Leveraging Variant-perturbed Gene Regulation to Support Precision Medicine in COPD

总结/摘要 微核糖核酸（miRNAs）对正常的肺发育、肺健康至关重要， 涉及肺部疾病，包括慢性阻塞性肺病（COPD）。此外，最近 研究已经鉴定了miRNA作为COPD的潜在治疗靶点。miRNAs在 基因调控miRNA在涉及其他生物分子的复杂调控结构内起作用， 包括转录因子、蛋白质、信使RNA（mRNA）和其他表观遗传机制，所有这些都是 这可能是受遗传变异的影响。许多遗传变异已被确定为 通过全基因组关联研究（GWAS）发现COPD的重要性。然而，大量的计算 和方法上的挑战阻碍了将遗传变异与改变的分子机制联系起来， 确定可以有效靶向这些机制以产生临床影响的治疗干预措施。 了解基因调控的复杂结构，包括miRNAs和miRNAs，以及它是如何改变的， 疾病或对遗传变异的反应，对于开发有效的，基于精确医学的 COPD的治疗策略 在这个项目中，我们假设基于网络的方法，它模拟生物的集体反应， 分子，有可能确定新的治疗策略，慢性阻塞性肺病。我们的目标是利用 在连接图分析中通过调节网络模型进行预测，以确定潜在的治疗 对COPD的干预。为了实现这一目标，我们将首先发展一个网络方法模型监管 使用COPDGene中血液样本中现有的mRNA和miRNA表达数据。我们 还将从肺组织研究联盟（LTRC）获得肺组织中的miRNA表达数据。 我们将使用这些数据来评估与COPD相关的miRNAs的变化，并量化COPD与 miRNAs和遗传变异。将开发共表达、调控和遗传关联网络， 支持与COPD相关的多组学预测。网络分析结果将在以下环境中进行分析： 从连接图的药物反应谱，以确定潜在的治疗策略。这场 该项目将更深入地了解miRNAs在COPD中的调节作用，疾病特异性miRNAs是如何在COPD中发挥作用的。 在COPD GWAS变异体的背景下，调节发生改变， 慢性阻塞性肺病该项目中开发的方法也将支持开发精确医学的更广泛目标 COPD的治疗策略

Summary/Abstract Micro-ribonucleic acids (miRNAs) are crucial for normal lung development, lung health, and have been implicated in lung diseases, including Chronic Obstructive Pulmonary Disease (COPD). In addition, recent studies have identified miRNAs as potential therapeutic targets for COPD. miRNAs play an important role in gene regulation. miRNAs act within a complex regulatory structure that involves other biological molecules, including transcription factors, proteins, messenger RNAs (mRNAs), and other epigenetic mechanisms, all of which may be under the influence of genetic variants. A number of genetic variants have been identified as important for COPD through Genome-Wide Association Studies (GWAS). However, substantial computational and methodological challenges impede both linking genetic variants to altered molecular mechanisms and identifying therapeutic interventions that can effectively target these mechanisms for clinical impact. Understanding the complex structure of gene regulation, including by and of miRNAs, and how it is altered in disease or in response to a genetic variant, is critical for developing effective, precision-medicine based therapeutic strategies in COPD. In this project, we hypothesize that network-based methods, which model the collective response of biological molecules, have the potential to identify novel therapeutic strategies for COPD. Our goal is to leverage the predictions made by regulatory network models in a Connectivity Map analysis to identify potential therapeutic interventions for COPD. To accomplish this goal, we will first develop a network approach to model regulation by and of miRNAs using existing mRNA and miRNA expression data from blood samples in COPDGene. We will also generate miRNA expression data in lung tissue from the Lung Tissue Research Consortium (LTRC). We will use these data to assess changes in miRNAs related to COPD and to quantify associations between miRNAs and genetic variants. Co-expression, regulatory, and genetic-association networks will be developed to support multi-Omics predictions relevant to COPD. Network analysis results will be analyzed in the context of drug response profiles from the Connectivity Map to identify potential treatment strategies. The outcome of this project will be a deeper understanding of the regulatory role of miRNAs in COPD, how disease-specific miRNA regulation is altered in the context of COPD GWAS variants, and predictions for novel therapeutic strategies for COPD. The methods developed in the project will also support the broader goal of developing precision-medicine strategies for COPD.