Microbiota profiles in pre-school children with respiratory infections: Modifications induced by the oral bacterial lysate OM-85.

To describe microbiota profiles considering potential influencing factors in pre-school children with recurrent respiratory tract infections (rRTIs) and to evaluate microbiota changes associated with oral bacterial lysate OM-85 treatment, we analyzed gut and nasopharynx (NP) microbiota composition in patients included in the OM-85-pediatric rRTIs (OMPeR) clinical trial (https://www.clinicaltrialsregister.eu/ctr-search/trial/2016-002705-19/IT). Relative percentage abundance was used to describe microbiota profiles in all the available biological specimens, grouped by age, atopy, and rRTIs both at inclusion (T0) and at the end of the study, after treatment with OM-85 or placebo (T1). At T0, and were the predominant genera in gut and , , and were the predominant genera in NP samples. Gut microbiota relative composition differed with age (<2 vs. ≥2 years) for (phyla) and (genera) ( < 0.05). was more enriched in the NP of patients with a history of up to three RTIs. Intra-group changes in relative percentage abundance were described only for patients with gut and NP microbiota analysis available at both T0 and T1 for each study arm. In this preliminary analysis, the gut microbiota seemed more stable over the 6-month study in the OM-85 group, whose mean age was lower, as compared to the placebo group ( = 0.004). In this latter group, the relative abundance of decreased significantly in children ≥2 years. Some longitudinal significant differences in genera relative abundance were also detected in children of ≥2 years for NP , , and in the placebo group only. Due to the small number of patients in the different sub-populations, we could not identify significant differences in the clinical outcome and therefore no associations with microbiota changes were searched. The use of bacterial lysates might play a role in microbiota rearrangement, but further data and advanced analysis are needed to prove this in less heterogeneous populations with higher numbers of samples considering the multiple influencing factors such as delivery method, age, environment, diet, antibiotic use, and type of infections to ultimately show any associations with prevention of rRTIs.

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