Version 1
: Received: 3 January 2024 / Approved: 3 January 2024 / Online: 4 January 2024 (03:43:27 CET)
How to cite:
Lee, H.-S.; Na, H.-K.; Chang, S.-S.; Kim, S.-Y.; Kim, C. S.; Song, Y.; Yang, M. Tobacco Smoking as an EDC in Aging. Preprints2024, 2024010211. https://doi.org/10.20944/preprints202401.0211.v1
Lee, H.-S.; Na, H.-K.; Chang, S.-S.; Kim, S.-Y.; Kim, C. S.; Song, Y.; Yang, M. Tobacco Smoking as an EDC in Aging. Preprints 2024, 2024010211. https://doi.org/10.20944/preprints202401.0211.v1
Lee, H.-S.; Na, H.-K.; Chang, S.-S.; Kim, S.-Y.; Kim, C. S.; Song, Y.; Yang, M. Tobacco Smoking as an EDC in Aging. Preprints2024, 2024010211. https://doi.org/10.20944/preprints202401.0211.v1
APA Style
Lee, H. S., Na, H. K., Chang, S. S., Kim, S. Y., Kim, C. S., Song, Y., & Yang, M. (2024). Tobacco Smoking as an EDC in Aging. Preprints. https://doi.org/10.20944/preprints202401.0211.v1
Chicago/Turabian Style
Lee, H., Yoonjeong Song and Mihi Yang. 2024 "Tobacco Smoking as an EDC in Aging" Preprints. https://doi.org/10.20944/preprints202401.0211.v1
Abstract
Tobacco smoke is an environmental mixture including polycyclic aromatic hydrocarbons and may interfere in endocrine system as an EDC in aging. Thus, we performed a molecular epidemiological approach with in-depth biological monitoring of combustible cigarette smoking among adolescents and adults in South Korea (N=620) with exposure biomarkers, i.e., exhaled CO, urinary cotinine, t,t-muconic acid (TTMA), malondialdehyde (MDA), and obtained information of their lifestyle and tobacco addiction status. We also diagnosed the genetic polymorphisms on the 96 SNPs for tobacco-metabolism, -addiction, and expression differences and compared mtDNA abnormalities in buccal and blood cells. As results, there were positive associations among the above tobacco exposure biomarkers. Man or youth smokers showed high frequency in some of mtDNA alteration, such as ‘SNPs for inconsistent bases between buccal and blood cells’. Among the SNPs, the polymorphisms on SULT1A1, DRD2, and ADH1B were related to multi-exposure biomarkers. Interestingly, youth showed similar levels of urinary TTMA and MDA to adults, although their pack-year was approx. 1/6 volume of that of adults. We also observed the negative association between urinary MDA levels and the growth rate in the adolescents (p<0.05). In conclusion, the present biological monitoring provides high susceptible population, i.e., adolescents rather than adults, and reliable genetic factors affecting tobacco exposure. The inferred environment-gene-gene interaction suggests tobacco smoking accelerats aging in adolescents as an EDC.
Medicine and Pharmacology, Pharmacology and Toxicology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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