DNA methylation at the mu-1 opioid receptor gene (OPRM1) promoter predicts preoperative, acute, and chronic postsurgical pain after spine fusion
Received 21 January 2017
Accepted for publication 9 March 2017
Published 9 May 2017 Volume 2017:10 Pages 157—168
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Martin Bluth
Vidya Chidambaran,1,2 Xue Zhang,3,4 Lisa J Martin,2,3 Lili Ding,5 Matthew T Weirauch,6–8 Kristie Geisler,1 Bobbie L Stubbeman,1 Senthilkumar Sadhasivam,1,2 Hong Ji4,9
1Department of Anesthesiology, 2Department of Pediatrics, 3Division of Human Genetics, 4Pyrosequencing Core for Genomic and Epigenomic Research, 5Division of Biostatistics and Epidemiology, 6Center for Autoimmune Genomics and Etiology, 7Division of Biomedical Informatics, 8Division of Developmental Biology, 9Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
Introduction: The perioperative pain experience shows great interindividual variability and is difficult to predict. The mu-1 opioid receptor gene (OPRM1) is known to play an important role in opioid-pain pathways. Since deoxyribonucleic acid (DNA) methylation is a potent repressor of gene expression, DNA methylation was evaluated at the OPRM1 promoter, as a predictor of preoperative, acute, and chronic postsurgical pain (CPSP).
Methods: A prospective observational cohort study was conducted in 133 adolescents with idiopathic scoliosis undergoing spine fusion under standard protocols. Data regarding pain, opioid consumption, anxiety, and catastrophizing (using validated questionnaires) were collected before and 2–3 months postsurgery. Outcomes evaluated were preoperative pain, acute postoperative pain (area under curve [AUC] for pain scores over 48 hours), and CPSP (numerical rating scale >3/10 at 2–3 months postsurgery). Blood samples collected preoperatively were analyzed for DNA methylation by pyrosequencing of 22 CpG sites at the OPRM1 gene promoter. The association of each pain outcome with the methylation percentage of each CpG site was assessed using multivariable regression, adjusting for significant (P<0.05) nongenetic variables.
Results: Majority (83%) of the patients reported no pain preoperatively, while CPSP occurred in 36% of the subjects (44/121). Regression on dichotomized preoperative pain outcome showed association with methylation at six CpG sites (1, 3, 4, 9, 11, and 17) (P<0.05). Methylation at CpG sites 4, 17, and 18 was associated with higher AUC after adjusting for opioid consumption and preoperative pain score (P<0.05). After adjusting for postoperative opioid consumption and preoperative pain score, methylation at CpG sites 13 and 22 was associated with CPSP (P<0.05).
Discussion: Novel CPSP biomarkers were identified in an active regulatory region of the OPRM1 gene that binds multiple transcription factors. Inhibition of binding by DNA methylation potentially decreases the OPRM1 gene expression, leading to a decreased response to endogenous and exogenous opioids, and an increased pain experience.
Keywords: OPRM1, epigenetics, pain, chronic postsurgical pain, DNA methylation
Inadequately controlled pain remains a significant problem after surgery, as it negatively affects quality of life and function and increases the risk of persistent postsurgical pain.1 Approximately 50%–75% of patients undergoing surgery experience moderate or severe pain, and this is true for the 6 million children who undergo surgery every year in the US.2,3 Chronic postsurgical pain (CPSP) is the pain that lasts beyond 2 months postsurgery.4 In children, the incidence of CPSP ranges from 13% to 68.8%.5,6 This implies that of the 1.5 million children who undergo major surgery every year in the US, ~225,000–1,000,000 children develop CPSP.7 Interindividual variability in pain sensitivity,8 acute postsurgical pain,9–11 and CPSP have been partly explained by genetic markers.12 The mu-1 opioid receptor gene (OPRM1) that codes for the mu opioid receptor (MOR) plays an important role in opioid-pain pathways.13 The OPRM1 variant that has been most commonly studied is the A118G variant; however, the results of association studies with pain and β-endorphin-binding activity between this variant and the wild-type receptors are controversial.14–17
Beyond genetics, chronic pain is a classic example of gene–environment interaction,18 and hence recently interest has been directed toward the role of epigenetics in pain. Epigenetics is the study of changes in chromosomes that do not alter the sequence of deoxyribonucleic acid (DNA),19 but may still lead to alterations in gene expression. Genetics and epigenetics together are important factors in the transition of acute postsurgical pain to CPSP.20,21 DNA methylation is a common epigenetic mechanism, which involves the addition of a methyl group to the 5′ position of a cytosine residue followed by a guanine residue (a CpG dinucleotide), which are often clustered (CpG islands) in the promoter regions of genes.22 DNA methylation at the OPRM1 promoter region regulates DNA binding of transcription factors and is a potent epigenetic repressor of gene transcription.23 An increase in the OPRM1 promoter methylation has been found to be associated with a decrease in protein expression of OPRM1.24 Because DNA methylation is reversible, there is much interest in understanding its association with pain, as a potential target for intervention. The OPRM1 DNA methylation levels have been found to be elevated in opioid and heroin addicts.25,26 However, this has not been studied in relation to perioperative pain and CPSP. It has been hypothesized that DNA methylation at the promoter region of OPRM1 will be associated with pain before and after surgery. Understanding the contribution of OPRM1 genetic–epigenetic interactions to pain outcomes will allow prediction of susceptibility to poor pain control and CPSP and will enable target identification for modification of risk studies in the future.
A prospective observational cohort study was conducted in 133 adolescents with idiopathic scoliosis undergoing posterior spine fusion under standard intraoperative anesthesia (propofol–remifentanil total intravenous anesthesia, guided by electroencephalography monitoring for depth of anesthesia) and postoperative analgesia with morphine patient-controlled analgesia along with adjuvants (scheduled intravenous acetaminophen, ketorolac, and diazepam as needed and methocarbamol) managed by perioperative pain team. The study was approved by the Cincinnati Children’s Hospital Institutional Review Board. This study is registered with ClinicalTrials.gov identifiers NCT01839461 and NCT01731873. Written informed consent was obtained from parents, and assent was obtained from children before enrollment.
Healthy nonobese subjects with an American Society of Anesthesiologists (ASA) physical status ≤2 (mild systemic disease), aged 10–18 years, with a diagnosis of idiopathic scoliosis and/or kyphosis, and undergoing elective spinal fusion were recruited. The exclusion criteria included pregnant or breastfeeding females, presence of chronic pain defined as use of opioids in the past 6 months, liver or renal diseases, and developmental delays.
Preoperatively, data regarding demographic factors (sex, age, and race), weight, pain scores (numerical rating scale [NRS]/0–10)27 on the day of surgery (P0), and pain medications used were obtained. Anxiety scores for both child and a parent were assessed using the 0–10 visual analog scale (VAS), a simple validated scale that has been used previously in children.28 Questionnaires were administered as described in the following sections. The intraoperative data collected included propofol and remifentanil doses, duration of surgery, and number of vertebral levels fused. In the immediate postoperative period (postoperative days [PODs] 1 and 2), pain scores (every 4 hours) and morphine and diazepam doses administered were noted. After hospital discharge, the questionnaires were administered per schedule presented in Table 1 to obtain psychosocial and pain measures in a standard fashion.
Pain outcomes evaluated were 1) preoperative pain, 2) acute postoperative pain (defined as area under curve [AUC] for pain scores over time on POD 1 and 2 [AUCPOD1–2] calculated using trapezoidal rule), and 3) chronic pain/CPSP (NRS >3/10 at 2–3 months postsurgery) as defined by the International Association for the Study of Pain.29 These cut offs for NRS were used because NRS pain scores >3 (moderate/severe pain) at 3 months have been described as a predictor for persistence of pain and associated with functional disability.30
Measurement of DNA methylation
Blood was drawn upon intravenous line placement before surgery, from which the DNA was isolated on the same day and frozen at –20°C. To study DNA methylation, the focus was on a 251 bp region, including 22 CpG sites reaching from position –93 to position +159, whose methylation levels were previously shown to be associated with the OPRM1 expression24 and opioid/heroin addiction (Figure 1).25,26 The CpG sites are numbered according to those studies25,26 to allow for an easy comparison. This included a CpG site at +117, reported by Oertel et al.24 The pyrosequencing assays utilize 50–500 ng of genomic DNA of acceptable quality (measured by Thermo Scientific NanoDrop spectrophotometer [Waltham, MA, USA] and with a 260/280 ratio ranging from 1.6 to 2.0). The extracted DNA was treated with bisulfite using Zymo EZ DNA Methylation Gold Kit (Zymo Research, Orange, CA, USA), according to the manufacturer’s instructions. Two sets of primers, long and nested, were designed using ZymoTaq Premix (Zymo Research) for two rounds of polymerase chain reaction (PCR). Methylation of the PCR products was quantified using PyroMark MD 1.0 software (Qiagen, Valencia, CA, USA). Primers used in the assays are listed in Table 2. Samples were repeated if the pyrosequencing runs did not pass quality checks of the pyrosequencer or if the internal bisulfite conversion controls failed. The sample runs were monitored through methylated and nonmethylated DNA as well as template-free negative controls.
Prior to the analyses, the data quality was assessed. Demographics and patients’ clinical characteristics were summarized as mean (standard deviation [SD]), median, and frequency (percentage) according to the distribution of the data. Prior to evaluation of the association between pain outcome and DNA methylation, the effects of covariables were tested, which included age, sex, race, morphine dose in mg/kg on POD 1 and 2, preoperative anxiety score (VAS), preoperative pain score, duration of surgery, vertebral levels fused, propofol and remifentanil doses used during surgery (per kg), use of intravenous acetaminophen/ketorolac (yes/no), diazepam doses (mg/kg), and pain catastrophizing scale (parent version) and parent pain history scores and sequential scores for Childhood Anxiety Sensitivity Index and pain catastrophizing scale (child version).31 Three pain outcomes were examined. Preoperative pain was dichotomized as yes versus no, because, although it was measured using NRS as a 0–10 scale, 83% of the patients reported no preoperative pain. It was then associated with covariables using logistic regression. Similarly, acute postoperative pain was analyzed using simple linear regression models, and CPSP using logistic regression models. Covariables associated at P<0.10 were entered into multivariable models, and stepwise selection was used to derive a final nongenetic model for each outcome where only variables with P<0.05 were retained.32 DNA methylation levels were then added to the final nongenetic model to assess their association with the pain outcomes. Statistical analyses were performed using Statistical Analysis System, version 9.3 (SAS Institute Inc., Cary, NC, USA). P≤0.05 was used as the threshold for statistical significance. No multiple testing correction was done, thus it is possible that some findings occurred by chance.
Functional genomics analysis
To identify potential regulatory mechanisms in the OPRM1 promoter, a large collection of functional genomics data sets from various sources, including ENCODE,33 Roadmap Epigenomics,34 Cistrome,35 and ReMap-ChIP, was compiled.36 The genomic coordinates of the OPRM1 promoter were intersected against the genomic coordinates contained in each data set. In total, this database contains 4,953 data sets performed in 1,706 different cell types and conditions; 1,911 data sets monitor binding interactions of transcription factors with the human genome using ChIP-seq; 1,214 measure the presence of a particular histone mark using ChIP-seq; 226 measure open chromatin through DNase-seq; 57 measure expression quantitative trait loci (eQTLs); and 558 predict “ActiveChromatin” states using combinations of histone marks.37 Collectively, 240 of these experiments were performed in brain-related cell lines and cell types.
The final cohort comprised 133 participants; the mean age was 14.49 years (SD 1.91), and they were mostly white (83%) and female (74%) (Table 3). The recruitment timeline is described in Figure 2. Descriptions of variables that were evaluated for inclusion in the multiple regression model are presented in Table 3.
Acute and chronic postoperative pain data were collected for 128 and 121 patients, respectively. The overall incidence of CPSP was found to be 36.4% (44/121). The preoperative pain score was 0 in 83% (106/127) of the cohort.
DNA methylation and pain
Three pain outcomes were examined. For the association with dichotomized preoperative pain scores, logistic regression was used. After adjusting for age and sex, the methylation level of six CpG sites (sites 1, 3, 4, 9, 11, and 17, Table 4) was significantly associated with whether a patient reported preoperative pain. For all the six CpG sites, higher methylation was associated with higher odds of reporting preoperative pain, except for site 17. No impact of the methylation on the actual pain scores was detected (data not shown). For acute postoperative pain (AUCPOD1–2), significant impact of methylation was detected in CpG sites 4, 17, and 18 (Table 4) when preoperative pain and morphine consumption were adjusted. For all three CpG sites, higher methylation was associated with higher preoperative pain. For chronic postoperative pain, significant association was detected for the nonpromoter site, CpG13 and 22 (Table 4), with preoperative pain and morphine consumption being controlled. For all the CpG sites, higher methylation was associated with higher odds of having chronic pain. Methylation at two CpG sites was associated with both preoperative pain and AUCPOD1–2 (CpG 4 and 17); methylation at these sites also showed a trend toward CPSP risk, although not statistically significant. Figure 3 depicts estimated probabilities of developing CPSP using median preoperative pain score (0), median morphine doses (1.7 mg/kg), and 2.5th, 25th, 50th, 75th and 97.5th percentiles of the methylation data of each of the two sites CpG13 and CpG22.
Functional genomics analysis
Query of the region evaluated using a large collection of ChIP-seq, DNase-seq, and eQTL data, as described in the “Methods” section, showed that this region is located in open chromatin and is marked by H3K27ac, H3K4me1, and H3K4me3 (indicative of active regulatory regions)38–40 in noncancer brain cells from the caudate–putamen, temporal, frontal lobes, and angular gyri. Moreover, this region contains ChIP-seq peaks for binding of multiple transcription factors, including REST, RAD21, SP1, YY1, and ZNF263 in various tissues. In particular, REST and RAD21 bind the OPRM1 promoter region in three cell lines (SK-N-SH, PFSK-1, and SK-N-SH) derived from brain tissue where the opioid receptors responsible for analgesia are found (Table 5). Collectively, these results suggest that the differential DNA methylation patterns observed in the OPRM1 promoter might functionally act by modulating the expression of OPRM1 via alteration of the binding of REST and other neuron-expressed transcription factors.
It has been previously shown that psychological and clinical variables contribute to CPSP.31 This study finds associations between epigenetics and CPSP in children for the first time and adds to the emerging evidence linking epigenetic mechanisms to the development of chronic pain states.41 Specifically, it was found that novel biomarkers (DNA methylation of certain CpG sites in the OPRM1 promoter region) associated with preoperative pain, acute postoperative pain, and CPSP following posterior spine fusion in healthy adolescents. DNA methylation was also associated with pain before surgical stimulus and exposure to opioids. These findings allow for prediction of risk for the pain response to surgery and possible novel mechanisms that could be targeted for prevention and treatment of CPSP.
Endogenous opioid peptides and exogenously administered opioid analgesics bind to MOR to regulate pain responses. The MOR activity is regulated at different levels, including epigenetic mechanisms.23 Many of the CpG sites found to be associated with pain outcomes (1, 3, 4, 9, 11, 13, 17, 18, and 22) have been previously described as putative Sp1 transcription factor-binding sites. These include CpG sites 9, 10, 12, 16, 21, and 23 at –18, –14, 12, +84, +145, and +159 from ATG site, respectively.26 Methylation levels at some of these sites were previously found to be associated with opioid addiction/dependence. Nielsen et al found that CpG sites at –18 and +84 (9 and 16) were more strongly methylated in heroin addicts than controls. Similarly, seven CpG sites showed significant hypermethylation of blood DNA taken from male opioid addicts when compared to blood DNA from controls (CpGs 5, 9, 10, 11, 18, and 23).26 Increased methylation within the OPRM1 promoter (at –14, –10 [sites 10, 11]) was also found to be associated with worse neonatal abstinence syndrome outcomes in infants exposed to opioids in utero.42 It has been shown in mouse brain tissues that DNA methylation of the OPRM1 promoter decreases expression of the gene; through interaction with chromatin-remodeling factors, remodeling occurs, thus allowing access for Sp1 binding,43 which results in the MOR upregulation. Thus, methylation at these sites can prevent the OPRM1 activation, leading to decreased endogenous and exogenous opioid effects, manifested in the experience of increased perioperative pain. In addition, Chorbov et al also observed increased DNA methylation in the sperm of addicts, which may suggest a means of epigenetic heritability of opioid phenotypes.25
Animal studies have shown that OPRM1 promoter methylation reduced OPRM1 expression.23 Knothe et al confirmed methylation effects on OPRM1 expression through experiments in human cell lines (neuronal SHSY5Y and Kelly, and nonneuronal HEK-293) with and without the demethylating agent 5′-aza-2′-deoxycytidine.44 But they did not find that methylation profiles across the OPRM1 gene from CpG position –93 to +159 in brain tissues collected postmortem from heroin addicts correlated with differences in OPRM1 mRNA expression in the corresponding brain regions.44 Opioid exposure in all their subjects may have played a role in minimizing methylation differences between the specimens and the individuals. Hence, the lack of correlation in their study does not rule out the differences that may exist between opioid-exposed and nonopioid-exposed (or pain vs no pain) subjects.
The findings of this study corroborate a growing body of evidence that OPRM1 DNA methylation affects pain behaviors and contributes to the limited efficacy of opiates in certain cases,45 which is improved upon blockade of methylation.46 In a neuropathic animal model, it was shown that increased methylation of the MOR gene proximal promoter in dorsal root ganglion decreased morphine analgesia.47 Administration of demethylating agents reversed the hypermethylation of the OPRM1 gene and improved the analgesic effect of morphine in mice pain models.47,48 It is not clear if pain is the trigger or the consequence of increased methylation of the OPRM1 promoter. In fact, chronic opioid use in methadone-substituted former opiate addicts was found to be associated with increased DNA methylation at the OPRM1 position +126 (CpG 18), correlating with increased pain, compared to controls with pain not treated with opioids.49 The authors note that causal relationships with opioid use could not be established, as there was no opioid dose dependency. In their discussion, they mentioned that the trigger for increased methylation may actually be the baseline increased pain.50 This might partly explain the association of OPRM1 methylation with baseline pain identified in this study, as MOR function is essential for endogenous opioid action even in the absence of opioids. Useful information would be gained by evaluating DNA methylation changes over time in those who do and do not develop CPSP, in the presence/absence of opioids.
Although the exact mechanisms by which DNA methylation of OPRM1 promoter region contributes to pain are not known, the computational analysis revealed a DNA region bound by the repressor element 1 silencing transcription factor (REST) in multiple neuronal cell lines at the OPRM1 promoter region (Table 5). Intriguingly, REST has previously been implicated in OPRM1 gene silencing via epigenetic modifications.51 REST, a member of the zinc finger transcription factor family, represses transcription of neural genes52 in nonneuronal cells by binding a DNA sequence element called the neuron-restrictive silencer element53 and recruiting several chromatin-modifying enzymes.54 There is also evidence for the involvement of REST in chronic neuropathy.52 Nerve injury results in a long-lasting increase in REST expression in mouse dorsal root ganglia.55 Hence, it is hypothesized that, in patients with already suppressed OPRM1 expression due to DNA methylation of the OPRM1 promoter, increased REST expression after injury possibly leads to further OPRM1 gene silencing and worsens the pain experience. If true, this mechanism could potentially create new avenues for pain therapy. Besides the sequence-specific REST, RAD21 was another transcription factor that was found to be relevant in neuronal cells for the OPRM1 promoter region. REST is involved in three-dimensional DNA organization. Recent research, using ChIP-seq and RNA-seq data from matching cell types from the human ENCODE resource, showed that RAD21 mostly functions as an activator of transcription.56 Although not known to play a role in OPRM1 regulation or pain, DNA methylation preventing binding of an activating transcription factor may also be responsible for decreased OPRM1 function and hence pain in these patients.
This study has a few limitations, one of which is the use of blood samples for DNA methylation, instead of target tissue like brain, which are understandably inaccessible in clinical human studies. However, this approach has been employed successfully before.25,26,42 Fan and Zhang compared methylation profiles of human chromosome 6 (OPRM1 gene location), derived from 12 tissues, and reported that CpG island methylation profiles were highly correlated between somatic tissues.57 Davies et al found that some interindividual variation in DNA methylation was reflected across brain and blood, indicating that peripheral tissues may have utility in studies of complex neurobiological phenotypes.58
In summary, we report novel associations of DNA methylation in the OPRM1 promoter with preoperative, acute, and CPSP in children undergoing spine surgery. Since DNA methylation is influenced by multiple modifiable factors (diet, exercise, parental upbringing, and stress), understanding the role of epigenetic regulation of OPRM1 in pain opens new avenues of pain research. Understanding susceptibility may act as a guide for targeted use of aggressive multimodal analgesia, use of calcium-channel modulators (like gabapentin) and preemptive analgesics like N-methyl-D-aspartate receptor antagonists (like ketamine), regional anesthesia, and behavioral therapies in patients with higher risk.59 Addressing this higher risk using alternative strategies may be especially important as the MOR protein encoded by OPRM1 plays a key role in mediating not only pain responses but also the development of tolerance and physical dependence.60,61 Future studies need to map methylation changes in the OPRM1 promoter over the time course of CPSP, and the effect of preventive and therapeutic strategies on transition of acute pain to CPSP, and development of tolerance/opioid hyperalgesia.
Surgery is a stressful and painful experience; however, some individuals continue to experience pain, even months or years after surgery. This is because pain experience is unique. It has been shown that psychological factors play a role in shaping pain responses after surgery. Genes also play an important role in determining pain. One such gene is the mu-1 opioid receptor gene (OPRM1) that codes for the mu opioid receptor (MOR), where potent pain medications (opioids) bind. In this study, we evaluated whether nonstructural changes in the deoxyribonucleic acid (DNA) (DNA methylation) of the regulatory region of the OPRM1 gene could predict the individual pain experience. In 133 adolescents undergoing spine fusion, after controlling for important nongenetic covariates identified from a previous analysis, it was found that methylation at several regulatory sites was associated with preoperative, immediate postoperative, and chronic postoperative pain. These sites were identified as binding regions for important transcription factors; methylation likely affects factor binding and decreases the OPRM1 expression, leading to increased pain sensitivity. These serve as novel biomarkers for pain and, since DNA methylation is modifiable, might provide a basis for future preventive and therapeutic strategies.
The authors would like to acknowledge Ashley Ulm and Veda Yadagiri (Pyrosequencing Core, Cincinnati Children’s Hospital Medical Center [CCHMC]) and Diane Kissell for their role in analyzing the DNA extraction and pyrosequencing, under the supervision of Hong Ji (Director, Pyrosequencing Core) and Kejian Zhang (Director of Molecular Genetics Lab, CCHMC). They would also like to acknowledge Kayla Stallworth and Hope Esslinger, CCRC IV, previous research coordinators for the Department of Anesthesia, CCHMC, for their help with patient recruitment in the earlier stages of the study. This study was supported by 5K23HD082782 through the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health (PI: Chidambaran), Center for Pediatric Genomics, and Shared Facility Discovery Award from CCHMC (PI: Chidambaran). The authors are solely responsible for the content, and it does not necessarily represent the official views of the National Institutes of Health.
The authors report no conflicts of interest in this work.
Kehlet H, Jensen TS, Woolf CJ. Persistent postsurgical pain: risk factors and prevention. Lancet. 2006;367(9522):1618–1625.
Gan TJ, Habib AS, Miller TE, White W, Apfelbaum JL. Incidence, patient satisfaction, and perceptions of post-surgical pain: results from a US national survey. Curr Med Res Opin. 2014;30(1):149–160.
Polkki T, Pietila AM, Vehvilainen-Julkunen K. Hospitalized children’s descriptions of their experiences with postsurgical pain relieving methods. Int J Nurs Stud. 2003;40(1):33–44.
Macrae WA. Chronic post-surgical pain: 10 years on. Br J Anaesth. 2008;101(1):77–86.
Landman Z, Oswald T, Sanders J, Diab M; Spinal Deformity Study Group. Prevalence and predictors of pain in surgical treatment of adolescent idiopathic scoliosis. Spine (Phila Pa 1976). 2011;36(10):825–829.
Page MG, Stinson J, Campbell F, Isaac L, Katz J. Identification of pain-related psychological risk factors for the development and maintenance of pediatric chronic postsurgical pain. J Pain Res. 2013;6:167–180.
Kain ZN, Mayes LC, O’Connor TZ, Cicchetti DV. Preoperative anxiety in children. Predictors and outcomes. Arch Pediatr Adolesc Med. 1996;150(12):1238–1245.
LaCroix-Fralish ML, Austin JS, Zheng FY, Levitin DJ, Mogil JS. Patterns of pain: meta-analysis of microarray studies of pain. Pain. 2011;152(8):1888–1898.
De Gregori M, Diatchenko L, Ingelmo PM, et al. Human genetic variability contributes to postoperative morphine consumption. J Pain. 2016;17(5):628–636.
Sadhasivam S, Chidambaran V. Pharmacogenomics of opioids and perioperative pain management. Pharmacogenomics. 2012;13(15):1719–1740.
Sadhasivam S, Chidambaran V, Olbrecht VA, et al. Genetics of pain perception, COMT and postoperative pain management in children. Pharmacogenomics. 2014;15(3):277–284.
Clarke H, Katz J, Flor H, Rietschel M, Diehl SR, Seltzer Z. Genetics of chronic post-surgical pain: a crucial step toward personal pain medicine. Can J Anaesth. 2015;62(3):294–303.
Uhl GR, Sora I, Wang Z. The mu opiate receptor as a candidate gene for pain: polymorphisms, variations in expression, nociception, and opiate responses. Proc Natl Acad Sci U S A. 1999;96(14):7752–7755.
Branford R, Droney J, Ross JR. Opioid genetics: the key to personalized pain control? Clin Genet. 2012;82(4):301–310.
Lee MG, Kim HJ, Lee KH, Choi YS. The influence of genotype polymorphism on morphine analgesic effect for postoperative pain in children. Korean J Pain. 2016;29(1):34–39.
Walter C, Lotsch J. Meta-analysis of the relevance of the OPRM1 118A>G genetic variant for pain treatment. Pain. 2009;146(3):270–275.
Beyer A, Koch T, Schroder H, Schulz S, Hollt V. Effect of the A118G polymorphism on binding affinity, potency and agonist-mediated endocytosis, desensitization, and resensitization of the human mu-opioid receptor. J Neurochem. 2004;89(3):553–560.
Mogil JS. Pain genetics: past, present and future. Trends Genet. 2012;28(6):258–266.
Bird A. Perceptions of epigenetics. Nature. 2007;447(7143):396–398.
Buchheit T, Van de Ven T, Shaw A. Epigenetics and the transition from acute to chronic pain. Pain Med. 2012;13(11):1474–1490.
Crow M, Denk F, McMahon SB. Genes and epigenetic processes as prospective pain targets. Genome Med. 2013;5(2):12.
Ushijima T, Nakajima T, Maekita T. DNA methylation as a marker for the past and future. J Gastroenterol. 2006;41(5):401–407.
Hwang CK, Song KY, Kim CS, et al. Evidence of endogenous mu opioid receptor regulation by epigenetic control of the promoters. Mol Cell Biol. 2007;27(13):4720–4736.
Oertel BG, Doehring A, Roskam B, et al. Genetic-epigenetic interaction modulates μ-opioid receptor regulation. Hum Mol Genet. 2012;21(21):4751–4760.
Chorbov VM, Todorov AA, Lynskey MT, Cicero TJ. Elevated levels of DNA methylation at the OPRM1 promoter in blood and sperm from male opioid addicts. J Opioid Manag. 2011;7(4):258–264.
Nielsen DA, Yuferov V, Hamon S, et al. Increased OPRM1 DNA methylation in lymphocytes of methadone-maintained former heroin addicts. Neuropsychopharmacology. 2009;34(4):867–873.
von Baeyer CL. Numerical rating scale for self-report of pain intensity in children and adolescents: recent progress and further questions. Eur J Pain. 2009;13(10):1005–1007.
Bringuier S, Dadure C, Raux O, Dubois A, Picot MC, Capdevila X. The perioperative validity of the visual analog anxiety scale in children: a discriminant and useful instrument in routine clinical practice to optimize postoperative pain management. Anesth Analg. 2009;109(3):737–744.
Macrae WA, Davies HTO. Chronic Postsurgical Pain. Seattle: IASP Press; 1999.
Gerbershagen HJ, Rothaug J, Kalkman CJ, Meissner W. Determination of moderate-to-severe postoperative pain on the numeric rating scale: a cut-off point analysis applying four different methods. Br J Anaesth. 2011;107(4):619–626.
Chidambaran V, Moore D, Spruance K, et al. Predicting the pain continuum after adolescent idiopathic scoliosis surgery – a prospective cohort study. Eur J Pain. In press 2017.
Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008;3:17.
ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57–74.
Bernstein BE, Stamatoyannopoulos JA, Costello JF, et al. The NIH Roadmap Epigenomics Mapping Consortium. Nat Biotechnol. 2010;28(10):1045–1048.
Liu T, Ortiz JA, Taing L, et al. Cistrome: an integrative platform for transcriptional regulation studies. Genome Biol. 2011;12(8):R83.
Griffon A, Barbier Q, Dalino J, van Helden J, Spicuglia S, Ballester B. Integrative analysis of public ChIP-seq experiments reveals a complex multi-cell regulatory landscape. Nucleic Acids Res. 2015;43(4):e27.
Ernst J, Kheradpour P, Mikkelsen TS, et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature. 2011;473(7345):43–49.
Koch CM, Andrews RM, Flicek P, et al. The landscape of histone modifications across 1% of the human genome in five human cell lines. Genome Res. 2007;17(6):691–707.
Barski A, Cuddapah S, Cui K, et al. High-resolution profiling of histone methylations in the human genome. Cell. 2007;129(4):823–837.
Creyghton MP, Cheng AW, Welstead GG, et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci U S A. 2010;107(50):21931–21936.
Denk F, McMahon SB, Tracey I. Pain vulnerability: a neurobiological perspective. Nat Neurosci. 2014;17(2):192–200.
Wachman EM, Hayes MJ, Lester BM, et al. Epigenetic variation in the mu-opioid receptor gene in infants with neonatal abstinence syndrome. J Pediatr. 2014;165(3):472–478.
Hwang CK, Song KY, Kim CS, et al. Epigenetic programming of mu-opioid receptor gene in mouse brain is regulated by MeCP2 and Brg1 chromatin remodelling factor. J Cell Mol Med. 2009;13(9B):3591–3615.
Knothe C, Oertel BG, Ultsch A, et al. Pharmacoepigenetics of the role of DNA methylation in μ-opioid receptor expression in different human brain regions. Epigenomics. 2016;8(12):1583–1599.
Porreca F, Tang QB, Bian D, Riedl M, Elde R, Lai J. Spinal opioid mu receptor expression in lumbar spinal cord of rats following nerve injury. Brain Res. 1998;795(1–2):197–203.
Viet CT, Dang D, Ye Y, Ono K, Campbell RR, Schmidt BL. Demethylating drugs as novel analgesics for cancer pain. Clin Cancer Res. 2014;20(18):4882–4893.
Zhou XL, Yu LN, Wang Y, et al. Increased methylation of the MOR gene proximal promoter in primary sensory neurons plays a crucial role in the decreased analgesic effect of opioids in neuropathic pain. Mol Pain. 2014;10:51.
Sun Y, Sahbaie P, Liang D, et al. DNA methylation modulates nociceptive sensitization after incision. PLoS One. 2015;10(11):e0142046.
Doehring A, Oertel BG, Sittl R, Lotsch J. Chronic opioid use is associated with increased DNA methylation correlating with increased clinical pain. Pain. 2013;154(1):15–23.
Denk F, McMahon SB. Chronic pain: emerging evidence for the involvement of epigenetics. Neuron. 2012;73(3):435–444.
Formisano L, Noh KM, Miyawaki T, Mashiko T, Bennett MV, Zukin RS. Ischemic insults promote epigenetic reprogramming of mu opioid receptor expression in hippocampal neurons. Proc Natl Acad Sci U S A. 2007;104(10):4170–4175.
Bruce AW, Donaldson IJ, Wood IC, et al. Genome-wide analysis of repressor element 1 silencing transcription factor/neuron-restrictive silencing factor (REST/NRSF) target genes. Proc Natl Acad Sci U S A. 2004;101(28):10458–10463.
Schoenherr CJ, Anderson DJ. The neuron-restrictive silencer factor (NRSF): a coordinate repressor of multiple neuron-specific genes. Science. 1995;267(5202):1360–1363.
Buckley NJ, Johnson R, Zuccato C, Bithell A, Cattaneo E. The role of REST in transcriptional and epigenetic dysregulation in Huntington’s disease. Neurobiol Dis. 2010;39(1):28–39.
Uchida H, Ma L, Ueda H. Epigenetic gene silencing underlies C-fiber dysfunctions in neuropathic pain. J Neurosci. 2010;30(13):4806–4814.
Banks CJ, Joshi A, Michoel T. Functional transcription factor target discovery via compendia of binding and expression profiles. Sci Rep. 2016;6:20649.
Fan S, Zhang X. CpG island methylation pattern in different human tissues and its correlation with gene expression. Biochem Biophys Res Commun. 2009;383(4):421–425.
Davies MN, Volta M, Pidsley R, et al. Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood. Genome Biol. 2012;13(6):R43.
Andreae MH, Andreae DA. Regional anaesthesia to prevent chronic pain after surgery: a Cochrane systematic review and meta-analysis. Br J Anaesth. 2013;111(5):711–720.
Kieffer BL, Evans CJ. Opioid tolerance-in search of the holy grail. Cell. 2002;108(5):587–590.
Law PY, Loh HH, Wei LN. Insights into the receptor transcription and signaling: implications in opioid tolerance and dependence. Neuropharmacology. 2004;47(Suppl 1):300–311.
This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.Download Article [PDF]