PubMed · 40972584
Network-based drug repurposing for psychiatric disorders using single-cell genomics.
Abstract
Neuropsychiatric disorders lack effective treatments due to a limited understanding of the underlying cellular and molecular mechanisms. To address this, we integrated population-scale single-cell genomics data and analyzed 23 cell-type-level gene regulatory networks across schizophrenia, bipolar disorder, and autism. Our analysis revealed potential druggable transcription factors co-regulating known risk genes that converge into cell-type-specific co-regulated modules. We applied graph neural networks on those modules to prioritize novel risk genes and leveraged them in a network-based drug repurposing framework to identify 220 drug molecules with the potential for targeting specific cell types. We found evidence for 37 of these drugs in reversing disorder-associated transcriptional phenotypes. Additionally, we discovered 335 drug-cell quantitative trait loci (eQTLs), revealing genetic variation's influence on drug target expression at the cell-type level. Our results provide a single-cell network medicine resource that provides potential mechanistic insights for advancing treatment options for neuropsychiatric disorders.
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Chirag Gupta, Noah Cohen Kalafut, Declan Clarke, Jerome J Choi, Kalpana Hanthanan Arachchilage, Saniya Khullar, Yan Xia, Xiao Zhou, Cagatay Dursun, Mark Gerstein, Daifeng Wang. 2025-09-18. Network-based drug repurposing for psychiatric disorders using single-cell genomics.. https://doi.org/10.1016/j.xgen.2025.101003
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