MicroRNAs as Biomarkers for Obstructive Sleep Apnea

MicroRNA 作为阻塞性睡眠呼吸暂停的生物标志物

• 批准号: 10555810
• 负责人: ULYSSES J MAGALANG
• 金额: $ 49.63万
• 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/10555810
• 关键词: Affect; Age; Area; Asthma; Biological Markers; Blood; Blood Pressure; Body mass index; Cardiovascular Diseases; Cholesterol; Chronic Obstructive Pulmonary Disease; Clinical; Code; Complement; Continuous Positive Airway Pressure; Data; Diabetes Mellitus; Disease; Drowsiness; Educational workshop; Effectiveness; Enrollment; Etiology; Exclusion Criteria; Foundations; Goals; Hour; Hypertension; Hypoxia; Individual; International; Literature; Lung diseases; Measurement; Measures; Medicine; Methods; MicroRNAs; Monitor; Obstructive Sleep Apnea; Participant; Pathogenesis; Patients; Persons; Predictive Value; Process; Proteins; RNA; Reporting; Research; Risk; Risk Factors; Sample Size; Sampling; Severities; Severity of illness; Sleep; Sleep Disorders; Sleep Fragmentations; Sleep disturbances; Sleeplessness; Symptoms; Techniques; Testing; Therapeutic; Translations; Treatment Efficacy; United States National Institutes of Health; Untranslated RNA; Validation; biomarker identification; cardiovascular risk factor; case control; clinical risk; clinical translation; comorbidity; effectiveness measure; efficacy evaluation; improved; microRNA biomarkers; next generation sequencing; polygenic risk score; population based; positive airway pressure; precision medicine; predictive signature; prognostic; prognostic value; programs; recruit; response; risk stratification; sex; sleep regulation; specific biomarkers; treatment response; Affect; Age; Area; Asthma; Biological Markers; Blood; Blood Pressure; Body mass index; Cardiovascular Diseases; Cholesterol; Chronic Obstructive Pulmonary Disease; Clinical; Code; Complement; Continuous Positive Airway Pressure; Data; Diabetes Mellitus; Disease; Drowsiness; Educational workshop; Effectiveness; Enrollment; Etiology; Exclusion Criteria; Foundations; Goals; Hour; Hypertension; Hypoxia; Individual; International; Literature; Lung diseases; Measurement; Measures; Medicine; Methods; MicroRNAs; Monitor; Obstructive Sleep Apnea; Participant; Pathogenesis; Patients; Persons; Predictive Value; Process; Proteins; RNA; Reporting; Research; Risk; Risk Factors; Sample Size; Sampling; Severities; Severity of illness; Sleep; Sleep Disorders; Sleep Fragmentations; Sleep disturbances; Sleeplessness; Symptoms; Techniques; Testing; Therapeutic; Translations; Treatment Efficacy; United States National Institutes of Health; Untranslated RNA; Validation; biomarker identification; cardiovascular risk factor; case control; clinical risk; clinical translation; comorbidity; effectiveness measure; efficacy evaluation; improved; microRNA biomarkers; next generation sequencing; polygenic risk score; population based; positive airway pressure; precision medicine; predictive signature; prognostic; prognostic value; programs; recruit; response; risk stratification; sex; sleep regulation; specific biomarkers; treatment response

ABSTRACT Identification of biomarkers of the severity of sleep-related conditions and the effectiveness of therapies was recently presented as the number one critical opportunity in the 2021 Sleep Research Plan from the National Institutes of Health and National Center on Sleep Disorders Research (NCSDR). While obstructive sleep apnea (OSA) is common, there are limited biomarkers for identification and management of the condition. Specific use cases for an OSA biomarker include: (i) improving case identification, (ii) monitoring efficacy of therapy, and (iii) providing prognostic value with respect to who will get particular consequences or how individuals respond to continuous positive airway pressure (CPAP) treatment. While different approaches can be used to define biomarkers, this project will focus on microRNAs, which have very recently been shown to be promising biomarkers in OSA. MicroRNAs are small non-coding RNAs that alter the translation of protein coding RNA. Their expression is dynamic and altered by many challenges, such as hypoxia. Expression of all microRNAs in blood can be assessed by sequencing all short RNAs. Prior studies, albeit with small sample sizes, suggest differences in microRNA expression between OSA cases and controls and that differences in microRNA expression can identify individuals with OSA who will show larger blood pressure responses to CPAP treatment. Using complementary sequencing approaches and clinically-feasible quantitative PCR (qPCR), we propose to validate and extend these initial observations. First, we will seek biomarkers that are specific to OSA by evaluating differences in microRNA profiles between cases with OSA and controls without OSA matched for age, sex, and body mass index and without other underlying conditions that could independently affect microRNA expression. While identifying microRNAs specific to OSA is important, it is also useful to determine microRNAs useful for improving OSA case identification beyond known clinical risk factors. Thus, this project will enroll a larger case-control sample with minimal exclusion criteria in which to assess the predictive value of differences in microRNA expression. To understand the utility of microRNAs as treatment-related biomarkers, cases with OSA will be studied before and after 6 months of CPAP. We anticipate that some microRNAs specific to OSA will normalize with CPAP treatment, thus providing an objective measure of effectiveness. In all OSA cases, we will assess 24-hour ambulatory blood pressure to validate and extend recent reports of a microRNA signature that predicts blood pressure response to CPAP. We will conduct robust validation for all biomarkers. First, using the same samples sequenced in discovery analyses, we will perform analytical validation via clinically-feasible qPCR techniques. Independent validation of microRNA signatures will be done in new samples, including cases and controls from Project 01. Moreover, the relative utility of microRNAs and other signatures developed in the Program, such as polygenic risk scores, will be assessed. Overall, this Project is directly aligned with the stated research objectives of the NCSDR and the specific goals of this Program Project.

抽象的 鉴定与睡眠相关疾病严重程度的生物标志物以及疗法的有效性为 最近作为2021年睡眠研究计划中的第一名关键机会 卫生研究院和国家睡眠障碍研究中心（NCSDR）。而阻塞性睡眠呼吸暂停 （OSA）很常见，鉴定和管理状况的生物标志物有限。具体用途 OSA生物标志物的病例包括：（i）改善病例识别，（ii）监测治疗的功效；（iii） 就谁将获得特殊后果或个人如何回应提供预后价值 连续阳性气道压力（CPAP）处理。虽然可以使用不同的方法来定义 生物标志物，该项目将集中于microRNA，最近被证明是有希望的 OSA的生物标志物。 microRNA是小的非编码RNA，可改变蛋白质编码RNA的翻译。 它们的表达是动态的，并因许多挑战（例如缺氧）而改变。所有microRNA的表达 可以通过对所有短RNA进行测序来评估血液。先前的研究，尽管样本量很小，但表明 OSA病例和对照组之间microRNA表达的差异以及microRNA的差异 表达可以识别患有OSA的人，他们将对CPAP治疗显示出更大的血压反应。 使用互补的测序方法和临床上可行的定量PCR（QPCR），我们建议 验证并扩展这些初始观察结果。首先，我们将寻求特定于OSA的生物标志物 评估OSA病例和没有OSA的对照组之间的microRNA轮廓差异，年龄匹配， 性别，体重指数，没有其他可能独立影响microRNA的潜在条件 表达。虽然识别特定于OSA的microRNA很重要，但确定microRNA也很有用 有助于改善OSA病例识别超出已知临床风险因素。因此，这个项目将注册 较大的病例对照样本具有最小的排除标准，其中评估差异的预测价值 在microRNA表达中。了解microRNA作为治疗相关的生物标志物的效用 OSA将在CPAP 6个月之前和之后进行研究。我们预计某些特定于OSA的microRNA 将通过CPAP处理正常化，从而提供客观的有效性度量。在所有OSA案件中，我们 将评估24小时的卧床血压，以验证并扩展有关microRNA签名的最新报告 这可以预测血压对CPAP的反应。我们将对所有生物标志物进行强大的验证。首先，使用 在发现分析中测序的相同样品，我们将通过临床上的可行性执行分析验证 QPCR技术。 MicroRNA签名的独立验证将在新样本中进行，包括案例 以及项目01的控制。此外，microRNA和其他特征的相对效用 将评估程序，例如多基因风险评分。总体而言，该项目直接与规定的 NCSDR的研究目标和该计划项目的具体目标。