Acute coronary syndromes (ACS) remain a major cause of worldwide mortality. ACS diagnosis is done by a combination of factors, such as electrocardiogram and plasma biomarkers. These biomarkers, however, lack the power to accurately stratify patients into different risk groups. Instead, we used changes in the circulating cell-free DNA (ccfDNA) methylation profiles to estimate the extent of heart injury and the severity of ACS. Our approach relies on the fact that dying cells in acutely damaged tissue release DNA into the blood, causing an increase in the ccfDNA. In addition, each cell type has a distinct DNA methylation profile. We leverage cell type/state specificity of DNA methylation to deconvolute the cell types of origin for ccfDNA and also find DNA methylation-based biomarkers that stratify patient cohorts. The cohorts consisted of healthy subjects, and patients from three ACS conditions: ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI) and unstable angina (UA). We have used two cohorts of patients - discovery, and validation, both consisting of the same conditions. We have sequenced the ccfDNA from the discovery cohort using Whole Bisulfite Genome Sequencing (WBGS), to obtain an unbiased overview of plasma DNA methylation profiles. We have found a total of 1,614 differential methylated regions (DMRs) in the three ACS groups. Many of the regions are associated with genes involved in cardiovascular conditions and inflammation. Using linear models, we were able to narrow down to 254 DMRs significantly associated with ACS severity. The reduced list of DMRs enabled a more accurate stratification of ACS patients. The predictive power of the DMRs was validated in the confirmation cohort using targeted methylation sequencing of the validation cohort.

中文翻译：

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源自循环无细胞 DNA 甲基化的心血管疾病生物标志物

急性冠状动脉综合征 (ACS) 仍然是全球死亡的主要原因。ACS 诊断是通过多种因素的组合完成的，例如心电图和血浆生物标志物。然而，这些生物标志物缺乏将患者准确地分为不同风险组的能力。相反，我们使用循环无细胞 DNA (ccfDNA) 甲基化谱的变化来估计心脏损伤的程度和 ACS 的严重程度。我们的方法依赖于这样一个事实，即严重受损组织中的垂死细胞将 DNA 释放到血液中，导致 ccfDNA 增加。此外，每种细胞类型都有不同的 DNA 甲基化谱。我们利用 DNA 甲基化的细胞类型/状态特异性来解卷积 ccfDNA 的细胞类型，并找到基于 DNA 甲基化的生物标志物来对患者群体进行分层。队列由健康受试者和来自三种 ACS 病症的患者组成：ST 段抬高型心肌梗死 (STEMI)、非 ST 段抬高型心肌梗死 (NSTEMI) 和不稳定型心绞痛 (UA)。我们使用了两组患者——发现组和验证组，两者都由相同的条件组成。我们使用全亚硫酸氢盐基因组测序 (WBGS) 对发现队列中的 ccfDNA 进行了测序，以获得血浆 DNA 甲基化谱的公正概览。我们在三个 ACS 组中总共发现了 1,614 个差异甲基化区域 (DMR)。许多区域与参与心血管疾病和炎症的基因有关。使用线性模型，我们能够缩小到 254 个与 ACS 严重程度显着相关的 DMR。减少的 DMR 列表能够更准确地对 ACS 患者进行分层。使用验证队列的靶向甲基化测序在确认队列中验证了 DMR 的预测能力。