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February 25, 2026Ecotoxicology and Environmental Safety2 citationsOpen Access

Environmental toxicant exposure and diabetes risk: An exposome-wide association study integrating mixture effects and molecular mechanisms

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QYQing-Shuang YangJXJia-Qi XuRLRuiling Liu

Key Points

  • This study aims to explore the link between environmental toxicant exposure and diabetes risk, integrating chemical interactions and biological pathways.
  • Analyzed data from 2689 NHANES participants, including 366 with diabetes.
  • Evaluated 46 toxicants using exposure-wide association studies and complex statistical modeling.
  • Conducted integrative bioinformatics analyses to explore biological pathways.
  • Used machine learning to identify key predictive genes associated with diabetes.
  • Five toxicants were associated with increased diabetes odds, with odds ratios ranging from 1.22 to 1.34.
  • Mixture analysis indicated cumulative risk amplification, with a qgcomp OR of 1.39.
  • Stronger associations were observed in obese individuals.
  • Identified 87 overlapping genes related to pathways involving oxidative stress and inflammation.
  • Highlighted five hub genes (MAPK8, SIRT1, PIK3R1, KRAS, MAPK1) prevalent in toxicant-diabetes networks.

Abstract

Environmental toxicant exposure has emerged as a potential contributor to diabetes, yet systematic investigations integrating multiple chemicals and biological mechanisms remain limited. This study employed a hypothesis-generating, exposome-toxicogenomic framework to examine the associations between diverse environmental toxicants and diabetes risk and to explore underlying biological pathways. Data from 2689 NHANES 2013–2016 participants (366 with diabetes and 2323 without) were analyzed. Forty-six toxicants across seven chemical classes were evaluated using exposure-wide association studies, deletion/substitution/addition modeling, restricted cubic splines, Bayesian kernel machine regression, and quantile-based g-computation. Integrative bioinformatics analyses, including Comparative Toxicogenomics Database annotations, transcriptomic profiling, pathway enrichment, protein–protein interaction networks, and machine learning, were conducted to explore potential biological pathways and support biological plausibility. Five toxicants-glycidamide, ethylene oxide, antimony, uranium, and NAC-3HPM-were consistently associated with higher odds of diabetes (OR range: 1.22–1.34). Mixture analyses revealed cumulative risk amplification (qgcomp OR 1.39, 95 % CI 1.21–1.60), with ethylene oxide showing the highest posterior inclusion probability (>0.5). Stronger associations were observed among obese individuals. Bioinformatics analyses identified 87 overlapping toxicant-diabetes-related genes enriched in pathways related to oxidative stress, apoptosis, AGE-RAGE signaling, and atherosclerosis. Machine learning across 113 models (optimal: Elastic Net; training AUC 0.956, test AUC 0.867) highlighted 14 key genes, of which five (MAPK8, SIRT1, PIK3R1, KRAS, MAPK1) overlapped as hub genes in protein–protein interaction networks. These findings suggest that background-level exposure to environmental toxicants is associated with increased diabetes risk, potentially involving biologically relevant pathways related to mitochondrial function, insulin signaling, and inflammatory processes, with obesity acting as a potential susceptibility factor. • Exposome-toxicogenomic analysis links toxicants to diabetes risk. • Glycidamide, ethylene oxide, Sb, U, and NAC-3HPM increase diabetes odds. • Co-exposure amplifies diabetes risk, with ethylene oxide contributing most. • Oxidative stress and inflammation are enriched in 87 shared toxicant–diabetes genes. • MAPK8, SIRT1, PIK3R1, KRAS, and MAPK1 are key regulatory genes.

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Cite This Study

Yang et al. (2026) studied this question.

synapsesocial.com/papers/699e921bf5123be5ed050292https://doi.org/10.1016/j.ecoenv.2026.119923
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