Developing a P4 Medicine Approach to Obstructive Sleep Apnea

摘要 该计划旨在开发一种基于精确度原则的OSA护理的新方法 医学，重点是改进预测、预防和个性化。该计划有4个项目和 3个核心，支持调查人员的工作。项目01(OSA和OSA极端表型的遗传学 相关的上呼吸道解剖学)专注于识别常见和罕见的遗传变异 与阻塞性睡眠呼吸暂停综合征的风险相关。由于阻塞性睡眠呼吸暂停综合征有多种致病途径，识别相关的基因 变种是具有挑战性的。这个项目调查了与数量中间性状相关的基因变异 这是一种混乱。重点放在结构性风险因素上--包括头面部尺寸和软组织。重点放在 舌脂肪，一种特殊的可遗传分布的脂肪，在肥胖导致阻塞性睡眠呼吸暂停的影响中起中介作用。机器 已经开发了学习方法，以允许从大量的 有遗传数据的个体的相关临床获得的CT和MR图像。来自该项目的数据将是 与正在进行的基因研究的数据结合使用，以开发OSA的多基因风险评分(PRS) 具有广泛的适用性。项目02(microRNAs作为阻塞性睡眠呼吸暂停的生物标记物)将研究 通过对所有短的microRNAs进行RNA测序，将microRNAs作为与OSA相关的生物标志物。的表达 MicroRNAs是动态的；它们对包括缺氧在内的多种挑战做出反应。MicroRNAs正被用于 在多个领域开发生物标记物，在OSA中有支持性数据，尽管样本相对较少。 因此，我们将采用假设驱动的方法和更广泛的发现相结合。 策略。将开发生物标志物，以帮助识别阻塞性睡眠呼吸暂停综合征病例，以及评估 治疗和提供谁患有OSA将有降压的预后信息。 治疗。项目03(解释阻塞性睡眠呼吸暂停综合征不同症状亚型的机制)将检查 阻塞性睡眠呼吸暂停综合征有效症状亚型的生理和多组学决定因素。将会有一个 重点关注过度嗜睡的亚型，这种亚型已被证明具有更高的心血管风险。我们 将评估不同类型的人在睡眠期间的生理反应是否存在差异 和/或是否存在遗传、表观遗传和代谢差异。项目04(从基因 与致病基因识别的关联)将集中于识别解释GWAs的致病基因 联想。对于导致阻塞性睡眠呼吸暂停低通气综合征风险的基因，我们将从现有的Gwas数据开始，再加上数据的补充 来自项目01。对于嗜睡，这个项目将从最近发表的遗传基因座开始，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原因 基因。这些基因的作用将在高多样性的小鼠模型中进行评估(对于与 在果蝇和斑马鱼中(寻找与嗜睡有关的基因)。

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).