Fig. 1: Schematic of data analysis pipeline.

A We performed a voxel-based unbiased brain-wide association study (BWAS) method on resting-state fMRI data to identify pathology as revealed by the significantly altered functional connectivity in DS and NDS patients compared to CN after controlling for age, sex, education, intracranial volume, and framewise displacement. To further test the clinical relevance of the main identified functional links as diagnostic features of DS and NDS, we applied a pattern classification approach using the alterations in the ROI as a biomarker to test how well this could distinguish patients with DS and NDS from the CN. To further assess the clinical significance of identified altered functional links in DS and NDS, we used linear regression model to quantify the dependency between differences in functional connectivity and deficit symptom severity as assessed by the SDS scale. B We used a WGCNA approach to identify the transcription-neuroimaging association between BWAS FC differences in DS and NDS and gene expression from the AHBA. C We calculated the overlapped genes between DS-related and NDS-related genes and schizophrenia-related genes in SZDB dataset. D GO, KEEG, and disease enrichment analysis was applied for these overlapped and non- overlapped genes between DS and NDS. Furthermore, we showed spatio-temporal expression patterns of the identified key genes. DS deficit schizophrenia, NDS non-deficit schizophrenia, CN healthy controls, ROI region of interest, FC functional connectivity, SDS schedule for deficit syndrome, AHBA Allen Human Brain Atlas, SZDB A Database for Schizophrenia Genetic Research (http://www.szdb.org/), GO Gene Ontology, BP biological process, CC cellular component, MF molecular function, KEGG Kyoto Encyclopedia of Genes and Genomes.