From gene networks to drugs: systems pharmacology approaches for AUD

Psychopharmacology
Laura B FergusonRoy Dayne Mayfield

Abstract

The alcohol research field has amassed an impressive number of gene expression datasets spanning key brain areas for addiction, species (humans as well as multiple animal models), and stages in the addiction cycle (binge/intoxication, withdrawal/negative effect, and preoccupation/anticipation). These data have improved our understanding of the molecular adaptations that eventually lead to dysregulation of brain function and the chronic, relapsing disorder of addiction. Identification of new medications to treat alcohol use disorder (AUD) will likely benefit from the integration of genetic, genomic, and behavioral information included in these important datasets. Systems pharmacology considers drug effects as the outcome of the complex network of interactions a drug has rather than a single drug-molecule interaction. Computational strategies based on this principle that integrate gene expression signatures of pharmaceuticals and disease states have shown promise for identifying treatments that ameliorate disease symptoms (called in silico gene mapping or connectivity mapping). In this review, we suggest that gene expression profiling for in silico mapping is critical to improve drug repurposing and discovery for AUD and other ps...Continue Reading

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Citations

Mar 1, 2019·Genes, Brain, and Behavior·Yuri A BlednovRobert A Harris
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Dec 22, 2020·Briefings in Bioinformatics·Apurva BadkasThomas Sauter

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Datasets Mentioned

BETA
GSE70138
GSE92742

Methods Mentioned

BETA
pharmacotherapies
geneotyping
SeT
gene knockdown
transgenic
genotyping

Clinical Trials Mentioned

NCT00457197
NCT00114686
NCT00223249
NCT00550394
NCT00434876
NCT00156715
NCT00352469
NCT02918370
NCT00929344
NCT00248612

Software Mentioned

Sig
SPIED
GeneGO Metacore for Process Networks
gutc
ChemBioServer
Ingenuity Pathway Analysis ( IPA® ) Tool
- Set Enrichment Analysis ( GSEA )
ENCODE
NetworkAnalyst
SPIEDw

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