Biomarkers of Vascular Disease Progression in Type 1 Diabetes Mellitus

描述(由申请人提供)：美国国立卫生研究院已宣布恢复法资金可用于竞争性修订申请(非-OD-09-058)。我们母公司RO1的目标是建立一组内皮细胞功能障碍/炎症/纤溶的生物标志物，以识别1型糖尿病患者发生并发症的高风险。为了实现这一目标，我们测量了DCCT/EDIC队列样本中循环中细胞黏附分子(CAM)、IL6、肿瘤坏死因子、CRP、PAI-1和纤维蛋白原的水平，这些样本纵向收集了20多年。这项工作的局限性之一是缺乏一个控制组，使我们能够为这一人群建立正常值。我们最近了解到，在DCCT/EDIC研究的28个中心中招募了年龄和性别匹配的健康组，作为队列中进行的颈动脉超声研究的对照。我们从这些受试者(N=620)那里获得了血清/血浆样本，现在我们提议作为本次竞争性修订的目标1，检测这些样本中的VCAM-1、ICAM-1、E-选择素、PAI-1、纤维蛋白原、CRP、IL-6和可溶性肿瘤坏死因子受体。我们将比较在这组对照受试者和DCCT/EDIC队列中没有和有糖尿病并发症的匹配的1型糖尿病受试者中测量的生物标记物的浓度，这些受试者的父母RO1正在测量。这将使我们能够比较患有和不患有1型糖尿病的人群以及患有1型糖尿病和并发症的受试者亚组之间的生物标志物的分布。虽然了解这些重要生物分析物在糖尿病患者和对照组中的水平对于评估它们作为生物标记物的作用至关重要，但我们也想扩大我们之前的研究，包括最近发现的两个生物标记物，鞘氨醇-1-磷酸(S1P)和脂蛋白相关磷脂酶A2(LP-PLA2)，它们分别影响凝血/纤溶途径和黏附分子/炎症，并且独立于其他生物标记物的水平。因此，在目标2中，我们建议在DCCT/EDIC队列中登记的636名患者的亚组基线样本中确定S1P和LP-PLA2的循环水平，在这些患者中，不进行生物标记物的纵向测量，但将用于测试/验证在其余队列中开发的生物标记物风险算法的预测价值。我们将确定这些新发现的生物标志物中的任何一个的定量是否会增加在我们的父代RO1的目标1中开发的算法的预测能力，并更好地预测该队列中微血管和大血管并发症的发展。 公共卫生相关性：糖尿病与心脏病和截肢的发病率增加有关，也是导致失明和肾脏疾病的主要因素之一。糖尿病的这些并发症明显增加了医疗费用，并给患者及其家人带来了巨大的痛苦。我们不知道如何预测这些并发症的发展，以便在疾病进程中更早地进行干预，并防止其发展。这些研究将确定选定的生物标志物(与众所周知的糖尿病代谢异常相关的蛋白质)的血液水平是否可以预测哪些糖尿病患者将出现糖尿病并发症，从而确定哪些患者需要早期干预以防止并发症的发展。

DESCRIPTION (provided by applicant): The NIH has announced the availability of Recovery Act Funds for Competitive Revision Applications (NOT-OD-09-058). The goal of our parent RO1 is to establish a panel of biomarkers for endothelial cell dysfunction/ inflammation/ fibrinolysis that may identify patients with type 1 diabetes at high risk to develop complications. To accomplish this goal, we are measuring circulating levels of cell adhesion molecules (CAM), IL6, TNF, CRP, PAI-1, and fibrinogen in samples from the DCCT/EDIC cohort, collected longitudinally over 20 years. One of the limitations of this work is the lack of a control group that will allow us to establish the normal values for this population. We recently learned that a healthy age and gender matched group was recruited within the 28 centers of the DCCT/EDIC study to serve as a control for the carotid ultrasound studies performed in the cohort. We received serum/plasma samples from these subjects (N=620) and we now propose as Aim 1 of this Competitive Revision to measure VCAM-1, ICAM-1, E-selectin, PAI-1, fibrinogen, CRP, IL-6, and soluble tumor necrosis factor receptors in these samples. We will compare the concentrations of the biomarkers measured in this group of control subjects with those of a matched group of subjects with type 1 diabetes from the DCCT/EDIC cohort without and with diabetes complications that are being measured in the parent RO1. This will enable us to compare the distribution of biomarkers between a population with and without type 1 diabetes as well as with the subgroup of subjects with type 1 diabetes and complications. While knowledge of the levels of these important bioanalytes in both diabetic patients and controls is critical to evaluate their role as biomarkers, we would also like to expand our previous studies to include determination of two recently identified biomarkers, sphingosine-1-phospate (S1P) and lipoprotein-associated phospholipase A2 (Lp- PLA2) which are known to affect the clotting/fibrinolytic pathways and adhesion molecules/inflammation, respectively, and are independent of the level of other biomarkers. Therefore, in Aim 2, we propose to determine the circulating levels of S1P and Lp-PLA2 in the baseline samples of the subgroup of 636 patients enrolled in the DCCT/EDIC cohort in whom longitudinal measurements of biomarkers will not be performed but who will be used to test/validate the predictive value of the biomarkers risk algorithm developed in the remaining cohort. We will determine whether quantitation of either of these newly discovered biomarkers will increase the predictive power of the algorithm developed in Aim 1 of our parent RO1 and better predict the development of micro- and macrovascular complications in this cohort. PUBLIC HEALTH RELEVANCE: Diabetes is associated with an increased incidence of heart disease and limb amputation and it is also one of the major contributors to blindness and kidney disease. These complications of diabetes markedly increase the cost of health care and lead to enormous suffering both to the patients and their families. We do not know how to predict the development of these complications in order to intervene earlier in the course of the disease and prevent their development. These studies will determine if blood levels of selected biomarkers (proteins that are associated with well known metabolic abnormalities in diabetes) can predict which diabetic patients will develop diabetic complications and, thus, identify those patients who will require early intervention to prevent the development of complications.