Division of Genetics, Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology , University of Isfahan, Isfahan, Iran.
Cellular and Molecular Research Center, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
Cell Mol Neurobiol. 2024 Nov 6;44(1):74. doi: 10.1007/s10571-024-01504-2.
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.
自 1999 年至 2020 年，美加两国已有超过 932400 人死于阿片类药物过量，超过了艾滋病流行高峰期的死亡率。这两个国家的阿片类药物消费水平明显高于发达国家的平均水平。阿片类镇痛药既有治疗益处，也有重大健康风险，因此需要对药物进行平衡监管、谨慎处方和专门管理。细胞色素 P450 2D6（CYP2D6）系统（酶功能）在代谢阿片类药物方面的作用突显了基于基因型的镇痛的潜力。通过整合药物基因组学（PGx），这种方法旨在优化疼痛管理、提高安全性并降低成瘾风险。这一认识促使我们利用多因素维度缩减（MDR）来探索一系列表型，包括健康队列中的 PGx 和基因-基因相互作用（GGI），从而实现疼痛管理策略的个性化。该研究在 100 名无关联的西方伊朗健康个体和 100 名 1000 基因组计划个体中进行采样。预测试涉及使用 PharmGKB 数据库搜索与疼痛敏感性和炎症相关的 PGx 注释（与药物-基因-疾病相关的变异），确定了 128 个相关基因。问卷调查帮助选择了 100 名从未使用过强效阿片类药物但也使用过其他精神活性药物（如尼古丁、安非他命等）和与疾病相关的药物的个体。然后对伊朗队列中的这些基因进行全外显子组测序（WES）分析。进一步的分析包括 MDR 以识别协同的基因注释，以及 GGI 以通过可视化统计上位网络（ViSEN）探索复杂的基因相互作用。该研究从 128 个基因中确定了一个疼痛、抗炎和免疫调节药物（PAIma）面板，在 21 个经过整理的途径中产生了 55590 个注释。经过过滤，确定了 54 个显著的结构或调节变异。该研究还强调了涉及 CYP3A5 基因、hsa-miR-355-5p、帕利哌酮和 CYP2D6 的新的基因关系，这些关系需要进一步研究。这项研究提供了一个新的药物遗传学框架，有可能改变阿片类药物的处方实践，以减少滥用并增强个性化疼痛管理。来自多个国家和种族群体的这些发现的进一步验证可以指导临床医生实施基于 DNA 的阿片类药物处方，使治疗更符合个体的基因特征。
