In this paper, we introduce a novel method to discover common and distinct structural connectivity patterns between SZP and MDD via a Cluster-Driven Nonnegative Matrix Factorization (called CD-NMF). Specifically, CD-NMF is applied to decompose the joint structural connectivity map into common and distinct parts, and each part is further factorized into two sub-matrices (i.e. common/distinct basis matrix and common/distinct encoding matrix) correspondingly. By imposing the clustering constraints on common and distinct encoding matrices, the discriminative patterns as well as the common patterns between the two disorders are extracted simultaneously. Experimental results demonstrate that CDNMF allows finding the common and distinct structural patterns effectively. More importantly, the derived distinct patterns, show powerful ability to discriminate the patients of schizophrenia and major depressive disorder.