Pharmacogenetics of new analgesics

The genetic variant SLC2A1 -rs1105297 is associated with the differential analgesic response to a glucose-based treatment in newborns

ABSTRACT

Neonatal pain is a critical issue in clinical practice. The oral administration of glucose-based solutions is currently one of the most common and effective nonpharmacologic strategies for neonatal pain relief in daily minor procedures. However, a varying degree of analgesic efficacy has been reported for this treatment. Environmental, maternal, and genetic factors may explain this variability and potentially allow for a personalized analgesic approach, maximizing therapeutic efficacy and preventing side effects. We investigated the exposome (ie, the set of clinical and anthropometric variables potentially affecting the response to the therapy) and the genetic variability of the noradrenaline transporter gene (solute carrier family 6 member 2 [ SLC6A2 ]) and 2 glucose transporter genes (solute carrier family 2 member 1 [ SLC2A1 ] and 2 [ SLC2A2 ]) in relation to the neonatal analgesic efficacy of a 33% glucose solution. The study population consisted in a homogeneous sample of more than 1400 healthy term newborns. No association for the exposome was observed, whereas a statistically significant association between the G allele of SLC2A1 -rs1105297 and a fourfold decreased probability of responding to the therapy was identified after multiple-testing correction (odds ratio of 3.98, 95% confidence interval 1.95-9.17; P = 4.05 × 10 -4 ). This allele decreases the expression of SLC2A1-AS1 , causing the upregulation of SLC2A1 in the dorsal striatum, which has been suggested to be involved in reward-related processes through the binding of opioids to the striatal mu-opioid receptors. Altogether, these results suggest the involvement of SLC2A1 in the analgesic process and highlight the importance of host genetics for defining personalized analgesic treatments.

Artificial intelligence and machine learning in clinical pharmacological research

BACKGROUND

Clinical pharmacology research has always involved computational analysis. With the abundance of drug-related data available, the integration of artificial intelligence (AI) and machine learning (ML) methods has emerged as a promising way to enhance clinical pharmacology research.

METHODS

Based on an accepted definition of clinical pharmacology as a field of research dealing with all aspects of drug-human interactions, the analysis included publications from institutes specializing in clinical pharmacology. Research topics and the most used machine learning methods in clinical pharmacology were retrieved from the PubMed database and summarized.

RESULTS

ML was identified in 674 publications attributed to clinical pharmacology research, with a significant increase in publication activity over the last decade. Notable research topics addressed by ML/AI included Covid-19-related clinical pharmacology research, clinical neuropharmacology, drug safety and risk assessment, clinical pharmacology related to cancer research, and antimicrobial and antiviral research unrelated to Covid-19. In terms of ML methods, neural networks, random forests, and support vector machines were frequently mentioned in the abstracts of the retrieved papers.

CONCLUSIONS

ML, and AI in general, is increasingly being used in various research areas within clinical pharmacology. This report presents specific examples of applications and highlights the most used ML methods.

Multi-animal-model study reveals mutations in neural plasticity and nociception genes linked to excessive alcohol drinking

BACKGROUND

The basis for familial alcohol use disorder (AUD) remains an enigma due to various biological and societal confounds. The present study used three of the most adopted and documented rat models, combining the alcohol-preferring/non-alcohol-preferring (P/NP) lines and high alcohol-drinking/low alcohol-drinking (HAD/LAD) replicated lines, of AUD as examined through the lens of whole genomic analyses.

METHODS

We used complete genome sequencing of the P/NP lines and previously published sequences of the HAD/LAD replicates to enhance the discovery of variants associated with AUD and to remove confounding with genetic background and random genetic drift. Specifically, we used high-order statistical methods to search for genetic variants whose frequency changes in whole sets of gene ontologies corresponded with phenotypic changes in the direction of selection, that is, ethanol-drinking preference.

RESULTS

Our first finding was that in addition to variants causing translational changes, the principal genetic changes associated with drinking predisposition were silent mutations and mutations in the 3' untranslated regions (3'UTR) of genes. Neither of these types of mutations alters the amino acid sequence of the translated protein but they influence both the rate and conformation of gene transcription, including its stability and posttranslational events that alter gene efficacy. This finding argues for refocusing human genomic studies on changes in gene efficacy. Among the key ontologies identified were the central genes associated with the Na+ voltage-gated channels of neurons and glia (including the Scn1a, Scn2a, Scn2b, Scn3a, Scn7a, and Scn9a subtypes) and excitatory glutamatergic secretion (including Grm2 and Myo6), both of which are essential in neuroplasticity. In addition, we identified "Nociception or Sensory Perception of Pain," which contained variants in nociception (Arrb1, Ccl3, Ephb1) and enlist sodium (Scn1a, Scn2a, Scn2b, Scn3a, Scn7a), pain activation (Scn9a), and potassium channel (Kcna1) genes.

CONCLUSION

The multi-model analyses used herein reduced the confounding effects of random drift and the "founders" genetic background. The most differentiated bidirectionally selected genes across all three animal models were Scn9a, Scn1a, and Kcna, all of which are annotated in the nociception ontology. The complexity of neuroplasticity and nociception adds strength to the hypothesis that neuroplasticity and pain (physical or psychological) are prominent phenotypes genetically linked to the development of AUD.

Pharmacological data science perspective on fatal incidents of morphine treatment

Morphine prescribed for analgesia has caused drug-related deaths at an estimated incidence of 0.3% to 4%. Morphine has pharmacological properties that make it particularly difficult to assess the causality of morphine administration with a patient's death, such as its slow transfer between plasma and central nervous sites of action and the existence of the active metabolite morphine-6-glucuronide with opioid agonistic effects, Furthermore, there is no well-defined toxic dose or plasma/blood concentration for morphine. Dosing is often adjusted for adequate pain relief. Here, we summarize reported deaths associated with morphine therapy, including associated morphine exposure and modulating patient factors such as pharmacogenetics, concomitant medications, or comorbidities. In addition, we systematically analyzed published numerical information on the stability of concentrations of morphine and its relevant metabolites in biological samples collected postmortem. A medicolegal case is presented in which the causality of morphine administration with death was in dispute and pharmacokinetic modeling was applied to infer the administered dose. The results of this analytical review suggest that (i) inference from postmortem blood concentrations to the morphine dose administered has low validity and (ii) causality between a patient's death and the morphine dose administered remains a highly context-dependent and collaborative assessment among experts from different medical specialties.

Pharmacogenetic profiling and individualised therapy in the treatment of degenerative spinal conditions

Patients presenting with degenerative spinal changes are often poor surgical candidates due to associated co-morbidities, frailty, or sarcopenia. Additionally, surgeries of a degenerative spine can prove difficult due to the distortion of normal surgical anatomy. Therefore, many patients are managed conservatively with a variety of modalities, including over-the-counter and prescription medications. Nevertheless, several patients do not experience adequate relief from pain with analgesic medications, precipitating multiple hospital visits, and usage of resources. As a result, back pain is regarded as a major economic burden, with total costs of associated treatment exceeding $100 billion annually. Pharmacogenetics is a relatively novel method of evaluating an individual's response to analgesic medications, through analysis of germline polymorphisms. It entails obtaining a genetic sample, often via buccal swab or peripheral blood sample, and genetic analysis achieved through either polymerase chain reaction +/- Sanger sequencing, microassays, restriction length fragment polymorphism analysis, or genetic library preparation and next generation sequencing. The potential efficacy of pharmacogenetic analysis has been highlighted across several specialities to date. However, a paucity of evidence exists regarding spine surgery populations. Nevertheless, regular prospective pharmacogenetic analysis may ultimately prove beneficial when concerning degenerative spinal cohorts due to aforementioned surgical and economic considerations. The purpose of this narrative review is to outline how metaboliser profile variants affect the pharmacokinetics of specific analgesia used to treat back pain, and to discuss the current potential and limitations of employing regular pharmacogenetic analysis for spine surgery populations with degenerative conditions.

An active ingredient isolated from Ganoderma lucidum promotes burn wound healing via TRPV1/SMAD signaling

The mushroom Ganoderma lucidum is a traditional Chinese medicine and G. lucidum spore oil (GLSO) is the lipid fraction isolated from Ganoderma spores. We examined the effect of GLSO on burn wound healing in mice. Following wounding, GLSO was applied on the wounds twice daily. Repair analysis was performed by Sirius-Red-staining at different time points. Cell proliferation and migration assays were performed to verify the effect of GLSO on growth. Network pharmacology analysis to identify possible targets was also carried out, followed by Western blotting, nuclear translocation, cell proliferation, and immunofluorescence assays for in-depth investigation of the mechanism. Our study showed that GLSO significantly promoted cell proliferation, and network pharmacology analysis suggested that GLSO might act through transient receptor potential vanilloid receptor 1 (TRPV1)/SMAD signaling. Furthermore, GLSO elevated SMAD2/3 expression in skin burn and promoted its nuclear translocation, and TRPV1 expression was also increased upon exposure to GLSO. Cell proliferation and immunofluorescence assays with TRPV1 inhibitor showed that GLSO accelerated skin burn wound healing through TRPV1 and SMADs signaling, which provides a foundation for clinical application of GLSO in the healing of deep skin burns.

Immunomodulatory Potential of Cannabidiol in Multiple Sclerosis: a Systematic Review

Multiple sclerosis (MS) is the most common chronic autoimmune disease of the central nervous system. Efficacy of treatments for MS is associated with risk of adverse effects, and effective and well-tolerated drugs remain a major unmet need. Cannabis (Cannabis sativa L., fam. Cannabaceae) and cannabinoids are popular among MS patients to treat spasticity and pain. Cannabinoids are endowed with remarkable immunomodulating properties, and in particular the non-psychotropic cannabinoid cannabidiol (CBD) is increasingly recognized as anti-inflammatory and immunosuppressive, nevertheless with excellent tolerability even at high doses. In this systematic review, we retrieved and critically evaluated available evidence regarding the immune and disease-modifying effects of CBD in experimental autoimmune encephalomyelitis (EAE) and in MS. Evidence in rodent models of EAE strongly supports CBD as effective, while clinical evidence is still limited and usually negative, due to paucity of studies and possibly to the use of suboptimal dosing regimens. Better characterization of targets acted upon by CBD in MS should be obtained in ex vivo/in vitro studies in human immune cells, and higher doses should be tested in well-designed clinical trials with clinically relevant efficacy endpoints. Graphical Abstract.

Computational Functional Genomics-Based AmpliSeq™ Panel for Next-Generation Sequencing of Key Genes of Pain

The genetic background of pain is becoming increasingly well understood, which opens up possibilities for predicting the individual risk of persistent pain and the use of tailored therapies adapted to the variant pattern of the patient's pain-relevant genes. The individual variant pattern of pain-relevant genes is accessible via next-generation sequencing, although the analysis of all "pain genes" would be expensive. Here, we report on the development of a cost-effective next generation sequencing-based pain-genotyping assay comprising the development of a customized AmpliSeq™ panel and bioinformatics approaches that condensate the genetic information of pain by identifying the most representative genes. The panel includes 29 key genes that have been shown to cover 70% of the biological functions exerted by a list of 540 so-called "pain genes" derived from transgenic mice experiments. These were supplemented by 43 additional genes that had been independently proposed as relevant for persistent pain. The functional genomics covered by the resulting 72 genes is particularly represented by mitogen-activated protein kinase of extracellular signal-regulated kinase and cytokine production and secretion. The present genotyping assay was established in 61 subjects of Caucasian ethnicity and investigates the functional role of the selected genes in the context of the known genetic architecture of pain without seeking functional associations for pain. The assay identified a total of 691 genetic variants, of which many have reports for a clinical relevance for pain or in another context. The assay is applicable for small to large-scale experimental setups at contemporary genotyping costs.

Genetics and Opioids: Towards More Appropriate Prescription in Cancer Pain

Opioids are extensively used in patients with cancer pain; despite their efficacy, several patients can experience ineffective analgesia and/or side effects. Pharmacogenetics is a new approach to drug prescription based on the “personalized-medicine” concept, i.e., the ability of tailoring treatments to each individual’s genetic/genomic profile. Pharmacogenetics aims to identify specific genetic variants that influence pharmacokinetics and pharmacodynamics of drugs, better determining their effectiveness/safety profile. Opioid response is a complex scenario, but some gene variants have shown a correlation with pain sensitivity, as well as with opioid metabolism and clinical efficacy/adverse events. Although questions remain unanswered, some of these gene variants may already be used to identify specific patients’ phenotypes that are more prone to experience better clinical response (i.e., better analgesia and/or less adverse events). Once adopted, this approach to opioid prescription may improve a patient’s outcome. This review summarizes the available data on genetic variants and opioid response: we will focus on basic pharmacogenetic and its impact in the clinical scenario discussing how they may lead to more appropriate opioid prescription in cancer patients.

Machine-Learned Association of Next-Generation Sequencing-Derived Variants in Thermosensitive Ion Channels Genes with Human Thermal Pain Sensitivity Phenotypes

Genetic association studies have shown their usefulness in assessing the role of ion channels in human thermal pain perception. We used machine learning to construct a complex phenotype from pain thresholds to thermal stimuli and associate it with the genetic information derived from the next-generation sequencing (NGS) of 15 ion channel genes which are involved in thermal perception, including ASIC1, ASIC2, ASIC3, ASIC4, TRPA1, TRPC1, TRPM2, TRPM3, TRPM4, TRPM5, TRPM8, TRPV1, TRPV2, TRPV3, and TRPV4. Phenotypic information was complete in 82 subjects and NGS genotypes were available in 67 subjects. A network of artificial neurons, implemented as emergent self-organizing maps, discovered two clusters characterized by high or low pain thresholds for heat and cold pain. A total of 1071 variants were discovered in the 15 ion channel genes. After feature selection, 80 genetic variants were retained for an association analysis based on machine learning. The measured performance of machine learning-mediated phenotype assignment based on this genetic information resulted in an area under the receiver operating characteristic curve of 77.2%, justifying a phenotype classification based on the genetic information. A further item categorization finally resulted in 38 genetic variants that contributed most to the phenotype assignment. Most of them (10) belonged to the TRPV3 gene, followed by TRPM3 (6). Therefore, the analysis successfully identified the particular importance of TRPV3 and TRPM3 for an average pain phenotype defined by the sensitivity to moderate thermal stimuli.

Computational functional genomics-based reduction of disease-related gene sets to their key components

MOTIVATION

The genetic architecture of diseases becomes increasingly known. This raises difficulties in picking suitable targets for further research among an increasing number of candidates. Although expression based methods of gene set reduction are applied to laboratory-derived genetic data, the analysis of topical sets of genes gathered from knowledge bases requires a modified approach as no quantitative information about gene expression is available.

RESULTS

We propose a computational functional genomics-based approach at reducing sets of genes to the most relevant items based on the importance of the gene within the polyhierarchy of biological processes characterizing the disease. Knowledge bases about the biological roles of genes can provide a valid description of traits or diseases represented as a directed acyclic graph (DAG) picturing the polyhierarchy of disease relevant biological processes. The proposed method uses a gene importance score derived from the location of the gene-related biological processes in the DAG. It attempts to recreate the DAG and thereby, the roles of the original gene set, with the least number of genes in descending order of importance. This obtained precision and recall of over 70% to recreate the components of the DAG charactering the biological functions of n=540 genes relevant to pain with a subset of only the k=29 best-scoring genes.

CONCLUSIONS

A new method for reduction of gene sets is shown that is able to reproduce the biological processes in which the full gene set is involved by over 70%; however, by using only ∼5% of the original genes.

AVAILABILITY AND IMPLEMENTATION

The necessary numerical parameters for the calculation of gene importance are implemented in the R package dbtORA at https://github.com/IME-TMP-FFM/dbtORA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genetic polymorphisms in the opioid receptor delta 1 (OPRD1) gene are associated with methadone dose in methadone maintenance treatment for heroin dependence

Delta opioid receptor (DOR) is well known to be involved in heroin dependence. This study tested the hypothesis that single nucleotide polymorphisms (SNPs) in the opioid receptor delta 1 (OPRD1) gene coding region are associated with treatment responses in a methadone maintenance therapy (MMT) cohort in Taiwan. Three hundred forty-four MMT patients were recruited. Diastolic/systolic blood pressure, heart rate, methadone dosage, and plasma concentrations of methadone were recorded. Twenty-five SNPs located within the OPRD1 genetic region were selected and genotyped from the genomic DNA of all 344 participants. After pairwise tagger analyses, tagger SNP rs204047 showed a significant association with methadone dosage (P = 0.0019), and tagger SNPs rs204047 and rs797397 were significantly associated with plasma R, S-methadone concentrations (P < 0.0006) in patients tested negative in the urine morphine test, which indicated patients with a better response to MMT. The major genotype carriers showed a higher methadone dosage and higher plasma concentrations of R, S-methadone than the minor genotype carriers. The results indicated that OPRD1 genetic variants were associated with methadone dosage and methadone plasma concentration in MMT patients with a negative morphine test result.

[Generating knowledge from complex data sets in human experimental pain research]

Pain has a complex pathophysiology that is expressed in multifaceted and heterogeneous clinical phenotypes. This makes research on pain and its treatment a potentially data-rich field as large amounts of complex data are generated. Typical sources of such data are investigations with functional magnetic resonance imaging, complex quantitative sensory testing, next-generation DNA sequencing and functional genomic research approaches, such as those aimed at analgesic drug discovery or repositioning of drugs known from other indications as new analgesics. Extracting information from these big data requires complex data scientific-based methods belonging more to computer science than to statistics. A particular interest is currently focused on machine learning, the methods of which are used for the detection of interesting and biologically meaningful structures in high-dimensional data. Subsequently, classifiers can be created that predict clinical phenotypes from, e.g. clinical or genetic features acquired from subjects. In addition, knowledge discovery in big data accessible in electronic knowledge bases, can be used to generate hypotheses and to exploit the accumulated knowledge about pain for the discovery of new analgesic drugs. This enables so-called data-information-knowledge-wisdom (DIKW) approaches to be followed in pain research. This article highlights current examples from pain research to provide an overview about contemporary data scientific methods used in this field of research.

Effects of continuous theta-burst stimulation of the primary motor and secondary somatosensory areas on the central processing and the perception of trigeminal nociceptive input in healthy volunteers

Supplemental Digital Content is Available in the Text.

Inactivating paired continuous theta-burst stimulation of the primary motor cortex but not on the secondary somatosensory area flattened the relationship between brain activation and stimulus strength while not impacting on the subjective perceptions.

Noninvasive modulation of the activity of pain-related brain regions by means of transcranial magnetic stimulation promises an innovative approach at analgesic treatments. However, heterogeneous successes in pain modulation by setting reversible “virtual lesions” at different brain areas point at unresolved problems including the optimum stimulation site. The secondary somatosensory cortex (S2) has been previously identified to be involved in the perception of pain-intensity differences. Therefore, impeding its activity should impede the coding of the sensory component of pain intensity, resulting in a flattening of the relationship between pain intensity and physical stimulus strength. This was assessed using inactivating spaced continuous theta-burst stimulation (cTBS) in 18 healthy volunteers. In addition, cTBS was applied on the primary motor cortex (M1) shown previously to yield moderate and variable analgesic effects, whereas sham stimulation at both sites served as placebo condition. Continuous theta-burst stimulation flattened the relationship between brain activation and stimulus strength, mainly at S2, the insular cortex, and the postcentral gyrus (16 subjects analyzed). However, these effects were observed after inactivation of M1 while this effect was not observed after inactivation of S2. Nevertheless, both the M1 and the S2-spaced cTBS treatment were not reflected in the ratings of the nociceptive stimuli of different strengths (17 subjects analyzed), contrasting with the clear coding of stimulus strength by these data. Hence, while modulating the central processing of nociceptive input, cTBS failed to produce subjectively relevant changes in pain perception, indicating that the method in the present implementation is still unsuitable for clinical application.

A machine-learned analysis of human gene polymorphisms modulating persisting pain points to major roles of neuroimmune processes

Background

Human genetic research has implicated functional variants of more than one hundred genes in the modulation of persisting pain. Artificial intelligence and machine‐learning techniques may combine this knowledge with results of genetic research gathered in any context, which permits the identification of the key biological processes involved in chronic sensitization to pain.

Methods

Based on published evidence, a set of 110 genes carrying variants reported to be associated with modulation of the clinical phenotype of persisting pain in eight different clinical settings was submitted to unsupervised machine‐learning aimed at functional clustering. Subsequently, a mathematically supported subset of genes, comprising those most consistently involved in persisting pain, was analysed by means of computational functional genomics in the Gene Ontology knowledgebase.

Results

Clustering of genes with evidence for a modulation of persisting pain elucidated a functionally heterogeneous set. The situation cleared when the focus was narrowed to a genetic modulation consistently observed throughout several clinical settings. On this basis, two groups of biological processes, the immune system and nitric oxide signalling, emerged as major players in sensitization to persisting pain, which is biologically highly plausible and in agreement with other lines of pain research.

Conclusions

The present computational functional genomics‐based approach provided a computational systems‐biology perspective on chronic sensitization to pain. Human genetic control of persisting pain points to the immune system as a source of potential future targets for drugs directed against persisting pain. Contemporary machine‐learned methods provide innovative approaches to knowledge discovery from previous evidence.

Significance

We show that knowledge discovery in genetic databases and contemporary machine‐learned techniques can identify relevant biological processes involved in Persitent pain.

Computational functional genomics-based approaches in analgesic drug discovery and repurposing

Persistent pain is a major healthcare problem affecting a fifth of adults worldwide with still limited treatment options. The search for new analgesics increasingly includes the novel research area of functional genomics, which combines data derived from various processes related to DNA sequence, gene expression or protein function and uses advanced methods of data mining and knowledge discovery with the goal of understanding the relationship between the genome and the phenotype. Its use in drug discovery and repurposing for analgesic indications has so far been performed using knowledge discovery in gene function and drug target-related databases; next-generation sequencing; and functional proteomics-based approaches. Here, we discuss recent efforts in functional genomics-based approaches to analgesic drug discovery and repurposing and highlight the potential of computational functional genomics in this field including a demonstration of the workflow using a novel R library ‘dbtORA’.

Experimental Drugs for Neuropathic Pain

BACKGROUND

Neuropathic pain (NP) is an important public health problem and despite recent progress in the understanding, diagnosis, pathophysiological mechanisms and the treatment of NP, many patients remain refractory to pharmacotherapy.

OBJECTIVE

Currently used drugs have limited efficacy and dose-limiting adverse effects, and thus there is a substantial need for further development of novel medications for its treatment. Alternatively, drugs approved for use in diseases other than NP can be applied as experimental for NP conditions. This paper covers advances in the field of NP treatment.

RESULTS

The prime focus of this paper is on drugs with well-established pharmacological activity whose current therapeutic applications are distinct from NP. These drugs could be a potential novel treatment of NP. Data from preclinical studies and clinical trials on these experimental drugs are presented. The development of advanced methods of genomics enabled to propose new targets for drugs which could be effective in the NP treatment.

CONCLUSION

Experimental drugs for NP can be a treatment option which should be tailor-made for each individual on the basis of pain features, previous therapies, associated clinical conditions, recurrence of pain, adverse effects, contraindications and patients' preferences. At present, there are only some agents which may have potential as novel treatments. Increasing knowledge about mechanisms underlying NP, mechanisms of drug action, as well as available data from preclinical and clinical studies make botulinum toxin A, minocycline, ambroxol, statins and PPAR agonists (ATx086001) promising potential future treatment options.

Effect of endocannabinoid degradation on pain: role of FAAH polymorphisms in experimental and postoperative pain in women treated for breast cancer

Fatty acid amide hydrolase (FAAH) metabolizes the endocannabinoid anandamide, which has an important role in nociception. We investigated the role of common FAAH single-nucleotide polymorphisms (SNPs) in experimentally induced and postoperative pain. One thousand women undergoing surgery for breast cancer participated in the study. They were tested for cold (n = 900) and heat pain (n = 1000) sensitivity. After surgery, their pain intensities and analgesic consumption were carefully registered. FAAH genotyping was performed using MassARRAY platform and genome-wide chip (n = 926). Association between 8 FAAH SNPs and 9 pain phenotypes was analyzed using linear regression models. The results showed that carrying 2 copies of a missense variant converting proline at position 129 to threonine (rs324420) resulted in significantly lower cold pain sensitivity and less need for postoperative analgesia. More specifically, rs324420 and another highly correlated SNP, rs1571138, associated significantly with cold pain intensity (corrected P value, 0.0014; recessive model). Patients homozygous for the minor allele (AA genotype) were less sensitive to cold pain (β = -1.48; 95% CI, -2.14 to -0.8). Two other SNPs (rs3766246 and rs4660928) showed nominal association with cold pain, and SNPs rs4141964, rs3766246, rs324420, and rs1571138 nominal association with oxycodone consumption. In conclusion, FAAH gene variation was shown to associate with cold pain sensitivity with P129T/rs324420 being the most likely causal variant as it is known to reduce the FAAH enzyme activity. The same variant showed nominal association with postoperative oxycodone consumption. Our conclusions are, however, limited by the lack of replication and the results should be replicated in an independent cohort.

Pharmacogenetics of analgesic drugs

• Individual variability in pain perception and differences in the efficacy of analgesic drugs are complex phenomena and are partly genetically predetermined.

• Analgesics act in various ways on the peripheral and central pain pathways and are regarded as one of the most valuable but equally dangerous groups of medications.

• While pharmacokinetic properties of drugs, metabolism in particular, have been scrutinised by genotype–phenotype correlation studies, the clinical significance of inherited variants in genes governing pharmacodynamics of analgesics remains largely unexplored (apart from the µ-opioid receptor).

• Lack of replication of the findings from one study to another makes meaningful personalised analgesic regime still a distant future.

• This narrative review will focus on findings related to pharmacogenetics of commonly used analgesic medications and highlight authors’ views on future clinical implications of pharmacogenetics in the context of pharmacological treatment of chronic pain.

Considerations when using pharmacokinetic/pharmacodynamic modeling to determine the effectiveness of simple analgesics in children

INTRODUCTION

Assessment of analgesic drugs includes comparative studies to other analgesics and local anesthesia blockade, number needed to treat estimates and opioid sparing descriptions. An additional methodology is to define the concentration-response relationship using pharmacokinetic/pharmacodynamic (PK/PD) modeling.

AREAS COVERED

A concentration-response relationship allows analgesic effect comparison between drugs for different acute pain types. Covariates such as size, age and organ function impact greatly on PK in children. The cumulative effect of confounding factors (e.g., pharmacogenetics, placebo and changes in baseline pain over time) complicates PD. Other factors (outcome measures, method of measurement, failure to account for study attrition) impact on outcome. Population PK/PD modeling approaches allow us to account for these various factors to some extent.

EXPERT OPINION

Nonlinear mixed effects models help interpret analgesic data and their use is increasing. The PK is relatively well understood. The next investigative step will involve investigation into covariate effects for PD. Mathematical functions for both placebo models and dropout models are well described and should be incorporated into analgesic effectiveness studies that investigate a range of doses. Improvements in pain assessment tools and a greater understanding of pharmacogenomics factors will help individualize analgesic therapy.

Antiepileptics for post-herpetic neuralgia in the elderly: current and future prospects

Post-herpetic neuralgia is a painful condition and its prevalence increases with age. It is a burden for older patients and the association of age-related pharmacokinetic and pharmacodynamic changes, high co-morbidity and polypharmacy leads to the risk of adverse drug reactions and interactions. This type of neuropathic pain is particularly difficult to treat and guidelines recommend the use of gabapentinoids and some antidepressants, the utility of which may be hampered by adverse effects such as sedation, dizziness and impaired age-related renal function. Re-formulations of antiepileptics (anticonvulsants) are being developed and/or marketed and suggest interesting innovative profiles with improved bioavailability, low drug-drug interactions and better tolerability that need to be confirmed in future studies. However, there are no new antiepileptics being developed for post-herpetic neuralgia, and prospective studies specifically focused on the older population are still missing, while this age group is particularly at risk of developing shingles and chronic neuropathic pain with a deleterious impact on quality of life.

Advances in Electrophysiological Research

Electrophysiological measures of brain function are effective tools to understand neurocognitive phenomena and sensitive indicators of pathophysiological processes associated with various clinical conditions, including alcoholism. Individuals with alcohol use disorder (AUD) and their high-risk offspring have consistently shown dysfunction in several electrophysiological measures in resting state (i.e., electroencephalogram) and during cognitive tasks (i.e., event-related potentials and event-related oscillations). Researchers have recently developed sophisticated signal-processing techniques to characterize different aspects of brain dynamics, which can aid in identifying the neural mechanisms underlying alcoholism and other related complex disorders.These quantitative measures of brain function also have been successfully used as endophenotypes to identify and help understand genes associated with AUD and related disorders. Translational research also is examining how brain electrophysiological measures potentially can be applied to diagnosis, prevention, and treatment.

Transient receptor potential ion channels in primary sensory neurons as targets for novel analgesics

The last decade has witnessed an explosion in novel findings relating to the molecules involved in mediating the sensation of pain in humans. Transient receptor potential (TRP) ion channels emerged as the greatest group of molecules involved in the transduction of various physical stimuli into neuronal signals in primary sensory neurons, as well as, in the development of pain. Here, we review the role of TRP ion channels in primary sensory neurons in the development of pain associated with peripheral pathologies and possible strategies to translate preclinical data into the development of effective new analgesics. Based on available evidence, we argue that nociception-related TRP channels on primary sensory neurons provide highly valuable targets for the development of novel analgesics and that, in order to reduce possible undesirable side effects, novel analgesics should prevent the translocation from the cytoplasm to the cell membrane and the sensitization of the channels rather than blocking the channel pore or binding sites for exogenous or endogenous activators.

Confronting the challenges of effective pain management in children following tonsillectomy

Tonsillectomy is an extremely common surgical procedure associated with significant morbidity and mortality. The post-operative challenges include: respiratory complications, post-tonsillectomy hemorrhage, nausea, vomiting and significant pain. The present model of care demands that most of these children are managed in an ambulatory setting. The recent Federal Drug Agency (FDA) warning contraindicating the use of codeine after tonsillectomy in children represents a significant change of practice for many pediatric otolaryngological surgeons. This introduces a number of other safety concerns when deciding on a safe alternative to codeine, especially since most tonsillectomy patients are managed by lay primary caregiver's at home. This review outlines the safety issues and proposes, based on currently available evidence, a preventative multi-modal strategy to manage pain, nausea and vomiting without increasing the risk of post-tonsillectomy bleeding.

No more pain upon Gq-protein-coupled receptor activation: role of endocannabinoids

Marijuana has been used to relieve pain for centuries. The analgesic mechanism of its constituents, the cannabinoids, was only revealed after the discovery of cannabinoid receptors (CB1 and CB2) two decades ago. The subsequent identification of the endocannabinoids, anandamide and 2-arachidonoylglycerol (2-AG), and their biosynthetic and degradation enzymes discloses the therapeutic potential of compounds targeting the endocannabinoid system for pain control. Inhibitors of the anandamide and 2-AG degradation enzymes, fatty acid amide hydrolase and monoacylglycerol lipase, respectively, may be superior to direct cannabinoid receptor ligands as endocannabinoids are synthesized on demand and rapidly degraded, focusing action at generating sites. Recently, a promising strategy for pain relief was revealed in the periaqueductal gray (PAG). It is initiated by Gq-protein-coupled receptor (Gq PCR) activation of the phospholipase C-diacylglycerol lipase enzymatic cascade, generating 2-AG that produces inhibition of GABAergic transmission (disinhibition) in the PAG, thereby leading to analgesia. Here, we introduce the antinociceptive properties of exogenous cannabinoids and endocannabinoids, involving their biosynthesis and degradation processes, particularly in the PAG. We also review recent studies disclosing the Gq PCR-phospholipase C-diacylglycerol lipase-2-AG retrograde disinhibition mechanism in the PAG, induced by activating several Gq PCRs, including metabotropic glutamatergic (type 5 metabotropic glutamate receptor), muscarinic acetylcholine (M1/M3), and orexin 1 receptors. Disinhibition mediated by type 5 metabotropic glutamate receptor can be initiated by glutamate transporter inhibitors or indirectly by substance P, neurotensin, cholecystokinin and capsaicin. Finally, the putative role of 2-AG generated after activating the above neurotransmitter receptors in stress-induced analgesia is discussed.

Ask the Experts: What do we know (and not know) about prescription opioid misuse in the context of chronic pain management?

James Zacny received his PhD in Psychology at West Virginia University (WV, USA) in 1984. From 1984 to 1986 he did a postdoctoral fellowship at The Johns Hopkins University School of Medicine (MD, USA) in the Behavioral Pharmacology Research Unit of the Department of Psychiatry and Behavioral Sciences. He then became Research Associate in the Department of Psychiatry at the University of Chicago (IL, USA) and conducted both preclinical and human psychopharmacology studies. In 1992 he joined the faculty in the Department of Anesthesia & Critical Care at the University where he is currently Professor. His two primary research interests have been in studying the psychopharmacological effects of drugs used in anesthesiology, chiefly inhaled and intravenous general anesthetics at subanesthestic doses, and opioid analgesics, in healthy nondrug-abusing volunteers. The unique research environment he is in fostered a large body of research that systematically characterized the subjective, psychomotor and reinforcing (rewarding) effects of a number of different anesthetic and analgesic agents. Dr Zacny's primary source of funding is through the National Institute on Drug Abuse and in 1999 was presented with a MERIT award for his research on opioids. In 2001 he focused his efforts on prescription opioids at about the same time that warning signs started to emerge indicating that prescription opioid abuse was on the rise. He has characterized the psychopharmacological effects of a number of prescription opioids, as well as investigated possible factors that might modulate their positive (as well as negative) subjective effects including gender, sensation seeking and alcohol. He has also written guest editorials on the psychomotor effects of opioids in relation to the ability of chronic pain patients on long-term opioid therapy to drive. He is an elected member of the College on Problems of Drug Dependence and of the Association of University Anesthesiologists, and served as President of the Division of Psychopharmacology and Substance Abuse of the American Psychological Association, and the International Study Group Investigating Drugs as Reinforcers.

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.

Modeling the Influence of the A118G Polymorphism in the OPRM1 Gene and of Noxious Stimulation on the Synergistic Relation between Propofol and Remifentanil

Background:

The presence of the A118G single nucleotide polymorphism in the OPRM1 gene as well as noxious stimulation might affect the requirements of remifentanil for patients undergoing ultrasonographic endoscopy under sedation-analgesia with propofol and remifentanil. Bispectral index (BIS) was used as a surrogate measure of effect.

Methods:

A total of 207 patients were screened for A118G and randomly received different combinations of propofol and remifentanil, changed depending on the nausea response to endoscopy tube introduction. Nonlinear mixed effects modelling was used to establish the relation between propofol and remifentanil with respect to BIS and to investigate the influence of A118G or noxious stimulation. The value of ke0 for propofol and remifentanil was estimated to avoid the hysteresis between predicted effect site concentration (Ce) and BIS.

Results:

Data from 176 patients were analysed. Eleven were recessive homozygous for A118G (OPRM = 1). A total of 165 patients were either dominant homozygous or heterozygous and considered normal (OPRM = 0). The estimated values of ke0 for propofol and remifentanil were 0.122 and 0.148min−1. Propofol and remifentanil were synergistic with respect to the BIS (α = 1.85). EC50 estimate for propofol was 3.86 µg/ml and for remifentanil 19.6 ng/ml in normal patients and 326ng/ml in OPRM = 1 patients. BIS increases around 4% for the same effect site concentrations with noxious stimulation.

Conclusions:

Predicted effect site concentration of remifentanil ranging 1–5ng/ml synergistically potentiates the effects of propofol on the BIS but has no effect in A118G patients. Noxious stimulation increases BIS values by 4% at the same concentrations of propofol and remifentanil.

Pharmacogenetics of opiates in clinical practice: the visible tip of the iceberg

Opioids are the cornerstone of analgesic therapy and are used as a substitution therapy for opiate addiction. Interindividual variability in response to opioids is a significant challenge in the management of pain and substitution. Therefore, treatment with opioids requires a careful individualization of dosage to achieve an appropriate balance of efficacy and adverse effects and, consequently, avoid toxicity, particularly respiratory depression, sedation and for some, cardiac ventricular fibrillations. Many studies have investigated the association between genetic factors and the variability of response to opioids. Variants in genes encoding proteins implied in opioid pharmacokinetics (absorption, distribution, metabolism, excretion and toxicity), together with those implied in opioids direct and indirect pharmacodynamics (genes of opioid receptors and monoaminergic systems), are the most studied. Many association studies have not been replicated. The purpose of this article is to summarize pharmacogenetic data associated with some opioids frequently encountered in managed care settings.

Influence of OPRM1 Asn40Asp variant (A118G) on [11C]carfentanil binding potential: preliminary findings in human subjects

The Asn40Asp variant (A118G) of the μ opioid receptor (OPRM1) gene is thought to contribute to the development and treatment of alcohol dependence. Employing positron emission tomography (PET), we first examined whether the single nucleotide polymorphism (SNP) modifies binding potential (BP(ND)) of the μ-selective ligand [(11)C]carfentanil in healthy control (Con) and 5-d abstinent alcohol-dependent (AD) subjects (unblocked basal scan). Second, we examined whether the allelic variants were associated with differences in OPRM1 occupancy by naltrexone (50 mg) in AD subjects. Con and AD carriers of the G allele (AG) had lower global BP(ND) at the basal scan than subjects homozygous for the A allele (AA). In AD subjects, naltrexone occupancy was slightly higher in AG subjects (98.9%) compared to AA subjects (93.1%), but this was not significant. We are the first to demonstrate using PET in healthy normal and AD subjects that the A118G SNP alters OPRM1 availability.

Family-based genome-wide association study of frontal θ oscillations identifies potassium channel gene KCNJ6

Event-related oscillations (EROs) represent highly heritable neuroelectric correlates of cognitive processes that manifest deficits in alcoholics and in offspring at high risk to develop alcoholism. Theta ERO to targets in the visual oddball task has been shown to be an endophenotype for alcoholism. A family-based genome-wide association study was performed for the frontal theta ERO phenotype using 634 583 autosomal single nucleotide polymorphisms (SNPs) genotyped in 1560 family members from 117 families densely affected by alcohol use disorders, recruited in the Collaborative Study on the Genetics of Alcoholism. Genome-wide significant association was found with several SNPs on chromosome 21 in KCNJ6 (a potassium inward rectifier channel; KIR3.2/GIRK2), with the most significant SNP at P = 4.7 × 10(-10)). The same SNPs were also associated with EROs from central and parietal electrodes, but with less significance, suggesting that the association is frontally focused. One imputed synonymous SNP in exon four, highly correlated with our top three SNPs, was significantly associated with the frontal theta ERO phenotype. These results suggest KCNJ6 or its product GIRK2 account for some of the variations in frontal theta band oscillations. GIRK2 receptor activation contributes to slow inhibitory postsynaptic potentials that modulate neuronal excitability, and therefore influence neuronal networks.

A future without chronic pain: neuroscience and clinical research

Chronic pain affects 1.5 billion people worldwide, an estimated 100 million of whom live in the United States. Yet we currently have no effective treatment options. Fortunately, writes David Borsook, director of the Pain and Imaging Neuroscience Group at Children's Hospital Boston, Massachusetts General Hospital, and McLean Hospital, research advances have determined some of the ways in which chronic pain changes the brain, and several promising research areas could lead to better treatment approaches. Dr. Borsook recommends steps to facilitate these new treatments, including the establishment of integrated clinical neuroscience centers bridging the gap between bench and bedside.

Delta opioid receptor analgesia: recent contributions from pharmacology and molecular approaches

Delta opioid receptors represent a promising target for the development of novel analgesics. A number of tools have been developed recently that have significantly improved our knowledge of δ receptor function in pain control. These include several novel δ agonists with potent analgesic properties, and genetic mouse models with targeted mutations in the δ opioid receptor gene. Also, recent findings have further documented the regulation of δ receptor function at cellular level, which impacts on the pain-reducing activity of the receptor. These regulatory mechanisms occur at transcriptional and post-translational levels, along agonist-induced receptor activation, signaling and trafficking, or in interaction with other receptors and neuromodulatory systems. All these tools for in-vivo research, and proposed mechanisms at molecular level, have tremendously increased our understanding of δ receptor physiology, and contribute to designing innovative strategies for the treatment of chronic pain and other diseases such as mood disorders.