Association of opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with nicotine dependence

Allele frequency and genotype distribution of the opioid receptor μ-1 (OPRM1) A118G polymorphism in the Western Saudi population

The single nucleotide polymorphism (SNP) A118G (rs1799971) in the Mu Opioid Receptor 1 (OPRM1) gene is associated with significant variations in analgesic doses and adverse effects of opioids. The A118G OPRM1 allele distributions vary significantly between different populations worldwide. The study aimed to assess the allele frequency and genotype distribution of OPRM1 A118G SNP in Saudis. This cross-sectional study included 124 healthy Saudis (62 males and 62 females) visiting the King Abdulaziz University Hospital in Jeddah, Saudi Arabia. The Oragene®-DISCOVER (OGR-600) kits were used to collect saliva samples from the participants. Polymerase chain reaction-restriction fragment length polymorphism was utilized to assess the SNP. Among the tested population, 79.03% (95% C.I. 70.81-85.82) were homozygous wild-type A118A, 16.13% (95% C.I. 10.14-23.80) were heterozygous A118G, and 4.84% (95% C.I. 1.80-10.23) were homozygous mutant G118G. OPRM1 A118G polymorphism allele frequencies were 87% (95% C.I. 79.89-92.44) and 13% (95% C.I. 7.56-20.11) for the 118A and 118G alleles, respectively. A higher frequency of the OPRM1 118G allele was present in females, 21% (95% C.I. 11.66-33.17) compared to males, 5% (95% C.I. 1.01-13.50). Relative to other Asian countries, the Saudi population showed a low prevalence of the OPRM1 A118G polymorphism, with a higher frequency of the 118G allele in females. Our research will contribute to the existing knowledge on the prevalence of OPRM1 A118G polymorphism, which could be considered for the personalized prescribing of opioid analgesics.

Development of a nomogram for the early prediction of PACU VAS in patients undergoing laparoscopic radical resection of colorectal cancer with fentanyl

INTRODUCTION

To make early predictions of PACU VAS before surgery, we created a novel nomogram for the early prediction of PACU VAS in patients having laparoscopic radical excision of colorectal cancer with fentanyl.

METHODS

From July 2018 to December 2020, a total of 101 patients in Zhongshan Hospital Affiliated to Fudan University who underwent laparoscopic radical resection of colorectal cancer were enrolled in this study. For feature selection, a stepwise regression model was utilized. Multivariable logistic regression analysis was used to establish a prediction model. We incorporated age, gender, weight, height, fentanyl dosage during operation, operation time, and OPRM1 genotype, and this was presented with a nomogram. The nomogram's performance was evaluated in terms of discrimination and clinical utility.

RESULTS

The signature, which comprised of seven carefully chosen characteristics, was linked to the PACU VAS for the development dataset. Predictors contained in the individualized prediction nomogram included age, gender, weight, height, fentanyl dosage during operation, operation time, and OPRM1 genotype. With an area under the ROC curve of 0.877 (95% CI, 0.6874-1.0000), the model showed good discrimination. The nomogram still had good discrimination. Decision curve analysis demonstrated that the nomogram was clinically useful.

CONCLUSIONS

The nomogram presented in this study incorporates age, gender, weight, height, fentanyl dosage during operation, operation time, and OPRM1 genotype and can be conveniently used to facilitate the individualized prediction of PACU VAS in patients undergoing laparoscopic radical resection of colorectal cancer with fentanyl.

Association of NRG3 and ERBB4 gene polymorphism with nicotine dependence in Turkish population

BACKGROUND

Nicotine dependence (ND) is characterized by regular smoking, anxiety, irritation, difficulty concentrating, impatience, restlessness, tremor, dizziness, hunger, nicotine demand, and the individual's reluctance to quit despite knowing the health risks of smoking. Recently, it has been reported that the Neuregulin 3 (NRG3)/Erb-B2 receptor tyrosine kinase 4 (ERBB4) signaling pathway plays a role in ND. NRG3, which is activated after nicotine intake, binds to ERBB4 and causes GABA release. GABA reduces anxiety and tension, which are one of the nicotine withdrawal symptoms. Therefore we aimed to investigate the relationship between NRG3 and ERBB4 gene polymorphisms and ND.

MATERIALS AND METHODS

The study population was comprised of patients with ND (n = 200) and healthy non-smoker control subjects (n = 200) who were matched for age, sex, and compared for comorbidity factors such as alcohol, smoking, duration, and education (age range 18-60). Genotypes were detected by Real-Time PCR using TaqMan technology. The Fagerström Nicotine Dependence Test (FTND) score was 5 and above for the patient group and 0 for the control group. DNA was obtained from whole peripheral blood and six polymorphisms of Neuregulin 3 (NRG3) (rs1836724, rs7562566, and rs10048757) and Erb-B2 Receptor Tyrosine Kinase 4 (ERBB4) (rs1764072, rs6584400, and rs10883934) genes were analyzed by real-time PCR method.

RESULTS

Our findings show that the six selected SNPs are not significantly associated with ND in the Turkish population and no correlation with dependence levels (p > 0.05).

CONCLUSION

Although our findings do not show a relationship between ND and these polymorphisms, it is the first study to investigate these single nucleotide polymorphisms (SNPs) for the first time in ND and to find some genotypes in the Turkish population when compared to other populations. Also, our findings are important in terms of their contribution to the literature and forensic genetics.

The Life Cycle of the Mu-Opioid Receptor

Opioid receptors (ORs) are undisputed targets for the treatment of pain. Unfortunately, targeting these receptors therapeutically poses significant challenges including addiction, dependence, tolerance, and the appearance of side effects, such as respiratory depression and constipation. Moreover, misuse of prescription and illicit narcotics has resulted in the current opioid crisis. The mu-opioid receptor (MOR) is the cellular mediator of the effects of most commonly used opioids, and is a prototypical G protein-coupled receptor (GPCR) where new pharmacological, signalling and cell biology concepts have been coined. This review summarises the knowledge of the life cycle of this therapeutic target, including its biogenesis, trafficking to and from the plasma membrane, and how the regulation of these processes impacts its function and is related to pathophysiological conditions.

Significant association of mu-opioid receptor 1 haplotype with tobacco smoking in healthy control subjects but not in patients with schizophrenia and alcohol dependence

Tobacco smoking is highly prevalent in patients with schizophrenia and alcohol dependence. The underlying neurobiology of nicotine addiction is complex. Rewarding effects of nicotine from cigarettes are associated, among others, with mu-opioid receptors encoded by the OPRM1 gene. The aim of the study was to evaluate the association between two OPRM1 gene polymorphisms, rs1799971 and rs510769, and tobacco smoking in Caucasian patients with schizophrenia, alcohol dependence, and healthy control subjects. The study included 1058 Caucasians (277 patients with schizophrenia, 359 patients with alcohol dependence, and 422 healthy control subjects), subdivided according to the nicotine dependence into smokers (i.e. current smokers) and non-smokers. A significant association was found between the GC haplotype (OPRM1 rs1799971 and rs510769) and smoking in healthy controls, but not in patients with schizophrenia and alcohol dependence. A nominal association was detected in all cases/controls, but this significance did not survive the correction for the multiple testing. This is the first study to reveal that nicotine dependence is associated with the GC haplotype of the OPRM1 rs1799971 and rs510769 in all subjects or specifically in healthy controls. These results did not confirm the strong connection between OPRM1 polymorphisms and nicotine dependence in schizophrenia or alcohol dependence.

Potential biomarkers for persistent and neuropathic pain therapy

Persistent, in particular neuropathic pain affects millions of people worldwide. However, the response rate of patients to existing analgesic drugs is less than 50%. There are several possibilities to increase this response rate, such as optimization of the pharmacokinetic and pharmacodynamic properties of analgesics. Another promising approach is to use prognostic biomarkers in patients to determine the optimal pharmacological therapy for each individual. Here, we discuss recent efforts to identify plasma and CSF biomarkers, as well as genetic biomarkers and sensory testing, and how these readouts could be exploited for the prediction of a suitable pharmacological treatment. Collectively, the information on single biomarkers may be stored in knowledge bases and processed by machine-learning and related artificial intelligence techniques, resulting in the optimal pharmacological treatment for individual pain patients. We highlight the potential for biomarker-based individualized pain therapies and discuss biomarker reliability and their utility in clinical practice, as well as limitations of this approach.