PGx-Based in silico Analyses Identifies the Interactive Role of Genes, Glucose Metabolism and Dopaminergic Dysfunctional Pathways with Chronic Cocaine use and Misuse
Year: 2025
Type: article
Abstract: Introduction: Our team conducted a pharmacogenomics (PGx) analysis to evaluate the interactions between cocaine, glucose metabolism, and functional connectivity using in-depth silico PGx methods. Methods: Utilizing PharmGKB, we extracted PGx annotations related to cocaine, glucose, and dopamine (raw data). After filtering, we refined a list of 49 unrepeated, brain-expressed genes and examined their interactions in a protein-protein interaction (PPI) network through STRING-MODEL, identifying top candidate genes. Results: Targeting key protein-coding genes with the highest connectivity, we identified COMT, DRD2, and SLC6A3, along with their 17 connected genes. A deep dive into gene-miRNA interactions (GMIs) using NetworkAnalyst revealed that COMT, DRD2, and hsa-miR-16-5p have multiple interactions with OPRM1 and BDNF. Enrichment analysis via Enrichr confirmed that this refined set of 17 impacts dopamine function and are interactive with dopaminergic pathways. Notably, Substance Use disorders (SUD) were the most significant manifestation predicted for the interplays among these genes. Discussion: Reviewing all PGx annotations for the 17 genes, we found 4,665 PGx entries, among which 1,970 were significant, with a p-value above 0.045. These were ultimately filtered down to 32 potential PGx annotations excluded in association with “Cocaine,” “Glucose or Diabetes,” and “Dopamine”. Accordingly, 12 Pharmacogenes represented 32 PGx-associated with Cocaine, Glucose, and Dopamine, including DRD2, COMT, OPRD1, OPRM1, SLC6A3, CHRNA5, CNR1, CYP2C19, DBH, GABRA2, NOS1AP, and SYT1. Conclusion: This in silico PGx analysis demonstrates strong, validated connections based on prior published data and robust computational predictions. Among the findings, the COMT gene was found to be the best-scoring gene here.
Source: Current Neuropharmacology
Authors: Alireza Sharafshah, Panayotis K. Thanos, Albert Pinhasov, Abdalla Bowirrat, Colin Hanna, Kai-Uwe Lewandrowski, Christopher Rowan, Igor Elman, Mark S. Gold, Catherine A. Dennen, Edward J. Modestino, Rajendra D. Badgaiyan, David Baron, Brian Fuehrlein, Ashim Gupta, Jean Lud Cadet, Aryeh R. Pollack, Jag Khalsa, Milan Makale, Alexander P.L. Lewandrowski, Kenneth Blum
Institutions: Guilan University of Medical Sciences, University of Guilan, Ariel University, University at Buffalo, State University of New York, Fundación Universitaria Sanitas, Universidade Federal do Estado do Rio de Janeiro, Cambridge Health Alliance, Harvard University, Washington University in St. Louis, Thomas Jefferson University Hospital, Curry College, Case Western Reserve University, Western University of Health Sciences, Yale New Haven Hospital, Yale University, National Institutes of Health, National Institute on Drug Abuse, University of Maryland, Baltimore, University of California San Diego, University of Southern California
Language: English
Subfield: Pharmacology
Domain: Life Sciences
Open Access status: green
Award: G7787933682
OpenAlex ID: W4414524869