For most datasets analyzed in MetaboAnalyst, the PLS-DA results should be taken as exploratory, to identify potential patterns in the dataset. For a deeper understanding of the permutation p-value in the PLS-DA module, see this post.
Omics datasets often have very low sample size (n = 3 is especially low), where the statistical power is quite low for moderate effect sizes, even if though many of these moderate effect sizes could still be biologically relevant. You can combat this by looking from the data from multiple perspectives (ie. differential abundance analysis, pathway analysis, PCA, PLS-DA, etc) and looking for consistent trends.