3 Scopus citations


Background: The pathophysiology of wheezing is multifactorial, impacted by medical, demographic, environmental, and immunologic factors. We hypothesized that multi-omic analyses of host and microbial factors in saliva would enhance the ability to identify infants at risk for wheezing. Methods: This longitudinal cohort study included 161 term infants. Infants who developed wheezing (n = 27) within 24 months of delivery were identified using the International Study of Asthma and Allergies in Childhood Written Questionnaire and review of the medical record. Standardized surveys were used to assess infant traits and environmental exposures. Saliva was collected for multi-omic assessment of cytokines, microRNAs, mRNAs, and microbiome/virome RNAs. Results: Two infant factors (daycare attendance, family history of asthma) and three salivary “omic” features (miR-26a-5p, Elusimicrobia, Streptococcus phage phiARI0131-1) differed between the two groups (adjusted p < 0.05). miR-26a-5p levels were correlated with Elusimicrobia (R = −0.87, p = 3.7 × 10−31). A model employing the three omic features plus daycare attendance and family asthma history yielded the highest predictive accuracy for future wheezing episodes (AUC = 0.74, 95% CI: 0.703–0.772, 77% sensitivity, 62% specificity). Conclusions: Host–microbiome interactions in saliva may yield pathophysiologic clues about the origins of wheezing and aid identification of infants at risk of future wheezing episodes. Impact: Wheezing is multi-factorial, but the relative contributions of infant traits, environment, and underlying biology are poorly understood.This multi-omic study identifies three molecular factors, including salivary microRNAs, microbes, and viral phages associated with increased risk of infant wheezing.Measurement of these molecular factors enhanced predictive accuracy for future wheezing when combined with family asthma history and daycare attendance.Validation of this approach could be used to identify infants at risk for wheezing and guide personalized medical management.

Original languageEnglish (US)
Pages (from-to)579-585
Number of pages7
JournalPediatric Research
Issue number3
StatePublished - Feb 2023

All Science Journal Classification (ASJC) codes

  • Pediatrics, Perinatology, and Child Health


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