sequence variants (ASVs), representing unique 16S rRNA V4 sequences. The 147 nasopharyngeal samples were clustered into microbiome profile groups (MPGs) using 148 hierarchical clustering methods. 3, 7 Nasal specimens were analyzed for common 149 respiratory viruses as previously described. 28, 29 150 151 Statistical methods 152 We used the relative abundances of common ASVs to determine clusters of individuals 153 who shared similar patterns ("trajectories") of changing microbiome during routine visits 154 (with healthy or mildly-ill samples). To generate these trajectories, we omitted all 155 samples obtained at 18 months of age because of a high rate of missing samples at this 156 timepoint. We then performed Multiple Factor Analysis (R package "FactoMineR"), 30 157 followed by K-means clustering.
To estimate a longitudinal asthma phenotype, simple latent class models were fit using To compare MPGs and MFA-k-means trajectories, Fisher exact tests and Chi-square 167 tests were used for categorical variables; Kruskal-Wallis, t-tests and ANOVAs for 168 continuous variables. More complex associations were assessed using generalized linear models (GLM) for subject-based analyses, or generalized estimating equations 170 (GEE, using R package "gee" v4.13.20) 31, 32 for sample-based analyses, adjusting for 171 gender, and age and season with repeated measures of multiple samples per child 172 subject, and unstructured correlation. These analyses were conducted using R v3.5.0.
Post-hoc comparisons with FDR correction were conducted where required.
Additional details on study and statistical methods are listed in the online data 176 supplement.
A total of 3147 nasal samples were analyzed for bacteria, including 1654 collected 181 during routine scheduled visits (2, 4, 6, 9, 12, 18 Demographic characteristics were similar among children in the four trajectories (Table   262 1). There were no significant differences among the microbiome trajectories in terms of (Table 1) . In addition, Trajectory C was also associated with greater frequency of physician-279 diagnosed asthma from age 6 years (47%, p=0.053) to 18 years (58%, p=0.019) 280 compared to the other trajectories ( Figure 4A ). Furthermore, we applied a latent class 281 model to asthma diagnoses at age 6, 8, 11, 13 and 18 years to identify four longitudinal 282 patterns of asthma (Supplementary Figure 6) : none/intermittent (63% subjects), persistent (19% subjects), remitting (10% subjects), and late onset (8% subjects).
Compared to other microbiome trajectories, Trajectory C (Staphylococcus.29eb 285 dominance) tended to be positively associated with a persistent asthma phenotype 286 (p=0.08, Figure 4B ). Moraxella.d253 during years 2 and 3 were strongly related to persistent asthma. 303 Given the close association between early onset of atopy and persistent asthma, we 304 next tested for associations between microbiome Trajectory C and indicators of type II 305 inflammation and allergic outcomes. Trajectory C was associated with a greater frequency of aeroallergen sensitization, especially during early childhood ( Figure 5A ).
The difference of trajectory C from the others was significant through to age 5 (p<0.05 308 at each age) and also when all years were considered together (Trajectory C vs. others, 309 p=0.05). There were similar nonsignificant trends for associations between Trajectory C 310 and increases in both total IgE and absolute eosinophil counts ( Figure 5 , B and C). We next tested whether the association between Trajectory C and asthma was 321 mediated via viral wheezing illnesses or allergic sensitization in early life. To test this, all 322 three variables (trajectory, early wheezing illness, aeroallergen sensitization) were 323 included in multivariable models with asthma diagnosis at various timepoints as 324 outcomes. The association between Trajectory C and asthma diagnoses at ages 6 to 13 325 was partially ablated when adjusting for both early aeroallergen sensitization (allergen-326 specific IgE>0.35 kU/L by age two) and number of early-life wheezing illnesses up to 327 age 3 (Supplementary Table 4 ). However, Trajectory C remained a statistically-328 significant predictor for asthma diagnosis at ages 11 and 13, suggesting that the 