Biomarkers in Diabetic Neuropathy

描述(由申请人提供)： 挑战领域：(03)生物标志物发现和验证 挑战主题：发现NIDDK感兴趣的疾病的疾病风险、进展或治疗反应的生物标记物。03-DK-101 糖尿病神经病变中的生物标志物 2000万美国人患有糖尿病，发病率每年以5%的速度增长。糖尿病最常见的并发症是糖尿病神经病变(DN)。目前用于确认糖尿病肾病并测量其进展的方法包括神经传导检查、定量感觉测量和降低的腓肠神经有髓纤维密度(MFD)。糖尿病肾病生物标志物的识别将大大增强我们对这一并发症的早期事件的了解，并可用于预测其发展和进展速度。目前还没有建立糖尿病肾病的生物标记物，使得这种并发症的发展没有得到控制。我们假设，2型糖尿病的代谢变化的复杂网络可能预测糖尿病肾病的发生和发展。应用于糖尿病肾病临床试验的代谢、神经解剖学和神经生理学数据的生物信息学方案表明，血脂异常，特别是甘油三酯水平升高，与糖尿病肾病的快速进展有关。目前的建议使用微阵列分析来检查人类腓肠神经样本和相关动物模型BKS-db/db小鼠的外周神经中涉及脂代谢的差异表达基因。我们在密歇根大学国家综合生物医学信息学中心(NCIBI)的成员资格为我们提供了高性能的计算环境和计算密集型分析的专业知识。我们有两个具体目标： 假设1：生物信息学的应用将确定参与糖尿病肾病发生和发展的靶点(基因、蛋白质和代谢标记物)。 具体目标1：确定在糖尿病肾病中跨物种调节的感兴趣基因。A.使用微阵列识别来自2型糖尿病和糖尿病肾病患者的人类腓肠神经样本中的生物标记物途径和靶点。B.在Aim 1a中对来自2型糖尿病小鼠的坐骨神经微阵列和人类腓肠神经微阵列进行跨物种验证。 假设2：经过验证的转录学将预测编码蛋白(在周围神经中)和代谢物(在血浆和尿液中)的变化，这些变化对人类患者和动物模型中糖尿病的发生和发展至关重要。这些功能反应将导致对人类糖尿病肾病的诊断和治疗有用的生物标志物的识别。 特定目标2：在2型糖尿病小鼠模型中验证已识别的基因靶点的生物学相关性 A.利用免疫定位和免疫印迹技术对坐骨神经中的靶基因产物(蛋白质)进行定位和定量 确定和检查生物体液(血浆和尿液)中的代谢物水平 公共卫生相关性：糖尿病最常见的并发症是周围神经病变(DN)。糖尿病肾病生物标志物的识别将大大增强我们对这一并发症的早期事件的了解，并可用于预测其发展和进展速度。我们假设糖尿病直接影响周围神经基因的表达，这些数据将有助于识别有用的糖尿病肾病生物标记物。微阵列分析将比较人类腓肠神经活检组织和BKS-db/db小鼠之间的基因表达变化，BKS-db/db小鼠是一种研究得很好的2型糖尿病模型。这些数据将用于识别失调的细胞内通路，这些通路将导致血清或尿液中可检测到的糖尿病肾病生物标志物，以及动物模型治疗后表达的变化。

DESCRIPTION (provided by applicant): Challenge Area: (03) Biomarker Discovery and Validation Challenge Topic: Discovery of biomarkers for disease risk, progression or response to therapy in diseases of interest to NIDDK. 03-DK-101 Title: Biomarkers in Diabetic Neuropathy Twenty million Americans have diabetes and the incidence is increasing by 5% per year. The most common complication of diabetes is diabetic neuropathy (DN). Current methods used to confirm DN and measure its progression include nerve conduction studies, quantitative sensory measures and decreased sural nerve myelinated fiber density (MFD). The identification of DN biomarkers would greatly enhance our understanding of early events in this complication and could be used to predict its development and rate of progression. No biomarkers have been established for DN leaving this complication to develop unchecked. We hypothesize that a complex network of metabolic changes in type 2 diabetes may predict the onset and progression of DN. Bioinformatics protocols applied to metabolic, neuroanatomical and neurophysiology data from a clinical trial of DN indicate that dyslipidemia, specifically elevated triglyceride levels, is associated with rapid progression of DN. The current proposal employs microarray analyses to examine differentially expressed genes involved in lipid metabolism in both human sural nerve samples and in peripheral nerves from a relevant animal model, the BKS-db/db mouse. Our membership in the National Center for Integrated Biomedical Informatics (NCIBI) at the University of Michigan provides us with a high-powered computing environment and the expertise for computationally intensive analyses. We have two Specific Aims: Hypothesis 1: The application of bioinformatics will identify targets (genes, proteins and metabolic markers) involved in the initiation and progression of DN. Specific Aim 1: Identify genes of interest regulated across species in DN. a. Use microarrays to identify biomarker pathways and targets in human sural nerve samples from patients with type 2 diabetes and DN. b. Perform cross-species validation between sciatic nerve microarrays from mice with type 2 diabetes and the human sural nerve microarrays in Aim 1a. Hypothesis 2: Verified transcriptomics will predict changes in encoded proteins (in peripheral nerve) and metabolites (in plasma and urine) critical to the initiation and progression of DN in human patients and animal models. These functional responses will lead to the identification of biomarkers useful in the diagnosis and therapeutic management of human DN. Specific Aim 2: Validate the biological relevance of identified gene targets in a type 2 murine model with DN a. Localize and quantify target gene products (proteins) in sciatic nerve using immunolocalization and western blotting b. Identify and examine metabolite levels in biological fluids (plasma and urine) PUBLIC HEALTH RELEVANCE: The most common complication of diabetes is peripheral neuropathy (DN). The identification of DN biomarkers would greatly enhance our understanding of early events in this complication and could be used to predict its development and rate of progression. We hypothesize that diabetes directly affects peripheral nerve gene expression and that these data will aid in the identification of useful DN biomarkers. Microarray analyses will compare changes in gene expression between human sural nerve biopsies and BKS-db/db mice, a well-researched model of type 2 diabetes. These data will be used to identify dysregulated intracellular pathways that would result in detectable biomarkers of DN in serum or urine and changes in expression following treatment in animal models.