Genomic variants associated with angina and health status outcome after MI

与心绞痛和心肌梗死后健康状况结果相关的基因组变异

• 批准号: 8339338
• 负责人: SHARON CRESCI
• 金额: $ 44.96万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-27 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8339338
• 关键词: Acute; Acute myocardial infarction; Address; Admission activity; Adult; Attention; Bar Codes; Cardiovascular system; Caring; Characteristics; Chest Pain; Clinical; Clinical Treatment; Coronary Arteriosclerosis; Data; Decision Making; Diabetes Mellitus; Diagnostic Procedure; Disease; Economic Factors; Enabling Factors; Enrollment; Event; Exons; Foundations; Frequencies; Funding; General Population; Genes; Genetic; Genetic Determinism; Genomics; Goals; Growth; Health Status; Healthcare Systems; Individual; Individual Differences; Information Technology; Institute of Medicine (U.S.); Kidney Diseases; Maps; Measures; Medical; Medicine; Mental Depression; Methods; Modeling; Molecular Biology; Myocardial Infarction; Outcome; Outcomes Research; Pain Threshold; Patients; Perception; Pharmacogenomics; Population; Process; Prospective Studies; Province; Qualifying; Quality of life; Questionnaires; Race; Recovery; Research; Risk; Screening procedure; Severity of illness; Staging; Statistical Methods; Symptoms; Testing; Therapeutic; Translating; United States; United States National Institutes of Health; Universities; Variant; Washington; adjudicate; clinical care; cohort; cost; cost effective; depressive symptoms; design; evidence base; experience; genetic risk factor; genetic variant; genome wide association study; insight; mortality; non-genomic; novel; patient oriented; pleiotropism; primary outcome; prognostic; programs; response; secondary outcome; sex; socioeconomics; tool; treatment strategy

DESCRIPTION (provided by applicant): Recovery from myocardial infarction (MI) is associated with a host of symptoms, including angina, depression, and worse quality of life (QoL) but little attention has been paid to these patient-centered health status outcomes. More than 10 million people in the US suffer from angina and approximately 500,000 new cases occur each year at an estimated cost of $20 billion dollars annually. We propose to identify genomic variants that contribute to inter-individual variation in post-MI angina and health status outcomes by using the TRIUMPH population, an NIH-funded cohort with exquisite disease-specific health status assessments at admission, and 1-month, 6-months and 1-year post-MI, along with adjudicated 1-year major adverse cardiovascular events and 5-year mortality. The study group is particularly well-qualified to perform this research, having expertise in genomics, pharmacogenomics, patient screening and risk profiling, outcomes research, and statistical genomics. We will also take advantage of the strengths of Washington University's CTSA, including its Cores and programs. Collectively, we will address the following Aims: AIM 1. To define the genetic contribution to the observed inter-individual variation in post-MI angina. The primary outcome will be post-MI angina over the first year, as measured by the well-validated, disease-specific Seattle Angina Questionnaire (SAQ) Angina Frequency score. Secondary outcomes are SAQ QoL score and depressive symptoms, as measured by PHQ-9. An unbiased GWAS approach will identify common genetic variants associated with these outcomes using two novel statistical genomic methods (Growth Curve Estimation and Pleiotropy). We will then use a novel, cost-efficient (multi-plexed, 'bar-coded') exomic sequencing method to finely map all exons in the genes under the association peaks and identify rare variants that are associated with these outcomes. AIM 2. To identify non-genomic factors that may potentially moderate the effects of the genetic variants identified in AIM 1. We will construct multivariable models that include genetic, clinical and treatment characteristics, with a specific focus upon interactions. These models, especially if important interactions with treatment are discovered, can serve as the foundation for estimating symptom outcomes as a function of treatment and, using these models, we can generate personalized treatment strategies. AIM 3. To test the feasibility of translating - into 'real world practice' - a prognostic modeling tool (PRISMTM) that includes genetic variants identified by AIM 1, to predict health status response to post-MI treatment. Our team has developed information technology with which to implement multivariable prediction models, executed with patient-specific data, in the process of clinical care. We will use these models to create a personalized risk profile and therapeutic strategy for post-MI treatment. In summary, we will use cutting edge experimental, statistical, and diagnostic methods to identify variants associated with post-MI angina and other health status outcomes and lay the foundation to personalize post-MI care and reduce symptom burden.

描述（由申请人提供）：心肌梗死（MI）恢复与一系列症状相关，包括心绞痛、抑郁和生活质量（QoL）下降，但很少关注这些以患者为中心的健康状况结局。在美国有超过1000万人患有心绞痛，并且每年发生大约500，000个新病例，估计每年花费200亿美元。我们建议通过使用TRIUMPH人群来确定导致MI后心绞痛和健康状况结局个体间差异的基因组变异，TRIUMPH人群是一个NIH资助的队列，在入院时、MI后1个月、6个月和1年时进行了精确的疾病特异性健康状况评估，沿着裁定的1年主要不良心血管事件和5年死亡率。该研究小组特别有资格进行这项研究，拥有基因组学，药物基因组学，患者筛查和风险分析，结果研究和统计基因组学方面的专业知识。我们还将利用华盛顿大学CTSA的优势，包括其核心和计划。总的来说，我们将致力于实现以下目标：目标1。明确心肌梗死后心绞痛中观察到的个体间变异的遗传贡献。主要结局将是第一年的MI后心绞痛，通过经过充分验证的疾病特异性西雅图心绞痛问卷（SAQ）心绞痛频率评分进行测量。次要结局是SAQ生活质量评分和抑郁症状，由PHQ-9测量。无偏的GWAS方法将使用两种新的统计基因组方法（生长曲线估计和多效性）来识别与这些结果相关的常见遗传变异。然后，我们将使用一种新的，具有成本效益的（多重，“条形码”）外显子组测序方法，精细地映射关联峰下的基因中的所有外显子，并识别与这些结果相关的罕见变异。AIM 2.确定可能潜在缓解AIM 1中确定的遗传变异影响的非基因组因素。我们将构建多变量模型，包括遗传，临床和治疗特征，特别关注相互作用。这些模型，特别是如果发现与治疗的重要相互作用，可以作为估计症状结果作为治疗的函数的基础，并且使用这些模型，我们可以生成个性化的治疗策略。AIM 3.测试将预后建模工具（PRISMTM）转化为“真实的世界实践”的可行性，该工具包括通过AIM 1识别的遗传变异，以预测MI治疗后的健康状况反应。我们的团队开发了信息技术，用于在临床护理过程中实施多变量预测模型，并使用患者特定数据执行。我们将使用这些模型为MI后治疗创建个性化的风险特征和治疗策略。总之，我们将使用最先进的实验，统计和诊断方法来识别与MI后心绞痛和其他健康状态结果相关的变异，并为个性化MI后护理和减轻症状负担奠定基础。