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

• 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
• 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

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).

摘要 该计划旨在开发一种新的方法来OSA护理的基础上的原则， 医学，重点是改善预测，预防和个性化。该计划有4个项目， 3个核心支助调查员的工作。项目01（OSA极端表型的遗传学和 相关的上呼吸道解剖学）的重点是确定常见和罕见的遗传变异， 与OSA的风险有关。由于OSA有多种致病途径， 变种是有挑战性的。该项目研究与数量中间性状相关的基因变异， 紊乱重点是结构风险因素颅面尺寸和软组织。一个重点是 舌脂肪，一种特殊的遗传性脂肪分布，介导肥胖导致OSA的作用。机 已经开发了学习方法，以允许从大量的数据中量化感兴趣的性状， 具有遗传数据的个体的相关临床获得的CT和MR图像。该项目的数据将 结合正在进行的遗传学研究的数据，开发OSA的多基因风险评分（PRS） 适用性广。项目02（MicroRNAs作为阻塞性睡眠呼吸暂停的生物标志物）将研究 microRNA作为与OSA相关的生物标志物，使用所有短microRNA的RNA测序。表达 microRNA是动态的;它们响应多种挑战，包括缺氧。MicroRNA被用于 在多个领域开发生物标志物，并获得了阻塞性睡眠呼吸暂停综合症的支持数据，尽管样本相对较小。 因此，我们将采用假设驱动的方法与更广泛的发现相结合 战略生物标志物将被开发，以帮助识别OSA病例，以及评估 治疗，并提供有关OSA患者血压降低的预后信息， 治疗项目03（解释OSA不同症状亚型的机制）将研究 稳健验证的阻塞性睡眠呼吸暂停综合症症状亚型的生理和多组学决定因素。会有一个 强调过度嗜睡的亚型，这已被证明是在心血管风险升高。我们 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（从基因 与致病基因鉴定的关联）将集中于鉴定解释GWAS的致病基因 协会.对于引起OSA风险的基因，我们将开始使用现有的GWAS数据， 项目01对于嗜睡，这个项目将从最近发表的遗传位点开始， 基于项目03中鉴定的基因。我们将首先使用基于细胞的方法来识别可能的病因 基因.这些基因的作用将在高多样性小鼠模型中进行评估（对于与肿瘤相关的基因）。 解剖学）以及果蝇和斑马鱼（与嗜睡相关的基因）。