Network-based drug repurposing for psychiatric disorders using single-cell genomics.

Area of Science:

• Neuroscience
• Genomics
• Pharmacology

Background:

• Effective treatments for neuropsychiatric disorders are limited by incomplete understanding of cellular and molecular mechanisms.
• Single-cell genomics offers a powerful approach to dissect brain cell heterogeneity and function in disease.

Purpose of the Study:

• To integrate population-scale single-cell genomics data to analyze cell-type-level gene regulatory networks in schizophrenia, bipolar disorder, and autism.
• To identify druggable targets and repurpose drugs for neuropsychiatric disorders using network medicine approaches.

Main Methods:

• Analysis of cell-type-specific gene regulatory networks from single-cell genomics data across 23 brain cell types.
• Application of graph neural networks for novel risk gene prioritization.
• Network-based drug repurposing framework to identify potential therapeutic agents.

Main Results:

• Identification of potential druggable transcription factors co-regulating known risk genes in specific cell types.
• Prioritization of novel risk genes and identification of 220 drug molecules for cell-type-specific targeting.
• Evidence for 37 drugs reversing disorder-associated transcriptional phenotypes and discovery of 335 drug-associated cell-type eQTLs.

Conclusions:

• The study provides a single-cell network medicine resource with mechanistic insights for neuropsychiatric disorders.
• Identified drug candidates and genetic insights offer a foundation for developing targeted therapeutic strategies.
• This work advances the understanding of genetic variation's role in drug response at the cell-type level.