The Molecular Pathogenesis of Health Disparities in Inf*

描述（由申请人提供）： 早产的发生率已经有很好的记录，但相对影响 与环境和行为因素相比， 不知道。本提案的目的是检验以下假设： 差异基因表达导致了感染相关的 早产第二个目标是建立两个大型和新颖的 资源研究早产：（1）候选人的关键数据库 基因，和（2）人基因表达组织库。我们建议 阐明早产的病理生理学需要执行 分析了分娩所需的母胎相互作用 基因组规模出于实践和伦理的原因，这种类型的初步研究 在人类中的应用将受到严重限制。因此，在第一阶段， 项目中，我们将使用一个经过验证的，严格控制的小鼠模型， 感染引起早产产生一个全面的基因目录 在多种组织中随时间的表达。早产妊娠小鼠将 随机分配至模拟临床状况之一的治疗组：A. 分娩感染; B.感染无分娩; C.分娩无感染; 和D.无感染/无分娩。然后从子宫肌层收集RNA， 卵巢、蜕膜、胎盘和胎膜， 时间序列，成千上万的基因的相对表达将是 使用DNA微阵列分析这些样本。相似性度量和 聚类算法将被用来分类个别基因的时间 表达模式一种新的减法策略将使我们能够 将感染诱导的特异性活性转录物与那些 对感染或分娩都很重要将得出关于 通过作图，涉及在微阵列中未被明确表示的基因 进入已知的功能通路。分析的最终结果将是 具有潜在关键作用的候选基因的“短名单”， 感染导致的分娩在项目的第二阶段，我们分析了人类 组织（子宫肌层、胎盘、绒毛膜、羊膜、蜕膜、滋养细胞和血液） 从约1360例足月和早产患者中收集 在一项与种族匹配的横断面病例对照研究中，表达 在这些组织中的分析将针对人类同源物， 在小鼠中鉴定的候选关键基因的丰富列表。 感染与未感染早产的基因表达差异 胎膜早破，以及不同种族群体之间，将是 表征了一种被称为支持向量机的计算工具将被 用于生成预测早产的排序列表， 考虑到历史、临床和实验室变量。本工具将 确定最有可能形成遗传基础的基因子集 早产，并可提供诊断分子谱分析仪器， 预测早产本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是有价值的， 可以在互联网上找到。

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.