De Benedetti Stefano, Lucchini Giorgio, Del Bò Cristian, Deon Valeria, Marocchi Alessandro, Penco Silvana, Lunetta Christian, Gianazza Elisabetta, Bonomi Francesco, Iametti Stefania
Department of Food, Environmental and Nutritional Sciences (DEFENS), Division of Chemical and Biomolecular Sciences, University of Milan, 20133, Milan, Italy.
Department of Agricultural and Environmental Sciences (DiSAA), University of Milan, 20133, Milan, Italy.
Biometals. 2017 Jun;30(3):355-365. doi: 10.1007/s10534-017-0011-4. Epub 2017 Mar 23.
Amyotrophic lateral sclerosis (ALS) is a fatal disorder with unknown etiology, in which genetic and environmental factors interplay to determine the onset and the course of the disease. Exposure to toxic metals has been proposed to be involved in the etiology of the disease either through a direct damage or by promoting oxidative stress. In this study we evaluated the concentration of a panel of metals in serum and whole blood of a small group of sporadic patients, all living in a defined geographical area, for which acid mine drainage has been reported. ALS prevalence in this area is higher than in the rest of Italy. Results were analyzed with software based on artificial neural networks. High concentrations of metals (in particular Se, Mn and Al) were associated with the disease group. Arsenic serum concentration resulted lower in ALS patients, but it positively correlated with disease duration. Comet assay was performed to evaluate endogenous DNA damage that resulted not different between patients and controls. Up to now only few studies considered geographically well-defined clusters of ALS patients. Common geographical origin among patients and controls gave us the chance to perform metallomic investigations under comparable conditions of environmental exposure. Elaboration of these data with software based on machine learning processes has the potential to be extremely useful to gain a comprehensive view of the complex interactions eventually leading to disease, even in a small number of subjects.
肌萎缩侧索硬化症(ALS)是一种病因不明的致命性疾病,其中遗传和环境因素相互作用,决定了疾病的发病和病程。有人提出,接触有毒金属可能通过直接损害或促进氧化应激参与该疾病的病因。在本研究中,我们评估了一小群散发性患者血清和全血中一组金属的浓度,这些患者都生活在一个特定的地理区域,该区域有酸性矿山排水的报告。该地区的ALS患病率高于意大利其他地区。结果使用基于人工神经网络的软件进行分析。高浓度的金属(特别是硒、锰和铝)与疾病组相关。ALS患者的砷血清浓度较低,但与疾病持续时间呈正相关。进行彗星试验以评估内源性DNA损伤,结果显示患者和对照组之间没有差异。到目前为止,只有少数研究考虑了地理上定义明确的ALS患者群体。患者和对照组的共同地理起源使我们有机会在可比的环境暴露条件下进行金属组学研究。使用基于机器学习过程的软件对这些数据进行处理,有可能非常有助于全面了解最终导致疾病的复杂相互作用,即使是在少数受试者中。