A practical approach to detect unique metabolic patterns for personalized medicine

被引:80
作者
Johnson, Jennifer M. [1 ,2 ,3 ]
Yu, Tianwei [4 ]
Strobel, Frederick H. [5 ]
Jones, Dean P. [1 ,3 ]
机构
[1] Emory Univ, Dept Med, Div Pulm Allergy & Crit Care, Atlanta, GA 30322 USA
[2] Emory Univ, Nutr & Hlth Sci Grad Program, Atlanta, GA 30322 USA
[3] Emory Univ, Clin Biomarkers Lab, Atlanta, GA 30322 USA
[4] Emory Univ, Dept Biostat & Bioinformat, Atlanta, GA 30322 USA
[5] Emory Univ, Mass Spectrometry Ctr, Atlanta, GA 30322 USA
关键词
MASS-SPECTROMETRY; LIQUID-CHROMATOGRAPHY; INBORN-ERRORS; HUMAN PLASMA; HUMAN URINE; DISEASE; IDENTIFICATION; STANDARDIZATION; OPPORTUNITIES; METABONOMICS;
D O I
10.1039/c0an00333f
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Information-rich technologies have advanced personalized medicine, yet obstacles limit measurement of large numbers of chemicals in human samples. Current laboratory tests measure hundreds of chemicals based upon existing knowledge of exposures, metabolism and disease mechanisms. Practical issues of cost and throughput preclude measurement of thousands of chemicals. Additionally, individuals are genetically diverse and have different exposures and response characteristics; some have disease mechanisms that have not yet been elucidated. Consequently, methods are needed to detect unique metabolic characteristics without presumption of known pathways, exposures or disease mechanisms, i.e., using a top-down approach. In this report, we describe profiling of human plasma with liquid chromatography (LC) coupled to Fourier-transform mass spectrometry (FTMS). FTMS is a high-resolution mass spectrometer providing mass accuracy and resolution to discriminate thousands of m/z features, which are peaks defined by m/z, retention time and intensity. We demonstrate that LC-FTMS detects 2000 m/z features in 10 min. These features include known and unidentified chemicals with m/z between 85 and 850, most with <10% coefficient of variation. Comparison of metabolic profiles for 4 healthy individuals showed that 62% of the m/z features were common while 10% were unique and 770 discriminated the individuals. Because the simple one-step extraction and automated analysis is rapid and cost-effective, the approach is practical for personalized medicine. This provides a basis to rapidly characterize novel metabolic patterns which can be linked to genetics, environment and/or lifestyle.
引用
收藏
页码:2864 / 2870
页数:7
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