The chemogenetic technology DREADD (designer receptors exclusively activated by designer drugs) is widely used for remote manipulation of neuronal activity in freely moving animals. DREADD technology posits the use of "designer receptors," which are exclusively activated by the "designer drug" clozapine N-oxide (CNO). Nevertheless, the in vivo mechanism of action of CNO at DREADDs has never been confirmed. CNO does not enter the brain after systemic drug injections and shows low affinity for DREADDs. Clozapine, to which CNO rapidly converts in vivo, shows high DREADD affinity and potency. Upon systemic CNO injections, converted clozapine readily enters the brain and occupies central nervous system-expressed DREADDs, whereas systemic subthreshold clozapine injections induce preferential DREADD-mediated behaviors.
BackgroundThe opioid epidemic in the United States is averaging over 100 deaths per day due to overdose. The effectiveness of opioids as pain treatments, and the drug-seeking behavior of opioid addicts, leads physicians in the United States to issue over 200 million opioid prescriptions every year. To better understand the biomedical profile of opioid-dependent patients, we analyzed information from electronic health records (EHR) including lab tests, vital signs, medical procedures, prescriptions, and other data from millions of patients to predict opioid substance dependence.ResultsWe trained a machine learning model to classify patients by likelihood of having a diagnosis of substance dependence using EHR data from patients diagnosed with substance dependence, along with control patients with no history of substance-related conditions, matched by age, gender, and status of HIV, hepatitis C, and sickle cell disease. The top machine learning classifier using all features achieved a mean area under the receiver operating characteristic (AUROC) curve of ~ 92%, and analysis of the model uncovered associations between basic clinical factors and substance dependence. Additionally, diagnoses, prescriptions, and procedures prior to the diagnoses of substance dependence were analyzed to elucidate the clinical profile of substance-dependent patients, relative to controls.ConclusionsThe predictive model may hold utility for identifying patients at risk of developing dependence, risk of overdose, and opioid-seeking patients that report other symptoms in their visits to the emergency room.Electronic supplementary materialThe online version of this article (10.1186/s13040-019-0193-0) contains supplementary material, which is available to authorized users.
The current opioid epidemic necessitates a better understanding of human addiction neurobiology to develop efficacious treatment approaches. Here, we perform genome-wide assessment of chromatin accessibility of the human striatum in heroin users and matched controls. Our study reveals distinct neuronal and non-neuronal epigenetic signatures, and identifies a locus in the proximity of the gene encoding tyrosine kinase FYN as the most affected region in neurons. FYN expression, kinase activity and the phosphorylation of its target Tau are increased by heroin use in the post-mortem human striatum, as well as in rats trained to self-administer heroin and primary striatal neurons treated with chronic morphine in vitro. Pharmacological or genetic manipulation of FYN activity significantly attenuates heroin self-administration and responding for drug-paired cues in rodents. Our findings suggest that striatal FYN is an important driver of heroin-related neurodegenerative-like pathology and drug-taking behavior, making FYN a promising therapeutic target for heroin use disorder.
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