Statistical analysis
dysbiosis
Statistical analyses for the baseline characteristics of the study population were performed using the χ2 test and Fisher´s exact test for dichotomous variables and an analysis of variance (ANOVA) or Kruskal-Wallis test for continuous variables, and data are presented as means (SD) for continuous variables and as numbers (percentage) for categorical variables.To assess the changes in microbiome composition, the microbiome features (MGS, genus, family, phylum, and GMMs) of the full-term reference and preterm reference groups (preterm infants who had received placebo) were compared for each time point separately using the Mann-Whitney U test. To assess whether gut microbiome modulation can revert microbiome dysbiosis in preterm infants, a comparison was made between the composition of the MGSs and GMMs of the preterm reference vs. preterm prebiotic and the preterm reference vs. preterm probiotic.When performing statistical testing on multiple hypotheses, the Benjamini – Hochberg (BH) method was used to control the FDR at a level of 10%, and a PERMANOVA was performed to test the community structure differences. This was done by using the adonis2 function from the vegan R package with 1000 permutations and by = “margin”, thus assessing the marginal effects of the terms (i.e. each marginal term was analyzed in a model with all the other variables).