Mengyue Zhang, Chunting Yang, Lingling Gao, Yuanyuan Zhao, Hongzhi Shi
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A total of 1150 significantly differential metabolites were selected between the HN and LN groups, such as cotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol-N-glucuronide. Two-way hierarchical clustering analysis also suggested noticeable differences between the two comparison groups Enrichment analysis indicates that the differential metabolites between the two groups were mainly enriched in 19 pathways, such as the protein kinase G (cGMP)-protein kinase G (PKG) signaling pathway, adenosine monophosphate (AMP)-activated protein kinase signaling pathway, mammalian target of rapamycin signaling pathway, and Parkinson's disease.</p><p><strong>Conclusions: </strong>Cigarettes with different nicotine content may alter the metabolism of smokers. 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引用次数: 0
摘要
简介:本研究旨在评估吸烟者吸食低尼古丁含量和高尼古丁含量香烟的尿液样本的代谢组学特征。方法:3名吸烟者参与本研究。他们被给予低尼古丁(LN)香烟,并在第三天结束时收集LN组的尿液。戒烟1周后,给予高尼古丁(HN)香烟,HN组收集尿液。尿液分析采用非靶向代谢组学和生物信息学分析方法。结果:PCA显示组内样本相似度高,组间样本距离大,说明两组之间存在显著差异。在HN组和LN组之间共选择了1150种差异显著的代谢物,如可替宁和4-(甲基亚硝胺)-1-(3-吡啶基)-1-丁醇- n -葡萄糖醛酸盐。双向分层聚类分析显示,两组差异代谢物主要富集在蛋白激酶G (cGMP)-蛋白激酶G (PKG)信号通路、单磷酸腺苷(AMP)激活的蛋白激酶信号通路、哺乳动物雷帕霉素靶点信号通路、帕金森病等19条通路上。结论:不同尼古丁含量的香烟可能改变吸烟者的代谢。HN组和LN组共鉴定出1150个差异显著的代谢物,主要富集于ABC转运蛋白、蛋白激酶G (cGMP)-蛋白激酶G (PKG)信号通路、咖啡因代谢和精氨酸生物合成途径。
Response of human metabolism to ultra-low and high nicotine cigarettes based on urine metabolomics and bioinformatic analysis.
Introduction: This study aimed to evaluate the metabolomic profiles of urine samples obtained from smokers who smoked cigarettes with low and high nicotine content.
Methods: Three smokers participated in this study. They were given low-nicotine (LN) cigarettes, and urine was collected at the end of the third day for the LN group. After 1 week of not smoking, they were given high-nicotine (HN) cigarettes, and urine was collected for the HN group. Untargeted metabolomics and bioinformatic analysis methods were used for urine analysis.
Results: PCA showed a high degree of similarity between samples within the group and a large distance between samples between groups, indicating a significant difference between the two groups. A total of 1150 significantly differential metabolites were selected between the HN and LN groups, such as cotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol-N-glucuronide. Two-way hierarchical clustering analysis also suggested noticeable differences between the two comparison groups Enrichment analysis indicates that the differential metabolites between the two groups were mainly enriched in 19 pathways, such as the protein kinase G (cGMP)-protein kinase G (PKG) signaling pathway, adenosine monophosphate (AMP)-activated protein kinase signaling pathway, mammalian target of rapamycin signaling pathway, and Parkinson's disease.
Conclusions: Cigarettes with different nicotine content may alter the metabolism of smokers. A total of 1150 significantly different metabolites were identified between the HN and LN groups, which were mainly enriched in ABC transporters, protein kinase G (cGMP)-protein kinase G (PKG) signaling pathway, caffeine metabolism, and arginine biosynthesis pathways.
期刊介绍:
Tobacco Induced Diseases encompasses all aspects of research related to the prevention and control of tobacco use at a global level. Preventing diseases attributable to tobacco is only one aspect of the journal, whose overall scope is to provide a forum for the publication of research articles that can contribute to reducing the burden of tobacco induced diseases globally. To address this epidemic we believe that there must be an avenue for the publication of research/policy activities on tobacco control initiatives that may be very important at a regional and national level. This approach provides a very important "hands on" service to the tobacco control community at a global scale - as common problems have common solutions. Hence, we see ourselves as "connectors" within this global community.
The journal hence encourages the submission of articles from all medical, biological and psychosocial disciplines, ranging from medical and dental clinicians, through health professionals to basic biomedical and clinical scientists.