PLoS ONE：王福俤等人类代谢相关疾病离子组学研究获进展

近日，PLoS ONE在线发表了营养所王福俤研究组、林旭研究组及中科院系统生物学重点实验室李亦学研究组在代谢相关疾病离子组学方面的合作研究成果。

生物体内的离子（包括金属、类金属和非金属）含量及分布具有重要的生理学意义并逐渐成为生命科学的研究热点，离子组学是利用现代高通量元素分析手段如电感耦合等离子质谱（ICP-MS），结合生物信息学和功能基因组学等手段来研究检测样本中的离子含量、分布、转运代谢规律等。离子组学在微生物学和植物学等领域的研究较为活跃，在医学和营养学中的研究却相对较少，且由于统计计算方法的缺失，主要集中于某一种或几种离子在疾病中的单一作用的研究。对比以往研究，本研究在样本选择、数据分析等方面有新的突破。

研究利用ICP-MS检测技术，结合生物信息学的手段来研究了976名正常及患代谢综合征、糖尿病和肥胖的中年患者血浆中18种离子谱网络调控规律。该工作将系统生物学统计分析方法mutual information引入离子谱调控规律研究，解析离子谱与病理和生理表型间的复杂和内在关联，为分析多离子的复杂调控关系提供了新的研究体系。研究不仅发现血浆铜和磷与肥胖、代谢综合征、2型糖尿病均具有显著的关联，还发现不同元素在与代谢性疾病的相互关联中所起作用的模式各不相同：钾和铬比较倾向于单独发挥作用；铁在2型糖尿病中更趋向于与其它元素如铜等互相影响而发挥作用；铜既可以单独在肥胖中发挥作用，也可以与其它离子互作从而影响肥胖代谢。虽然还需要在不同追踪人群中进行验证，但该研究在国际上首先提出“疾病离子组学”（Disease Ionomics）的新概念，为今后进一步研究金属离子在代谢相关疾病中的作用及机制提供了重要理论依据和新的思路。

该项工作得到了国家科技部、国家自然科学基金委、中国科学院及上海市科委等经费资助。

doi:10.1371/journal.pone.0038845
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Associations between Ionomic Profile and Metabolic Abnormalities in Human Population

Liang Sun1#, Yu Yu1#, Tao Huang2#, Peng An1, Danxia Yu1, Zhijie Yu1, Huaixing Li1, Hongguang Sheng3, Lu Cai4, Jun Xue5, Miao Jing6, Yixue Li2,7*, Xu Lin1*, Fudi Wang1*

Background Few studies assessed effects of individual and multiple ions simultaneously on metabolic outcomes, due to methodological limitation. Methodology/Principal Findings By combining advanced ionomics and mutual information, a quantifying measurement for mutual dependence between two random variables, we investigated associations of ion modules/networks with overweight/obesity, metabolic syndrome (MetS) and type 2 diabetes (T2DM) in 976 middle-aged Chinese men and women. Fasting plasma ions were measured by inductively coupled plasma mass spectroscopy. Significant ion modules were selected by mutual information to construct disease related ion networks. Plasma copper and phosphorus always ranked the first two among three specific ion networks associated with overweight/obesity, MetS and T2DM. Comparing the ranking of ion individually and in networks, three patterns were observed (1) “Individual ion,” such as potassium and chrome, which tends to work alone; (2) “Module ion,” such as iron in T2DM, which tends to act in modules/network; and (3) “Module-individual ion,” such as copper in overweight/obesity, which seems to work equivalently in either way. Conclusions In conclusion, by using the novel approach of the ionomics strategy and the information theory, we observed potential associations of ions individually or as modules/networks with metabolic disorders. Certainly, these findings need to be confirmed in future biological studies.