代谢组学在识别锰暴露生物标志物中的应用。
The Use of Metabolomics to Identify Biological Signatures of Manganese Exposure.
机构信息
Department of Environmental and Occupational Health Sciences, University of Washington, 4225 Roosevelt Way NE Suite 100, Seattle, WA 98105, USA.
Department of Pharmaceutics, University of Washington, H272 Health Science Building, Seattle WA 98195, USA.
出版信息
Ann Work Expo Health. 2017 May 1;61(4):406-415. doi: 10.1093/annweh/wxw032.
OBJECTIVES
Manganese (Mn) is a known neurotoxicant, and given its health effects and ubiquitous nature in metal-working settings, identification of a valid and reproducible biomarker of Mn exposure is of interest. Here, global metabolomics is utilized to determine metabolites that differ between groups defined by Mn exposure status, with the goal being to help inform a potential metabolite biomarker of Mn exposure.
METHODS
Mn exposed subjects were recruited from a Mn steel foundry and Mn unexposed subjects were recruited from crane operators at a metal recycling facility. Over the course of a work day, each subject wore a personal inhalable dust sampler (IOM), and provided an end of shift urine sample that underwent global metabolomics profiling. Both exposed and unexposed subjects were divided into a training set and demographically similar validation set. Using a two-sided adjusted t-test, relative abundances of all metabolites found were compared between Mn exposed and unexposed training sets, and those with a false discovery rates (FDR) <0.1 were further tested in the validation sets.
RESULTS
Fifteen ions were found to be significantly different (FDR < 0.1) between the exposed and unexposed training sets, and nine of these ions remained significantly different between the exposed and unexposed validation set as well. When further dividing exposure status into 'lower exposure' and 'higher exposure', several of these nine ions exhibited an apparent exposure-response relationship.
CONCLUSIONS
This is the first time that metabolomics has been used to distinguish between Mn exposure status in an occupational cohort, though additional work should be done to replicate these findings with a larger cohort. With metabolite identification by name, empirical formula, or pathway, a better understanding of the relationship between Mn exposure and neurotoxic effects could be elucidated, and a potential metabolite biomarker of Mn exposure could be determined.
目的
锰（Mn）是一种已知的神经毒物，鉴于其对健康的影响以及在金属加工环境中的普遍存在，确定一种有效的、可重复的 Mn 暴露生物标志物具有重要意义。本研究采用代谢组学方法来确定 Mn 暴露组和非暴露组之间存在差异的代谢物，以期为 Mn 暴露的潜在代谢生物标志物提供信息。
方法
在 Mn 钢铸造厂招募 Mn 暴露工人，在金属回收厂招募 Mn 非暴露的吊车操作员。在一个工作日内，每位研究对象都佩戴个人可吸入粉尘采样器（IOM），并在下班时提供尿液样本进行代谢组学分析。暴露组和非暴露组的研究对象均分为训练集和具有相似人口统计学特征的验证集。采用双侧调整 t 检验比较 Mn 暴露组和非暴露组训练集之间所有代谢物的相对丰度，对 FDR<0.1 的代谢物在验证集中进一步测试。
结果
在暴露组和非暴露组训练集之间发现 15 个离子存在显著差异（FDR<0.1），其中 9 个离子在暴露组和非暴露组验证集之间也存在显著差异。当进一步将暴露状态分为“低暴露”和“高暴露”时，这 9 个离子中的几个表现出明显的暴露反应关系。
结论
这是代谢组学首次用于区分职业队列中的 Mn 暴露状态，但需要进一步的研究来用更大的队列复制这些发现。通过对代谢物进行命名、经验公式或途径的鉴定，可以更好地阐明 Mn 暴露与神经毒性之间的关系，并确定 Mn 暴露的潜在代谢生物标志物。
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