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Mitochondrial health, cardiovascular risk, and blood pressure targets in hypertensive adults

成人高血压患者的线粒体健康、心血管风险和血压目标

基本信息

批准号：
10470375
负责人：
Vasantha Kolavennu Jotwani
金额：
$ 71.44万
依托单位：
NORTHERN CALIFORNIA INSTITUTE/RES/EDU
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2025-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10470375
关键词：
Accounting Acute Renal Failure with Renal Papillary Necrosis Adoption Adult Adverse effects Affect Age Aging Animal Model Antihypertensive Agents Benefits and Risks Bioenergetics Blood Blood Pressure Body Composition Calibration Cardiovascular Diseases Cardiovascular system Cessation of life Chronic Kidney Failure Clinical Clinical Data DNA DNA copy number Data Dementia Diabetes Mellitus Discrimination Disease Elderly Electrolytes Energy Metabolism Equilibrium Event Fresh Tissue Genomic Instability Genomics Glean Goals Guidelines Health Heart Diseases Human Hypertension Hypotension Impaired cognition Individual Individual Differences Inherited Intervention Intervention Trial Knowledge Link Machine Learning Measures Methods Mitochondria Mitochondrial DNA Modeling Mutation Nerve Degeneration Network-based Neurodegenerative Disorders Nuclear Observational Study Organelles Outcome Participant Pathway interactions Performance Persons Physical Function Play Risk Risk Factors Role Safety Stress Stroke Structure Subgroup Syncope Technology Testing United States National Institutes of Health Variant Work adverse event risk adverse outcome age related blood pressure control blood pressure elevation blood pressure intervention blood pressure reduction cardiovascular disorder risk cardiovascular risk factor clinical risk cognitive function falls frailty functional status genomic data heart disease risk high risk hypertension treatment hypertensive hypoperfusion innovation insight lifestyle intervention machine learning method mild cognitive impairment mitochondrial DNA mutation mitochondrial dysfunction mitochondrial genome mitochondrial metabolism mortality mortality risk neural network next generation sequencing novel patient subsets personalized medicine precision medicine randomized trial response risk prediction risk prediction model risk stratification stressor tool treatment effect walking speed

项目摘要

PROJECT SUMMARY The Systolic Blood Pressure Intervention Trial (SPRINT) demonstrated that intensive blood pressure (BP) targets significantly reduced risks of cardiovascular disease (CVD) and mortality, leading to new guidelines recommending a lower BP target of <130/80 mm Hg. However, intensive BP targets may increase the risk of adverse events from antihypertensive therapy. With widespread adoption of the new BP guidelines, there is an urgent need to evaluate whether there are subgroups of patients who may have an unfavorable balance of benefits and harms from intensive BP lowering. We propose an innovative approach to risk stratification that integrates traditional risk factors with novel information gleaned from mitochondrial DNA (mtDNA). Mitochondria are intracellular organelles that are essential for energy metabolism and stress adaptation. In animal models, mitochondrial dysfunction plays a fundamental role in aging, CVD, and neurodegenerative diseases. Because mitochondrial metabolism is vital to adapt positively to bioenergetic stressors such as BP lowering, measures of mitochondrial health may help to predict beneficial and adverse outcomes among adults undergoing intensive treatment for hypertension. Recent observational studies have linked novel mtDNA measures with several age-related outcomes, including risks of CVD, hypertension, death, dementia, and reduced functional status. However, the optimal methods for integrating data across the mitochondrial genome have not been established, nor have prior studies investigated the utility of mtDNA measures for identification of subgroups who may derive greatest benefits or harms from intensive BP targets. This proposal will leverage next-gen sequencing technology and machine learning analytics to develop and validate mtDNA risk scores that predict CVD risk, mortality risk, and longitudinal changes in cognitive and physical function in older adults. Our first Aim will implement a biologically-informed neural network among participants of the Health, Aging, and Body Composition Study (Health ABC; N=3,075) and the Lifestyle Interventions and Independence for Elders Study (LIFE; N=1,755) to develop two mtDNA risk scores for prediction of CVD and cognitive and physical function outcomes, while accounting for the competing risk of death. Our second and third Aims will validate these mtDNA risk scores in two landmark trials that evaluated the impact of intensive vs standard BP targets on cardiovascular outcomes: SPRINT (N=9,361) and Action to Control Cardiovascular Risk in Diabetes (ACCORD; N=2,488). We will then examine whether mitochondrial risk, assessed by these mtDNA scores, modifies the efficacy or safety of the BP interventions. This work will: 1) develop innovative methods for analysis of mitochondrial genomic data; 2) provide novel hypotheses regarding pathways linking mitochondrial health, CVD risk and functional status; and 3) explore the potential of mtDNA measures for personalized health interventions in older adults.

项目摘要收缩压干预试验（SPRINT）表明，强化血压（BP）目标显着降低心血管疾病（CVD）和死亡率的风险，导致新的指南推荐较低的BP目标<130/80 mm Hg。然而，密集的BP目标可能会增加风险，降压治疗的不良事件。随着BP新准则的广泛采用，迫切需要评估是否有患者亚组可能存在不利的平衡，强化降压的好处和危害。我们提出了一种风险分层的创新方法，将传统的风险因素与从线粒体DNA（mtDNA）收集的新信息相结合。线粒体是细胞内的细胞器，对能量代谢和应激适应至关重要。在在动物模型中，线粒体功能障碍在衰老、CVD和神经退行性疾病中起着重要作用。疾病因为线粒体代谢对于积极适应生物能量应激源（如BP）至关重要降低，线粒体健康的措施可能有助于预测有益和不利的结果，正在接受高血压强化治疗的成年人。最近的观察性研究表明， mtDNA测量与几个年龄相关的结果，包括心血管疾病，高血压，死亡，痴呆，功能状态下降。然而，整合线粒体数据的最佳方法基因组尚未建立，以前的研究也没有调查mtDNA措施的效用，确定可能从强化BP目标中获得最大获益或危害的亚组。该提案将利用下一代测序技术和机器学习分析，验证mtDNA风险评分，预测CVD风险，死亡风险和认知和老年人的身体功能。我们的第一个目标将实现一个生物信息神经网络，健康、衰老和身体成分研究（Health ABC; N= 3，075）和生活方式研究的参与者老年人干预和独立性研究（LIFE; N= 1，755），以制定两个mtDNA风险评分，预测心血管疾病以及认知和身体功能结果，同时考虑死亡我们的第二个和第三个目标将在两项具有里程碑意义的试验中验证这些线粒体DNA风险评分，这些试验评估强化与标准BP目标对心血管结局的影响：SPRINT（N= 9，361）和控制糖尿病患者的心血管风险（雅阁; N= 2，488）。然后我们将检查线粒体是否通过这些mtDNA评分评估的风险改变了BP干预的有效性或安全性。这项工作将： 1)开发线粒体基因组数据分析的创新方法; 2）提供新的假设关于连接线粒体健康，CVD风险和功能状态的途径;和3）探索潜在的 mtDNA测量用于老年人的个性化健康干预。