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      Dysregulated Metabolites Serve as Novel Biomarkers for Metabolic Diseases Caused by E-Cigarette Vaping and Cigarette Smoking

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      1 , 2 , 1 , *
      Metabolites
      MDPI
      metabolome, TCA, lipids, e-cigarette, cigarette, biomarkers

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          Abstract

          Metabolites are essential intermediate products in metabolism, and metabolism dysregulation indicates different types of diseases. Previous studies have shown that cigarette smoke dysregulated metabolites; however, limited information is available with electronic cigarette (e-cig) vaping. We hypothesized that e-cig vaping and cigarette smoking alters systemic metabolites, and we propose to understand the specific metabolic signature between e-cig users and cigarette smokers. Plasma from non-smoker controls, cigarette smokers, and e-cig users was collected, and metabolites were identified by UPLC-MS (ultra-performance liquid chromatography mass spectrometer). Nicotine degradation was activated by e-cig vaping and cigarette smoking with increased concentrations of cotinine, cotinine N-oxide, (S)-nicotine, and (R)-6-hydroxynicotine. Additionally, we found significantly decreased concentrations in metabolites associated with tricarboxylic acid (TCA) cycle pathways in e-cig users versus cigarette smokers, such as d-glucose, (2R,3S)-2,3-dimethylmalate, (R)-2-hydroxyglutarate, O-phosphoethanolamine, malathion, d-threo-isocitrate, malic acid, and 4-acetamidobutanoic acid. Cigarette smoking significant upregulated sphingolipid metabolites, such as d-sphingosine, ceramide, N-(octadecanoyl)-sphing-4-enine, N-(9Z-octadecenoyl)-sphing-4-enine, and N-[(13Z)-docosenoyl]-sphingosine, versus e-cig vaping. Overall, e-cig vaping dysregulated TCA cycle-related metabolites while cigarette smoking altered sphingolipid metabolites. Both e-cig and cigarette smoke increased nicotinic metabolites. Therefore, specific metabolic signatures altered by e-cig vaping and cigarette smoking could serve as potential systemic biomarkers for early pathogenesis of cardiopulmonary diseases.

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          Most cited references60

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          Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI).

          There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msi-workgroups-feedback@lists.sourceforge.net. Further, community input related to this document can also be provided via this electronic forum.
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            R-2HG Exhibits Anti-tumor Activity by Targeting FTO/m 6 A/MYC/CEBPA Signaling

            R-2-hydroxyglutarate (R-2HG), produced at high levels by mutant isocitrate dehydrogenase 1/2 (IDH1/2) enzymes, was reported as an oncometabolite. We show here that R-2HG also exerts a broad anti-leukemic activity in vitro and in vivo by inhibiting leukemia cell proliferation/viability and by promoting cell-cycle arrest and apoptosis. Mechanistically, R-2HG inhibits fat mass and obesity-associated protein (FTO) activity, thereby increasing global N6-methyladenosine (m6A) RNA modification in R-2HG-sensitive leukemia cells, which in turn decreases the stability of MYC/CEBPA transcripts, leading to the suppression of relevant pathways. Ectopically expressed mutant IDH1 and S-2HG recapitulate the effects of R-2HG. High levels of FTO sensitize leukemic cells to R-2HG, whereas hyperactivation of MYC signaling confers resistance that can be reversed by the inhibition of MYC signaling. R-2HG also displays anti-tumor activity in glioma. Collectively, while R-2HG accumulated in IDH1/2 mutant cancers contributes to cancer initiation, our work demonstrates anti-tumor effects of 2HG in inhibiting proliferation/survival of FTO-high cancer cells via targeting FTO/m6A/MYC/CEBPA signaling.
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              Sphingolipid metabolites in inflammatory disease.

              Sphingolipids are ubiquitous building blocks of eukaryotic cell membranes. Progress in our understanding of sphingolipid metabolism, state-of-the-art sphingolipidomic approaches and animal models have generated a large body of evidence demonstrating that sphingolipid metabolites, particularly ceramide and sphingosine-1-phosphate, are signalling molecules that regulate a diverse range of cellular processes that are important in immunity, inflammation and inflammatory disorders. Recent insights into the molecular mechanisms of action of sphingolipid metabolites and new perspectives on their roles in regulating chronic inflammation have been reported. The knowledge gained in this emerging field will aid in the development of new therapeutic options for inflammatory disorders.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Metabolites
                Metabolites
                metabolites
                Metabolites
                MDPI
                2218-1989
                29 May 2021
                June 2021
                : 11
                : 6
                : 345
                Affiliations
                [1 ]Department of Environmental Medicine, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY 14642, USA; Qixin_Wang@ 123456URMC.Rochester.edu
                [2 ]Department of Nutrition, Byrdine F. Lewis School of Nursing and Health Professions, Georgia State University, Atlanta, GA 30302, USA; xji4@ 123456gsu.edu
                Author notes
                Author information
                https://orcid.org/0000-0001-9051-8388
                https://orcid.org/0000-0003-2274-2454
                Article
                metabolites-11-00345
                10.3390/metabo11060345
                8229291
                34072305
                6d17457f-f226-4749-a3ba-6b855de0b6f9
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 07 April 2021
                : 24 May 2021
                Categories
                Article

                metabolome,tca,lipids,e-cigarette,cigarette,biomarkers
                metabolome, tca, lipids, e-cigarette, cigarette, biomarkers

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