Identification of sex-specific genetic associations in response to opioid analgesics in a White, non-Hispanic cohort from Southeast Minnesota

Pharmacogenetic landscape of pain management variants among Mediterranean populations

Background

Chronic pain is a major socioeconomic burden in the Mediterranean region. However, we noticed an under-representation of these populations in the pharmacogenetics of pain management studies. In this context, we aimed 1) to decipher the pharmacogenetic variant landscape among Mediterranean populations compared to worldwide populations in order to identify therapeutic biomarkers for personalized pain management and 2) to better understand the biological process of pain management through in silico investigation of pharmacogenes pathways.

Materials and Methods

We collected genes and variants implicated in pain response using the Prisma guidelines from literature and PharmGK database. Next, we extracted these genes from genotyping data of 829 individuals. Then, we determined the variant distribution among the studied populations using multivariate (MDS) and admixture analysis with R and STRUCTURE software. We conducted a Chi2 test to compare the interethnic frequencies of the identified variants. We used SNPinfo web server, miRdSNP database to identify miRNA-binding sites. In addition, we investigated the functions of the identified genes and variants using pathway enrichment analysis and annotation tools. Finally, we performed docking analysis to assess the impact of variations on drug interactions.

Results

We identified 63 variants implicated in pain management. MDS analysis revealed that Mediterranean populations are genetically similar to Mexican populations and divergent from other populations. STRUCTURE analysis showed that Mediterranean populations are mainly composed of European ancestry. We highlighted differences in the minor allele frequencies of three variants (rs633, rs4680, and rs165728) located in the COMT gene. Moreover, variant annotation revealed ten variants with potential miRNA-binding sites. Finally, protein structure and docking analysis revealed that two missense variants (rs4680 and rs6267) induced a decrease in COMT protein activity and affinity for dopamine.

Conclusion

Our findings revealed that Mediterranean populations diverge from other ethnic groups. Furthermore, we emphasize the importance of pain-related pathways and miRNAs to better implement these markers as predictors of analgesic responses in the Mediterranean region.

Endogenous opiates and behavior: 2022

This paper is the forty-fifth consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2022 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Personalized Medicine in Cancer Pain Management

BACKGROUND

Previous studies have documented pain as an important concern for quality of life (QoL) and one of the most challenging manifestations for cancer patients. Thus, cancer pain management (CPM) plays a key role in treating pain related to cancer. The aim of this systematic review was to investigate CPM, with an emphasis on personalized medicine, and introduce new pharmacogenomics-based procedures for detecting and treating cancer pain patients.

METHODS

This study systematically reviewed PubMed from 1990 to 2023 using keywords such as cancer, pain, and personalized medicine. A total of 597 publications were found, and after multiple filtering processes, 75 papers were included. In silico analyses were performed using the GeneCards, STRING-MODEL, miRTargetLink2, and PharmGKB databases.

RESULTS

The results reveal that recent reports have mainly focused on personalized medicine strategies for CPM, and pharmacogenomics-based data are rapidly being introduced. The literature review of the 75 highly relevant publications, combined with the bioinformatics results, identified a list of 57 evidence-based genes as the primary gene list for further personalized medicine approaches. The most frequently mentioned genes were CYP2D6, COMT, and OPRM1. Moreover, among the 127 variants identified through both the literature review and data mining in the PharmGKB database, 21 variants remain as potential candidates for whole-exome sequencing (WES) analysis. Interestingly, hsa-miR-34a-5p and hsa-miR-146a-5p were suggested as putative circulating biomarkers for cancer pain prognosis and diagnosis.

CONCLUSIONS

In conclusion, this study highlights personalized medicine as the most promising strategy in CPM, utilizing pharmacogenomics-based approaches to alleviate cancer pain.

Genetic Variants Associated with Opioid Use Disorder

Genetics are presumed to contribute 30-40% to opioid use disorder (OUD), allowing for the possibility that genetic markers could be used to identify personal risk for developing OUD. We aimed to test the potential association among 180 candidate single nucleotide polymorphisms (SNPs), 120 of which were related to the dopamine reward pathway and 60 related to pharmacokinetics. Participants were randomly recruited in 2020-2021 in a cross-sectional genetic association study. Self-reported health history including Diagnostic and Statistical Manual of Mental Disorders (DSM-5) OUD criteria and buccal swabs were collected. A total of 1,301 participants were included in the analyses for this study. Of included participants, 250 met the DSM-5 criteria for ever having OUD. Logistic regression, adjusting for age and biologic sex, was used to characterize the association between each SNP and DSM-5 criteria consistent with OUD. Six SNPs found in 4 genes were associated with OUD: increased odds with CYP3A5 (rs15524 and rs776746) and DRD3 (rs324029 and rs2654754), and decreased odds with CYP3A4 (rs2740574) and CYP1A2 (rs2069514). Homozygotic CYP3A5 (rs15524 and rs776746) had the highest adjusted odds ratio of 2.812 (95% confidence interval (CI) 1.737, 4.798) and 2.495 (95% CI 1.670, 3.835), respectively. Variants within the dopamine reward and opioid metabolism pathways have significant positive (DRD3 and CYP3A5) and negative (CYP3A4 and CYP1A2) associations with OUD. Identification of these variants provides promising possibilities for genetic prognostic and therapeutic targets for future investigation.

Single cell transcriptomics reveals distinct transcriptional responses to oxycodone and buprenorphine by iPSC-derived brain organoids from patients with opioid use disorder

The opioid epidemic represents a national crisis. Oxycodone is one of the most prescribed opioid medications in the United States, whereas buprenorphine is currently the most prescribed medication for opioid use disorder (OUD) pharmacotherapy. Given the extensive use of prescription opioids and the global opioid epidemic, it is essential to understand how opioids modulate brain cell type function at the single-cell level. We performed single nucleus RNA-seq (snRNA-seq) using iPSC-derived forebrain organoids from three male OUD subjects in response to oxycodone, buprenorphine, or vehicle for seven days. We utilized the snRNA-seq data to identify differentially expressed genes following drug treatment using the Seurat integrative analysis pipeline. We utilized iPSC-derived forebrain organoids and single-cell sequencing technology as an unbiased tool to study cell-type-specific and drug-specific transcriptional responses. After quality control filtering, we analyzed 25787 cells and identified sixteen clusters using unsupervised clustering analysis. Our results reveal distinct transcriptional responses to oxycodone and buprenorphine by iPSC-derived brain organoids from patients with OUD. Specifically, buprenorphine displayed a significant influence on transcription regulation in glial cells. However, oxycodone induced type I interferon signaling in many cell types, including neural cells in brain organoids. Finally, we demonstrate that oxycodone, but not buprenorphine activated STAT1 and induced the type I interferon signaling in patients with OUD. These data suggest that elevation of STAT1 expression associated with OUD might play a role in transcriptional regulation in response to oxycodone. In summary, our results provide novel mechanistic insight into drug action at single-cell resolution.