National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Fuwai Hospital, National Center for Cardiovascular Diseases, 167 Beilishi Road, Beijing, 100037, People's Republic of China.
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, People's Republic of China.
BMC Cardiovasc Disord. 2021 May 12;21(1):240. doi: 10.1186/s12872-021-02001-w.
Systemic studies of association of genome-wide DNA methylated sites with cardiovascular disease (CVD) in prospective cohorts are lacking. Our aim was to identify DNA methylation sites associated with the risk of CVD and further investigate their potential predictive value in CVD development for high-risk subjects.
We performed an epigenome-wide association study (EWAS) to identify CpGs related to CVD development in a Chinese population.We adopted a nested case-control design based on data from China PEACE Million Persons Project. A total of 83 cases who developed CVD events during follow-up and 83 controls who were matched with cases by age, sex, BMI, ethnicity, medications treatment and behavior risk factors were included in the discovery stage. Genome-wide DNA methylation from whole blood was detected using Infinium Human Methylation EPIC Beadchip (850 K). For significant CpGs [FDR(false discovery rate) < 0.005], we further validated in an independent cohort including 38 cases and 38 controls.
In discovery set, we identified 8 significant CpGs (FDR < 0.005) associated with the risk of CVD after adjustment for cell components, demographic and cardiac risk factors and the first 5 principal components. Two of these identified CpGs (cg06901278 and cg09306458 in UACA) were replicated in another independent set (p < 0.05). Enrichment analysis in 787 individual genes from 1036 CpGs in discovery set revealed a significant enrichment for anatomical structure homeostasis as well as regulation of vesicle-mediated transport. Receiver operating characteristic (ROC) analysis showed that the model combined 8 CVD-related CpGs with baseline characteristics showed much better predictive effect for CVD occurrence compared with the model with baseline characteristics only [AUC (area under the curve) = 0.967, 95% CI (0.942 - 0.991); AUC = 0.621, 95% CI (0.536 - 0.706); p = 9.716E-15].
Our study identified the novel CpGs associated with CVD development and revealed their additional predictive power in the risk of CVD for high-risk subjects.
缺乏全基因组 DNA 甲基化位点与前瞻性队列中心血管疾病 (CVD) 关联的系统研究。我们的目的是确定与 CVD 风险相关的 DNA 甲基化位点,并进一步研究其在 CVD 高危人群发展中的潜在预测价值。
我们进行了一项基于中国 PEACE 百万人群项目数据的表观基因组关联研究 (EWAS),以确定与 CVD 发展相关的 CpG。我们采用了基于病例的巢式病例对照设计。在随访期间发生 CVD 事件的 83 例病例和与病例按年龄、性别、BMI、种族、药物治疗和行为危险因素相匹配的 83 例对照纳入发现阶段。使用 Infinium Human Methylation EPIC Beadchip (850K) 检测全血的全基因组 DNA 甲基化。对于具有统计学意义的 CpG[FDR(false discovery rate) < 0.005],我们在包括 38 例病例和 38 例对照的另一个独立队列中进一步进行了验证。
在发现组中,我们鉴定了 8 个与 CVD 风险相关的显著 CpG(FDR < 0.005),这些 CpG 经过细胞成分、人口统计学和心脏危险因素以及前 5 个主成分调整后仍然具有统计学意义。在另一个独立队列中,鉴定出的这两个 CpG(cg06901278 和 cg09306458 在 UACA 中)具有统计学意义(p < 0.05)。在发现组中,对 1036 个 CpG 中的 787 个个体基因进行富集分析,发现其显著富集了解剖结构稳态以及囊泡介导的运输调节。接收者操作特征 (ROC) 分析表明,与仅使用基线特征的模型相比,组合了 8 个与 CVD 相关的 CpG 与基线特征的模型对 CVD 发生具有更好的预测效果 [AUC (曲线下面积) = 0.967,95%CI (0.942-0.991); AUC = 0.621,95%CI (0.536-0.706); p = 9.716E-15]。
本研究确定了与 CVD 发展相关的新型 CpG,并揭示了其在 CVD 高危人群中 CVD 风险预测中的额外预测能力。