The Molecular Pathogenesis of Health Disparities in Inf*

Inf* 健康差异的分子发病机制

• 批准号: 6776475
• 负责人: EMMET HIRSCH
• 金额: $ 30万
• 依托单位: NORTHSHORE UNIVERSITY HEALTHSYSTEM
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-24 至 2006-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6776475
• 关键词: DNA; Escherichia coli; RNA; bacteria infection mechanism; decidua; disease /disorder model; disease /disorder proneness /risk; embryo /fetus membrane; epidemiology; female; gene expression; genetic susceptibility; human tissue; induced labor; infection; laboratory mouse; microarray technology; molecular biology information system; myometrium; ovary; pathologic process; placenta; premature labor; racial /ethnic difference; tissue /cell culture

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.

描述（由申请人提供）：种族和种族差异 早产的发病率已得到充分记录，但是相对影响 与环境和行为因素相比 不知道。该提议的目的是检验以下假设 差异基因表达有助于感染相关的差异 早产。第二个目标是创建两个大型新颖的 研究早产的资源：（1）候选人关键数据库 基因，以及（2）人类基因表达组织库。我们建议这样做 阐明早产的病理生理学需要执行的能力 分区所需的胎儿相互作用的分析 基因组量表。出于实用和道德原因，这类型的主要研究 在人类中，将受到严格的限制。因此，在第一阶段 项目，我们将使用经过验证的紧密控制的鼠模型 感染引起的早产，以产生全面的基因目录 随着时间的流逝在多个组织中表达。早产怀孕的小鼠将是 随机分配到建模临床条件之一的治疗组：A。 劳动感染； B.没有劳动的感染； C.没有感染的劳动； 和D.没有感染/没有劳动。然后，RNA将从子宫骨架中收集， 卵巢，De​​cidua，胎盘和胎儿膜来自A的每个组 时间序列，数千个基因的相对表达将是 使用DNA微阵列在这些样品中分析。相似度量和一个 聚类算法将用于按时间分类单个基因 表达模式。一种新颖的减法策略将使我们能够 区分有效的感染引起的转录本与那些 仅感染或劳动重要。关于 通过映射而不是在微阵列中表示的基因的参与 进入已知的功能途径。该分析的最终结果将是 候选基因的“简短列表”在 感染引起的劳动。在项目的第二阶段，我们分析人类 组织（子宫肌，胎盘，绒毛膜，羊膜，Decidua，羊膜细胞和血液） 从大约1360名患者和早产中收集 在横断面的病例对照研究中，劳动与种族匹配。表达 这些组织中的分析将针对人类的同源物 在小鼠中鉴定出的候选关键基因的富集列表。 在有或没有感染的情况下，学期劳动中的差异基因表达和 过早的破裂膜以及不同种族群体将是 特征。一种称为支持向量机的计算工具将是 用于生成一份排名订单清单预测早产，服用 考虑到历史，临床和实验室变量。该工具将 确定最有可能形成遗传基础的基因的子集 早产，可以提供诊断性分子分析仪器 预测早产。本研究中生成的大数据库将 对于对分娩感兴趣的任何研究人员都很有价值，并将被制造 可以在互联网上访问。