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Related Concept Videos

Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...

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Preparation of Neuronal Co-cultures with Single Cell Precision
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Network-based drug repurposing for psychiatric disorders using single-cell genomics.

Chirag Gupta1, Noah Cohen Kalafut2, Declan Clarke3

  • 1Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53076, USA.

Cell Genomics
|September 19, 2025
PubMed
Summary
This summary is machine-generated.

This study integrates single-cell genomics and gene networks to find new drug targets for neuropsychiatric disorders like schizophrenia and autism. It identifies potential medicines that could reverse disease-related gene expression changes in specific brain cells.

Keywords:
cell-type-disorder genesdrug repurposingpsychiatric disorderssingle-cell network medicine

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Area of Science:

  • Neuroscience
  • Genomics
  • Pharmacology

Background:

  • Neuropsychiatric disorders lack effective treatments due to poor understanding of cellular and molecular mechanisms.
  • Existing treatments are limited by incomplete knowledge of disease underpinnings.

Purpose of the Study:

  • To identify druggable targets and repurpose drugs for neuropsychiatric disorders using single-cell genomics.
  • To create a cell-type-specific network medicine resource for advancing treatment options.

Main Methods:

  • Integrated population-scale single-cell genomics data from schizophrenia, bipolar disorder, and autism.
  • Analyzed 23 cell-type-level gene regulatory networks.
  • Applied graph neural networks for risk gene prioritization and network-based drug repurposing.

Main Results:

  • Identified co-regulated modules and potential druggable transcription factors linked to neuropsychiatric risk genes.
  • Prioritized novel risk genes and identified 220 drug molecules for cell-type-specific targeting.
  • Found evidence for 37 drugs reversing disorder-associated transcriptional phenotypes.
  • Discovered 335 drug-cell quantitative trait loci (eQTLs) impacting drug target expression.

Conclusions:

  • The study provides a valuable single-cell network medicine resource.
  • Offers potential mechanistic insights for developing novel therapeutic strategies for neuropsychiatric disorders.
  • Highlights the importance of cell-type-specific genetic variations in drug response.