Biomarkers in Fasting Serum to Estimate Glucose Tolerance, Insulin Sensitivity, and Insulin Secretion
Biomarkers in Fasting Serum to Estimate Glucose Tolerance, Insulin Sensitivity, and Insulin Secretion
复制标题
DOI：
10.1373/clinchem.2010.156133
复制
发表时间：
2011-02-01
影响因子：
9.3
通讯作者：
Patti, Mary Elizabeth
中科院分区：
文献类型：
--
作者：
Goldfine, Allison B.;Gerwien, Robert W.;Patti, Mary Elizabeth
背景：评估糖耐量降低、胰岛素敏感性或胰岛素分泌受损的生物标志物将在临床上有用，因为这些生理指标在2型糖尿病的发病机制中是重要的。方法：我们进行了一项横断面研究，94名受试者接受了口服葡萄糖耐量试验，其中84人有1个或更多的糖尿病危险因素，10人没有已知的危险因素。我们在250亩L的空腹血清样本中检测了34个与糖尿病风险相关的蛋白质生物标志物。我们应用多元回归选择技术来确定信息量最大的生物标志物，并开发多变量模型来估计葡萄糖耐量、胰岛素敏感性和胰岛素分泌。通过ROC曲线下面积(AUC)分析评估糖耐量模型区分糖尿病个体和糖耐量受损或正常个体的能力。结果：在高危参与者中，25名(30%)被发现存在糖耐量受损，11名(13%)被发现患有糖尿病。利用分子计数技术，我们在小体积样本中高精度地评估了多个生物标志物。从空腹样本得到的多变量生物标志物模型与2小时后糖耐量(R-2=0.45，P<；0.0001)、综合胰岛素敏感指数(R-2=0.91，P<；0.0001)和胰岛素分泌(R-2=0.45，P<；0.0001)有很强的相关性。此外，糖耐量模型提供了糖尿病与糖耐量受损或正常糖耐量(AUC 0.89)以及糖尿病与糖耐量受损与正常耐量(AUC 0.78)之间的强烈区分。结论：空腹血样中的生物标志物可能有助于评估糖耐量、胰岛素敏感性和胰岛素分泌。(C)2010年美国临床化学协会
BACKGROUND: Biomarkers for estimating reduced glucose tolerance, insulin sensitivity, or impaired insulin secretion would be clinically useful, since these physiologic measures are important in the pathogenesis of type 2 diabetes mellitus.METHODS: We conducted a cross-sectional study in which 94 individuals, of whom 84 had 1 or more risk factors and 10 had no known risk factors for diabetes, underwent oral glucose tolerance testing. We measured 34 protein biomarkers associated with diabetes risk in 250-mu L fasting serum samples. We applied multiple regression selection techniques to identify the most informative biomarkers and develop multivariate models to estimate glucose tolerance, insulin sensitivity, and insulin secretion. The ability of the glucose tolerance model to discriminate between diabetic individuals and those with impaired or normal glucose tolerance was evaluated by area under the ROC curve (AUC) analysis.RESULTS: Of the at-risk participants, 25 (30%) were found to have impaired glucose tolerance, and 11 (13%) diabetes. Using molecular counting technology, we assessed multiple biomarkers with high accuracy in small volume samples. Multivariate biomarker models derived from fasting samples correlated strongly with 2-h postload glucose tolerance (R-2 = 0.45, P < 0.0001), composite insulin sensitivity index (R-2 = 0.91, P < 0.0001), and insulin secretion (R-2 = 0.45, P < 0.0001). Additionally, the glucose tolerance model provided strong discrimination between diabetes vs impaired or normal glucose tolerance (AUC 0.89) and between diabetes and impaired glucose tolerance vs normal tolerance (AUC 0.78).CONCLUSIONS: Biomarkers in fasting blood samples may be useful in estimating glucose tolerance, insulin sensitivity, and insulin secretion. (C) 2010 American Association for Clinical Chemistry