The Molecular Pathogenesis of Health Disparities in Inf*

描述(由申请人提供)：种族和民族差异 早产的发生率已经有了很好的记录，但相对的影响 遗传易感性，与环境和行为因素相比 是未知的。这项提议的目的是检验这样一种假设 差异基因表达导致感染相关基因差异 早产。第二个目标是创作两部大型和新奇的 研究早产的资源：(1)关键候选人数据库 基因，以及(2)人类基因表达组织库。我们建议 阐明早产的病理生理学需要有能力进行 家猪分娩所需的母胎相互作用分析 基因组规模。出于实践和伦理方面的原因，这种类型的初步研究 在人类身上的应用将受到严重限制。因此，在这个第一阶段， 项目中，我们将使用经过验证的、严格控制的小鼠模型 感染诱导早产产生全面的基因目录 随着时间的推移，在多个组织中表达。早产怀孕的小鼠将会 随机分成治疗组，模拟其中一种临床情况：A. 有分娩感染；B.无分娩感染；C.无感染分娩； 以及D.无感染/无分娩。然后从子宫肌层收集RNA， 每组的卵巢、蜕膜、胎盘和胎膜 时间序列，以及数千个基因的相对表达 在这些样本中使用DNA微阵列进行分析。一个相似性度量和一个 将使用聚类算法对单个基因按时间进行分类 表情模式。一种新的减法策略将使我们能够 区分感染诱导的特异活性转录本与那些 仅对感染或分娩很重要。将得出关于以下方面的推论 通过作图发现微阵列中非医学表达的基因的参与 进入已知的功能通路。此分析的最终结果将是 具有潜在关键作用的候选基因“候选名单” 感染引产。在项目的第二阶段，我们分析了人类 组织(子宫肌层、胎盘、绒毛、羊膜、蜕膜、羊膜细胞和血液) 收集自约1360名足月和早产患者 一项与种族匹配的横断面病例对照研究中的劳动。表达式 在这些组织中的分析将针对人类的同源物 在小鼠中识别的候选关键基因的丰富列表。 感染和非感染早产的差异基因表达及意义 早产胎膜，以及在不同种族之间，将是 特色化的。一种被称为支持向量机的计算工具将是 用于生成预测早产、服用 考虑到历史、临床和实验室变量。此工具将 确定最有可能构成糖尿病遗传基础的基因子集(S) 早产，并可能提供一种诊断分子图谱仪器 预测早产。这项研究中生成的大型数据库将 对任何对分娩感兴趣的研究人员都有价值，并将被 可在互联网上访问。

DESCRIPTION (provided by applicant): Racial and ethnic disparities in the incidence of preterm labor have been well documented, but the relative impact of genetic predisposition, as compared to environmental and behavioral factors is not known. The objective of this proposal is to test the hypothesis that differential gene expression contributes to disparity in infection-associated preterm labor. A second objective is the creation of two large and novel resources for studying preterm labor: (1) a database of candidate critical genes, and, (2) a human gene expression tissue bank. We suggest that elucidating the pathophysiology of preterm labor requires the power to perform analyses of the fetomaternal interactions required for parturition on a genomic scale. For practical and ethical reasons, a primary study of this type in humans would be severely limited. Therefore, in the first phase of this project, we will use a validated, tightly controlled murine model of infection-induced preterm labor to generate a comprehensive catalogue of gene expression over time in multiple tissues. Preterm pregnant mice will be randomized to treatment groups modeling one of clinical conditions: A. infection with labor; B. infection without labor; C. labor without infection; and D. no infection/no labor. RNA will then be collected from myometrium, ovaries, decidua, placentas and fetal membranes from each of the groups in a time series, and the relative expression of thousands of genes will be analyzed in these samples using DNA microarrays. A similarity metric and a clustering algorithm will be used to categorize individual genes by temporal expression patterns. A novel subtractive strategy will allow us to differentiate transcripts active specifically in infection-induced from those important for infection or labor alone. Inferences will be drawn regarding the involvement of genes not physic represented in the micro arrays by mapping into known functional pathways. The final result of this analysis will be a "short list" of candidate genes with potentially critical roles in infection-induced labor. In the second phase of the project, we analyze human tissues (myometrium, placenta, chorion, amnion, decidua, amniocytes and blood) collected from approximately 1360 patients presenting in term and preterm labor in a cross-sectional case-control study matching for race. Expression analysis in these tissues will be targeted to the human homologues of the enriched list of candidate critical genes identified in the mouse. Differential gene expression in pre term labor with or without infection and premature rupture membranes, as well as among different racial groups, will be characterized. A computational tool known as a support vector machine will be used to generate a rank order list predictive of preterm delivery, taking into account historical, clinical and laboratory variables. This tool will identify the subset(s) of genes most likely to form the genetic basis of preterm labor, and may provide a diagnostic molecular profiling instrument for predicting preterm delivery. The large databases generated in this study will be valuable to any researcher interested in parturition and will be made accessible on the Internet.