EARLY DETECTION OF DISEASE ONSET USING NEW METABOLOME PHASE PORTRAITS

使用新的代谢组相图早期检测疾病发作

• 批准号: 8168980
• 负责人: FARIBA M ASSADI-PORTER
• 金额: $ 3.84万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-03-01 至 2011-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8168980
• 关键词: Acute; Adult; Androgens; Animal Model; Biochemical; Biochemical Pathway; Biological Markers; Biology; Cardiovascular Diseases; Chronic; Classification; Clinical; Clinical Research; Complement; Complex; Computer Retrieval of Information on Scientific Projects Database; Data; Detection; Development; Diagnosis; Diagnostic; Diet; Disease; Disease Progression; Early Diagnosis; Endometrial Carcinoma; Engineering; Etiology; Exclusion; Female; Funding; Genes; Grant; Health; Hospitals; Hyperlipidemia; Inflammation; Inflammatory Response; Institution; Intervention; Knowledge; Life; Macaca mulatta; Mass Spectrum Analysis; Menstrual cycle; Metabolic; Metabolic Pathway; Methodology; Modeling; Monkeys; Non-Insulin-Dependent Diabetes Mellitus; Nuclear Magnetic Resonance; Obesity; Onset of illness; Patients; Pattern; Phase; Phenotype; Polycystic Ovary Syndrome; Portraits; Prevention approach; Preventive; Regimen; Research; Research Personnel; Resources; Sleep Apnea Syndromes; Source; Staging; Syndrome; Therapeutic; Ultrasonography; United States National Institutes of Health; Woman; aged; base; design; early onset; fetal programming; human disease; improved; innovation; multidisciplinary; outcome forecast; pathogen; prevent; reproductive; success

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We propose to apply a multidisciplinary team approach to develop an innovative platform (metabolome phase portrait) to detect early onset of complex disease that capitalizes on our earlier success identifying biomarkers of acute inflammatory response. We plan to systematically enhance our current metabolic analysis methodology to rapidly identify early and reliable biomarkers of diseases with seemingly unrelated complex phenotypes using polycystic ovary syndrome (PCOS) as our case model. Our ability to overcome human disease is conventionally based on understanding causation. Such enlightenment usually generates therapeutic designs and diagnostic approaches for prevention, treatment, or elimination of the health disorder. Complex diseases (e.g. PCOS), however, do not follow such first order causes and effect. They are not limited to specific genes, pathogens, toxicoses, or identifiable environmental influences (e.g., diet). Biomarker patterns after disease onset may not be the same as biomarkers at early stages. PCOS is the most prevalent endocrinopathy in reproductive aged women and presents a complex and difficult to diagnose phenotype. PCOS diagnosis includes intermittent or absent menstrual cycles, clinical and/or biochemical signs of androgen excess, and ultrasound imaging of polycystic ovaries. PCOS is also a diagnosis of exclusion, since clinicians must demonstrate a lack of disorders that mimics PCOS. The syndrome's major health complications arise outside its diagnostic criteria and include obesity, type 2 diabetes, hyperlipidemia, cardiovascular disease, endometrial cancer, sleep apnea, and chronic inflammation. Early diagnosis and intervention is thus crucial to prevent the life-threatening consequences of PCOS. Identification, modeling, and detection of metabolite changes that are reliable early indicators of PCOS will significantly improve both the diagnosis of and prognosis for women afflicted with the syndrome. We propose to utilize the prenatally androgenized (PA) female rhesus monkey model for PCOS, developed by Dr. Abbott in our group. The animal model indicates fetal programming as the common etiology for the adult phenotype. It provides our team with a unique ability to manipulate and track the development of PCOS. Combined with an ongoing clinical study at UW Hospital that is geared toward determining energetic mechanisms underlying obesity in PCOS patients, we will develop a metabolome phase portrait of PCOS patients and PA monkeys that will elucidate the dynamics of biomarker patterns. Knowledge of dynamics is required for reverse-engineering the biomarker patterns in early disease states. Our metabolome phase portrait is a model of the metabolic dynamics (WARF REF; P93081, P05416, P05420), constructed from experimental metabolic pathway data obtained from comprehensive and unbiased nuclear magnetic resonance (NMR) and mass-spectrometry (MS) analyses complemented by knowledge of existing and putative biochemical pathways. This model will facilitate accurate sub-classification of a complex disease such as PCOS, staging of the disease progression, and elucidation of preventive regimens. In contrast to statistical approaches for clustering patterns of data, our ability to construct a mtabolome phase portrait of PCOS provides the needed understanding of the underlying biology with a means to modulate it for therapeutic purposes.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 我们建议采用多学科团队的方法来开发创新的平台（代谢型相肖像），以检测早期的复杂疾病发作，该疾病利用了我们早期的成功识别急性炎症反应的生物标志物。我们计划系统地增强我们当前的代谢分析方法，以快速识别出使用多囊卵巢综合征（PCOS）看似无关的复杂表型的疾病的早期和可靠的生物标志物，作为我们的病例模型。 我们克服人类疾病的能力通常基于理解因果关系。这种启蒙通常会生成用于预防，治疗或消除健康障碍的治疗设计和诊断方法。但是，复杂的疾病（例如PCOS）不遵循这种一阶原因和作用。它们不仅限于特定基因，病原体，有毒性或可识别的环境影响（例如饮食）。疾病发作后的生物标志物模式可能与早期阶段的生物标志物不同。 PCOS是生殖老年妇女中最普遍的内分泌病，并且表现出复杂且难以诊断的表型。 PCOS诊断包括间歇性或不存在月经周期，雄激素过量的临床和/或生化迹象，以及多囊卵巢的超声成像。 PCOS也是排除的诊断，因为临床医生必须证明缺乏模仿PCOS的疾病。该综合征的主要健康并发症出现在其诊断标准之外，包括肥胖症，2型糖尿病，高脂血症，心血管疾病，子宫内膜癌，睡眠呼吸暂停和慢性炎症。因此，早期诊断和干预对于防止PCOS的威胁生命后果至关重要。可靠的PCOS早期指标的代谢物变化的鉴定，建模和检测将显着改善患有综合征的女性的诊断和预后。 我们建议利用由Abbott博士在我们小组中开发的PCOS的产前雄激素化（PA）女性恒河猴模型。动物模型表示胎儿编程是成人表型的常见病因。它为我们的团队提供了操纵和跟踪PCOS开发的独特能力。结合UW医院正在进行的临床研究，该研究旨在确定PCOS患者肥胖症的能量机制，我们将开发PCOS患者和PA猴子的代谢组相肖像，以阐明生物标志物模式的动力学。在早期疾病状态下对生物标志物模式进行反向工程需要动态知识。我们的代谢阶段肖像是代谢动力学的模型（WARF REF; P93081，P05416，P05420），该模型是由实验性代谢途径数据构建的，这些数据是从综合且无偏置的核磁共振（NMR）和质谱（MS）的全面且无偏置的核磁共振（MS）中构建的，该数据通过对现有和假定的BioChem的知识进行了补充。该模型将促进复杂疾病（例如PCOS）的准确亚分类，疾病进展的分期以及预防方案的阐明。与数据聚类模式的统计方法相反，我们构建PCOS的MTABOLOME相肖像的能力提供了对基础生物学的所需理解，并以一种用于治疗目的调节它的方法。