risk for childhood respiratory diseases, e.g. during fetal life, are sparse. <bold>Aim:</bold> We aimed to examine if ultrasound-monitored fetal lung growth trajectories can predict the risk for respiratory infections and asthma early in life. <bold>Methods:</bold> Fetal lung size was serially assessed at standardized timepoints by ultrasound in pregnant women within the pregnancy cohort PRINCE (PRenatal determINants of Children’s hEalth). The number of respiratory infections in infancy was reported. Early-onset asthma risk was determined based on standardized universally used criteria (Asher MI et al. Eur Respir J 1995;8:483-91). Correlations among fetal lung growth, early-life respiratory infections and asthma were examined. Finally, machine-learning models were developed to predict the risk for early-life respiratory infections or early-onset asthma based on fetal lung growth. <bold>Results:</bold> Enhanced fetal lung growth throughout pregnancy predicted a lower risk for early-life respiratory infections. Male sex was associated with a higher risk for respiratory infections in infancy. Based on these findings, we developed novel accurate machine-learning models to predict the risk for early-life respiratory infections and early-onset asthma manifestation. Model variants included known influential factors and novel predictors, such as the ultrasound-monitored fetal lung growth. <bold>Conclusions:</bold> A non-invasive serial assessment of fetal lung growth can predict respiratory health risks, such as early-life respiratory infections and childhood asthma.