Large-scale non-targeted metabolomic profiling in three human population-based studies
Large-scale non-targeted metabolomic profiling in three human population-based studies
复制标题
DOI：
10.1007/s11306-015-0893-5
复制
发表时间：
2016-01-01
期刊：
影响因子：
3.6
通讯作者：
Ingelsson, Erik
中科院分区：
文献类型：
--
作者：
Ganna, Andrea;Fall, Tove;Ingelsson, Erik
非靶向代谢组学分析用于同时评估生物样品中的大部分代谢组。在这里，我们描述了分析和计算方法，用于分析一个大型的UPLC-Q-TOF MS为基础的代谢组学分析工作，使用血浆和血清样本的参与者在三个瑞典的人口为基础的研究，中年和老年人受试者：TwinGene，ULSAM和PIVUS。目前，超过200种代谢物已在超过3600名参与者中使用内部标准品库和色谱可用的光谱数据库进行手动注释。代谢物知识库提供的数据包括个人未经处理的原始数据、经处理的数据、基本人口统计学变量和注释代谢物的光谱。其他表型和遗传数据可应要求提供给队列指导委员会。这些研究代表了探索和评估个体间代谢变异性如何影响人类疾病的独特资源。
Non-targeted metabolomic profiling is used to simultaneously assess a large part of the metabolome in a biological sample. Here, we describe both the analytical and computational methods used to analyze a large UPLC-Q-TOF MS-based metabolomic profiling effort using plasma and serum samples from participants in three Swedish population-based studies of middle-aged and older human subjects: TwinGene, ULSAM and PIVUS. At present, more than 200 metabolites have been manually annotated in more than 3600 participants using an in-house library of standards and publically available spectral databases. Data available at the metabolights repository include individual raw unprocessed data, processed data, basic demographic variables and spectra of annotated metabolites. Additional phenotypical and genetic data is available upon request to cohort steering committees. These studies represent a unique resource to explore and evaluate how metabolic variability across individuals affects human diseases.