From gene networks to drugs: systems pharmacology approaches for AUD

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 psychiatric illnesses. We highlight studies that successfully apply gene mapping computational approaches to identify or repurpose pharmaceutical treatments for psychiatric illnesses. Furthermore, we address important challenges that must be overcome to maximize the potential of these strategies to translate to the clinic and improve healthcare outcomes.

Topological network measures for drug repositioning

“…Several databases are now recording gene expression signatures of known/approved drugs to document the extent of drug action. Some methods look for drugs that show gene expression signature reversals of those in diseased states, so as to turn the disease phenotype into a healthy one [ 35 ]. Literature mining to build relationship graphs [ 36 ], deep learning using gene expression profiles on perturbagen treatments [ 37 ], using structural similarity between proteins, drugs, molecular docking techniques [ 25 ], pathway-based target identification [ 38 ], are among the many approaches seen.…”

Scn4b regulates the hypnotic effects of ethanol and other sedative drugs

“…32,33 These studies provided evidence that gene expression profiling can identify molecular determinants of ethanol drinking and that neuroimmune/inflammatory pathways are relevant targets. 36 Institute, University of California San Diego, USA) for the NeuroExpress software. 34 Many single genetic deletions in mice have been associated with decreased ethanol consumption, 35 but most were based on the known function of the gene from behavioral traits.…”

“…A better alternative to the single gene approach may be to integrate expression signatures in different brain areas, species and stages of alcohol addiction with computational, systems pharmacology approaches to identify drug targets for the altered gene networks. 36 Institute, University of California San Diego, USA) for the NeuroExpress software.…”

A Pathway-Based Genomic Approach to Identify Medications: Application to Alcohol Use Disorder

“…These databases include the gene expression responses to thousands of pharmacological agents applied to human cell lines. Researchers have used these databases to perform in silico gene mapping to identify drugs that are predicted to reverse disease-related gene expression levels and treat various diseases, including several cancers, inflammatory diseases, and brain diseases, among others [18][19][20][21]. The goal of gene mapping is to assess the similarity of the pharmacological-induced gene expression signatures to the gene expression signatures from a biological state of interest, for example, a disease state.…”