BACKGROUND: Individual response to opioid analgesics varies among patients. OBJECTIVE: This study sought to clarify the impact of distinct genetic variations on pain, opioid consumption, and opioid side effects in patients with postoperative pain. STUDY DESIGN: A systematic review and meta-analysis of associations between genetic single-nucleotide polymorphisms (SNPs) and opioids used for acute postoperative pain. SETTING: This meta-analysis examined all studies involving an association between genetic polymorphisms and the analgesic efficacy or clinical outcome of opioid analgesics for postoperative pain. METHODS: A literature search was performed up to January 31, 2014, using the PubMed, EMBase, ISI Web of Science, and Cochrane Library databases. RESULTS: Fifty-nine studies were included in this systematic review, and 23 studies (a total of 5,902 patients) were included in the final meta-analysis. The results showed that human μ-opioid receptor gene (OPRM1) 118G allele variant carriers consumed more opioids for analgesia (SMD = -0.17, 95% CI = [-0.25, -0.10], P < 0.00001), but reported higher pain scores (MD = -0.11, 95% CI = [-0.17, -0.04], P = 0.002) and less nausea and vomiting (odds ratio = 1.30, 95% CI = [1.08, 1.55], P = 0.005) than the homozygous 118AA patients during the first 24 hour but not the 48 hour postoperative period. Moreover, CYP3A4*1G carriers consumed less opioids than homozygous CYP3A4*1/*1 patients during the first 24 hours postoperative period (MD = 45.12, 95% CI = [36.17, 54.06], P < 0.00001). No significant differences were found in CYP3A5*3, ABCB1 C3435T, and G2477T/A genetic polymorphisms. LIMITATIONS: Some potential non-genetic factors can modify the effects of gene SNP on pain and opioid consumption during the postoperative period, such as age, gender, mood, anxiety, and drug-drug interactions. But further analyses could not be performed in the present meta-analysis due to limited information. CONCLUSION: The results indicate that among the genetic SNPs we studied which include those affecting analgesic drug metabolism, transport of analgesic agents across the blood-brain barrier, and their activity at target receptors and ion channels and in the modulation of neurotransmitter pathways, the A118G allele variant of OPRM1 has the most potent influence on pain management of postoperative patients. Opioid receptor gene information may provide valuable information for clinicians to properly manage the analgesic use of opioids individually for better pain management.
BACKGROUND: Individual response to opioid analgesics varies among patients. OBJECTIVE: This study sought to clarify the impact of distinct genetic variations on pain, opioid consumption, and opioid side effects in patients with postoperative pain. STUDY DESIGN: A systematic review and meta-analysis of associations between genetic single-nucleotide polymorphisms (SNPs) and opioids used for acute postoperative pain. SETTING: This meta-analysis examined all studies involving an association between genetic polymorphisms and the analgesic efficacy or clinical outcome of opioid analgesics for postoperative pain. METHODS: A literature search was performed up to January 31, 2014, using the PubMed, EMBase, ISI Web of Science, and Cochrane Library databases. RESULTS: Fifty-nine studies were included in this systematic review, and 23 studies (a total of 5,902 patients) were included in the final meta-analysis. The results showed that human μ-opioid receptor gene (OPRM1) 118G allele variant carriers consumed more opioids for analgesia (SMD = -0.17, 95% CI = [-0.25, -0.10], P < 0.00001), but reported higher pain scores (MD = -0.11, 95% CI = [-0.17, -0.04], P = 0.002) and less nausea and vomiting (odds ratio = 1.30, 95% CI = [1.08, 1.55], P = 0.005) than the homozygous 118AA patients during the first 24 hour but not the 48 hour postoperative period. Moreover, CYP3A4*1G carriers consumed less opioids than homozygous CYP3A4*1/*1 patients during the first 24 hours postoperative period (MD = 45.12, 95% CI = [36.17, 54.06], P < 0.00001). No significant differences were found in CYP3A5*3, ABCB1C3435T, and G2477T/A genetic polymorphisms. LIMITATIONS: Some potential non-genetic factors can modify the effects of gene SNP on pain and opioid consumption during the postoperative period, such as age, gender, mood, anxiety, and drug-drug interactions. But further analyses could not be performed in the present meta-analysis due to limited information. CONCLUSION: The results indicate that among the genetic SNPs we studied which include those affecting analgesic drug metabolism, transport of analgesic agents across the blood-brain barrier, and their activity at target receptors and ion channels and in the modulation of neurotransmitter pathways, the A118G allele variant of OPRM1 has the most potent influence on pain management of postoperative patients. Opioid receptor gene information may provide valuable information for clinicians to properly manage the analgesic use of opioids individually for better pain management.
Authors: Jennifer F Waljee; David C Cron; Rena M Steiger; Lin Zhong; Michael J Englesbe; Chad M Brummett Journal: Ann Surg Date: 2017-04 Impact factor: 12.969
Authors: Andrzej Wasilewski; Urszula Lewandowska; Paula Mosinska; Cezary Watala; Martin Storr; Jakub Fichna; Thangam Venkatesan Journal: Am J Gastroenterol Date: 2017-03-28 Impact factor: 10.864
Authors: Ke Peng; Meryem A Yücel; Christopher M Aasted; Sarah C Steele; David A Boas; David Borsook; Lino Becerra Journal: Neurophotonics Date: 2017-10-16 Impact factor: 3.593
Authors: Heba Khalil; Susan M Sereika; Feng Dai; Sheila Alexander; Yvette Conley; Gary Gruen; Li Meng; Peter Siska; Ivan Tarkin; Richard Henker Journal: Biol Res Nurs Date: 2016-11-30 Impact factor: 2.522
Authors: Sara J Hyland; Kara K Brockhaus; William R Vincent; Nicole Z Spence; Michelle M Lucki; Michael J Howkins; Robert K Cleary Journal: Healthcare (Basel) Date: 2021-03-16
Authors: Emily E Hartwell; Richard Feinn; Paige E Morris; Joel Gelernter; John Krystal; Albert J Arias; Michaela Hoffman; Ismene Petrakis; Ralitza Gueorguieva; Joseph P Schacht; David Oslin; Raymond F Anton; Henry R Kranzler Journal: Addiction Date: 2020-02-11 Impact factor: 6.526