Low-Dose Tramadol as an Off-Label Antidepressant: A Data Mining Analysis from the Patients' Perspective

Biomedical data analytics for better patient outcomes

Medical professionals today have access to immense amounts of data, which enables them to make decisions that enhance patient care and treatment efficacy. This innovative strategy can improve global health care by bridging the divide between clinical practice and medical research. This paper reviews biomedical developments aimed at improving patient outcomes by addressing three main questions regarding techniques, data sources and challenges. The review includes peer-reviewed articles from 2018 to 2023, found via systematic searches in PubMed, Scopus and Google Scholar. The results show diverse disease-specific applications. Challenges such as data quality and ethics are discussed, underscoring data analytics' potential for patient-focused health care. The review concludes that successful implementation requires addressing gaps, collaboration and innovation in biomedical science and data analytics.

A synopsis of multitarget therapeutic effects of anesthetics on depression

Depression is a profound mental disorder that dampens the mood and undermines volition, which exhibited an increased incidence over the years. Although drug-based interventions remain the primary approach for depression treatment, the available medications still can't satisfy the patients. In recent years, the newly discovered therapeutic targets such as N-methyl-D-aspartate (NMDA) receptor, α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) receptor, and tyrosine kinase B (TrkB) have brought new breakthroughs in the development of antidepressant drugs. Moreover, it has come to light that certain anesthetics possess pharmacological mechanisms intricately linked to the aforementioned therapeutic targets for depression. At present, numerous preclinical and clinical studies have explored the therapeutic effects of anesthetic drugs such as ketamine, isoflurane, N2O, and propofol, on depression. These investigations suggested that these drugs can swiftly ameliorate patients' depression symptoms and engender long-term effects. In this paper, we provide a comprehensive review of the research progress and potential molecular mechanisms of various anesthetic drugs for depression treatment. By shedding light on this subject, we aim to facilitate the development and clinical implementation of new antidepressant drugs based on anesthetic medications.

Genomic-Analysis-Oriented Drug Repurposing in the Search for Novel Antidepressants

From inadequate prior antidepressants that targeted monoamine neurotransmitter systems emerged the discovery of alternative drugs for depression. For instance, drugs targeted interleukin 6 receptor (IL6R) in inflammatory system. Genomic analysis-based drug repurposing using single nucleotide polymorphism (SNP) inclined a promising method for several diseases. However, none of the diseases was depression. Thus, we aimed to identify drug repurposing candidates for depression treatment by adopting a genomic-analysis-based approach. The 5885 SNPs obtained from the machine learning approach were annotated using HaploReg v4.1. Five sets of functional annotations were applied to determine the depression risk genes. The STRING database was used to expand the target genes and identify drug candidates from the DrugBank database. We validated the findings using the ClinicalTrial.gov and PubMed databases. Seven genes were observed to be strongly associated with depression (functional annotation score = 4). Interestingly, IL6R was auspicious as a target gene according to the validation outcome. We identified 20 drugs that were undergoing preclinical studies or clinical trials for depression. In addition, we identified sarilumab and satralizumab as drugs that exhibit strong potential for use in the treatment of depression. Our findings indicate that a genomic-analysis-based approach can facilitate the discovery of drugs that can be repurposed for treating depression.

Multiple suicide attempts associated with addiction to tramadol

BACKGROUND

The opioid tramadol is used as analgesic drug, and more recently was also proposed for the management of major depressive disorder. However, growing evidence suggests a link between opioid system dysfunction and suicidal behaviors, raising the question of tramadol use in view of the high addictive and suicidal risk. Here, we present the case of a young adult woman with multiple suicide attempts related to tramadol addiction.

CASE PRESENTATION

A 25-year-old woman was admitted for suicide attempt by phlebotomy in the Department of Psychiatric Emergency and Acute Care, Montpellier (France), in March 2020. The suicide attempt occurred 3 days after an abrupt tramadol withdrawal. In 2018, due to spinal disc herniation, she had a first prescription of tramadol to which she became addicted. The patient described an effect on psychological pain and suicidal ideation. However, she had to increase tramadol dose to obtain the desired effects, and for several months her intake was 2 000 mg per day. When she could not obtain tramadol any longer, suicidal ideation and psychological pain increased, leading to the suicide attempt. At the time of a worldwide opioid crisis that contributes to increasing suicidal behaviors, this case raises questions about tramadol prescription (often considered to be less addictive and with lower abuse potential) to individuals at risk of suicide.

Prevalence, correlates, and consequences of attention-deficit/hyperactivity disorder in a clinical sample of adults with tramadol use in Egypt

BACKGROUND AND OBJECTIVES

Many studies investigated the association between attention-deficit/hyperactivity disorder (ADHD) and substance use disorders (SUDs) but none focused on the association between ADHD and nonmedical prescription opioids such as tramadol. The objective of this study was to assess the prevalence, correlates, and consequences of co-occurrence of ADHD and tramadol use among adults.

METHODS

This study included 122 Egyptian adults with opioid use disorders attributed to tramadol (N = 122). Participants were recruited from the psychiatric outpatient clinic and inpatient unit of Zagazig University Hospital, Egypt. ADHD and SUDs were assessed by using the Adult ADHD Self-Report Scale (ASRS-v 1.1) and SCID-I criteria of DSM-5, respectively. All participants were screened for drugs by urinalysis.

RESULTS

Forty percent of the participants used tramadol alone, whereas the remaining used it with other substances, such as alcohol (51.6%) and cannabis (48.4%). Thirty-eight cases (31%) had adult ADHD and most of them had inattentive or mixed types. Adults with tramadol use and ADHD were more likely to have a younger age of onset of tramadol use, use a higher dose of tramadol, and use it for a longer duration than those with tramadol use without ADHD.

CONCLUSIONS AND DISCUSSION

ADHD in adults with tramadol use is common and is associated with early-onset, high dose, and long duration of tramadol use.

SCIENTIFIC SIGNIFICANCE

This is the first study to investigate the co-occurrence of ADHD and tramadol misuse among adults.

Tramadol-Related Deaths: Genetic Analysis in Relation to Metabolic Ratios

Tramadol (TR) metabolism is mainly dependent on the enzymatic activity of CYP2D6, which is controlled by genetic polymorphisms. Individuals are classified as poor (PMs), intermediate (IMs), extensive (EMs) or ultrarapid metabolizers (UMs) according to their genotype or phenotype. The determination of the metabolic phenotype for CYP2D6 can be of utmost importance in forensic and clinical contexts that involve TR intake. The present study aimed to describe CYP2D6 genetic variants in cases of TR-related deaths and to assess which metabolic ratio(s) (MRs) would allow to determine CYP2D6 phenotype without having to perform genetic analyses. Forty-eight postmortem blood samples were selected from TR-related death cases previously analyzed in a forensic context in North of France between 2013 and 2019. Initial available data included blood concentrations of TR and its two main metabolites (M1& M2) determined using a LC-MS/MS method. TR metabolism was expressed as various MRs comprising TR/M1, TR/M2 and M2/M1. After DNA extraction, sequencing was used for genetic variant detections that affect CYP2D6 activity/expression. In the present study, the allelic variants with the higher frequency were CYP2D6*1 (68%), followed by *4 (21%). The most frequent phenotype is EMs (59.6%), followed by IMs (23.4%), PMs (12.8%), and UMs (6.4%). There was no significant correlation between each calculated MR and the genotypically-predicted phenotypes, except for M2/M1 which appears related to the PM phenotype. The observed distribution of CYP2D6 genetic variants in this TR-related death population was similar to that found in the general Caucasian population. The present study displayed that the blood M2/M1 ratio could be the best-correlated tramadol MR to the PM phenotype, and could thus be used in forensic contexts where genetic analyses are not possible or poorly informative. For the other phenotypes, especially the UM phenotype, genetic analysis appears to be the only reliable method to predict the CYP2D6 phenotype.

Current attention-deficit/hyperactivity disorder and nonmedical prescription opioid use attributed to tramadol among male adolescents without conduct disorder in Egypt

Background: Evidence for the association between attention-deficit/hyperactivity disorder (ADHD) and substance use disorders (SUDs) is common. However, little research has investigated this relationship among adolescents using nonmedical prescription opioids, particularly tramadol.Objective: To estimate the prevalence and correlates of ADHD among adolescents with tramadol misuse and without conduct disorder (CD).Methods: This study included 122 Egyptian adolescents (100% male) with opioid use disorders attributed to tramadol. The diagnosis of SUDs, ADHD, and CD (to exclude) was based on the SCID-I criteria of the DSM-IV-TR. Drug-related problems were assessed using the Drug Use Disorders Identification Test (DUDIT). All adolescents were screened for drugs by urinalysis.Results: Thirty-eight percent of adolescents with tramadol misuse had ADHD. Adolescents with tramadol misuse and ADHD were more likely to have a younger age of onset of smoking, substance use, and tramadol misuse than adolescents without ADHD.Conclusions: ADHD is common among adolescents with tramadol misuse. There is an association between ADHD and young age of onset of tramadol misuse and drug-related problems.

EEG and Sleep Effects of Tramadol Suggest Potential Antidepressant Effects with Different Mechanisms of Action

Tramadol is a widely used, centrally acting, opioid analgesic compound, with additional inhibitory effects on the synaptic reuptake of serotonin and noradrenaline, as well as on the 5-HT₂ and NMDA receptors. Preclinical and clinical evidence also suggests its therapeutic potential in the treatment of depression and anxiety. The effects of most widely used antidepressants on sleep and quantitative electroencephalogram (qEEG) are well characterized; however, such studies of tramadol are scarce. Our aim was to characterize the effects of tramadol on sleep architecture and qEEG in different sleep–wake stages. EEG-equipped Wistar rats were treated with tramadol (0, 5, 15 and 45 mg/kg) at the beginning of the passive phase, and EEG, electromyogram and motor activity were recorded. Tramadol dose-dependently reduced the time spent in rapid eye movement (REM) sleep and increased the REM onset latency. Lower doses of tramadol had wake-promoting effects in the first hours, while 45 mg/kg of tramadol promoted sleep first, but induced wakefulness thereafter. During non-REM sleep, tramadol (15 and 45 mg/kg) increased delta and decreased alpha power, while all doses increased gamma power. In conclusion, the sleep-related and qEEG effects of tramadol suggest antidepressant-like properties, including specific beneficial effects in selected patient groups, and raise the possibility of a faster acting antidepressant action.