Transient postnatal fluoxetine decreases brain concentrations of 20-HETE and 15-epi-LXA4, arachidonic acid metabolites in adult mice

Machine Learning Identifies Metabolic Signatures that Predict the Risk of Recurrent Angina in Remitted Patients after Percutaneous Coronary Intervention: A Multicenter Prospective Cohort Study

Recurrent angina (RA) after percutaneous coronary intervention (PCI) has few known risk factors, hampering the identification of high-risk populations. In this multicenter study, plasma samples are collected from patients with stable angina after PCI, and these patients are followed-up for 9 months for angina recurrence. Broad-spectrum metabolomic profiling with LC-MS/MS followed by multiple machine learning algorithms is conducted to identify the metabolic signatures associated with future risk of angina recurrence in two large cohorts (n = 750 for discovery set, and n = 775 for additional independent discovery cohort). The metabolic predictors are further validated in a third cohort from another center (n = 130) using a clinically-sound quantitative approach. Compared to angina-free patients, the remitted patients with future RA demonstrates a unique chemical endophenotype dominated by abnormalities in chemical communication across lipid membranes and mitochondrial function. A novel multi-metabolite predictive model constructed from these latent signatures can stratify remitted patients at high-risk for angina recurrence with over 89% accuracy, sensitivity, and specificity across three independent cohorts. Our findings revealed reproducible plasma metabolic signatures to predict patients with a latent future risk of RA during post-PCI remission, allowing them to be treated in advance before an event.

Potential Adverse Cardiovascular Effects of Treatment With Fluoxetine and Other Selective Serotonin Reuptake Inhibitors (SSRIs) in Patients With Geriatric Depression: Implications for Atherogenesis and Cerebromicrovascular Dysregulation

Late life depression is an important public health problem, which associates with increased risk of morbidity and mortality. Selective serotonin reuptake inhibitors (SSRIs), including fluoxetine, are often prescribed to treat geriatric depression. There is increasing evidence that fluoxetine and other SSRIs exert a wide range of cardiovascular side effects. Furthermore, there is evidence that aging may increase plasma level of SSRIs. In this overview, the potential role of side effects of treatment with fluoxetine and other SSRIs in the pathogenesis of age-related cardiovascular diseases, including atherogenesis, cardiac pathologies, and cerebromicrovascular impairment, is discussed.

Impact of Drug Treatment at Neonatal Ages on Variability of Drug Metabolism and Drug-drug Interactions in Adult Life

PURPOSE OF REVIEW

As the number of patients taking more than one medication concurrently continues to increase, predicting and preventing drug-drug interactions (DDIs) is now more important than ever. Administration of one drug can cause changes in the expression and activity of drug metabolizing enzymes (DMEs) and alter the efficacy or toxicity of other medications that are substrates for these enzymes, resulting in a DDI. In today's medical practice, potential DDIs are evaluated based on the current medications a patient is taking with little regard to drugs the patient has been exposed to in the past. The purpose of this review is to discuss potential impacts of drug treatment at neonatal ages on the variability of drug metabolism and DDIs in adult life.

RECENT FINDINGS

Existing evidence from the last thirty years has shown that exposure to certain xenobiotics during neonatal life has the potential to persistently alter DME expression through adult life. With recent advancements in the understanding of epigenetic regulation on gene expression, this phenomenon is resurfacing in the scientific community in hopes of defining possible mechanisms. Exposure to compounds that have the ability to bind nuclear receptors and trigger epigenetic modifications at neonatal and pediatric ages may have long-term, if not permanent, consequences on gene expression and DME activity.

SUMMARY

The information summarized in this review should challenge the way current healthcare providers assess DDI potential and may offer an explanation to the significant interindividual variability in drug metabolism that is observed among patients.

Pathophysiological implications of neurovascular P450 in brain disorders

Over the past decades, the significance of cytochrome P450 (CYP) enzymes has expanded beyond their role as peripheral drug metabolizers in the liver and gut. CYP enzymes are also functionally active at the neurovascular interface. CYP expression is modulated by disease states, impacting cellular functions, detoxification, and reactivity to toxic stimuli and brain drug biotransformation. Unveiling the physiological and molecular complexity of brain P450 enzymes will improve our understanding of the mechanisms underlying brain drug availability, pharmacological efficacy, and neurotoxic adverse effects from pharmacotherapy targeting brain disorders.