HeartShare: Next-Generation Phenomics to Define Heart Failure Subtypes and Treatment Targets - Clinical Centers

HeartShare：定义心力衰竭亚型和治疗目标的下一代表型组学 - 临床中心

基本信息

批准号：
10483139
负责人：
JULIO ALONSO CHIRINOS MEDINA
金额：
$ 27.85万
依托单位：
UNIVERSITY OF PENNSYLVANIA
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：
2021-09-10 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10483139
关键词：
Abdomen Accelerometer Adult Aerobic Affect Anxiety Bicycling Bioinformatics Biopsy Blood Blood Vessels Blood specimen Body Composition Body measure procedure Cardiac Cardiopulmonary Cardiovascular system Cessation of life Characteristics Cine Magnetic Resonance Imaging Clinical Clinical Data Collection Communities Complement Coupled Coupling Data Data Collection Detection Doppler Echocardiography EFRAC Echocardiography Economic Burden Electronic Health Record Enrollment Ergometry Exercise Exercise Test Fatty acid glycerol esters Fibrosis Gases Goals Gold Heart Heart Atrium Heart failure Heterogeneity Hip region structure Home Home Blood Pressure Monitoring Hospitalization Human Hypertension Hypertrophy Individual Left Left Ventricular Mass Liver Magnetic Resonance Imaging Measures Mental Depression Methods MicroRNAs Monitor Myocardial Infarction Myocardial tissue Nature Outcome Participant Pathogenicity Pathologic Patient Outcomes Assessments Patients Pericardial body location Pharmacology Phenotype Physical activity Plasma Polysomnography Population Control Process Prospective cohort Proteomics Protocols documentation Public Health Pulmonary function tests Pump Quality of life Randomized Clinical Trials Recording of previous events Research Research Personnel Resistance Rest Sampling Skeletal Muscle Sleep Stroke Supination Symptoms Techniques Tissues Urine Venous Ventricular Visceral Work adjudicate adverse outcome arterial tonometry base biobank bioinformatics tool clinical center cohort disorder subtype electric impedance endophenotype follow-up functional status in vivo innovation member metabolomics molecular phenotype multiple omics myocardial biopsy neurocognitive test next generation novel strategies patient oriented patient subsets phase II trial phenome phenomics phenotypic data preservation pressure prospective randomized trial social social health determinants socioeconomics subcutaneous symptomatic improvement targeted treatment therapeutically effective transcriptome sequencing treatment response urinary

项目摘要

PROJECT SUMMARY Heart failure (HF) is a critical public health issue that affects over 5 million US adults and imposes an enormous clinical, social, and economic burden. Over half of individuals with HF have HF with preserved ejection fraction (HFpEF). Furthermore, HFpEF is highly heterogeneous, and different pathologic mechanisms contribute to symptoms and poor outcomes in several different subgroups of the disease. Although several largescale randomized trials have been performed, no pharmacological therapies have been identified that improve symptoms or clinical outcomes in patients with HFpEF. Our group and others have identified that novel approaches to deeply phenotyping patients with HFpEF can identify subgroups of patients with HFpEF that are likely to benefit from targeted therapy. The overarching goal of the current proposal is to establish a large cohort of deeply phenotyped patients with HF with a focus on patients with HFpEF. We propose establishing a cohort of 1000 patients across all 4 Penn clinical centers: 700 patients with HFpEF, 200 patients with HFrEF (including 100 patients with mid-range LV EF, 40-50%) and 100 non-HF patients with hypertension (a suitable control population, given that most patients with HFpEF have a history of hypertension). We will incorporate comprehensive clinical data, socioeconomic data (particularly as they relate to social determinants of health), patient-centered data (such as quality of life and functional status), structural and mechanistic cardiac and extracardiac phenotypes (including in-lab characterization and innovative ambulatory approaches to data collection) and multi-omics approaches. The phenotypic data will be complemented by contemporary bioinformatic approaches to enhance our understanding of human HFpEF. Our phenotyping protocol will provide the opportunity for cross-sectional comparisons against other groups above, application of within-group clustering approaches, as well as establishing a comprehensively characterized large prospective cohort of patients with strictly adjudicated HFpEF for prospective follow-up of hard outcomes. In these patients, we will assess detailed cardiac and extracardiac phenotypes, electronic health record data, patient-reported outcomes, aerobic adaptations to exercise, and plasma and urinary proteomics and metabolomics and micro RNAs. We will also assess key ambulatory phenotypes including innovative approaches to home blood pressure monitoring, physical activity, sleep duration and quality, and important social determinants of health. Heart failure outcomes will be prospectively adjudicated, including heart-failure related hospitalization, death, myocardial infarction and stroke. Our analytic approach will include hypothesis-based research as well as unbiased discovery approaches that will leverage contemporary bioinformatics tools but will be subject to expert interpretation by members of the Steering Committee, investigator teams at the other Clinical Centers, and scientific community at large.

项目概要心力衰竭 (HF) 是一个严重的公共卫生问题，影响超过 500 万美国成年人，并导致巨大的临床、社会和经济负担。超过一半的心力衰竭患者患有射血功能保留的心力衰竭分数（HFpEF）。此外，HFpEF 具有高度异质性，不同的病理机制导致该疾病的几个不同亚组的症状和不良结果。虽然有几个大型已进行随机试验，尚未发现任何药物疗法可以改善 HFpEF 患者的症状或临床结果。我们的小组和其他人已经确定了这部小说对 HFpEF 患者进行深入表型分析的方法可以识别 HFpEF 患者的亚组，这些亚组是可能受益于靶向治疗。当前提案的总体目标是建立一大批深度表型患者 HF，重点关注 HFpEF 患者。我们建议建立一个包含 4 个领域 1000 名患者的队列 Penn 临床中心：700 名 HFpEF 患者，200 名 HFrEF 患者（包括 100 名中度患者） LV EF，40-50%）和 100 名非心力衰竭高血压患者（合适的对照人群，因为大多数 HFpEF 患者有高血压病史）。我们将整合全面的临床数据，社会经济数据（特别是与健康的社会决定因素相关的数据）、以患者为中心的数据（例如生活质量和功能状态）、结构和机械心脏和心外表型（包括实验室表征和创新的流动数据收集方法）和多组学方法。表型数据将通过当代生物信息学方法进行补充，以增强我们的研究能力。了解人类 HFpEF。我们的表型分析方案将提供与其他方案进行横断面比较的机会上述群体，应用群体内聚类方法，以及建立一个全面的对患有严格判定的 HFpEF 的大型前瞻性队列进行前瞻性随访艰难的结果。在这些患者中，我们将评估详细的心脏和心外表型、电子健康记录数据、患者报告的结果、运动的有氧适应以及血浆和尿液蛋白质组学以及代谢组学和微小RNA。我们还将评估关键的动态表型，包括创新家庭血压监测、体力活动、睡眠持续时间和质量以及重要社交的方法健康的决定因素。将前瞻性地判定心力衰竭结果，包括心力衰竭相关的结果住院、死亡、心肌梗塞和中风。我们的分析方法将包括基于假设的研究以及公正的发现方法将利用当代生物信息学工具，但将接受指导委员会成员、其他临床研究小组的专家解释中心和整个科学界。