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利用体外人细胞系数据的信号转导和代谢途径预测电磁场中的人类疾病靶点。

The Use of Signal-Transduction and Metabolic Pathways to Predict Human Disease Targets from Electric and Magnetic Fields Using in vitro Data in Human Cell Lines.

机构信息

National Institute of Environmental Health Sciences, Research Triangle Park , Durham, NC , USA.

Environmental Health Research , Thun , Switzerland.

出版信息

Front Public Health. 2016 Sep 7;4:193. doi: 10.3389/fpubh.2016.00193. eCollection 2016.

Abstract

Using in vitro data in human cell lines, several research groups have investigated changes in gene expression in cellular systems following exposure to extremely low frequency (ELF) and radiofrequency (RF) electromagnetic fields (EMF). For ELF EMF, we obtained five studies with complete microarray data and three studies with only lists of significantly altered genes. Likewise, for RF EMF, we obtained 13 complete microarray datasets and 5 limited datasets. Plausible linkages between exposure to ELF and RF EMF and human diseases were identified using a three-step process: (a) linking genes associated with classes of human diseases to molecular pathways, (b) linking pathways to ELF and RF EMF microarray data, and (c) identifying associations between human disease and EMF exposures where the pathways are significantly similar. A total of 60 pathways were associated with human diseases, mostly focused on basic cellular functions like JAK-STAT signaling or metabolic functions like xenobiotic metabolism by cytochrome P450 enzymes. ELF EMF datasets were sporadically linked to human diseases, but no clear pattern emerged. Individual datasets showed some linkage to cancer, chemical dependency, metabolic disorders, and neurological disorders. RF EMF datasets were not strongly linked to any disorders but strongly linked to changes in several pathways. Based on these analyses, the most promising area for further research would be to focus on EMF and neurological function and disorders.

摘要

利用人类细胞系中的体外数据,几个研究小组研究了在暴露于极低频(ELF)和射频(RF)电磁场(EMF)后细胞系统中基因表达的变化。对于 ELF EMF,我们获得了五项具有完整微阵列数据的研究和三项仅有显著改变基因列表的研究。同样,对于 RF EMF,我们获得了 13 项完整的微阵列数据集和 5 项有限的数据集。通过三个步骤确定了 ELF 和 RF EMF 与人类疾病之间的潜在联系:(a)将与人类疾病类别的基因与分子途径联系起来,(b)将途径与 ELF 和 RF EMF 微阵列数据联系起来,以及(c)确定人类疾病与 EMF 暴露之间的关联,其中途径非常相似。共有 60 条途径与人类疾病相关,主要集中在基本细胞功能(如 JAK-STAT 信号传导)或代谢功能(如细胞色素 P450 酶的外来代谢物代谢)上。ELF EMF 数据集与人类疾病偶有联系,但没有出现明显的模式。个别数据集显示与癌症、化学依赖、代谢紊乱和神经紊乱有一定联系。RF EMF 数据集与任何疾病没有强烈联系,但与几个途径的变化有强烈联系。基于这些分析,进一步研究的最有前途的领域将是关注 EMF 和神经功能和疾病。

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