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[Formula: see text] and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China

BACKGROUND: Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of [Formula: see text] ([Formula: see text])] exposure. Previous experimental and epi...

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Autores principales: Zhao, Liang, Fang, Jianlong, Tang, Song, Deng, Fuchang, Liu, Xiaohui, Shen, Yu, Liu, Yuanyuan, Kong, Fanling, Du, Yanjun, Cui, Liangliang, Shi, Wanying, Wang, Yan, Wang, Jiaonan, Zhang, Yingjian, Dong, Xiaoyan, Gao, Ying, Dong, Li, Zhou, Huichan, Sun, Qinghua, Dong, Haoran, Peng, Xiumiao, Zhang, Yi, Cao, Meng, Wang, Yanwen, Zhi, Hong, Du, Hang, Zhou, Jingyang, Li, Tiantian, Shi, Xiaoming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Environmental Health Perspectives 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8843086/
https://www.ncbi.nlm.nih.gov/pubmed/35157499
http://dx.doi.org/10.1289/EHP9688
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author Zhao, Liang
Fang, Jianlong
Tang, Song
Deng, Fuchang
Liu, Xiaohui
Shen, Yu
Liu, Yuanyuan
Kong, Fanling
Du, Yanjun
Cui, Liangliang
Shi, Wanying
Wang, Yan
Wang, Jiaonan
Zhang, Yingjian
Dong, Xiaoyan
Gao, Ying
Dong, Li
Zhou, Huichan
Sun, Qinghua
Dong, Haoran
Peng, Xiumiao
Zhang, Yi
Cao, Meng
Wang, Yanwen
Zhi, Hong
Du, Hang
Zhou, Jingyang
Li, Tiantian
Shi, Xiaoming
author_facet Zhao, Liang
Fang, Jianlong
Tang, Song
Deng, Fuchang
Liu, Xiaohui
Shen, Yu
Liu, Yuanyuan
Kong, Fanling
Du, Yanjun
Cui, Liangliang
Shi, Wanying
Wang, Yan
Wang, Jiaonan
Zhang, Yingjian
Dong, Xiaoyan
Gao, Ying
Dong, Li
Zhou, Huichan
Sun, Qinghua
Dong, Haoran
Peng, Xiumiao
Zhang, Yi
Cao, Meng
Wang, Yanwen
Zhi, Hong
Du, Hang
Zhou, Jingyang
Li, Tiantian
Shi, Xiaoming
author_sort Zhao, Liang
collection PubMed
description BACKGROUND: Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of [Formula: see text] ([Formula: see text])] exposure. Previous experimental and epidemiological studies have proposed several potential mechanisms by which [Formula: see text] contributes to IR/T2DM, including inflammation imbalance, oxidative stress, and endothelial dysfunction. Recent evidence suggests that the imbalance of the gut microbiota affects the metabolic process and may precede IR. However, the underlying mechanisms of [Formula: see text] , gut microbiota, and metabolic diseases are unclear. OBJECTIVES: We investigated the associations between personal exposure to [Formula: see text] and fasting blood glucose and insulin levels, the IR index, and other related biomarkers. We also explored the potential underlying mechanisms (systemic inflammation and sphingolipid metabolism) between [Formula: see text] and insulin resistance and the mediating effects between [Formula: see text] and sphingolipid metabolism. METHODS: We recruited 76 healthy seniors to participate in a repeated-measures panel study and conducted clinical examinations every month from September 2018 to January 2019. Linear mixed-effects (LME) models were used to analyze the associations between [Formula: see text] and health data (e.g., functional factors, the IR index, inflammation and other IR-related biomarkers, metabolites, and gut microbiota). We also performed mediation analyses to evaluate the effects of mediators (gut microbiota) on the associations between exposures ([Formula: see text]) and featured metabolism outcomes. RESULTS: Our prospective panel study illustrated that exposure to [Formula: see text] was associated with an increased risk of higher IR index and functional biomarkers, and our study provided mechanistic evidence suggesting that [Formula: see text] exposure may contribute to systemic inflammation and altered sphingolipid metabolism. DISCUSSION: Our findings demonstrated that [Formula: see text] was associated with the genera of the gut microbiota, which partially mediated the association between [Formula: see text] and sphingolipid metabolism. These findings may extend our current understanding of the pathways of [Formula: see text] and IR. https://doi.org/10.1289/EHP9688
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spelling pubmed-88430862022-02-17 [Formula: see text] and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China Zhao, Liang Fang, Jianlong Tang, Song Deng, Fuchang Liu, Xiaohui Shen, Yu Liu, Yuanyuan Kong, Fanling Du, Yanjun Cui, Liangliang Shi, Wanying Wang, Yan Wang, Jiaonan Zhang, Yingjian Dong, Xiaoyan Gao, Ying Dong, Li Zhou, Huichan Sun, Qinghua Dong, Haoran Peng, Xiumiao Zhang, Yi Cao, Meng Wang, Yanwen Zhi, Hong Du, Hang Zhou, Jingyang Li, Tiantian Shi, Xiaoming Environ Health Perspect Research BACKGROUND: Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of [Formula: see text] ([Formula: see text])] exposure. Previous experimental and epidemiological studies have proposed several potential mechanisms by which [Formula: see text] contributes to IR/T2DM, including inflammation imbalance, oxidative stress, and endothelial dysfunction. Recent evidence suggests that the imbalance of the gut microbiota affects the metabolic process and may precede IR. However, the underlying mechanisms of [Formula: see text] , gut microbiota, and metabolic diseases are unclear. OBJECTIVES: We investigated the associations between personal exposure to [Formula: see text] and fasting blood glucose and insulin levels, the IR index, and other related biomarkers. We also explored the potential underlying mechanisms (systemic inflammation and sphingolipid metabolism) between [Formula: see text] and insulin resistance and the mediating effects between [Formula: see text] and sphingolipid metabolism. METHODS: We recruited 76 healthy seniors to participate in a repeated-measures panel study and conducted clinical examinations every month from September 2018 to January 2019. Linear mixed-effects (LME) models were used to analyze the associations between [Formula: see text] and health data (e.g., functional factors, the IR index, inflammation and other IR-related biomarkers, metabolites, and gut microbiota). We also performed mediation analyses to evaluate the effects of mediators (gut microbiota) on the associations between exposures ([Formula: see text]) and featured metabolism outcomes. RESULTS: Our prospective panel study illustrated that exposure to [Formula: see text] was associated with an increased risk of higher IR index and functional biomarkers, and our study provided mechanistic evidence suggesting that [Formula: see text] exposure may contribute to systemic inflammation and altered sphingolipid metabolism. DISCUSSION: Our findings demonstrated that [Formula: see text] was associated with the genera of the gut microbiota, which partially mediated the association between [Formula: see text] and sphingolipid metabolism. These findings may extend our current understanding of the pathways of [Formula: see text] and IR. https://doi.org/10.1289/EHP9688 Environmental Health Perspectives 2022-02-14 /pmc/articles/PMC8843086/ /pubmed/35157499 http://dx.doi.org/10.1289/EHP9688 Text en https://ehp.niehs.nih.gov/about-ehp/licenseEHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted.
spellingShingle Research
Zhao, Liang
Fang, Jianlong
Tang, Song
Deng, Fuchang
Liu, Xiaohui
Shen, Yu
Liu, Yuanyuan
Kong, Fanling
Du, Yanjun
Cui, Liangliang
Shi, Wanying
Wang, Yan
Wang, Jiaonan
Zhang, Yingjian
Dong, Xiaoyan
Gao, Ying
Dong, Li
Zhou, Huichan
Sun, Qinghua
Dong, Haoran
Peng, Xiumiao
Zhang, Yi
Cao, Meng
Wang, Yanwen
Zhi, Hong
Du, Hang
Zhou, Jingyang
Li, Tiantian
Shi, Xiaoming
[Formula: see text] and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China
title [Formula: see text] and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China
title_full [Formula: see text] and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China
title_fullStr [Formula: see text] and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China
title_full_unstemmed [Formula: see text] and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China
title_short [Formula: see text] and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China
title_sort [formula: see text] and serum metabolome and insulin resistance, potential mediation by the gut microbiome: a population-based panel study of older adults in china
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8843086/
https://www.ncbi.nlm.nih.gov/pubmed/35157499
http://dx.doi.org/10.1289/EHP9688
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