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基于中国同卵双胞胎的全基因组关联研究鉴定出与血压相关的 DNA 甲基化位点。

Epigenome-wide association study in Chinese monozygotic twins identifies DNA methylation loci associated with blood pressure.

机构信息

Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China.

Jiangsu Health Development Research Center, Nanjing, Jiangsu, China.

出版信息

Clin Epigenetics. 2023 Mar 3;15(1):38. doi: 10.1186/s13148-023-01457-1.

DOI:10.1186/s13148-023-01457-1
PMID:36869404
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9985232/
Abstract

BACKGROUND

Hypertension is a crucial risk factor for developing cardiovascular disease and reducing life expectancy. We aimed to detect DNA methylation (DNAm) variants potentially related to systolic blood pressure (SBP) and diastolic blood pressure (DBP) by conducting epigenome-wide association studies in 60 and 59 Chinese monozygotic twin pairs, respectively.

METHODS

Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing, yielding 551,447 raw CpGs. Association between DNAm of single CpG and blood pressure was tested by applying generalized estimation equation. Differentially methylated regions (DMRs) were identified by comb-P approach. Inference about Causation through Examination of Familial Confounding was utilized to perform the causal inference. Ontology enrichment analysis was performed using Genomic Regions Enrichment of Annotations Tool. Candidate CpGs were quantified using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data.

RESULTS

The median age of twins was 52 years (95% range 40, 66). For SBP, 31 top CpGs (p < 1 × 10) and 8 DMRs were identified, with several DMRs within NFATC1, CADM2, IRX1, COL5A1, and LRAT. For DBP, 43 top CpGs (p < 1 × 10) and 12 DMRs were identified, with several DMRs within WNT3A, CNOT10, and DAB2IP. Important pathways, such as Notch signaling pathway, p53 pathway by glucose deprivation, and Wnt signaling pathway, were significantly enriched for SBP and DBP. Causal inference analysis suggested that DNAm at top CpGs within NDE1, MYH11, SRRM1P2, and SMPD4 influenced SBP, while SBP influenced DNAm at CpGs within TNK2. DNAm at top CpGs within WNT3A influenced DBP, while DBP influenced DNAm at CpGs within GNA14. Three CpGs mapped to WNT3A and one CpG mapped to COL5A1 were validated in a community population, with a hypermethylated and hypomethylated direction in hypertension cases, respectively. Gene expression analysis by WGCNA further identified some common genes and enrichment terms.

CONCLUSION

We detect many DNAm variants that may be associated with blood pressure in whole blood, particularly the loci within WNT3A and COL5A1. Our findings provide new clues to the epigenetic modification underlying hypertension pathogenesis.

摘要

背景

高血压是导致心血管疾病和缩短预期寿命的关键风险因素。我们旨在通过对 60 对和 59 对中国同卵双胞胎分别进行全基因组范围内的关联研究,检测与收缩压(SBP)和舒张压(DBP)相关的 DNA 甲基化(DNAm)变异。

方法

使用简化代表性亚硫酸氢盐测序对双胞胎的全血进行全基因组 DNA 甲基化谱分析,产生 551,447 个原始 CpG。通过应用广义估计方程来测试单个 CpG 的 DNAm 与血压之间的关联。通过组合 P 方法识别差异甲基化区域(DMR)。通过检查家族性混杂的因果推断,利用因果推断通过检查家族性混杂的方法进行因果推断。使用基因组区域注释工具进行本体论富集分析。使用社区人群中的 Sequenom MassARRAY 平台对候选 CpG 进行定量。使用基因表达数据进行加权基因共表达网络分析(WGCNA)。

结果

双胞胎的中位年龄为 52 岁(95%范围 40,66)。对于 SBP,鉴定出 31 个 top CpG(p < 1 × 10)和 8 个 DMR,其中一些 DMR 位于 NFATC1、CADM2、IRX1、COL5A1 和 LRAT 内。对于 DBP,鉴定出 43 个 top CpG(p < 1 × 10)和 12 个 DMR,其中一些 DMR 位于 WNT3A、CNOT10 和 DAB2IP 内。Notch 信号通路、葡萄糖剥夺时的 p53 通路和 Wnt 信号通路等重要途径对 SBP 和 DBP 均有明显富集。因果推断分析表明,NDE1、MYH11、SRRM1P2 和 SMPD4 内的 top CpG 的 DNAm 影响 SBP,而 SBP 影响 TNK2 内的 CpG 的 DNAm。WNT3A 内的 top CpG 的 DNAm 影响 DBP,而 DBP 影响 GNA14 内的 CpG 的 DNAm。在一个社区人群中验证了三个位于 WNT3A 内和一个位于 COL5A1 内的 CpG,在高血压病例中分别呈高甲基化和低甲基化方向。WGCNA 的基因表达分析进一步确定了一些共同的基因和富集术语。

结论

我们在全血中检测到许多可能与血压相关的 DNAm 变异,特别是 WNT3A 和 COL5A1 内的基因座。我们的发现为高血压发病机制的表观遗传修饰提供了新的线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f44e/9985232/e44c449d570a/13148_2023_1457_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f44e/9985232/fa81cedadbf7/13148_2023_1457_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f44e/9985232/e44c449d570a/13148_2023_1457_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f44e/9985232/fa81cedadbf7/13148_2023_1457_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f44e/9985232/e44c449d570a/13148_2023_1457_Fig2_HTML.jpg

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