Bruno G. Oertel

A Common Human μ-Opioid Receptor Genetic Variant Diminishes the Receptor Signaling Efficacy in Brain Regions Processing the Sensory Information of Pain

The single nucleotide polymorphism 118A>G of the human μ-opioid receptor gene OPRM1, which leads to an exchange of the amino acid asparagine (N) to aspartic acid (D) at position 40 of the extracellular receptor region, alters the in vivo effects of opioids to different degrees in pain-processing brain regions. The most pronounced N40D effects were found in brain regions involved in the sensory processing of pain intensity. Using the μ-opioid receptor-specific agonist DAMGO, we analyzed the μ-opioid receptor signaling, expression, and binding affinity in human brain tissue sampled postmortem from the secondary somatosensory area (SII) and from the ventral posterior part of the lateral thalamus, two regions involved in the sensory processing and transmission of nociceptive information. We show that the main effect of the N40D μ-opioid receptor variant is a reduction of the agonist-induced receptor signaling efficacy. In the SII region of homo- and heterozygous carriers of the variant 118G allele (n = 18), DAMGO was only 62% as efficient (p = 0.002) as in homozygous carriers of the wild-type 118A allele (n = 15). In contrast, the number of [3H]DAMGO binding sites was unaffected. Hence, the μ-opioid receptor G-protein coupling efficacy in SII of carriers of the 118G variant was only 58% as efficient as in homozygous carriers of the 118A allele (p < 0.001). The thalamus was unaffected by the OPRM1 118A>G SNP. In conclusion, we provide a molecular basis for the reduced clinical effects of opioid analgesics in carriers of μ-opioid receptor variant N40D.

Differential Opioid Action on Sensory and Affective Cerebral Pain Processing

Low doses of morphine, the most commonly used opioid analgesic, have been shown to significantly reduce the affective but not the sensory intensive dimension of pain. This suggests differential dose–response relationships of opioid analgesia on the sensory and affective components of pain. We investigated the effects of different alfentanil plasma concentration levels (0, 19.6±2.7, 47.2±7.6, and 76.6±11.3 ng/ml) on pain‐related brain activation achieved by short pulses of gaseous CO2 delivered to the nasal mucosa, using functional magnetic resonance imaging (fMRI) on a 3.0 T MRI scanner in 16 non‐carriers and 9 homozygous carriers of the μ‐opioid receptor gene variant OPRM1 118A>G. Increasing opioid concentrations had differential effects in brain regions processing the sensory and affective dimensions of pain. In brain regions associated with the processing of the sensory intensity of pain (primary and secondary somatosensory cortices, posterior insular cortex), activation decreased linearly in relation to alfentanil concentrations, which was significantly less pronounced in OPRM1 118G carriers. In contrast, in brain regions known to process the affective dimension of pain (parahippocampal gyrus, amygdala, anterior insula), pain‐related activation disappeared at the lowest alfentanil dose, without genotype differences.

Chronic opioid use is associated with increased DNA methylation correlating with increased clinical pain

Summary Chronic opioid exposure is associated with OPRM1 and global DNA hypermethylation. Global DNA methylation correlates with chronic pain in opioid‐treated but not non‐opioid‐treated patients. Abstract Environmentally caused changes in chromosomes that do not alter the DNA sequence but cause phenotypic changes by altering gene transcription are summarized as epigenetics. A major epigenetic mechanism is methylation or demethylation at CpG‐rich DNA islands. DNA methylation triggered by drugs has largely unexplored therapeutic consequences. Here we report increased methylation at a CpG rich island in the OPRM1 gene coding for μ‐opioid receptors and at a global methylation site (LINE‐1) in leukocytes of methadone‐substituted former opiate addicts compared with matched healthy controls. Higher DNA methylation associated with chronic opioid exposure was reproduced in an independent cohort of opioid‐treated as compared to non‐opioid‐treated pain patients. This suggests that opioids may stimulate DNA methylation. The OPRM1 methylation had no immediate effect on μ‐opioid receptor transcription and was not associated with opioid dosing requirements. However, the global DNA methylation at LINE‐1 was significantly correlated with increased chronic pain. This suggests inhibitory effects on the transcription of still unspecified nocifensive gene products. It further implies that opioids may be causally associated with increased genome‐wide DNA methylation, although currently there is no direct evidence of this. This has phenotypic consequences for pain and may provide a new, epigenetics‐associated mechanism of opioid‐induced hyperalgesia. The results indicate a potential influence of opioid analgesics on the patients’ epigenome. They emphasize the need for reliable and cost‐effective screening tools and may imply that high‐throughput screening for lead compounds in artificial expression systems may not provide the best tools for identifying new pain medications.

Genetic–epigenetic interaction modulates µ-opioid receptor regulation

Genetic and epigenetic mechanisms play important roles in protein expression, although at different levels. Genetic variations can alter CpG sites and thus influence the epigenetic regulation of mRNA expression, providing an increasingly recognized mechanism of functional consequences of genetic polymorphisms. One of those genetic effects is the association of reduced μ-opioid receptor expression with the functional genetic variant N40D (OPRM1 118A>G, rs1799971) that causes an amino acid exchange in the extracellular terminal of the μ-opioid receptor. We report that the nucleotide exchange at gene position +118 introduces a new CpG-methylation site into the OPRM1 DNA at position +117. This leads to an enhanced methylation of the OPRM1 DNA at this site and downstream. This epigenetic mechanism impedes μ-opioid receptor upregulation in brain tissue of Caucasian chronic opiate addicts, assessed postmortem. While in wild-type subjects, a reduced signalling efficiency associated with chronic heroin exposure was compensated by an increased receptor density, this upregulation was absent in carriers of the 118G receptor variant due to a diminished OPRM1 mRNA transcription. Thus, the OPRM1 118A>G SNP variant not only reduces µ-opioid receptor signalling efficiency, but, by a genetic-epigenetic interaction, reduces opioid receptor expression and therefore, depletes the opioid system of a compensatory reaction to chronic exposure. This demonstrates that a change in the genotype can cause a change in the epigenotype with major functional consequences.

Selective antagonism of opioid-induced ventilatory depression by an ampakine molecule in humans without loss of opioid analgesia.

Ventilatory depression is a significant risk associated with the use of opioids. We assessed whether opioid‐induced ventilatory depression can be selectively antagonized by an ampakine without reduction of analgesia. In 16 healthy men, after a single oral dose of 1,500 mg of the ampakine CX717, a target concentration of 100 ng/ml alfentanil decreased the respiratory frequency by only 2.9 ± 33.4% as compared with 25.6 ± 27.9% during placebo coadministration (P < 0.01). Blood oxygenation and the ventilatory response to hypercapnic challenge also showed significantly smaller decreases with CX717 than with placebo. In contrast, CX717 did not affect alfentanil‐induced analgesia in either electrical or heat‐based experimental models of pain. Both ventilatory depression and analgesia were reversed with 1.6 mg of naloxone. These results support the use of ampakines as selective antidotes in humans to counter opioid‐induced ventilatory depression without affecting opioid‐mediated analgesia.

Separating brain processing of pain fromthat of stimulus intensity.

Regions of the brain network activated by painful stimuli are also activated by nonpainful and even nonsomatosensory stimuli. We therefore analyzed where the qualitative change from nonpainful to painful perception at the pain thresholds is coded. Noxious stimuli of gaseous carbon dioxide (n = 50) were applied to the nasal mucosa of 24 healthy volunteers at various concentrations from 10% below to 10% above the individual pain threshold. Functional magnetic resonance images showed that these trigeminal stimuli activated brain regions regarded as the “pain matrix.” However, most of these activations, including the posterior insula, the primary and secondary somatosensory cortex, the amygdala, and the middle cingulate cortex, were associated with quantitative changes in stimulus intensity and did not exclusively reflect the qualitative change from nonpainful to pain. After subtracting brain activations associated with quantitative changes in the stimuli, the qualitative change, reflecting pain‐exclusive activations, could be localized mainly in the posterior insular cortex. This shows that cerebral processing of noxious stimuli focuses predominately on the quantitative properties of stimulus intensity in both their sensory and affective dimensions, whereas the integration of this information into the perception of pain is restricted to a small part of the pain matrix. Hum Brain Mapp, 2012.

Clinical pharmacology of analgesics assessed with human experimental pain models: bridging basic and clinical research

The medical impact of pain is such that much effort is being applied to develop novel analgesic drugs directed towards new targets and to investigate the analgesic efficacy of known drugs. Ongoing research requires cost‐saving tools to translate basic science knowledge into clinically effective analgesic compounds. In this review we have re‐examined the prediction of clinical analgesia by human experimental pain models as a basis for model selection in phase I studies. The overall prediction of analgesic efficacy or failure of a drug correlated well between experimental and clinical settings. However, correct model selection requires more detailed information about which model predicts a particular clinical pain condition. We hypothesized that if an analgesic drug was effective in an experimental pain model and also a specific clinical pain condition, then that model might be predictive for that particular condition and should be selected for development as an analgesic for that condition. The validity of the prediction increases with an increase in the numbers of analgesic drug classes for which this agreement was shown. From available evidence, only five clinical pain conditions were correctly predicted by seven different pain models for at least three different drugs. Most of these models combine a sensitization method. The analysis also identified several models with low impact with respect to their clinical translation. Thus, the presently identified agreements and non‐agreements between analgesic effects on experimental and on clinical pain may serve as a solid basis to identify complex sets of human pain models that bridge basic science with clinical pain research.

Quick Discrimination of Adelta and C Fiber Mediated Pain Based on Three Verbal Descriptors

Background Aδ and C fibers are the major pain-conducting nerve fibers, activate only partly the same brain areas, and are differently involved in pain syndromes. Whether a stimulus excites predominantly Aδ or C fibers is a commonly asked question in basic pain research but a quick test was lacking so far. Methodology/Principal Findings Of 77 verbal descriptors of pain sensations, “pricking”, “dull” and “pressing” distinguished best (95% cases correctly) between Aδ fiber mediated (punctate pressure produced by means of von Frey hairs) and C fiber mediated (blunt pressure) pain, applied to healthy volunteers in experiment 1. The sensation was assigned to Aδ fibers when “pricking” but neither “dull” nor “pressing” were chosen, and to C fibers when the sum of the selections of “dull” or “pressing” was greater than that of the selection of “pricking”. In experiment 2, with an independent cohort, the three-descriptor questionnaire achieved sensitivity and specificity above 0.95 for distinguishing fiber preferential non-mechanical induced pain (laser heat, exciting Aδ fibers, and 5-Hz electric stimulation, exciting C fibers). Conclusion A three-item verbal rating test using the words “pricking”, “dull”, and “pressing” may provide sufficient information to characterize a pain sensation evoked by a physical stimulus as transmitted via Aδ or via C fibers. It meets the criteria of a screening test by being easy to administer, taking little time, being comfortable in handling, and inexpensive while providing high specificity for relevant information.

The Partial 5-Hydroxytryptamine1A Receptor Agonist Buspirone does not Antagonize Morphine-induced Respiratory Depression in Humans

Based on experiments in rats, serotonin receptor 5‐hydroxytryptamine (5‐HT)1A agonists have been proposed as a potential therapeutic strategy for the selective treatment of opioid‐induced respiratory depression. We investigated the clinical applicability of this principle in healthy volunteers. Twelve subjects received 0.43 mg/kg morphine (30 mg for 70 kg body weight) administered intravenously (i.v.) over approximately 2 h. At the start of the morphine infusion, they received in a randomized, double‐blind cross‐over design 60 mg p.o. buspirone or placebo. Respiratory depression (hypercapnic challenge) and pain (electrical stimuli: 5 Hz sinus 0–20 mA; chemical stimuli: 200 ms gaseous CO2 pulses applied to the nasal mucosa) were assessed at baseline, at the end of the morphine infusion, and a third time after antagonizing the opioid effects by i.v. administration of 2 mg naloxone. The linear relationship between the minute ventilation and the CO2 concentration in the inspired air of 1.07±0.27 l/mm Hg CO2 at baseline conditions became shallower (0.45±0.23 l/mm Hg CO2) after morphine administration (P<0.001), indicating respiratory depression, which was significantly reversed by naloxone (0.95±0.43 l/mm Hg CO2; P=0.001). Co‐administration of buspirone had no effect on morphine‐induced respiratory depression (slope 0.45±0.23 l/mm Hg CO2 under morphine plus placebo versus 0.38±0.25 l/mm Hg CO2 under morphine plus buspirone; P=0.7). Significant morphine‐induced analgesia was observed in both pain models and was reversed by naloxone but unaffected by buspirone. Buspirone significantly increased the nausea induced by morphine (P=0.011). Oral co‐administration of a high dose of the clinically available 5‐HT1A agonist buspirone cannot be advised as a remedy for opioid‐induced respiratory depression. This is indicated by its lack of anti‐respiratory depressive effects and by the buspirone‐associated increase of morphine‐induced nausea.

Human models of pain for the prediction of clinical analgesia

&NA; Supported by a bioinformatics analysis, we present a set of experimental human pain models for which currently the strongest empirical evidence is available that they will identify analgesic drug efficacies that agree with those observed in clinical settings and thereby provide a correct prediction of drug effects for clinical analgesia. &NA; Human experimental pain models are widely used to study drug effects under controlled conditions. However, efforts to improve both animal and human experimental model selection, on the basis of increased understanding of the underlying pathophysiological pain mechanisms, have been disappointing, with poor translation of results to clinical analgesia. We have developed an alternative approach to the selection of suitable pain models that can correctly predict drug efficacy in particular clinical settings. This is based on the analysis of successful or unsuccessful empirical prediction of clinical analgesia using experimental pain models. We analyzed statistically the distribution of published mutual agreements or disagreements between drug efficacy in experimental and clinical pain settings. Significance limits were derived by random permutations of agreements. We found that a limited subset of pain models predicts a large number of clinically relevant pain settings, including efficacy against neuropathic pain for which novel analgesics are particularly needed. Thus, based on empirical evidence of agreement between drugs for their efficacy in experimental and clinical pain settings, it is possible to identify pain models that reliably predict clinical analgesic drug efficacy in cost‐effective experimental settings.