Developing a P4 Medicine Approach to Obstructive Sleep Apnea

开发治疗阻塞性睡眠呼吸暂停的 P4 医学方法

基本信息

批准号：
10555805
负责人：
Allan I Pack
金额：
$ 250.06万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-07-01 至 2028-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10555805
关键词：
Advisory Committees Affect Anatomy Apnea Area Biological Biological Markers Biological Models Biometry Blood Pressure Cardiovascular system Caring Cells Characteristics Chronic Obstructive Pulmonary Disease Clinical Clinical Data Data Data Analyses Data Collection Data Set Development Diagnosis Dimensions Disease Drosophila genus Drowsiness Early identification Early treatment Ensure Epigenetic Process Etiology Evaluation Fatty acid glycerol esters Genes Genetic Genetic study Glues Goals Grant Heritability Heterogeneity Hypoxia Individual Informatics Information Dissemination Infrastructure Knowledge Link Lung diseases Machine Learning Magnetic Resonance Imaging Manuscripts Mediating Medicine Methods MicroRNAs Modeling Mus Obesity Obstructive Sleep Apnea Outcome Pathway interactions Patient Care Phenotype Physiological Prevention Preventive measure Process Publishing Reaction Research Research Design Research Personnel Research Proposals Risk Risk Assessment Risk Factors Role Sampling Sleep Sleep Deprivation Sleep Disorders Sleep Fragmentations Symptoms Techniques Tongue Treatment Effectiveness Update Work Writing X-Ray Computed Tomography Zebrafish adverse outcome biobank biomarker development blood pressure reduction body system cardiovascular risk factor clinical application clinical care clinical heterogeneity clinical subtypes clinical translation clinically relevant comorbidity craniofacial craniofacial structure data integration data quality design disease heterogeneity disorder prevention effectiveness evaluation genetic association genetic risk factor genetic signature genetic variant genome wide association study genomic locus improved interest meetings metabolomics mouse model multiple omics novel marker novel strategies patient engagement personalized approach personalized diagnostics personalized management personalized medicine polygenic risk score pre-clinical precision medicine prevent prognostic programs quality assurance response soft tissue statistical and machine learning tool trait transcriptome sequencing treatment response

项目摘要

ABSTRACT This program is directed at developing a new approach to OSA care based on the principles of Precision Medicine, with a focus on improving prediction, prevention and personalization. The program has 4 projects and 3 cores to support the work of the investigators. Project 01 (Genetics of Extreme Phenotypes of OSA and Associated Upper Airway Anatomy) is focused on identifying both common and rare genetic variants that are associated with risk for OSA. Since OSA has multiple pathways to disease, identifying associated genetic variants is challenging. This project investigates gene variants associated with quantitative intermediate traits for the disorder. The focus is on structural risk factors—both craniofacial dimensions and soft tissues. A focus is on tongue fat, a specific heritable distribution of fat that mediates the effect of obesity in causing OSA. Machine learning approaches have been developed to allow quantification of traits of interest from a large number of relevant clinically-obtained CT and MR images in individuals with genetic data. Data from this project will be used in combination with data from ongoing genetic studies to develop a polygenic risk score (PRS) for OSA with wide-applicability. Project 02 (MicroRNAs as Biomarkers for Obstructive Sleep Apnea) will study microRNAs as a biomarker relevant to OSA using RNA sequencing of all short microRNAs. Expression of microRNAs is dynamic; they respond to multiple challenges, including hypoxia. MicroRNAs are being used in development of biomarkers in multiple areas, with supportive data in OSA, albeit in relatively small samples. Thus, we will employ a combination of a hypothesis-driven approach complimented by a broader discovery strategy. Biomarkers will be developed to help identify cases with OSA, as well as to assess effectiveness of therapy and to provide prognostic information about who with OSA will have blood pressure reduction with treatment. Project 03 (Mechanisms that Account for Different Symptom Subtypes of OSA) will examine the physiological and multi-omics determinants of robustly validated symptom subtypes of OSA. There will be an emphasis on the excessively sleepy subtype, which has been shown to be at elevated cardiovascular risk. We will evaluate whether there are differences in physiological responses during sleep in the different subtypes and/or whether there are genetic, epigenetic, and metabolomic differences. Project 04 (Going from Genetic Associations to Identification of Causative Genes) will focus on identifying causative genes that explain GWAS associations. For genes conferring risk for OSA, we will begin with existing GWAS data complimented by data from Project 01. For sleepiness, this project will start with recently published genetic loci, and include analyses based on genes identified in Project 03. We will first use cell-based approaches to identify possible causative genes. The role of these genes will be assessed in high-diversity mouse models (for genes associated with anatomy) and in Drosophila and zebrafish (for genes associated with sleepiness).

抽象的该计划旨在根据精准原则开发一种新的 OSA 护理方法医学，重点是改善预测、预防和个性化。该计划有 4 个项目。支持研究人员工作的 3 个核心项目 01（OSA 和极端表型的遗传学）。相关上呼吸道解剖学）专注于识别常见和罕见的遗传变异由于 OSA 有多种致病途径，因此需要确定相关的遗传因素。变异是具有挑战性的项目，研究与数量中间性状相关的基因变异。重点是结构性风险因素——颅面尺寸和软组织。脂肪舌头，一种特定的遗传性脂肪分布，介导肥胖对导致 OSA 的影响。已经开发出学习方法来量化大量感兴趣的特征具有该项目数据的个体的相关临床 CT 和 MR 图像将被获取。与正在进行的遗传学研究的数据相结合，制定 OSA 的多基因风险评分 (PRS) 具有广泛适用性的项目 02（MicroRNA 作为阻塞性睡眠呼吸暂停的生物标志物）将进行研究。使用所有短 microRNA 表达的 RNA 测序，将 microRNA 作为与 OSA 相关的生物标志物。 microRNA 是动态的；它们可以应对多种挑战，包括用于缺氧的情况。尽管样本相对较小，但在多个领域开发生物标志物，并有 OSA 的支持数据。因此，我们将采用假设驱动的方法与更广泛的发现相结合将开发生物标志物来帮助识别 OSA 病例，并评估治疗的有效性。治疗并提供有关 OSA 患者血压可降低的预后信息项目 03（OSA 不同症状亚型的机制）将检查经严格验证的 OSA 症状亚型的生理学和多组学决定因素。重点关注过度困倦的亚型，该亚型已被证明会增加心血管疾病的风险。将评估不同亚型在睡眠期间的生理反应是否存在差异和/或是否存在遗传、表观遗传和代谢组学差异项目 04（从遗传开始。致病基因识别协会）将重点关注识别解释 GWAS 的致病基因对于赋予 OSA 风险的基因，我们将从现有的 GWAS 数据开始，并辅之以数据。来自项目 01。对于嗜睡，该项目将从最近发表的遗传位点开始，并包括分析基于项目 03 中确定的基因。我们将首先使用基于细胞的方法来确定可能的致病因素这些基因的作用将在高多样性小鼠模型中进行评估（针对与相关基因相关的基因）。解剖学）以及果蝇和斑马鱼（与嗜睡相关的基因）。