Abstract
Opioid analgesics are commonly used for the treatment of acute as well as chronic, moderate to severe pain. Well-known, however, is the wide interindividual variability in sensitivity to opioids that exists, which has often been a critical problem in pain treatment. To date, only a limited number of studies have addressed the relationship between human genetic variations and sensitivity to opioids, and such studies are still in their early stages. Therefore, revealing the relationship between genetic variations in many candidate genes and individual differences in sensitivity to opioids will provide valuable information for appropriate individualization of opioid doses required for adequate pain control. Although the methodologies for such association studies can be diverse, here we summarize protocols for investigating the association between genetic polymorphisms and sensitivity to opioids in human volunteers and patients undergoing painful surgery.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ikeda K, Ide S, Han W, Hayashida M, Uhl GR, Sora I (2005) How individual sensitivity to opiates can be predicted by gene analyses. Trends Pharmacol Sci 26:311–317
Coulbault L, Beaussier M, Verstuyft C, Weickmans H, Dubert L, Trégouet D, Descot C, Parc Y, Lienhart A, Jaillon P, Becquemont L (2006) Environmental and genetic factors assoÂciated with morphine response in the postoperative period. Clin Pharmacol Ther 79:316–324
Bruehl S, Chung OY, Donahue BS, Burns JW (2006) Anger regulation style, postoperative pain, and relationship to the A118G mu opioid receptor gene polymorphism: a preliminary study. J Behav Med 29:161–169
Chou WY, Wang CH, Liu PH, Liu CC, Tseng CC, Jawan B (2006) Human opioid receptor A118G polymorphism affects intravenous patient-controlled analgesia morphine consumption after total abdominal hysterectomy. Anesthesiology 105:334–337
Chou WY, Yang LC, Lu HF, Ko JY, Wang CH, Lin SH, Lee TH, Concejero A, Hsu CJ (2006) Association of μ-opioid receptor gene polymorphism (A118G) with variations in morphine consumption for analgesia after total knee arthroplasty. Acta Anaesthesiol Scand 50:787–792
Klepstad P, Rakvåg TT, Kaasa S, Holthe M, Dale O, Borchgrevink PC, Baar C, Vikan T, Krokan HE, Skorpen F (2004) The 118 A > G polymorphism in the human μ-opioid receptor gene may increase morphine requirements in patients with pain caused by malignant disease. Acta Anaesthesiol Scand 48:1232–1239
Hayashida M, Nagashima M, Satoh Y, Katoh R, Tagami M, Ide S, Kasai S, Nishizawa D, Ogai Y, Hasegawa J, Komatsu H, Sora I, Fukuda K, Koga H, Hanaoka K, Ikeda K (2008) Analgesic requirements after major abdominal surgery are associated with OPRM1 gene polymorphism genotype and haplotype. Pharmacogenomics 9:1605–1616
8.Fukuda K, Hayashida M, Ide S, Saita N, Kokita Y, Kasai S, Nishizawa D, Ogai Y, Hasegawa J, Nagashima M, Tagami M, Komatsu H, Sora I, Koga H, Kaneko Y, Ikeda K (2009) Association between OPRM1 gene polymorphisms and fentanyl sensitivity in patients undergoing painful cosmetic surgery. Pain 147:194–201
Dripps RD (1963) New classification of physical status. Anesthesiology 24:111
Vinik HR, Kissin I (1998) Rapid developÂment of tolerance to analgesia during remifentanil infusion in humans. Anesth Analg 86:1307–1311
Wu CL (2005) Acute postoperative pain. In: Miller RD (ed) Miller’s anesthesia, 6th edn. Elsevier/Churchill-Livingstone, Philadelphia, pp 2729–2762
Shi MM, Bleavins MR, de la Iglesia FA (1999) Technologies for detecting genetic polymorphisms in pharmacogenomics. Mol Diagn 4:343–351
Syvänen AC (2001) Accessing genetic variation: genotyping single nucleotide polymorphisms. Nat Rev Genet 2:930–942
Shi MM (2001) Enabling large-scale pharmacogenetic studies by high-throughput mutation detection and genotyping technologies. Clin Chem 47:164–172
Chen X, Sullivan PF (2003) Single nucleotide polymorphism genotyping: biochemistry, protocol, cost and throughput. Pharmacogenomics J 3:77–96
Jannetto PJ, Laleli-Sahin E, Wong SH (2004) Pharmacogenomic genotyping methodologies. Clin Chem Lab Med 42:1256–1264
Nishizawa D, Nagashima M, Katoh R, Satoh Y, Tagami M, Kasai S, Ogai Y, Han W, Hasegawa J, Shimoyama N, Sora I, Hayashida M, Ikeda K (2009) Association between KCNJ6 (GIRK2) gene polymorphisms and postoperative analgesic requirements after major abdominal surgery. PLoS ONE 4:e7060
Germer S, Higuchi R (1999) Single-tube genotyping without oligonucleotide probes. Genome Res 9:72–78
Myakishev MV, Khripin Y, Hu S, Hamer DH (2001) High-throughput SNP genotyping by allele-specific PCR with universal energy-transfer-labeled primers. Genome Res 11:163–169
Nishizawa D, Han W, Hasegawa J, Ishida T, Numata Y, Sato T, Kawai A, Ikeda K (2006) Association of μ-opioid receptor gene polymorphism A118G with alcohol dependence in a Japanese population. Neuropsychobiology 53:137–141
Livak KJ, Flood SJ, Marmaro J, Giusti W, Deetz K (1995) Oligonucleotides with fluorescent dyes at opposite ends provide a quenched probe system useful for detecting PCR product and nucleic acid hybridization. PCR Methods Appl 4:357–362
Imai K, Ogai Y, Nishizawa D, Kasai S, Ikeda K, Koga H (2007) A novel SNP detection technique utilizing a multiple primer extension (MPEX) on a phospholipid polymer-coated surface. Mol Biosyst 3:547–553
Ide S, Kobayashi H, Ujike H, Ozaki N, Sekine Y, Inada T, Harano M, Komiyama T, Yamada M, Iyo M, Iwata N, Tanaka K, Shen H, Iwahashi K, Itokawa M, Minami M, Satoh M, Ikeda K, Sora I (2006) Linkage disequilibrium and association with methamphetamine dependence/psychosis of μ-opioid receptor gene polymorphisms. Pharmacogenomics J 6:179–188
Balding DJ (2006) A tutorial on statistical methods for population association studies. Nat Rev Genet 7:781–791
Carlson CS, Eberle MA, Rieder MJ, Yi Q, Kruglyak L, Nickerson DA (2004) Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet 74:106–120
Nyholt DR (2001) Genetic case-control association studies: correcting for multiple testing. Hum Genet 109:564–567
Perneger TV (1998) What’s wrong with Bonferroni adjustments. BMJ 316:1236–1238
Curtis D, Xu K (2007) Minor differences in haplotype frequency estimates can produce very large differences in heterogeneity test statistics. BMC Genet 8:38
Mooney S (2005) Bioinformatics approaches and resources for single nucleotide polymorphism functional analysis. Brief Bioinform 6:44–56
Smigielski EM, Sirotkin K, Ward M, Sherry ST (2000) dbSNP: a database of single nucleotide polymorphisms. Nucleic Acids Res 28:352–355
Fredman D, Siegfried M, Yuan YP, Bork P, Lehväslaiho H, Brookes AJ (2002) HGVbase: a human sequence variation database emphasizing data quality and a broad spectrum of data sources. Nucleic Acids Res 30:387–391
International HapMap Consortium (2005) A haplotype map of the human genome. Nature 437:1299–1320
Raymond M, Rousset F (1995) GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J. Heredity 86:248–249
Stephens M, Smith NJ, Donnelly P (2001) A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 68:978–989
Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21:263–265
Abecasis GR, Cookson WO (2000) GOLD: graphical overview of linkage disequilibrium. Bioinformatics 16:182–183
Niu T, Qin ZS, Xu X, Liu JS (2002) Bayesian haplotype inference for multiple linked single-nucleotide polymorphisms. Am J Hum Genet 70:157–169
de Bakker PI, Yelensky R, Pe’er I, Gabriel SB, Daly MJ, Altshuler D (2005) Efficiency and power in genetic association studies. Nat Genet 37:1217–1223
Zhang K, Jin L (2003) HaploBlockFinder: haplotype block analyses. Bioinformatics 19:1300–1301
Zhao JH, Lissarrague S, Essioux L, Sham PC (2002) GENECOUNTING: haplotype analysis with missing genotypes. Bioinformatics 18:1694–1695
Zhang K, Qin Z, Chen T, Liu JS, Waterman MS, Sun F (2005) HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms. Bioinformatics 21:131–134
Greenspan G, Geiger D (2004) High density linkage disequilibrium mapping using models of haplotype block variation. Bioinformatics 20(Suppl 1):i137-i144
Shimo-onoda K, Tanaka T, Furushima K, Nakajima T, Toh S, Harata S, Yone K, Komiya S, Adachi H, Nakamura E, Fujimiya H, Inoue I (2002) Akaike’s information criterion for a measure of linkage disequilibrium. J Hum Genet 47:649–655
Zhao JH, Curtis D, Sham PC (2000) Model-free analysis and permutation tests for allelic associations. Hum Hered 50:133–139
Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol Bioinform Online 1:47–50
Zaykin DV, Westfall PH, Young SS, Karnoub MA, Wagner MJ, Ehm MG (2002) Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum Hered 53:79–91
Guo SW, Thompson EA (1992) Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics 48:361–372
Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA (2002) Score tests for association between traits and haplotypes when linkage phase is ambiguous. Am J Hum Genet 70:425–434
Dudbridge F (2003) Pedigree disequilibrium tests for multilocus haplotypes. Genet EpideÂmiol 25:115–121
Purcell S, Cherny SS, Sham PC (2003) Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 19:149–150
Epstein MP, Satten GA (2003) Inference on haplotype effects in case-control studies using unphased genotype data. Am J Hum Genet 73:1316–1329
Gordon D, Finch SJ, Nothnagel M, Ott J (2002) Power and sample size calculations for case-control genetic association tests when errors are present: application to single nucleotide polymorphisms. Hum Hered 54:22–33
Gauderman WJ (2002) Sample size requirements for matched case-control studies of gene-environment interaction. Stat Med 21:35–50
Zhao LP, Li SS, Khalid N (2003) A method for the assessment of disease associaÂtions with single-nucleotide polymorphism haplotypes and environmental variables in case-control studies. Am J Hum Genet 72:1231–1250
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575
Acknowledgments
We acknowledge Mr. Michael Arends for his assistance with editing the manuscript. This work was supported by grants from the Ministry of Health, Labour and Welfare of Japan (H17-Pharmaco-001, H19-Iyaku-023), the Ministry of Education, Culture, Sports, Science and Technology of Japan (20602020, 19659405, 20390162), The Naito Foundation, and The Mitsubishi Foundation.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Nishizawa, D., Hayashida, M., Nagashima, M., Koga, H., Ikeda, K. (2010). Genetic Polymorphisms and Human Sensitivity to Opioid Analgesics. In: Szallasi, A. (eds) Analgesia. Methods in Molecular Biology, vol 617. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60327-323-7_29
Download citation
DOI: https://doi.org/10.1007/978-1-60327-323-7_29
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-60327-322-0
Online ISBN: 978-1-60327-323-7
eBook Packages: Springer Protocols