Antibiotic use during infancy alters gut microbiota and immune development and is associated with an increased risk of childhood asthma. The impact of prenatal antibiotic exposure is unclear. We sought to characterise the association between prenatal antibiotic exposure and childhood asthma.We performed a population-based cohort study using prescription records, hospitalisation records and physician billing claims from 213 661 mother-child dyads born in Manitoba, Canada between 1996 and 2012. Associations were determined using Cox regression, adjusting for maternal asthma, postnatal antibiotics and other potential confounders. Sensitivity analyses evaluated maternal antibiotic use before and after pregnancy.36.8% of children were exposed prenatally to antibiotics and 10.1% developed asthma. Prenatal antibiotic exposure was associated with an increased risk of asthma (adjusted hazard ratio (aHR) 1.23, 95% CI 1.20-1.27). There was an apparent dose response (aHR 1.15, 95% CI 1.11-1.18 for one course; aHR 1.26, 95% CI 1.21-1.32 for two courses; and aHR 1.51, 95% CI 1.44-1.59 for three or more courses). Maternal antibiotic use during 9 months before pregnancy (aHR 1.27, 95% CI 1.24-1.31) and 9 months postpartum (aHR 1.32, 95% CI 1.28-1.36) were similarly associated with asthma.Prenatal antibiotic exposure was associated with a dose-dependent increase in asthma risk. However, similar associations were observed for maternal antibiotic use before and after pregnancy, suggesting the association is either not directly causal, or not specific to pregnancy.

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Human rhinovirus (RV) is a major cause of common cold and triggers acute episodes of asthma. Little is known about T-cell mechanisms of cross-protection to different RV strains. We aimed to rigorously interrogate virus-specific T cells in a sequential experimental infection model in humans. METHODS: Healthy subjects were infected with RV-A16 and rechallenged 15 weeks later with either RV-A16 or RV-A39. Circulating T-cells were sampled over 30 weeks, including peak effector and convalescent infection phases. T cells were phenotyped using a 24-marker spectral flow cytometry panel including up to three RV peptide/MHCII tetramers. Computational tools, including uniform manifold approximation and projection (UMAP), k-nearest neighbor (KNN), and marker enrichment modeling (MEM), were used to quantify signature features of RV-specific T cells and compare them to other T cells in phenotypic neighborhoods either enriched or lacking in RV-specific T cells. RESULTS: Before RV challenge, virus-specific T cells were predominanty CCR5 + PD-1 + central memory and follicular helper (Tfh) cells. During peak effector phases, phenotypically distinct CD4 + T cell types became enriched for RV-specific T cells, including proliferating (Ki67 +) activated Th1 (CCR7 low , CD127 low , CXCR3 + , CD95 + , CD38 + , ICOS + , Tbet + , Tcf-1 +) and Tfh (CCR7 low , CD127 low , PD-1 hi , CXCR5 + , ICOS + , CD38 + , CD95 + , Tcf-1 +) cells. T-cells expanded up to 10-fold, returned to baseline levels during convalescence, and were re-boosted upon re-challenge with either RV strain. Whereas T-cells targeting specific RV epitopes markedly expanded, those targeting other epitopes did not, despite activation during both effector phases. CONCLUSIONS: By integrating high-dimensional phenotyping and computational methods we can reliably identify T-cell hallmarks of protection to different RV strains.