The Molecular Pathogenesis of Health Disparities in Inf*

Inf* 健康差异的分子发病机制

• 批准号: 6929305
• 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/6929305
• 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）： 种族和民族差异 早产的发生率已有详细记录，但相对影响 与环境和行为因素相比，遗传倾向的影响 尚不清楚。该提案的目的是检验以下假设： 差异基因表达导致感染相关的差异 早产。第二个目标是创造两个大型且新颖的 研究早产的资源：（1）候选关键数据库 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执行的能力 分析分娩所需的母胎相互作用 基因组规模。出于实际和伦理原因，此类初步研究 在人类中将受到严重限制。因此，在本次活动的第一阶段 项目中，我们将使用经过验证的、严格控制的小鼠模型 感染引起的早产生成全面的基因目录 随着时间的推移在多个组织中表达。早产怀孕的老鼠会 随机分配到模拟临床病症之一的治疗组：A. 劳动感染； B.不经劳动而感染； C.分娩时无感染； D. 无感染/无分娩。然后从子宫肌层收集 RNA， 各组的卵巢、蜕膜、胎盘和胎膜 时间序列，数千个基因的相对表达量将是 使用 DNA 微阵列对这些样品进行分析。相似度度量和 聚类算法将用于按时间对各个基因进行分类 表达模式。一种新颖的减法策略将使我们能够 区分在感染诱导中特异活跃的转录本 对于感染或单独分娩很重要。将得出有关以下方面的推论 通过映射在微阵列中未物理表示的基因的参与 进入已知的功能途径。该分析的最终结果将是 具有潜在关键作用的候选基因的“短名单” 感染引起的分娩。在该项目的第二阶段，我们分析了人类 组织（子宫肌层、胎盘、绒毛膜、羊膜、蜕膜、羊膜细胞和血液） 收集自大约 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力。表达 这些组织中的分析将针对该基因的人类同源物 在小鼠中鉴定出的候选关键基因的丰富列表。 有或没有感染的早产中的差异基因表达和 胎膜早破，以及不同种族群体之间的情况，将 特点。称为支持向量机的计算工具将是 用于生成预测早产的排名顺序列表，采取 考虑历史、临床和实验室变量。这个工具将 识别最有可能形成遗传基础的基因子集 早产，并可以提供诊断分子分析仪器 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很有价值，并将被制作 可通过互联网访问。