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ORIGINAL RESEARCH article

Front. Pharmacol.

Sec. Translational Pharmacology

Volume 16 - 2025 | doi: 10.3389/fphar.2025.1629866

A case-control study on individualized use of opioid analgesics based on single nucleotide polymorphism

Provisionally accepted
Jing  YangJing Yang1,2Zheng  FuZheng Fu3Shu  Han ZhouShu Han Zhou4Lei  ZhengLei Zheng2liang-Wei  Sunliang-Wei Sun2*chao  Songchao Song2*
  • 1School of Management, Ocean University of China, Qingdao, China
  • 2Department of Pharmacy, Shandong Provincial Third Hospital, Cheeloo College of Medicine, Shandong University, Jian, China
  • 3Department of Pharmacy, Shandong Medical College, jinan, China
  • 4School of Medicine and Pharmacy, Ocean University of China, qingdao, China

The final, formatted version of the article will be published soon.

Objective: To explore the relationship between gene polymorphism and the efficacy and adverse reactions (ADR) of opioid analgesics, improve medication safety, and promote personalized medication. Methods:Firstly, the method of evidence-based medicine retrieval and evaluation was adopted to systematically summarize the opioid analgesic drug ADR and efficacy related gene loci currently recommended by guidelines, authoritative genetic information databases, and low bias clinical trial studies. The gene loci with strong correlation evaluation were selected as target genes for testing. Then, a clinical case-control trial was designed, divided into two groups: ADR research group and dose demand research group. A total of 480 enrolled patients were tested for target genes. Finally, the gene test results were evaluated for ADR association and drug dose association using SPSS 26.0 software and SNPStats tool. Results: 4 genes were selected for detection: CYP2D6, CYP3A5*3, ABCB1 and OPRM1. The results of the correlation analysis showed that in the ADR research group, compared with the control subgroup, the OPRM1 (rs1799971, A>G) AG+GG type distribution was less and the AA type distribution was more in the observation subgroup (P<0.05). Individual statistics of patients using oxycodone also revealed differences in OPRM1 (rs1799971, A>G). The SNPStats program was used to analyze the association between SNP polymorphism and ADR in 5 genetic models. The results showed that co dominant, dominant, and allele models all suggested a significant association between OPRM1 (rs1799971) and ADR incidence (P<0.05). In the dose demand evaluation group, The results showed that there was no significant difference in genotype distribution between the observation subgroup and the control subgroup (P>0.05). However, attention should be paid to the ABCB1 gene. At the current sample size, the ABCB1 (rs1045642, C>T) CC+CT ratio in the observation subgroup tends to be higher than that in the control subgroup compared to TT. Conclusion: OPRM1 (rs1799971) AA genotype patients have a higher risk of ADR. The patients should pay more attention to ADR and the dosage can be started from low doses. The association between dose demand and SNPs needs to be evaluated in more cases, and it is suggested to pay attention to the ABCB1 gene.

Keywords: Opioid analgesics, Single nucleotide polymorphism, Adverse drug reaction (ADR), Drug dose demand, Personalized medication

Received: 19 May 2025; Accepted: 21 Jul 2025.

Copyright: © 2025 Yang, Fu, Zhou, Zheng, Sun and Song. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
liang-Wei Sun, Department of Pharmacy, Shandong Provincial Third Hospital, Cheeloo College of Medicine, Shandong University, Jian, China
chao Song, Department of Pharmacy, Shandong Provincial Third Hospital, Cheeloo College of Medicine, Shandong University, Jian, China

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