Synergistic Epistasis and Systems Biology Approaches to Uncover a Pharmacogenomic Map Linked to Pain, Anti-Inflammatory and Immunomodulating Agents (PAIma) in a Healthy Cohort

Abstract

The global public health addiction crisis has been stark, with over 932,400 deaths in the USA and Canada from opioid overdose since 1999–2020, surpassing the mortality rates at the top of the HIV/AIDS epidemic. Both nations exhibit opioid consumption rates significantly above the norm for developed countries. Analgesic type of opioids present both therapeutic benefits and substantial health risks, necessitating balanced drug regulation, careful prescribing, and dedicated opioid stewardship. The role of the cytochrome P450 2D6 (CYP2D6) system (Enzymatic functions) in metabolizing opioids highlights the potential of genotype-guided analgesia. By integrating Pharmacogenomics (PGx), this approach aims to optimize pain management, enhance safety, and reduce addiction risks. This understanding prompted the utilization of multifactor dimensionality reduction (MDR) to explore a range of phenotypes including PGx and gene–gene interactions (GGI) in a healthy cohort, thereby personalizing pain management strategies. The study sampled 100 unrelated healthy Western Iranians and 100 individuals from the 1000 Genome Project. Pre-testing involved searching for PGx annotations (variants associated with drug-gene-diseases) related to pain sensitivity and inflammation using the PharmGKB database, which identified 128 relevant genes. A questionnaire helped select 100 participants who had never used potent opioids but also other psychoactive agents (e.g., nicotine, amphetamines, etc.) and disease-related drugs. Whole-exome sequencing (WES) was then employed to analyze these genes in an Iranian cohort. Further analyses included MDR for identifying synergistic gene annotations and GGI for exploring complex gene interactions through the Visualization of Statistical Epistasis Networks (ViSEN). The study identified a Pain, Anti-Inflammatory, and Immunomodulating agents (PAIma) panel from the 128 genes, resulting in 55,590 annotations across 21 curated pathways. After filtering, 54 significant structural or regulatory variants were identified. This research also highlighted novel gene relationships involving the CYP3A5 gene, hsa-miR-355-5p, Paliperidone, and CYP2D6, which warrant further investigation. This study offers a novel pharmacogenetic framework that could potentially transform opioid prescribing practices to mitigate misuse and enhance personalized pain management. Further validation of these findings from multi countries and ethnic groups could guide clinicians in implementing DNA-based opioid prescribing, aligning treatment more closely with individual genetic profiles. Graphical abstract