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分析前将比重归一化可提高人类尿液高分辨率质谱代谢组学图谱的信息回收率。

Normalization to specific gravity prior to analysis improves information recovery from high resolution mass spectrometry metabolomic profiles of human urine.

机构信息

Biomarkers Group, Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC) , 150 cours Albert Thomas, 69372 Lyon Cedex 08, France.

出版信息

Anal Chem. 2014 Nov 4;86(21):10925-31. doi: 10.1021/ac503190m. Epub 2014 Oct 17.

Abstract

Extraction of meaningful biological information from urinary metabolomic profiles obtained by liquid-chromatography coupled to mass spectrometry (MS) necessitates the control of unwanted sources of variability associated with large differences in urine sample concentrations. Different methods of normalization either before analysis (preacquisition normalization) through dilution of urine samples to the lowest specific gravity measured by refractometry, or after analysis (postacquisition normalization) to urine volume, specific gravity and median fold change are compared for their capacity to recover lead metabolites for a potential future use as dietary biomarkers. Twenty-four urine samples of 19 subjects from the European Prospective Investigation into Cancer and nutrition (EPIC) cohort were selected based on their high and low/nonconsumption of six polyphenol-rich foods as assessed with a 24 h dietary recall. MS features selected on the basis of minimum discriminant selection criteria were related to each dietary item by means of orthogonal partial least-squares discriminant analysis models. Normalization methods ranked in the following decreasing order when comparing the number of total discriminant MS features recovered to that obtained in the absence of normalization: preacquisition normalization to specific gravity (4.2-fold), postacquisition normalization to specific gravity (2.3-fold), postacquisition median fold change normalization (1.8-fold increase), postacquisition normalization to urinary volume (0.79-fold). A preventative preacquisition normalization based on urine specific gravity was found to be superior to all curative postacquisition normalization methods tested for discovery of MS features discriminant of dietary intake in these urinary metabolomic datasets.

摘要

从通过液相色谱-质谱联用 (MS) 获得的尿代谢组学谱中提取有意义的生物信息,需要控制与尿液样本浓度差异较大相关的不可变源。不同的归一化方法,无论是在分析之前(通过折射仪测量的最低比重对尿液样本进行预采集归一化)还是在分析之后(通过尿液体积、比重和中位数倍数变化进行后采集归一化),都被比较了它们恢复铅代谢物的能力,以便将来用作饮食生物标志物。根据欧洲癌症前瞻性调查和营养 (EPIC) 队列中 19 名受试者的 24 小时膳食回忆评估的高摄入和低/非摄入六种富含多酚的食物,选择了 24 个尿液样本。基于最小判别选择标准选择的 MS 特征通过正交偏最小二乘判别分析模型与每个饮食项目相关联。当比较恢复的总判别 MS 特征的数量与没有归一化时获得的数量时,归一化方法的排序如下:基于比重的预采集归一化(4.2 倍)、基于比重的后采集归一化(2.3 倍)、中位数倍数变化后采集归一化(1.8 倍增加)、基于尿液体积的后采集归一化(0.79 倍)。在这些尿液代谢组学数据集中,发现基于尿液比重的预防性预采集归一化优于所有测试的治疗性后采集归一化方法,用于发现饮食摄入的 MS 特征判别。

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