Microbial Disturbances Caused by Pesticide Exposure and Their Predictive Implications for Gestational Diabetes Mellitus

Previous studies have suggested that pesticide exposure and gut microbiome alterations are associated with gestational diabetes mellitus (GDM) risk. Understanding the complex interactive effect of these factors on GDM is essential. In a cohort of 852 pregnant women, we assessed pesticide levels in serum and analyzed the gut microbiota using 16S rRNA and shotgun metagenomic sequencing. We explored the interactions between pesticides and gut microbiota, assessed their roles in GDM development, and proposed a predictive model based on identified biomarkers. We identified an environmental risk score (ERS), denoting the pesticide mixture level significantly associated with GDM, with the gut microbiota, particularly involving the <i>Dorea</i> branch, playing a crucial mediating role. In addition, we found an interactive effect of pesticide exposure and gut microbiota on GDM risk. Notably, low <i>Prevotella</i> enrichment combined with high ERS arisen from pesticide levels led to a 10.36-fold increased GDM risk. The identified pesticide and gut microbial biomarkers achieved high predictive accuracy for GDM (AUC: 0.833, 95% CI: 0.748-0.918). Collectively, maternal pesticide exposure may induce disrupted microbiome-dependent glycemic alteration, necessitating future assessment of clinical implications. Potential GDM markers can serve as targets for therapeutic intervention caused by pesticides, leading to prevention.

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Publication Details

Journal
Environmental Science & Technology
Published
2025-05-06
DOI
https://doi.org/10.1021/acs.est.5c01076
Citations
1
Primary Topic
Gestational Diabetes Research and Management
Type
article
Field-Weighted Citation Impact
2.06
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article

Microbial Disturbances Caused by Pesticide Exposure and Their Predictive Implications for Gestational Diabetes Mellitus

Quanquan Guan, Yifan Xu, Yankai Xia, Yuqing Zhang et al.
1 citations
Environmental Science & Technology
Gestational Diabetes Research and Management
2.06
article

Microbial Disturbances Caused by Pesticide Exposure and Their Predictive Implications for Gestational Diabetes Mellitus

Quanquan Guan, Yifan Xu, Yankai Xia, Yuqing Zhang, Hein M. Tun, Mingzhi Zhang, Weiyue Hu, Yadan Xu, Xu Yang
article en
1 citations

Abstract

Previous studies have suggested that pesticide exposure and gut microbiome alterations are associated with gestational diabetes mellitus (GDM) risk. Understanding the complex interactive effect of these factors on GDM is essential. In a cohort of 852 pregnant women, we assessed pesticide levels in serum and analyzed the gut microbiota using 16S rRNA and shotgun metagenomic sequencing. We explored the interactions between pesticides and gut microbiota, assessed their roles in GDM development, and proposed a predictive model based on identified biomarkers. We identified an environmental risk score (ERS), denoting the pesticide mixture level significantly associated with GDM, with the gut microbiota, particularly involving the <i>Dorea</i> branch, playing a crucial mediating role. In addition, we found an interactive effect of pesticide exposure and gut microbiota on GDM risk. Notably, low <i>Prevotella</i> enrichment combined with high ERS arisen from pesticide levels led to a 10.36-fold increased GDM risk. The identified pesticide and gut microbial biomarkers achieved high predictive accuracy for GDM (AUC: 0.833, 95% CI: 0.748-0.918). Collectively, maternal pesticide exposure may induce disrupted microbiome-dependent glycemic alteration, necessitating future assessment of clinical implications. Potential GDM markers can serve as targets for therapeutic intervention caused by pesticides, leading to prevention.

Environmental Science & TechnologyVol. 59(19)
Chinese University of Hong Kong (HK), Nanjing Maternity and Child Health Care Hospital (CN), Hong Kong Jockey Club (HK), Suzhou Municipal Hospital (CN), Center for Global Health (US), Nanjing Medical University (CN)
Zero hunger
Openalex Percentile: Top 16%
Gestational Diabetes Research and Management
2.06
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