Yang Jun, Xu Guowang, Hong Qunfa, Liebich Hartmut M, Lutz Katja, Schmülling R-M, Wahl Hans Günther
National Chromatographic R. and A. Center, Dalian Institute of Chemical Physics, Chinese Academy of Science, 116011 Dalian, P.R. China.
J Chromatogr B Analyt Technol Biomed Life Sci. 2004 Dec 25;813(1-2):53-8. doi: 10.1016/j.jchromb.2004.09.023.
Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields, including work in cardiovascular research and drug toxicology. In this study, metabonomics method was employed to the diagnosis of Type 2 diabetes mellitus (DM2) based on serum lipid metabolites. The results suggested that serum fatty acid profiles determined by capillary gas chromatography combined with pattern recognition analysis of the data might provide an effective approach to the discrimination of Type 2 diabetic patients from healthy controls. And the applications of pattern recognition methods have improved the sensitivity and specificity greatly.
代谢组学是对代谢物及其在各种疾病状态中的作用进行的研究,是后基因组时代出现的一种新方法。该方法已应用于许多领域,包括心血管研究和药物毒理学研究。在本研究中,采用代谢组学方法基于血清脂质代谢物对2型糖尿病(DM2)进行诊断。结果表明,通过毛细管气相色谱法测定血清脂肪酸谱并结合数据的模式识别分析,可能为区分2型糖尿病患者和健康对照提供一种有效方法。而且模式识别方法的应用极大地提高了敏感性和特异性。