Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition, and Public Health, Tianjin Medical University, Tianjin 300070, China; Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China; Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, Tianjin Medical University, Tianjin 300070, China; Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, China.
Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; Tianjin Key Laboratory of Environment, Nutrition, and Public Health, Tianjin Medical University, Tianjin 300070, China; Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China; Key Laboratory of Prevention and Control of Major Diseases in the Population, Ministry of Education, Tianjin Medical University, Tianjin 300070, China.
Environ Int. 2024 Aug;190:108921. doi: 10.1016/j.envint.2024.108921. Epub 2024 Jul 30.
Little is known about the combined effect of bisphenol mixtures and metal mixtures on type 2 diabetes mellitus (T2DM) risk, and the mediating roles of metabolites.
The study included 606 pairs of T2DM cases and controls matched by age and sex, and information of participants was collected through questionnaires and laboratory tests. Serum bisphenol and plasma metal concentrations were measured using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. Widely targeted metabolomics was employed to obtain the serum metabolomic profiles. Conditional logistic regression models were used to assess the single associations of bisphenols and metals with T2DM risk after multivariable adjustment. Additionally, the joint effects of bisphenol mixtures and metal mixtures were examined using quantile-based g-computation (QG-C) models. Furthermore, differential metabolites associated with T2DM were identified, and mediation analyses were performed to explore the role of metabolites in the associations of bisphenols and metals with T2DM risk.
The results showed bisphenol mixtures were associated with an increased T2DM risk, with bisphenol A (BPA) identified as the primary contributor. While the association between metal mixtures and T2DM remained inconclusive, cobalt (Co), iron (Fe), and zinc (Zn) showed the highest weight indices for T2DM risk. A total of 154 differential metabolites were screened between the T2DM cases and controls. Mediation analyses indicated that 9 metabolites mediated the association between BPA and T2DM, while L-valine mediated the association between Zn and T2DM risk.
The study indicated that BPA, Co, Fe, and Zn were the primary contributors to increased T2DM risk, and metabolites played a mediating role in the associations of BPA and Zn with the risk of T2DM. Our findings contribute to a better understanding of the mechanisms underlying the associations of bisphenols and metals with T2DM.
关于双酚混合物和金属混合物对 2 型糖尿病（T2DM）风险的综合影响，以及代谢物的介导作用，目前知之甚少。
该研究纳入了 606 对年龄和性别相匹配的 T2DM 病例和对照，通过问卷调查和实验室检测收集参与者的信息。采用超高效液相色谱-质谱联用（UPLC-MS/MS）和电感耦合等离子体质谱（ICP-MS）分别测定血清双酚和血浆金属浓度。采用广泛靶向代谢组学方法获得血清代谢组图谱。采用条件逻辑回归模型，在多变量调整后评估双酚和金属单独与 T2DM 风险的关联。此外，还采用基于分位数的 g 计算（QG-C）模型检验双酚混合物和金属混合物的联合效应。此外，鉴定与 T2DM 相关的差异代谢物，并进行中介分析以探讨代谢物在双酚和金属与 T2DM 风险关联中的作用。
结果显示，双酚混合物与 T2DM 风险增加相关，其中双酚 A（BPA）是主要贡献者。而金属混合物与 T2DM 之间的关联仍不确定，但钴（Co）、铁（Fe）和锌（Zn）显示出对 T2DM 风险的最高权重指数。在 T2DM 病例和对照之间共筛选出 154 个差异代谢物。中介分析表明，9 个代谢物介导了 BPA 与 T2DM 之间的关联，而 L-缬氨酸介导了 Zn 与 T2DM 风险之间的关联。
该研究表明，BPA、Co、Fe 和 Zn 是导致 T2DM 风险增加的主要因素，代谢物在 BPA 和 Zn 与 T2DM 风险关联中起中介作用。我们的研究结果有助于更好地理解双酚和金属与 T2DM 之间关联的机制。
