Laboratory issues: Use of nutritional biomarkers
Laboratory issues: Use of nutritional biomarkers
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DOI：
10.1093/jn/133.3.888s
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发表时间：
2003-03-01
影响因子：
4.2
通讯作者：
Miller, DT
中科院分区：
文献类型：
--
作者：
Blanck, HM;Bowman, BA;Miller, DT
营养状况的生物标志物提供了膳食摄入量的替代措施。就像与饮食摄入测量相关的误差和变化一样，在使用生物标志物时，需要考虑生物（分析前）和实验室（分析）变异性的大小和影响。在选择生物标志物时，重要的是要了解它与营养摄入的关系，以及它所反映的特定暴露时间框架，以及它如何受到抽样和实验室程序的影响。个体的遗传和疾病状态引起的生物变异来源会影响生物标志物，但它们也会受到标本收集和储存、季节性、一天中的时间、污染、稳定性和实验室质量保证等引起的非生物变异来源的影响。在选择进行生物标志物评估的实验室时，研究人员应尝试通过纳入某些技术，如实验室工作人员对疾病状况的盲法，以及包括实验室工作人员对盲法的外部联合标准，确保将随机和系统误差降至最低。此外，分析质量控制应通过在整个可能值范围内使用内部标准或认证材料来确保控制方法的准确性。必须考虑随机实验室误差对测量精度的影响，并了解该方法的检测限和实验室切点。在经常出现弱关联的营养流行病学中，选择适当的切入点和减少误差是极其重要的。作为这篇综述的一部分，血脂被作为一个生物标志物的例子，通过合作的努力，已经提出了了解变异的生物来源和标准化实验室结果。
Biomarkers of nutritional status provide alternative measures of dietary intake. Like the error and variation associated with dietary intake measures, the magnitude and impact of both biological (preanalytical) and laboratory (analytical) variability need to be considered when one is using biomarkers. When choosing a biomarker, it is important to understand how it relates to nutritional intake and the specific time frame of exposure it reflects as well as how it is affected by sampling and laboratory procedures. Biological sources of variation that arise from genetic and disease states of an individual affect biomarkers, but they are also affected by nonbiological sources of variation arising from specimen collection and storage, seasonality, time of day, contamination, stability and laboratory quality assurance. When choosing a laboratory for biomarker assessment, researchers should try to make sure random and systematic error is minimized by inclusion of certain techniques such as blinding of laboratory staff to disease status and including external pooled standards to which laboratory staff are blinded. In addition analytic quality control should be ensured by use of internal standards or certified materials over the entire range of possible values to control method accuracy. One must consider the effect of random laboratory error on measurement precision and also understand the method's limit of detection and the laboratory cutpoints. Choosing appropriate cutpoints and reducing error is extremely important in nutritional epidemiology where weak associations are frequent. As part of this review, serum lipids are included as an example of a biomarker whereby collaborative efforts have been put forth to both understand biological sources of variation and standardize laboratory results.