Quantitative and computational characterization of oxytocin receptor signaling

催产素受体信号传导的定量和计算表征

• 批准号: 10636923
• 负责人: Sarah K. England
• 金额: $ 48.46万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-19 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10636923
• 关键词: Address; Affect; Alleles; Binding; Birth; Cell membrane; Cells; Cesarean section; Childhood; Clinical; Clinical Trials; Code; Computer Models; Computer software; Data; Databases; Discipline of obstetrics; Disease; Dose; Drug usage; Effectiveness; Embryo; England; Event; Genes; Genetic; Genetic Transcription; Goals; Human; Individual; Induced Labor; Inflammatory; Kidney; Kinetics; Knowledge; Label; Labor augmentation; Measures; Membrane; Methods; Modeling; Molecular; Mutation Analysis; Myometrial; Obesity; Obstetric pharmacology; Oxytocin; Oxytocin Receptor; Patients; Pharmaceutical Preparations; Phenotype; Post-Traumatic Stress Disorders; Premature Birth; Proteins; Provider; Receptor Signaling; Regimen; Reproduction; Safety; Signal Pathway; Signal Transduction; Single Nucleotide Polymorphism; Smooth Muscle; Smooth Muscle Myocytes; Social Anxiety Disorder; System; Testing; Therapeutic; Therapeutic Agents; Therapeutic Uses; Tissues; Translating; Translational Research; United States; Untranslated RNA; Uterus; Variant; Woman; Work; autism spectrum disorder; beta-arrestin; exome; genetic variant; improved; mRNA Expression; neonatal outcome; pediatric pharmacology; protein expression; receptor; receptor expression; receptor function; recruit; reproductive outcome; response; tool; trafficking

PROJECT SUMMARY Oxytocin is administered to approximately one-half of the four million women who give birth in the United States each year. A significant challenge for providers is that the oxytocin dose required to induce or augment labor varies by up to 20-fold, and they have no way to predict how, or even whether, a woman will respond to a given dose. This lack of predictability raises important safety concerns and underlies oxytocin's association with adverse maternal events and neonatal outcomes. Thus, it is essential to develop a method to predict oxytocin responsiveness and thereby personalize the dosing regimens. This proposal takes the first step in addressing this need by testing the central hypothesis that the oxytocin responsiveness of uterine (myometrial) smooth muscle cells (MSMCs) can be predicted by oxytocin receptor (OXTR) gene variants. Such variants are common; the Exome Aggregation Consortium identified 132 missense single nucleotide variants (mSNVs) in OXTR, of which ~50% are predicted by mutation analysis software to be deleterious to OXTR function. Our hypothesis is supported by two studies identifying rare mSNVs and common noncoding single nucleotide polymorphisms (SNPs) in OXTR that are associated with oxytocin dose requirement. Additionally, several OXTR coding and noncoding variants have been implicated in adverse reproductive outcomes including preterm birth and long labor duration. Although these studies provide evidence that OXTR variants associate with clinically important phenotypes, the underlying mechanisms are unknown. This lack of knowledge hampers our ability to translate OXTR genetics to personalized labor management approaches. To fill this gap, we propose to determine the effects of mSNVs and common SNPs on OXTR expression and function in MSMCs by pursuing the following Specific Aims: 1) Determinw the mechanisms by which OXTR mSNVs affect oxytocin signaling, 2) Determine the effect of OXTR noncoding SNPs on OXTR mRNA and protein expression in MSMCs, and 3) Developing and test a computational model to predict the effect of OXTR variants on oxytocin signaling efficacy. The work proposed here will be directed under a multi-PI plan bringing together Dr. Sarah England, who has expertise in reproduction and myometrial smooth muscle, and Dr. Princess Imoukhuede, who uses quantitative and computational approaches to define the cellular and molecular underpinnings of disease and has specific expertise in quantitative analysis of receptors. Successful completion of these aims will provide important information regarding the influence of OXTR variants on responsiveness to oxytocin.

项目摘要 催产素用于在美国生育的四百万妇女中的大约一半 每年。对于提供者来说，一个重大挑战是诱导或增加劳动所需的催产剂剂量 最多不同20倍，他们无法预测女性是否会对给定的响应 剂量。缺乏可预测性引发了重要的安全问题，并构成了催产素与 不利的孕产妇事件和新生儿结果。因此，开发一种预测催产素的方法至关重要 响应能力，从而个性化给药方案。该提案迈出了解决的第一步 通过测试中心假设，即子宫（肌层）光滑的催产素反应性 可以通过催产素受体（OXTR）基因变异来预测肌肉细胞（MSMC）。这种变体很常见； 外部聚集财团确定了132个错义单核苷酸变体（MSNV），OXTR，OF 通过突变分析软件预测约50％对OXTR功能有害。我们的假设是 由两项识别稀有MSNV和常见的非编码单核苷酸多态性的研究支持 （SNP）在OXTR中与催产素剂量的需求有关。此外，几个OXTR编码和 非编码变体与不利的生殖结果有关，包括早产和长期 劳动期。尽管这些研究提供了证据，表明OXTR变体与临床上重要 表型，基本机制是未知的。缺乏知识阻碍了我们翻译的能力 OXTR遗传学到个性化的劳动管理方法。为了填补这一空白，我们建议确定 MSNV和常见SNP对MSMC中OXTR表达和功能的影响通过追求以下 具体目的：1）确定OXTR MSNV影响催产素信号的机制，2）确定 OXTR非编码SNP对MSMC中OXTR mRNA和蛋白质表达的影响，以及3）发展和 测试一个计算模型，以预测OXTR变体对催产素信号传导功效的影响。工作 在这里提出的建议将根据一个多PI计划，将莎拉·英格兰博士召集在一起，他在 繁殖和肌层平滑肌，以及使用定量和 定义疾病的细胞和分子基础的计算方法 受体定量分析方面的专业知识。这些目标成功完成将提供重要的 有关OXTR变体对催产素反应性的影响的信息。