Novel ECG Measures and Risk of Sudden Cardiac Death

描述（由申请人提供）：心源性猝死（SCD）是一个主要的公共卫生问题，在美国每年有40万人死亡。临床和尸检研究一致证明了西方人群中主要的、常见的病理生理，表明SCD最常见的电生理机制是心室颤动（VF），最常见的病理底物是冠心病（CHD）。在大约一半的SCD病例中，死亡是冠心病的第一个临床表现。然而，在SCD易感性的自然病史中早期SCD的危险因素尚未完全确定，并且在一般人群中尚未制定SCD风险分层策略。心电图是一种容易获得、不昂贵和无创的工具，它携带有价值的心脏电生理特性信息。然而，传统的心电图分析对致心律失常底物的评估非常有限。最近，我们开发了一种新的12导联心电图SCD风险评分，由以下参数组成：(1)传导缓慢中断，(2)颞复极不稳定性，(3)不良电重构。社区动脉粥样硬化（ARIC）研究的初步性别、种族和年龄匹配病例对照分析显示，与单独的Framingham风险评分相比，总持续净重分类改善率为86.0%。我们假设：(1)由静息12导联心电图分析中得出的致心律失常底物的机制心电图标志物组成的“SCD心电图危险评分”准确地将人划分为高、中、低危险组，与传统的基于冠心病危险因素的危险分层相比，分级更加完善；(2)新型ECG表型的遗传因素与SCD风险增加有关。这一应用弥补了对SCD机制和普通人群中SCD风险分层的理解之间的关键差距。我们将利用2个独特的大型美国国立卫生研究院资助的前瞻性社区住宅GWAS队列和可用的数字12导联心电图存储库：ARIC和CHS。基线数字12导联心电图将在PI实验室使用定制的Matlab软件进行分析。SCD心电图风险评分将在ARIC中开发，并在CHS队列中验证。将评估净改级改进情况。在第5次ARIC就诊时通过超声心动图评估，研究心电图参数在20年随访期间的纵向变化将作为心脏结构和功能表型的预测因子。我们的研究将确定与特定ECG特征相关的基因，这将导致新的治疗靶点，并在未来实现SCD的预防。

DESCRIPTION (provided by applicant): Sudden cardiac death (SCD) is a major public health concern, accounting for 400,000 deaths in the US each year. Clinical and autopsy studies have consistently demonstrated a predominant, common pathophysiology in Western populations, showing that the most common electro-physiologic mechanism for SCD is ventricular fibrillation (VF) and the most common pathologic substrate is coronary heart disease (CHD). In about half of SCD cases, death is the first clinical manifestation of CHD. Yet risk factors of SCD early in the natural history of conditions predisposing SCD have not been fully identified, and SCD risk stratification strategy in general population has not been developed. ECG is easy available, non-expensive and non- invasive tool, which carries valuable information on electrophysiological properties of the heart. However, traditional analysis of ECG includes very limited assessment of the arrhythmogenic substrate. Recently we developed novel 12-lead ECG SCD risk score, composed of parameters that measure (1) slow discontinued conduction, (2) temporal repolarization lability, and (3) adverse electrical remodeling. Preliminary gender-, race-, and age-matched case-control analysis of the Atherosclerosis In Community (ARIC) study showed a total continuous net reclassification improvement of 86.0% as compared to the Framingham risk score alone. We hypothesize that (1) the "SCD ECG risk score", comprised of the mechanistic ECG markers of arrhythmogenic substrate derived in the resting 12-lead ECG analysis accurately stratify persons into high-, intermediate- and low-risk groups and improve classification in comparison to the risk stratification on the basis of traditional CHD risk factor; (2) heritable factors of the novel ECG phenotype are associated with the increased SCD risk. This application bridges a critical gap between understanding of the SCD mechanisms and SCD risk stratification in a general population. We will leverage 2 unique large NIH-funded prospective community-dwelling GWAS cohorts with an available digital 12-lead ECG repository: ARIC and CHS. Baseline digital 12-lead ECG will be analyzed by customized Matlab software in PI's laboratory. The SCD ECG risk score will be developed in ARIC and validated in the CHS cohort. Net reclassification improvement will be assessed. Longitudinal changes in studied ECG parameters over 20 years of follow-up will be evaluated as predictors of cardiac structural and functional phenotype, assessed by echocardiography at the 5th ARIC visit. Our study will identify genes, associated with specific ECG traits, which will lead to novel targets fo treatments and in the future will enable SCD prevention.