Dataset Information

Metabolomics analysis of serum in a rat heroin self-administration model undergoing reinforcement based on 1H-nuclear magnetic resonance spectra.

ABSTRACT: BACKGROUND:Understanding the process of relapse to abused drugs and ultimately developing treatments that can reduce the incidence of relapse remains the primary goal for the study of substance dependence. Therefore, exploring the metabolite characteristics during the relapse stage is valuable. METHODS:A heroin self-administered rat model was employed, and analysis of the 1H-nuclear magnetic resonance-based metabolomics was performed to investigate the characteristic metabolite profile upon reintroduction to the drug after abstinence. RESULTS:Sixteen metabolites in the serum of rats, including phospholipids, intermediates in TCA (Tricarboxylic Acid Cycle) cycle, keto bodies, and precursors for neurotransmitters, underwent a significant change in the reinstatement stage compared with those in the control group. In particular, energy production was greatly disturbed as evidenced by different aspects such as an increase in glucose and decrease in intermediates of glycolysis and the TCA cycle. The finding that the level of 3-hydroxybutyrate and acetoacetate increased significantly suggested that energy production was activated from fatty acids. The concentration of phenylalanine, glutamine, and choline, the precursors of major neurotransmitters, increased during the reinstatement stage which indicated that an alteration in neurotransmitters in the brain might occur along with the disturbance in substrate supply in the circulatory system. CONCLUSIONS:Heroin reinforcement resulted in impaired energy production via different pathways, including glycolysis, the TCA cycle, keto body metabolism, etc. A disturbance in the substrate supply in the circulatory system may partly explain heroin toxicity in the central nervous system. These findings provide new insight into the mechanism underlying the relapse to heroin use.

SUBMITTER: Ning T

PROVIDER: S-EPMC5836429 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Metabolomics analysis of serum in a rat heroin self-administration model undergoing reinforcement based on <sup>1</sup>H-nuclear magnetic resonance spectra.

Ning Tingting T Leng Changlong C Chen Lin L Ma Baomiao B Gong Xiaokang X

BMC neuroscience 20180305 1

<h4>Background</h4>Understanding the process of relapse to abused drugs and ultimately developing treatments that can reduce the incidence of relapse remains the primary goal for the study of substance dependence. Therefore, exploring the metabolite characteristics during the relapse stage is valuable.<h4>Methods</h4>A heroin self-administered rat model was employed, and analysis of the <sup>1</sup>H-nuclear magnetic resonance-based metabolomics was performed to investigate the characteristic me ...[more]

PMID: 29502536

Similar Datasets

Project description:UnlabelledDengue, due to its global burden, is the most important arthropod-borne flavivirus disease, and early detection lowers fatality rates to below 1%. Since the metabolic resources crucial for viral replication are provided by host cells, detection of changes in the metabolic profile associated with disease pathogenesis could help with the identification of markers of prognostic and diagnostic importance. We applied (1)H nuclear magnetic resonance exploratory metabolomics to study longitudinal changes in plasma metabolites in a cohort in Recife, Brazil. To gain statistical power, we used innovative paired multivariate analyses to discriminate individuals with primary and secondary infection presenting as dengue fever (DF; mild) and dengue hemorrhagic fever (DHF; severe) and subjects with a nonspecific nondengue (ND) illness (ND subjects). Our results showed that a decrease in plasma low-density lipoprotein (LDL) and very-low-density lipoprotein (VLDL) discriminated dengue virus (DENV)-infected subjects from ND subjects, and also, subjects with severe infection even presented a decrease in lipoprotein concentrations compared to the concentrations in subjects with mild infection. These results add to the ongoing discussion that the manipulation of lipid metabolism is crucial for DENV replication and infection. In addition, a decrease in plasma glutamine content was characteristic of DENV infection and disease severity, and an increase in plasma acetate levels discriminated subjects with DF and DHF from ND subjects. Several other metabolites shown to be altered in DENV infection and the implications of these alterations are discussed. We hypothesize that these changes in the plasma metabolome are suggestive of liver dysfunction, could provide insights into the underlying molecular mechanisms of dengue virus pathogenesis, and could help to discriminate individuals at risk of the development of severe infection and predict disease outcome.ImportanceDengue, due to its global burden, is the most important mosquito-borne viral disease. There is no specific treatment for dengue disease, and early detection lowers fatality rates to below 1%. In this study, we observed the effects of dengue virus infection on the profile of small molecules in the blood of patients with mild and severe infection. Variations in the profiles of these small molecules reflected the replication of dengue virus in different tissues and the extent of tissue damage during infection. The results of this study showed that the molecules that changed the most were VLDL, LDL, and amino acids. We propose that these changes reflect liver dysfunction and also that they can be used to discriminate subjects with mild dengue from those with severe dengue.

Dataset Information

Metabolomics analysis of serum in a rat heroin self-administration model undergoing reinforcement based on 1H-nuclear magnetic resonance spectra.

Publications

Metabolomics analysis of serum in a rat heroin self-administration model undergoing reinforcement based on <sup>1</sup>H-nuclear magnetic resonance spectra.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets