That's the main drawback of PCA - the principal components are linear combinations of all the original features. An attempt to remedy this is callled Sparse PC

That's the main drawback of PCA - the principal components are linear combinations of all the original features. An attempt to remedy this is callled Sparse PCA (you can look it up on Google Scholar), in which the principal components are combinations of only a few features. This allows you to figure out which features are not important.