@dowdlelt and @handwerkerd might be the best folks to answer this, but my first thought is that there is probably a lot of redundant info between the two sets of regressors, and including both would probably be a bit of a hit to your degrees of freedom.
The orthogonalization step will orthogonalize all noise regressors w.r.t. the signal regressors, so you would end up with your 36P regressors being modified as well. If you think that the 36P regressors would include noise signals that also appear in the tedana signal regressors, then that would definitely be an issue. My understanding of the literature is that multi-echo denoising cannot identify BOLD-based noise (e.g., physiological noise), so if you expect the 36P regressors to include signals that reflect BOLD-based noise from non-neural physiological processes, then you should avoid orthogonalizing them w.r.t. the tedana signal regressors.
An alternative might be to orthogonalize the tedana noise regressors w.r.t. its signal regressors before feeding them into XCP-D.