Evidence map›Paper›PMID 39697303›Full record

ArticleTobacco induced diseases2024

Response of human metabolism to ultra-low and high nicotine cigarettes based on urine metabolomics and bioinformatic analysis.

Mengyue Zhang, Chunting Yang, Lingling Gao, Yuanyuan Zhao, Hongzhi Shi

Abstract read
In one paragraph

Article in Tobacco induced diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mengyue ZhangCollege of Tobacco Science, Henan Agricultural University, Zhengzhou, China.
Chunting YangCollege of Tobacco Science, Henan Agricultural University, Zhengzhou, China.
Lingling GaoHenan Academy of Agricultural Sciences, Zhengzhou, China.
Yuanyuan ZhaoCollege of Tobacco Science, Henan Agricultural University, Zhengzhou, China.
Hongzhi ShiCollege of Tobacco Science, Henan Agricultural University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis study aimed to evaluate the metabolomic profiles of urine samples obtained from smokers who smoked cigarettes with low and high nicotine content.

methodsThree 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.

resultsPCA 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.

conclusionsCigarettes 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.

Indexed as

bioinformaticscigarettenicotineuntargeted metabolomics

Identifiers

PMID39697303
PMCPMC11653067

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