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Metabolic Differences between Ex-Smokers and Nonsmokers: A Metabolomic Analysis
The aim of this study was to compare changes in the metabolite levels of ex-smokers and nonsmokers using a metabolomics approach, accounting for the weight gain in ex-smokers. Volunteer ex-smokers and nonsmokers were recruited from two cohorts Shijingshan (174) and Xishan (78), respectively, at a 1 ...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034916/ https://www.ncbi.nlm.nih.gov/pubmed/35469229 http://dx.doi.org/10.1155/2022/6480749 |
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author | Liang, Lirong Feng, Lin Zhou, Long Chu, Shuilian Zhang, Di Jin, Hang Li, Jiachen Zhao, Liancheng Tong, Zhaohui |
author_facet | Liang, Lirong Feng, Lin Zhou, Long Chu, Shuilian Zhang, Di Jin, Hang Li, Jiachen Zhao, Liancheng Tong, Zhaohui |
author_sort | Liang, Lirong |
collection | PubMed |
description | The aim of this study was to compare changes in the metabolite levels of ex-smokers and nonsmokers using a metabolomics approach, accounting for the weight gain in ex-smokers. Volunteer ex-smokers and nonsmokers were recruited from two cohorts Shijingshan (174) and Xishan (78), respectively, at a 1 : 1 ratio for age and sex. Nontargeted metabolomics was performed on the volunteers' blood samples using liquid chromatography-mass spectrometry, and multivariate statistical analysis was performed using principal component analysis and orthogonal partial least squares discriminant analysis. Enrichment analysis was used to identify Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with differential metabolites and weighted gene co-expression network analysis and maximal correlation coefficient (MCC) algorithms were used to identify key metabolites. The results revealed no significant differences between the distribution of blood metabolite levels in the ex-smokers and nonsmokers. The biosynthesis of valine, leucine, and isoleucine was determined to be associated with differential metabolites, and five key metabolites were identified. Further analysis revealed differences in weight gain and regained metabolite levels in ex-smokers, and 10 differential metabolites were identified that may be associated with weight gain in ex-smokers. These findings suggest that quitting smoking restores metabolites to almost normal levels and results in weight gain. The identified key metabolites and metabolic pathways may also provide a basis for clinical studies. |
format | Online Article Text |
id | pubmed-9034916 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-90349162022-04-24 Metabolic Differences between Ex-Smokers and Nonsmokers: A Metabolomic Analysis Liang, Lirong Feng, Lin Zhou, Long Chu, Shuilian Zhang, Di Jin, Hang Li, Jiachen Zhao, Liancheng Tong, Zhaohui J Healthc Eng Research Article The aim of this study was to compare changes in the metabolite levels of ex-smokers and nonsmokers using a metabolomics approach, accounting for the weight gain in ex-smokers. Volunteer ex-smokers and nonsmokers were recruited from two cohorts Shijingshan (174) and Xishan (78), respectively, at a 1 : 1 ratio for age and sex. Nontargeted metabolomics was performed on the volunteers' blood samples using liquid chromatography-mass spectrometry, and multivariate statistical analysis was performed using principal component analysis and orthogonal partial least squares discriminant analysis. Enrichment analysis was used to identify Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with differential metabolites and weighted gene co-expression network analysis and maximal correlation coefficient (MCC) algorithms were used to identify key metabolites. The results revealed no significant differences between the distribution of blood metabolite levels in the ex-smokers and nonsmokers. The biosynthesis of valine, leucine, and isoleucine was determined to be associated with differential metabolites, and five key metabolites were identified. Further analysis revealed differences in weight gain and regained metabolite levels in ex-smokers, and 10 differential metabolites were identified that may be associated with weight gain in ex-smokers. These findings suggest that quitting smoking restores metabolites to almost normal levels and results in weight gain. The identified key metabolites and metabolic pathways may also provide a basis for clinical studies. Hindawi 2022-04-16 /pmc/articles/PMC9034916/ /pubmed/35469229 http://dx.doi.org/10.1155/2022/6480749 Text en Copyright © 2022 Lirong Liang et al. https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Research Article Liang, Lirong Feng, Lin Zhou, Long Chu, Shuilian Zhang, Di Jin, Hang Li, Jiachen Zhao, Liancheng Tong, Zhaohui Metabolic Differences between Ex-Smokers and Nonsmokers: A Metabolomic Analysis |
title | Metabolic Differences between Ex-Smokers and Nonsmokers: A Metabolomic Analysis |
title_full | Metabolic Differences between Ex-Smokers and Nonsmokers: A Metabolomic Analysis |
title_fullStr | Metabolic Differences between Ex-Smokers and Nonsmokers: A Metabolomic Analysis |
title_full_unstemmed | Metabolic Differences between Ex-Smokers and Nonsmokers: A Metabolomic Analysis |
title_short | Metabolic Differences between Ex-Smokers and Nonsmokers: A Metabolomic Analysis |
title_sort | metabolic differences between ex-smokers and nonsmokers: a metabolomic analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034916/ https://www.ncbi.nlm.nih.gov/pubmed/35469229 http://dx.doi.org/10.1155/2022/6480749 |
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