Biomarkers in Diabetic Neuropathy

糖尿病神经病变的生物标志物

• 批准号: 7812489
• 负责人: Eva Lucille Feldman
• 金额: $ 25.56万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7812489
• 关键词: Affect; American; Animal Model; Area; Behavior; Biochemical Pathway; Bioinformatics; Biological; Biological Markers; Biomedical Research; Biopsy; Clinical Treatment; Clinical Trials; Complex; Complication; Complications of Diabetes Mellitus; Data; Data Set; Development; Diabetes Mellitus; Diabetic Neuropathies; Diagnosis; Disease; Disease model; Dyslipidemias; Environment; Event; Fiber; Figs - dietary; Gene Expression; Gene Expression Profiling; Gene Proteins; Gene Targeting; Generations; Genes; Goals; Human; Hypertriglyceridemia; Incidence; Lead; Left; Lipids; Liquid substance; Measurable; Measures; Metabolic; Metabolic Marker; Methods; Michigan; Modeling; Mus; National Institute of Diabetes and Digestive and Kidney Diseases; Neural Conduction; Non-Insulin-Dependent Diabetes Mellitus; Onset of illness; Pathway interactions; Patients; Pattern; Peripheral Nerves; Peripheral Nervous System Diseases; Plasma; Process; Proteins; Protocols documentation; Public Health; Regulation; Research; Sampling; Sensory; Serum; Systems Biology; Therapeutic; Tissues; United States National Institutes of Health; Universities; Urine; Validation; Western Blotting; biological systems; biomedical informatics; cell growth regulation; clinically relevant; db/db mouse; density; disorder risk; in vivo Model; interest; lipid metabolism; macromolecule; neurophysiology; novel; protein metabolite; public health relevance; response; sciatic nerve; single molecule; sural nerve; transcriptomics; Affect; American; Animal Model; Area; Behavior; Biochemical Pathway; Bioinformatics; Biological; Biological Markers; Biomedical Research; Biopsy; Clinical Treatment; Clinical Trials; Complex; Complication; Complications of Diabetes Mellitus; Data; Data Set; Development; Diabetes Mellitus; Diabetic Neuropathies; Diagnosis; Disease; Disease model; Dyslipidemias; Environment; Event; Fiber; Figs - dietary; Gene Expression; Gene Expression Profiling; Gene Proteins; Gene Targeting; Generations; Genes; Goals; Human; Hypertriglyceridemia; Incidence; Lead; Left; Lipids; Liquid substance; Measurable; Measures; Metabolic; Metabolic Marker; Methods; Michigan; Modeling; Mus; National Institute of Diabetes and Digestive and Kidney Diseases; Neural Conduction; Non-Insulin-Dependent Diabetes Mellitus; Onset of illness; Pathway interactions; Patients; Pattern; Peripheral Nerves; Peripheral Nervous System Diseases; Plasma; Process; Proteins; Protocols documentation; Public Health; Regulation; Research; Sampling; Sensory; Serum; Systems Biology; Therapeutic; Tissues; United States National Institutes of Health; Universities; Urine; Validation; Western Blotting; biological systems; biomedical informatics; cell growth regulation; clinically relevant; db/db mouse; density; disorder risk; in vivo Model; interest; lipid metabolism; macromolecule; neurophysiology; novel; protein metabolite; public health relevance; response; sciatic nerve; single molecule; sural nerve; transcriptomics

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.

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感兴趣疾病的疾病风险，进展或对治疗的反应的生物标志物。 03-DK-101 标题：糖尿病神经病中的生物标志物 两千万美国人患有糖尿病，发病率每年增加5％。糖尿病最常见的并发症是糖尿病神经病（DN）。用于确认DN和测量其进展的当前方法包括神经传导研究，定量感觉测量和降低的Sural神经髓纹纤维密度（MFD）。 DN生物标志物的识别将大大增强我们对这种并发症早期事件的理解，并可用于预测其发展和进展速度。尚未确定生物标志物用于DN，这使这种并发症不受组织。我们假设2型糖尿病中代谢变化的复杂网络可能可以预测DN的发作和进展。来自DN的临床试验的代谢，神经解剖学和神经生理学数据应用的生物信息学方案表明，血脂异常，特异性升高的甘油三酸酯水平与DN的快速进展有关。当前的提案采用微阵列分析来检查人类手术神经样品中涉及脂质代谢的差异表达基因以及相关动物模型的外周神经，即BKS-DB/DB小鼠。我们在密歇根大学国家综合生物医学信息学（NCIBI）的会员资格为我们提供了高功率的计算环境和计算密集型分析的专业知识。我们有两个具体的目标： 假设1：生物信息学的应用将识别涉及DN启动和进展的靶标（基因，蛋白质和代谢标记）。 特定目的1：确定跨DN物种的感兴趣基因。一个。使用微阵列鉴定来自2型糖尿病和DN患者的人类Sural神经样本中的生物标志物途径和靶标。 b。在AIM 1A中的2型糖尿病小鼠的坐骨神经微阵列和人类的Sural神经微阵列之间进行跨物种验证。 假设2：经过验证的转录组学将预测编码的蛋白质（外周神经）和代谢物（在血浆和尿液中）对人类患者和动物模型中DN的起始和进展至关重要。这些功能反应将导致对生物标志物的鉴定，可用于人类DN的诊断和治疗管理。 特定目标2：验证具有DN的2型鼠模型中鉴定基因靶标的生物学相关性 一个。使用免疫定位和蛋白质印迹将靶基因产物（蛋白质）定位和量化靶基因产物（蛋白质） b。识别和检查生物液（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（DN）。 DN生物标志物的识别将大大增强我们对这种并发症早期事件的理解，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，这些数据将有助于鉴定有用的DN生物标志物。微阵列分析将比较人类Sural神经活检与BKS-DB/DB小鼠之间基因表达的变化，BKS-DB/DB小鼠是2型糖尿病的经过精心研究的模型。这些数据将用于鉴定失调的细胞内途径，这将导致血清或尿液中DN的可检测到的生物标志物以及动物模型治疗后表达的变化。