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. 2021 May 29;11(6):345.
doi: 10.3390/metabo11060345.

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

Affiliations

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

Qixin Wang et al. Metabolites. .

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.

Keywords: TCA; biomarkers; cigarette; e-cigarette; lipids; metabolome.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Metabolites from plasma were analyzed from ultra-performance liquid chromatography mass spectrometry (UPLC-MS). Spectra from UPLC-MS measured from (A) negative and (B) positive ion modes were used to identify individual metabolites. Score plots including all samples from principal component analysis (PCA) based on (C) negative and (D) positive ion modes presented dysregulated metabolomics affected by e-cig vaping and cigarette smoking.
Figure 2
Figure 2
Metabolites from plasma were analyzed from UPLC-MS, metabolite fold changes were analyzed based on the normalized spectrum area. Heatmap representing significant dysregulated metabolites from nicotine degradation, TCA cycle, and sphingolipid metabolism among control (n = 6), e-cig (n = 12), and cigarette smoke (n = 6). Data are summarized as normalized log2 transformed.
Figure 3
Figure 3
Metabolites from plasma analyzed from UPLC-MS from positive ion mode identified dysregulated nicotine degradation related metabolites in e-cig users and cigarette smokers. Fold changes were calculated based on the normalized area from UPLC-MS spectra, and control groups were used as a baseline. Data are shown as mean ± SEM (n = 6 for non-smoking control and cigarette smoke groups, n = 12 for e-cig group; * p < 0.05, ** p < 0.01 vs. control non-smokers).
Figure 4
Figure 4
Metabolites from plasma analyzed from UPLC-MS from negative ion mode identified dysregulated TCA cycle related metabolites in e-cig users. Fold changes were calculated based on the normalized area from UPLC-MS spectra, and control groups were used as a baseline. Data are shown as mean ± SEM (n = 6 for non-smoking control and cigarette smoke groups, n = 12 for e-cig group; * p < 0.05, ** p < 0.01 vs. non-smoking control; # p < 0.05, ## p < 0.01 vs. e-cig).
Figure 5
Figure 5
Metabolites from plasma analyzed from UPLC-MS from positive ion mode identified dysregulated sphingolipid metabolites in cigarette smokers. Fold changes were calculated based on the normalized area from UPLC-MS spectra, and control groups were used as a baseline. Data are shown as mean ± SEM (n = 6 for non-smoking control and cigarette smoke groups, n = 12 for e-cig group; * p < 0.05 vs. non-smoking control; # p < 0.05 vs. e-cig).
Figure 6
Figure 6
Metabolites from plasma analyzed from UPLC-MS from both negative and positive ion mode identified dysregulated metabolites in either e-cig users or cigarette smoker. Fold changes were calculated based on the normalized area from UPLC-MS spectra, and control groups were used as a baseline. Data are shown as mean ± SEM (n = 6 for non-smoking control and cigarette smoke groups, n = 12 for e-cig group; * p < 0.05, ** p < 0.01 vs. non-smoking control; # p < 0.05, ## p < 0.01 vs. e-cig).

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References

    1. Patel D., Davis K.C., Cox S., Bradfield B., King B.A., Shafer P., Caraballo R., Bunnell R. Reasons for current E-cigarette use among U.S. adults. Prev. Med. 2016;93:14–20. doi: 10.1016/j.ypmed.2016.09.011. - DOI - PMC - PubMed
    1. Madison M.C., Landers C.T., Gu B.-H., Chang C.-Y., Tung H.-Y., You R., Hong M.J., Baghaei N., Song L.-Z., Porter P., et al. Electronic cigarettes disrupt lung lipid homeostasis and innate immunity independent of nicotine. J. Clin. Investig. 2019;129:4290–4304. doi: 10.1172/JCI128531. - DOI - PMC - PubMed
    1. Goniewicz M.L., Kuma T., Gawron M., Knysak J., Kosmider L. Nicotine Levels in Electronic Cigarettes. Nicotine Tob. Res. 2012;15:158–166. doi: 10.1093/ntr/nts103. - DOI - PubMed
    1. Grana R.A., Popova L., Ling P.M. A Longitudinal Analysis of Electronic Cigarette Use and Smoking CessationElectronic Cigarette Use and Smoking CessationLetters. JAMA Intern. Med. 2014;174:812–813. doi: 10.1001/jamainternmed.2014.187. - DOI - PMC - PubMed
    1. Muthumalage T., Friedman M.R., McGraw M.D., Ginsberg G., Friedman A.E., Rahman I. Chemical Constituents Involved in E-Cigarette, or Vaping Product Use-Associated Lung Injury (EVALI) Toxics. 2020;8:25. doi: 10.3390/toxics8020025. - DOI - PMC - PubMed

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