We combine VBM and TBSS analysis to investigate GM/WM changes in TS children. We apply most-representative-subject TBSS procedure suitable for young children. We integrate multi-modal image features using multiple kernel learning. We achieved an excellent accuracy of 94.24%. We identify the most discriminative ROIs and features for classification.