AIM: A finite number of variants in the OPRM1, COMT, MC1R, ABCB1 and CYP2D6 genes has been identified to significantly modulate the effects of opioids in controlled homogenous settings. We analyzed the imprint of these variants in opioid therapy in a highly variable cohort of pain patients treated in outpatient units to test whether genotyping may play a role in this clinical setting. METHODS: In a multicenter study conducted in tertiary care outpatient pain centers, 352 patients (156 men and 196 women, aged 58.5+/- 14.6 years) treated for 1-600 months (63.4 +/- 92.4 months) with various opioids for pain of various origins were included. Genotyping was performed for all the variants reportedly modulating pain in well-defined cohorts. Association analyses focused on opioid dosing, the actual 24-h pain score on a 0-10 rating scale and the occurrence of side effects. RESULTS: The frequency of the genetic variants in the patients did not significantly differ from that in the average Caucasian population. Daily opioid doses ranged from 4 to 1750 mg oral morphine equivalents (133.4 +/- 203.2 mg) and significantly decreased in a gene dose-dependent manner with the P-glycoprotein variant ABCB1 3435C>T. Pain was rated on average at 3.7 +/- 2.6. There was a tendency towards increased pain in a gene dose-dependent manner with the mu-opioid receptor variant OPRM1 118A>G. CONCLUSION: Genetics were reflected in the outpatient pain therapy only to a modest degree. The need of outpatient therapy of pain of various causes guided by the presently known functional genetic variants cannot be convincingly concluded from the present data. Using the ABCB1 3435 genotype to predefine lower individual opioid doses barely merits the laboratory effort. If any, the results suggest that a genetics guided outpatient pain therapy may be based on ABCB1 and OPRM1 variants.
AIM: A finite number of variants in the OPRM1, COMT, MC1R, ABCB1 and CYP2D6 genes has been identified to significantly modulate the effects of opioids in controlled homogenous settings. We analyzed the imprint of these variants in opioid therapy in a highly variable cohort of painpatients treated in outpatient units to test whether genotyping may play a role in this clinical setting. METHODS: In a multicenter study conducted in tertiary care outpatientpain centers, 352 patients (156 men and 196 women, aged 58.5+/- 14.6 years) treated for 1-600 months (63.4 +/- 92.4 months) with various opioids for pain of various origins were included. Genotyping was performed for all the variants reportedly modulating pain in well-defined cohorts. Association analyses focused on opioid dosing, the actual 24-h pain score on a 0-10 rating scale and the occurrence of side effects. RESULTS: The frequency of the genetic variants in the patients did not significantly differ from that in the average Caucasian population. Daily opioid doses ranged from 4 to 1750 mg oral morphine equivalents (133.4 +/- 203.2 mg) and significantly decreased in a gene dose-dependent manner with the P-glycoprotein variant ABCB1 3435C>T. Pain was rated on average at 3.7 +/- 2.6. There was a tendency towards increased pain in a gene dose-dependent manner with the mu-opioid receptor variant OPRM1 118A>G. CONCLUSION: Genetics were reflected in the outpatientpain therapy only to a modest degree. The need of outpatient therapy of pain of various causes guided by the presently known functional genetic variants cannot be convincingly concluded from the present data. Using the ABCB1 3435 genotype to predefine lower individual opioid doses barely merits the laboratory effort. If any, the results suggest that a genetics guided outpatientpain therapy may be based on ABCB1 and OPRM1 variants.
Authors: Eric W Klee; Henning Schneider; Karl J Clark; Margot A Cousin; Jon O Ebbert; W Michael Hooten; Victor M Karpyak; David O Warner; Stephen C Ekker Journal: Hum Genet Date: 2011-12-30 Impact factor: 4.132
Authors: K R Crews; A Gaedigk; H M Dunnenberger; T E Klein; D D Shen; J T Callaghan; E D Kharasch; T C Skaar Journal: Clin Pharmacol Ther Date: 2011-12-28 Impact factor: 6.875
Authors: Shannon N Saldaña; David K Hooper; Tanya E Froehlich; Kathleen M Campbell; Cynthia A Prows; Senthilkumar Sadhasivam; Todd G Nick; Michael Seid; Alexander A Vinks; Tracy A Glauser Journal: Clin Ther Date: 2011-12-02 Impact factor: 3.393
Authors: Konrad Meissner; Michael J Avram; Viktar Yermolenka; Amber M Francis; Jane Blood; Evan D Kharasch Journal: Anesthesiology Date: 2013-10 Impact factor: 7.892
Authors: Catherine L Carpenter; Angela M Wong; Zhaoping Li; Ernest P Noble; David Heber Journal: Obesity (Silver Spring) Date: 2013-05-13 Impact factor: 5.002