Statistical Analysis
Statistical analyses were processed
by R (v.4.0.3; R Foundation for Statistical Computing, Vienna, Austria)
following the workflow presented by Kim To investigate
age and product effects, the previously selected features with significant
postprandial response were tested by f1.ld.f1 using the iAUCs (nparLD,
p < 0.05). If a feature showed significant differences in the acute
response between the YA and OA groups (age effect) or after milk or
yogurt intake (product effect), a Wilcoxon signed-rank test was applied
to identify which of the groups responded significantly: a feature
with a significant product effect was confirmed by the test in the
separate age group (YA-M The features showing
a significant product and/or age effect were
then manually integrated with MassHunter Quantitative Analysis (Agilent
Technology, v10.1) on all batches to remove analytical false positives,
and signal drift was corrected via the QC-based robust locally estimated
scatterplot smoothing signal (LOESS) correction methodTo test the behavior of the above molecules during the 3 week restriction
phase eliminating dairy products and significantly reducing fermented
foods, the manually integrated postprandial features were tested for
treatment (Postprandial kinetics were visualized
using heatmaps generated
with hcluster from the R package amap (version 0.8-19).