Development of a Symptom-Based Tool for Screening of Children at High Risk of Preschool Asthma

Human milk oligosaccharides are associated with maternal genetics and respiratory health of human milk-fed children

Breastfeeding provides many health benefits, but its impact on respiratory health remains unclear. This study addresses the complex and dynamic nature of the mother-milk-infant triad by investigating maternal genomic factors regulating human milk oligosaccharides (HMOs), and their associations with respiratory health among human milk-fed infants. Nineteen HMOs are quantified from 980 mothers of the CHILD Cohort Study. Genome-wide association studies identify HMO-associated loci on chromosome 19p13.3 and 19q13.33 (lowest P = 2.4e-118), spanning several fucosyltransferase (FUT) genes. We identify novel associations on chromosome 3q27.3 for 6'-sialyllactose (P = 2.2e-9) in the sialyltransferase (ST6GAL1) gene. These, plus additional associations on chromosomes 7q21.32, 7q31.32 and 13q33.3, are replicated in the independent INSPIRE Cohort. Moreover, gene-environment interaction analyses suggest that fucosylated HMOs may modulate overall risk of recurrent wheeze among preschoolers with variable genetic risk scores (P < 0.01). Thus, we report novel genetic factors associated with HMOs, some of which may protect the respiratory health of children.

Emergency management and asthma risk in young Medicaid-enrolled children with recurrent wheeze

OBJECTIVES

To describe clinical characteristics of young children presenting to the emergency department (ED) for early recurrent wheeze, and determine factors associated with subsequent persistent wheeze and risk for early childhood asthma.

METHODS

Retrospective cohort study of Medicaid-enrolled children 0-3 years old with an index ED visit for wheeze (e.g. bronchiolitis, reactive airway disease) from 2009 to 2013, and at least one prior documented episode of wheeze at an ED or primary care visit. The primary outcome was persistent wheeze between 4 and 6 years of age. Demographics and clinical characteristics were collected from the index ED visit. Logistic regression was used to estimate the association between potential risk factors and subsequent persistent wheeze.

RESULTS

During the study period, 41,710 children presented to the ED for recurrent wheeze. Mean age was 1.3 years; 59% were male, 42% Black, and 6% Hispanic. At index ED visits, the most common diagnosis was acute bronchiolitis (40%); 77% of children received an oral corticosteroid prescription. Between 4 and 6 years of age, 11,708 (28%) children had persistent wheeze. A greater number of wheezing episodes was associated with an increased odds of ED treatment with asthma medications. Subsequent persistent wheeze was associated with male sex, Black race, atopy, prescription for bronchodilators or corticosteroids, and greater number of visits for wheeze.

CONCLUSIONS

Young children with persistent wheeze are at risk for childhood asthma. Thus, identification of risk factors associated with persistent wheeze in young children with recurrent wheeze might aid in early detection of asthma and initiation of preventative therapies.

Artificial intelligence and wheezing in children: where are we now?

Wheezing is a common condition in childhood, and its prevalence has increased in the last decade. Up to one-third of preschoolers develop recurrent wheezing, significantly impacting their quality of life and healthcare resources. Artificial Intelligence (AI) technologies have recently been applied in paediatric allergology and pulmonology, contributing to disease recognition, risk stratification, and decision support. Additionally, the COVID-19 pandemic has shaped healthcare systems, resulting in an increased workload and the necessity to reduce access to hospital facilities. In this view, AI and Machine Learning (ML) approaches can help address current issues in managing preschool wheezing, from its recognition with AI-augmented stethoscopes and monitoring with smartphone applications, aiming to improve parent-led/self-management and reducing economic and social costs. Moreover, in the last decade, ML algorithms have been applied in wheezing phenotyping, also contributing to identifying specific genes, and have been proven to even predict asthma in preschoolers. This minireview aims to update our knowledge on recent advancements of AI applications in childhood wheezing, summarizing and discussing the current evidence in recognition, diagnosis, phenotyping, and asthma prediction, with an overview of home monitoring and tele-management.

Dysregulation of iron homeostasis in airways associated with persistent preschool wheezing

BACKGROUND

Currently, there are no reliable clinical tools available to identify persistent asthma symptoms among preschool children with recurrent wheezing. We investigated iron homeostasis in the airways of preschoolers with recurrent wheezing and assessed whether iron homeostasis-related indices may reliably predict persistent wheezing.

METHODS

Iron levels and mRNA expression levels of iron homeostasis molecules were examined in bronchoalveolar lavage samples from 89 preschoolers with recurrent wheezing and 56 controls, with a 12-month follow-up conducted. Risk factors for persistent wheezing were identified using least absolute shrinkage and selection operator and multivariate logistic regression. The addition of predictive values of iron indices to the modified Asthma Predictive Index (mAPI) or clinical predictors was determined using area under receiver operating characteristic curves (AUC).

RESULTS

Preschoolers with recurrent wheezing had reduced iron levels in their airways, associated with significantly decreased expression of iron export molecule SLC40A1 and increased expression of iron intake factor TFR1 and iron storage factors FTH and FTL. Risk factors for persistent wheezing included mAPI positivity, iron predictors (lower expression of SLC40A1 and higher expression of FTL), and clinical predictors (aeroallergen sensitivity, shorter breastfeeding duration, and earlier age of first wheezing episode). The addition of information on iron predictors significantly enhanced the power of clinical predictors (AUC: 84%, increase of 12%) and mAPI (AUC: 81%, increase of 14%).

CONCLUSIONS

Iron homeostasis is altered in the airways of preschoolers with recurrent wheezing. Adding information on iron-related indices to clinical information significantly improves accurate prediction of persistent wheezing in preschool-aged children.