血浆氨基酸代谢谱与糖尿病相关性研究

Classification of Diabetes Volunteers Based on Plasma Amino Acids Metabolic Profiling

为了利用代谢组学手段研究血浆氨基酸代谢谱与糖尿病相关性,采用邻苯二甲醛(OPA)柱前在线衍生反相高效液相色谱法,建立了血浆中21种氨基酸代谢谱的相对定量分析方法。衍生由自动进样器在线自动完成,紫外检测器检测,流动相A为10mmol/LNa2HPO4-Na2B4O7缓冲液(pH7.95),B为乙腈-甲醇-水(45∶45∶10,V/V),线性梯度洗脱,流动相B在30min内由5%增加至46%,27min内21种氨基酸全部得到良好分离。用此方法测定了51位临床糖尿病人血浆氨基酸代谢谱。以相对峰面积作为原始数据,按血糖值高低预分组,通过Spss和Matlab软件平台,用线性判别分析、逐步判别分析和得分图进行关联研究,结果表明:血浆中氨基酸代谢谱与血糖值的高低存在相关性,对血糖值低于6.2的志愿者和血糖值高于9.5的志愿者,判别分析的总正判率达到了94.1%。逐步判别分析结果表明,有7种氨基酸(Arg,Cit,Asp,Asn,Thr,Leu,Trp)承载了上述分组的重要信息。其对上述分组的判别分析总正判率为90.2%,可作为反映血糖值高低变化的标志物组,对于糖尿病的早期诊断及深入研究具有潜在的科研及临床价值。

To study the relation of plasma amino acids metabolic profiling and diabetes blood sugar level by using metabolomics, an on-line pre-column o-phthalic dicarboxaldehyde （OPA） derivatization HPLC method for the relative quantitative determination of 21 amino acids in plasma samples was developed. The derivatization procedure was accomplished by an online auto-injector and the signals were detected with a UV detector. Mobile phase A was 10 mmol/L Na2HPO4-Na2B4O7 buffer at pH 7.95, and B was acetonitrile-methanol-water （45∶45∶10 by volume）. The elution program was 5% B at the start and 46% B at the end in 30 min. The 21 amino acids were satisfactorily separated in 27 min. Fifty-one plasma samples from diabetes volunteers were analyzed and were pre-divided into blood sugar （B.S.）6.2 group and B.S9.5 group. By SPSS and Matlab software platform, relation analysis was performed by using linear discriminant analysis, stepwise discriminant analysis, and scores plot models. By correlating the levels of blood sugar（B.S.） to 20 amino acids peak areas except glutamine, the results showed that the B.S.6.2 group was discriminated from the B.S9.5 group with a total hit ratio of 94.1%, stepwise discriminant analysis （SDA） model indicated that 7 out of 20 amino acids,i.e., Arg, Cit, Leu, Asp, Asn, Thr and Trp essentially contributed to the above two groups division with the total hit ratio of 90.2%, which maybe have more means as potential marker groups for the early diagnosis of diabetes and in-depth research.