I think rather than the biplot and correlation you might want to look into either complex tensor factorization in Gemelli or rPCA in DEICODE. The advantage of these over traditional metrics is that the features are embded in the ordination, so you can use them to figure out what side of the ordination features are associated with... or to even build ALRs if you're into amalgamated microbial statistics. I happen to really like amalgamated values
If it's helpful or interesting, I'll mention that I recently did something similar and our preprint is out. (Manuscript is still under review). I used Gemelli to look for directional changes between tissue types between two survival groups. Sub tissue for time point and survival group for treatment, and I think its similar.
Best,
Justine