Literature DB >> 22701325

Pain management with morphine: variation in analgesic response secondary to genetic polymorphisms.

Shailendra Kapoor1.   

Abstract

Entities:  

Year:  2012        PMID: 22701325      PMCID: PMC3373199          DOI: 10.2147/TCRM.S32184

Source DB:  PubMed          Journal:  Ther Clin Risk Manag        ISSN: 1176-6336            Impact factor:   2.423


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To the editor

The recent article by Villesen et al in a recent issue of your journal was most interesting.1 Recent studies show that the potency of morphine in efficacious pain control may be influenced greatly by polymorphisms of certain genes. For instance, Klepstad et al have recently shown that cancer patients on opioid maintenance therapy who are homozygous for the variant G allele of the 118 A > G polymorphism of the mu opioid receptor (OPRM1) gene require higher doses of morphine for efficacious pain control in comparison with patients who are heterozygous.2 In fact, the morphine requirement is almost 93% less in AA genotypes in contrast with morphine requirements in cancer patients who carry the GG genotype of the OPRM1 gene.3 Similar pain modulation variation is seen with polymorphisms of the OPRM1 gene and perioperative fentanyl administration.4 Furthermore, more profound CNS depressant side effects after morphine administration are noticed in cancer patients with certain polymorphisms of the multidrug resistance-1 gene.5 Similarly, the potency of morphine in pain management in cancer patients is influenced and varies greatly with polymorphisms of the catechol-O-methyl transferase gene.6 For instance, individuals with the Met/Met genotype of the catechol-O-methyl transferase gene require 63% less morphine in comparison with those who have the Val/Val genotype of the catechol-O-methyl transferase gene.3 More profound central nervous system side effects are seen following morphine administration in cancer patients with single nucleotide polymorphisms in intron 1 of the catechol-O-methyl transferase gene.5 The above examples clearly illustrate the variation in adequate pain control with morphine secondary to genetic mutations. Further research is needed to identify other similar gene polymorphisms that may affect opioid requirements in patients being managed with other nonmorphine narcotics.
  6 in total

1.  The 118 A > G polymorphism in the human mu-opioid receptor gene may increase morphine requirements in patients with pain caused by malignant disease.

Authors:  P Klepstad; T T Rakvåg; S Kaasa; M Holthe; O Dale; P C Borchgrevink; C Baar; T Vikan; H E Krokan; F Skorpen
Journal:  Acta Anaesthesiol Scand       Date:  2004-11       Impact factor: 2.105

2.  Exploring joint effects of genes and the clinical efficacy of morphine for cancer pain: OPRM1 and COMT gene.

Authors:  Cielito C Reyes-Gibby; Sanjay Shete; Trude Rakvåg; Samrat V Bhat; Frank Skorpen; Eduardo Bruera; Stein Kaasa; Pål Klepstad
Journal:  Pain       Date:  2006-12-06       Impact factor: 6.961

3.  Polymorphism of the micro-opioid receptor gene (OPRM1 118A>G) affects fentanyl-induced analgesia during anesthesia and recovery.

Authors:  Wei Dong Wu; Yi Wang; Yong Ming Fang; Hai Yan Zhou
Journal:  Mol Diagn Ther       Date:  2009       Impact factor: 4.074

4.  Genetic variation and response to morphine in cancer patients: catechol-O-methyltransferase and multidrug resistance-1 gene polymorphisms are associated with central side effects.

Authors:  Joy R Ross; Julia Riley; Annie B Taegetmeyer; Hiroe Sato; Sophy Gretton; Roland M du Bois; Kenneth I Welsh
Journal:  Cancer       Date:  2008-03-15       Impact factor: 6.860

5.  Genetic variation in the catechol-O-methyltransferase (COMT) gene and morphine requirements in cancer patients with pain.

Authors:  Trude T Rakvåg; Joy R Ross; Hiroe Sato; Frank Skorpen; Stein Kaasa; Pål Klepstad
Journal:  Mol Pain       Date:  2008-12-18       Impact factor: 3.395

6.  Pharmacokinetics of morphine and oxycodone following intravenous administration in elderly patients.

Authors:  Hanne H Villesen; Anne-Marie Banning; Rasmus H Petersen; Sebatian Weinelt; Jesper B Poulsen; Steen H Hansen; Lona L Christrup
Journal:  Ther Clin Risk Manag       Date:  2007-10       Impact factor: 2.423

  6 in total

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