Lokhov Petr G, Balashova Elena E, Voskresenskaya Anna A, Trifonova Oxana P, Maslov Dmitry L, Archakov Alexander I
Institute of Biomedical Chemistry, Moscow 119121, Russia.
Biomed Rep. 2016 Jan;4(1):122-126. doi: 10.3892/br.2015.548. Epub 2015 Nov 24.
In metabolomics, a large number of small molecules can be detected in a single run. However, metabolomic data do not include the absolute concentrations of each metabolite. Generally, mass spectrometry analyses provide metabolite concentrations that are derived from mass peak intensities, and the peak intensities are strictly dependent on the type of mass spectrometer used, as well as the technical characteristics, options and protocols applied. To convert mass peak intensities to actual concentrations, calibration curves have to be generated for each metabolite, and this represents a significant challenge depending on the number of metabolites that are detected and involved in metabolome-based diagnostics. To overcome this limitation, and to facilitate the development of diagnostic tests based on metabolomics, mass peak intensities may be expressed in quintiles. The present study demonstrates the advantage of this approach. The examples of diagnostic signatures, which were designed in accordance to this approach, are provided for lung and prostate cancer (leading causes of mortality due to cancer in developed countries) and impaired glucose tolerance (which precedes type 2 diabetes, the most common endocrinology disease worldwide).
在代谢组学中，一次分析就能检测出大量小分子。然而，代谢组学数据并不包含每种代谢物的绝对浓度。一般来说，质谱分析提供的代谢物浓度是根据质谱峰强度得出的，而峰强度严格取决于所用质谱仪的类型以及所应用的技术特性、选项和方案。为了将质谱峰强度转换为实际浓度，必须为每种代谢物生成校准曲线，而这对于基于代谢组学诊断中所检测和涉及的代谢物数量而言是一项重大挑战。为克服这一限制，并促进基于代谢组学的诊断测试的开发，质谱峰强度可用五分位数表示。本研究证明了这种方法的优势。文中给出了按照这种方法设计的诊断特征示例，涉及肺癌和前列腺癌（发达国家癌症致死的主要原因）以及糖耐量受损（2型糖尿病之前的阶段，2型糖尿病是全球最常见的内分泌疾病）。
