Suppose an Euclidean distance $D\in\mathbb{R}^{n\times n}$ matrix between a set of $n$ objects is given. To obtain inner-products (which will be further be used to recover coordinates), entries of $D$ are squared, and the matrix is double-centered and scaled, ie., $K=-\frac{1}{2}JD^{(2)}J$, where matrix $J=I-\frac{1}{n}11^T$ defines the origin wrt which the inner-products are formed. So, the aim is to reconstruct coordinates $X$ that give rise to inner products $K$, $$K=-\frac{1}{2}JD^{(2)}J=JXX^TJ.$$ This is done by eigendecomposition of $K$.
Given the above equation, I wonder if one could use a shortcut $-\frac{1}{2}D^{(2)}=XX^T$, ie, obtain coordinates $X$ without double-centering $-\frac{1}{2}D^{(2)}$ (matrix $J$ is removed from the left and from the right).