Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin 150086, PR China.
J Chromatogr B Analyt Technol Biomed Life Sci. 2010 Oct 15;878(28):2817-25. doi: 10.1016/j.jchromb.2010.08.035. Epub 2010 Sep 16.
Isolated post-challenge diabetes (IPD, 2h-PG ≥11.1mmol/L and FPG <7.0mmol/L) is often ignored in screening for diabetes by fasting plasma glucose (FPG) levels. The aim of this study was to investigate the metabolic profiles of serum free fatty acids (FFAs) and to identify biomarkers that can be used to distinguish patients with IPD from those with type 2 diabetes mellitus (T2DM) or healthy control individuals. FFA profiles of the subjects were investigated using gas chromatography-mass spectrometry (GC-MS). Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used for classification and prediction among the three groups. The predictive correct rates were 92.86% for IPD and healthy control individuals and 90.70% for T2DM and healthy control individuals, indicating that PLS-DA could satisfactorily distinguish IPD individuals from healthy controls and those with T2DM. Finally, palmitic acid, stearic acid, oleic acid, linoleic acid and α-linolenic acid were identified as potential biomarkers for distinguishing IPD from healthy control and T2DM individuals. These potential biomarkers might be helpful for diagnosis and characterization of diabetes.
空腹血糖(FPG)水平筛查糖尿病时,常忽略餐后挑战后糖尿病(IPD,2h-PG≥11.1mmol/L 且 FPG<7.0mmol/L)。本研究旨在研究血清游离脂肪酸(FFA)的代谢谱,并确定可用于区分 IPD 患者与 2 型糖尿病(T2DM)患者或健康对照个体的生物标志物。采用气相色谱-质谱联用技术(GC-MS)检测受试者的 FFA 谱。采用主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)进行三组间的分类和预测。IPD 与健康对照组的预测正确率为 92.86%,T2DM 与健康对照组的预测正确率为 90.70%,表明 PLS-DA 可满意地区分 IPD 患者与健康对照者和 T2DM 患者。最后,鉴定出棕榈酸、硬脂酸、油酸、亚油酸和α-亚麻酸为区分 IPD 与健康对照和 T2DM 个体的潜在生物标志物。这些潜在的生物标志物可能有助于糖尿病的诊断和特征描述。