Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis

Identification of stress-induced epigenetic methylation onto dopamine D2 gene and neurological and behavioral consequences

The D2 dopamine receptor (DRD2) gene has garnered substantial attention as one of the most extensively studied genes across various neuropsychiatric disorders. Since its initial association with severe alcoholism in 1990, particularly through the identification of the DRD2 Taq A1 allele, numerous international investigations have been conducted to elucidate its role in different conditions. As of February 22, 2024, there are 5485 articles focusing on the DRD2 gene listed in PUBMED. There have been 120 meta-analyses with mixed results. In our opinion, the primary cause of negative reports regarding the association of various DRD2 gene polymorphisms is the inadequate screening of controls, not adequately eliminating many hidden reward deficiency syndrome behaviors. Moreover, pleiotropic effects of DRD2 variants have been identified in neuropsychologic, neurophysiologic, stress response, social stress defeat, maternal deprivation, and gambling disorder, with epigenetic DNA methylation and histone post-translational negative methylation identified as discussed in this article. There are 70 articles listed in PUBMED for DNA methylation and 20 articles listed for histone methylation as of October 19, 2022. For this commentary, we did not denote DNA and/or histone methylation; instead, we provided a brief summary based on behavioral effects. Based on the fact that Blum and Noble characterized the DRD2 Taq A1 allele as a generalized reward gene and not necessarily specific alcoholism, it now behooves the field to find ways to either use effector moieties to edit the neuroepigenetic insults or possibly harness the idea of potentially removing negative mRNA-reduced expression by inducing "dopamine homeostasis."

Multiscale topology in interactomic network: from transcriptome to antiaddiction drug repurposing

The escalating drug addiction crisis in the United States underscores the urgent need for innovative therapeutic strategies. This study embarked on an innovative and rigorous strategy to unearth potential drug repurposing candidates for opioid and cocaine addiction treatment, bridging the gap between transcriptomic data analysis and drug discovery. We initiated our approach by conducting differential gene expression analysis on addiction-related transcriptomic data to identify key genes. We propose a novel topological differentiation to identify key genes from a protein-protein interaction network derived from DEGs. This method utilizes persistent Laplacians to accurately single out pivotal nodes within the network, conducting this analysis in a multiscale manner to ensure high reliability. Through rigorous literature validation, pathway analysis and data-availability scrutiny, we identified three pivotal molecular targets, mTOR, mGluR5 and NMDAR, for drug repurposing from DrugBank. We crafted machine learning models employing two natural language processing (NLP)-based embeddings and a traditional 2D fingerprint, which demonstrated robust predictive ability in gauging binding affinities of DrugBank compounds to selected targets. Furthermore, we elucidated the interactions of promising drugs with the targets and evaluated their drug-likeness. This study delineates a multi-faceted and comprehensive analytical framework, amalgamating bioinformatics, topological data analysis and machine learning, for drug repurposing in addiction treatment, setting the stage for subsequent experimental validation. The versatility of the methods we developed allows for applications across a range of diseases and transcriptomic datasets.

Neuroimmune Mechanisms of Opioid Use Disorder and Recovery: Translatability to Human Studies, and Future Research Directions

Opioid use disorder (OUD) is a major current cause of morbidity and mortality. Long-term exposure to short-acting opioids (MOP-r agonists such as heroin or fentanyl) results in complex pathophysiological changes to neuroimmune and neuroinflammatory functions, affected in part by peripheral mechanisms (e.g., cytokines in blood), and by neuroendocrine systems such as the hypothalamic-pituitary-adrenal (HPA) stress axis. There are important findings from preclinical models, but their role in the trajectory and outcomes of OUD in humans is not well understood. The goal of this narrative review is to examine available data on immune and inflammatory functions in persons with OUD, and to identify major areas for future research. Peripheral blood biomarker studies revealed a pro-inflammatory state in persons with OUD in withdrawal or early abstinence, consistent with available postmortem brain studies (which show glial activation) and diffusion tensor imaging studies (indicating white matter disruptions), with gradual abstinence-associated recovery. The mechanistic roles of these neuroimmune and neuroinflammatory changes in the trajectory of OUD (including recovery and medication management) cannot be examined practically with postmortem data. Collection of longitudinal data in larger-scale human cohorts would allow examination of these mechanisms associated with OUD stage and progression. Given the heterogeneity in presentation of OUD, a precision medicine approach integrating multi-omic peripheral biomarkers and comprehensive phenotyping, including neuroimaging, can be beneficial in risk stratification, and individually optimized selection of interventions for individuals who will benefit, and assessments under refractory therapy.

Identification of key genes and therapeutic drugs for cocaine addiction using integrated bioinformatics analysis

Introduction

Cocaine is a highly addictive drug that is abused due to its excitatory effect on the central nervous system. It is critical to reveal the mechanisms of cocaine addiction and identify key genes that play an important role in addiction.

Methods

In this study, we proposed a centrality algorithm integration strategy to identify key genes in a protein-protein interaction (PPI) network constructed by deferential genes from cocaine addiction-related datasets. In order to investigate potential therapeutic drugs for cocaine addiction, a network of targeted relationships between nervous system drugs and key genes was established.

Results

Four key genes (JUN, FOS, EGR1, and IL6) were identified and well validated using CTD database correlation analysis, text mining, independent dataset analysis, and enrichment analysis methods, and they might serve as biomarkers of cocaine addiction. A total of seventeen drugs have been identified from the network of targeted relationships between nervous system drugs and key genes, of which five (disulfiram, cannabidiol, dextroamphetamine, diazepam, and melatonin) have been shown in the literature to play a role in the treatment of cocaine addiction.

Discussion

This study identified key genes and potential therapeutic drugs for cocaine addiction, which provided new ideas for the research of the mechanism of cocaine addiction.

Endogenous opiates and behavior: 2020

This paper is the forty-third consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2020 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).

Inflammatory Biomarkers in Addictive Disorders

Substance use disorders are a group of diseases that are associated with social, professional, and family impairment and that represent a high socio-economic impact on the health systems of countries around the world. These disorders present a very complex diagnosis and treatment regimen due to the lack of suitable biomarkers supporting the correct diagnosis and classification and the difficulty of selecting effective therapies. Over the last few years, several studies have pointed out that these addictive disorders are associated with systemic and central nervous system inflammation, which could play a relevant role in the onset and progression of these diseases. Therefore, identifying different immune system components as biomarkers of such addictive disorders could be a crucial step to promote appropriate diagnosis and treatment. Thus, this work aims to provide an overview of the immune system alterations that may be biomarkers of various addictive disorders.