Dynamics of respiratory symptoms during infancy and associations with wheezing at school age
Jakob Usemann1,2,3, Binbin Xu1,3, Edgar Delgado-Eckert1
1University Children's Hospital Basel (UKBB), Basel, Switzerland.
Insights
Infant respiratory symptom patterns predict later wheezing. A new method identified high-risk phenotypes associated with increased wheezing by age six, aiding early intervention for childhood respiratory health.
Area of Science:
- Pediatric Pulmonology
- Computational Biology
- Epidemiology
Background:
- Frequent infant respiratory symptoms are linked to later wheezing.
- The dynamics of these symptoms and their predictive value are not well understood.
- Objective methods are needed to characterize infant respiratory symptom patterns.
Purpose of the Study:
- To develop an observer-independent method to characterize respiratory symptom dynamics in infancy.
- To identify distinct infant respiratory symptom phenotypes.
- To investigate the association between these phenotypes and wheezing at age six.
Main Methods:
- A birth cohort study prospectively collected weekly respiratory symptom data for infants.
- A Markov matrix and entropy parameter were used to quantify symptom dynamics.
- Hierarchical clustering identified distinct dynamic phenotypes.
- Phenotypes were associated with wheezing at six years using logistic regression.
Main Results:
- Three distinct infant respiratory symptom dynamics phenotypes were identified.
- A high-risk phenotype, characterized by high entropy, was significantly associated with increased wheezing at age six (OR 3.01).
- Factors associated with the high-risk phenotype included male sex, environmental tobacco smoke exposure, siblings, and childcare attendance.
Conclusions:
- A novel, objective method quantifies infant respiratory symptom dynamics.
- These dynamics can identify infants at higher risk for persistent wheezing.
- Understanding symptom dynamics aids in identifying abnormal airway susceptibility and recovery patterns in infants.
Abstract:
Children with frequent respiratory symptoms in infancy have an increased risk for later wheezing, but the association with symptom dynamics is unknown. We developed an observer-independent method to characterise symptom dynamics and tested their association with subsequent respiratory morbidity. In this birth-cohort of healthy neonates, we prospectively assessed weekly respiratory symptoms during infancy, resulting in a time series of 52 symptom scores. For each infant, we calculated the transition probability between two consecutive symptom scores. We used these transition probabilities to construct a Markov matrix, which characterised symptom dynamics quantitatively using an entropy parameter. Using this parameter, we determined phenotypes by hierarchical clustering. We then studied the association between phenotypes and wheezing at 6 years. In 322 children with complete data for symptom scores during infancy (16 864 observations), we identified three dynamic phenotypes. Compared to the low-risk phenotype, the high-risk phenotype, defined by the highest entropy parameter, was associated with an increased risk of wheezing (odds ratio (OR) 3.01, 95% CI 1.15-7.88) at 6 years. In this phenotype, infants were more often male (64%) and had been exposed to environmental tobacco smoke (31%). In addition, more infants had siblings (67%) and attended childcare (38%). We describe a novel method to objectively characterise dynamics of respiratory symptoms in infancy, which helps identify abnormal clinical susceptibility and recovery patterns of infant airways associated with persistent wheezing.
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