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PREDICTION OF OUTCOMES IN HEART FAILURE WITH PRESERVED EJECTION FRACTION (HFPEF): A NEW PLASMA BIOMARKER

PREDICTION OF OUTCOMES IN HEART FAILURE WITH PRESERVED EJECTION FRACTION (HFPEF): A NEW PLASMA BIOMARKER
保留射血分数 (HFPEF) 的心力衰竭结果预测:一种新的血浆生物标志物
批准号:
9810249
负责人:
SHARON CRESCI
金额:
$11.78万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-01 至 2021-07-31

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中文摘要
翻译
摘要 射血分数保留性心力衰竭(HFpEF)影响了美国约290万患者 States. HFpEF是一种病态和致命的疾病。住院后五年死亡率为60-65%, 比大多数癌症都严重不幸的是,医生不能直接解决极高的发病率, 发病率和死亡率,因为目前没有改善生存率的治疗方法。还有一个亲戚 缺乏关于生物标志物在这种疾病的预后或治疗中的效用的数据,特别是在比较中, 射血分数降低的心力衰竭患者此外,HFpEF患者通常有几种共病, 条件,如肥胖和肾功能不全,这可能会影响标准的心力衰竭生物标志物, 利钠肽及其解释。 我们小组最近的流行病学数据表明,一种新的生物标志物,即特定脂质的比例, 等离子体,即,神经酰胺24:0/神经酰胺16:0(C24:0/C16:0)预测心力衰竭事件和全因死亡率 在两个基于社区的队列中的> 5,000名受试者中:Fractionary Offspring队列和健康研究 即使在考虑了标准的心血管风险因素后,波美拉尼亚的情况也是如此。此外,血浆C24:0/C16:0 改变了预测全因死亡率的c统计量。这种新的生物标志物是否也能预测全因 已知HFpEF患者的死亡率和其他继发性事件尚不清楚。的特定基因 参与这种新生物标志物的表达和调节的基因也是未知的。这项研究将解决这些问题 差距。我们已经获得BioLINCC储存库的批准,可以使用现有的数据和血浆和基因数据。 来自TOPCAT临床试验的样本,该临床试验在HFpEF患者中进行,目的如下所列。 我们将利用一种独特的、经过充分验证的液相色谱-串联质谱(LC/MS-MS)脂质组学方法, 检测,这是在我们的机构开发的。此外,我们将纳入新的统计基因组 方法,以实现以下目标: 1.评估血浆C24:0/C16:0神经酰胺比值对继发性风险预测的效用, TOPCAT试验中已知HFpEF的患者。全因死亡率将是主要终点。一 心血管死亡、心力衰竭住院、心脏骤停流产和心肌梗死的联合终点 梗死将作为次要终点进行评价, 还将评价次要结局。 2.描述HFpEF中血浆C24:0/C16:0比值和死亡风险的遗传贡献 并使用TOPCAT的数据和遗传样本确定该比率的潜在因果影响, 以及新的统计基因组方法,包括孟德尔随机化。
英文摘要
ABSTRACT Heart failure with preserved ejection fraction (HFpEF) affects approximately 2.9 million patients in the United States. HFpEF is both a morbid and mortal disease. It has a 60-65% five-year mortality rate after hospitalization, which is worse than most cancers. Unfortunately, physicians cannot directly address the extremely high rates of morbidity and mortality, as currently there are no treatments that improve survival. There is a also a relative paucity of data on the utility of biomarkers in prognosis or treatment of this disease, especially in comparison with heart failure with reduced ejection fraction. Moreover, patients with HFpEF often have several co-morbid conditions, such as obesity, and renal dysfunction, which can affect standard heart failure biomarkers such as natriuretic peptides and their interpretation. Recent epidemiologic data from our group showed that a new biomarker, the ratio of specific lipids in the plasma, i.e., ceramide 24:0/ceramide 16:0 (C24:0/C16:0) predicted incident heart failure and all-cause mortality in >5,000 subjects in two community-based cohorts: the Framingham Offspring cohort and the Study for Health in Pomerania even after accounting for standard cardiovascular risk factors. Moreover, the plasma C24:0/C16:0 altered the c-statistic for prediction of all-cause mortality. Whether this novel biomarker also predicts all-cause mortality and other secondary events in patients with known HFpEF is, as yet, unknown. The specific genes involved in the expression and regulation of this new biomarker is also not known. This study will address these gaps. We have approval from the BioLINCC repository to use already available data and plasma and genetic samples from the TOPCAT clinical trial, which was performed in patients with HFpEF for the Aims listed below. We will utilize a unique, well-validated liquid chromatography-tandem mass spectrometry (LC/MS-MS) lipidomic assay, which was developed at our institution. In addition, we will incorporate novel statistical genomic methodology to achieve the following Aims: 1. To assess the utility of the plasma C24:0/C16:0 ceramide ratio for secondary risk prediction in patients with known HFpEF from the TOPCAT trial. All-cause mortality will be the primary endpoint. A combined endpoint of cardiovascular death, heart failure hospitalizations, aborted cardiac arrest, and myocardial infarction will be evaluated as a secondary endpoint and all occurrences of the individual components of the secondary outcome will also be evaluated. 2. To characterize the genetic contributions to the plasma C24:0/C16:0 ratio and risk of death in HFpEF and to determine the potential causal impact of this ratio using data and genetic samples from TOPCAT, as well as novel statistical genomic methods including Mendelian Randomization.
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