肺腺癌患者差异甲基化区域分析

目的探讨DNA甲基化在肺腺癌发生中的作用机制。方法收集2019年1月至12月新疆肿瘤医院确诊的肺腺癌和正常对照者外周血各4例,850K芯片甲基化检测平台检测肺腺癌组与正常对照组甲基化区域,Bump hunter寻找两组差异区域。Gene Ontology数据库和KOBAS软件对差异区域对应目的基因进行GO分析和KEEG分析。结果1.共筛选出DMR-1、DMR-2、DMR-3、DMR-4、DMR-6(以上位于chr6),DMR-5(位于chr11)和DMR-7(位于chr20)(P<0.05)七组差异甲基化区域。DMR-1目的基因为HLA-DPB1、HLA-DPA1,DMR-2的为POU5F1,DMR-3的为RP5-1186N24.3、SCAND3,DMR-4的为ZFP57,DMR-5的为LDHC,DMR-6的为LTA,DMR-7的为OXT。其中HLA-DPB1、HLA-DPA1等为高甲基化,SCANDS3和LTA为低甲基化。2.GO分析表明目的基因主要在干扰素-γ、MHC-Ⅱ类复合物等功能中发挥重要作用。KEGG分析显示目的基因甲基化主要在Ⅰ型糖尿病、NF-κB信号通路中高度富集。结论1.肺腺癌患者DNA甲基化的状态可能是引起肺腺癌发生的关键因素,尤其是HLA-DP,POU5F1及LDHC的甲基化状态,在肺腺癌的发生中起着重要的作用。2.在GO功能和KEGG通路中,阐明了DNA甲基化异常导致疾病发展的作用机制。     

肺腺癌患者差异甲基化区域分析

目的探讨DNA甲基化在肺腺癌发生中的作用机制。方法收集2019年1月至12月新疆肿瘤医院确诊的肺腺癌和正常对照者外周血各4例,850K芯片甲基化检测平台检测肺腺癌组与正常对照组甲基化区域,Bump hunter寻找两组差异区域。Gene Ontology数据库和KOBAS软件对差异区域对应目的基因进行GO分析和KEEG分析。结果1.共筛选出DMR-1、DMR-2、DMR-3、DMR-4、DMR-6(以上位于chr6),DMR-5(位于chr11)和DMR-7(位于chr20)(P<0.05)七组差异甲基化区域。DMR-1目的基因为HLA-DPB1、HLA-DPA1,DMR-2的为POU5F1,DMR-3的为RP5-1186N24.3、SCAND3,DMR-4的为ZFP57,DMR-5的为LDHC,DMR-6的为LTA,DMR-7的为OXT。其中HLA-DPB1、HLA-DPA1等为高甲基化,SCANDS3和LTA为低甲基化。2.GO分析表明目的基因主要在干扰素-γ、MHC-Ⅱ类复合物等功能中发挥重要作用。KEGG分析显示目的基因甲基化主要在Ⅰ型糖尿病、NF-κB信号通路中高度富集。结论1.肺腺癌患者DNA甲基化的状态可能是引起肺腺癌发生的关键因素,尤其是HLA-DP,POU5F1及LDHC的甲基化状态,在肺腺癌的发生中起着重要的作用。2.在GO功能和KEGG通路中,阐明了DNA甲基化异常导致疾病发展的作用机制。     

应用MS-RDA筛选胃癌甲基化差异片段

目的:应用甲基化敏感性代表性差异分析法(methylation-sensitive representational difference analysis,MS-RDA)筛选胃癌和正常胃组织间甲基化差异DNA片段．方法:通过MS-RDA筛选胃癌和正常胃组织间DNA甲基化差异片段,经克隆、测序后进行生物信息学分析．结果:获得3个甲基化差异片段,分别为 CRS1308,CRS1309,CRS1310k列,其中 CRS1309和CRS1310已被GenBank收录,登陆亏分别为AY887106和AY887107,CRS1309 序列与LOC440683基因第11外显子、 LOC440887基因的3’端,DRD5基因启动子和外显子区域均有很高的相似性(分别为98％,99％, 94％),CRS1310序列与1999年Minoru Toyota在人类结肠癌中分离出的核糖体RNA上的甲基化差异性CpG岛有很高的相似性(98％)．结论:胃癌和正常胃组织间DNA甲基化存在差异,MS-RDA可有效分析这两种不同组织间甲基化的差异,筛选出有意义的甲基化差异片段.     

Isolation and bioinformatics analysis of differentially methylated genomic fragments in human gastric cancer

AIM：To isolate and analyze the DNA sequences which are methylated differentially between gastric cancer and normal gastric mucosa.
METHODS： The differentially methylated DNA sequences between gastric cancer and normal gastric mucosa were isolated by methylation-sensitive representational difference analysis （MS-RDA）. Similarities between the separated fragments and the human genomic DNA were analyzed with Basic Local Alignment Search Tool （BLAST）.
RESULTS： Three differentially methylated DNA sequences were obtained, two of which have been accepted by GenBank. The accession numbers are AY887106 and AY887107. AY887107 was highly similar to the 11th exon of LOC440683 （98%）, 3＇ end of LOC440887 （99%）, and promoter and exon regions of DRD5 （94%）. AY887106 was consistent （98%） with a CpG island in ribosomal RNA isolated from colorectal cancer by Minoru Toyota in 1999.
CONCLUSION： The methylation degree is different between gastric cancer and normal gastric mucosa. The differentially methylated DNA sequences can be isolated effectively by MS-RDA.     

The role of X-inactivation in the gender bias of patients with acquired α-thalassaemia and myelodysplastic syndrome (ATMDS)

Αlpha thalassaemia myelodysplastic syndrome (ATMDS) is an unusual complication of chronic myeloid malignancy that is associated with a striking red cell phenotype. It represents an acquired form of α-thalassaemia that most commonly arises in the context of myelodysplasia. It has recently been shown that this condition occurs in association with somatic mutations of a known X-encoded trans -acting regulator of α globin gene ( HBA ) expression, ATRX. There is an unexplained, strong male preponderance of individuals with the ATMDS phenotype with a >5:1 male–female ratio and furthermore, all the somatic ATRX mutations described to date have been in males. Here we report the identification, in a single centre, of two females with ATMDS and mutations in the ATRX gene, proving that ATMDS associated with such mutations may occur, albeit rarely, in females. It seemed possible that females might be less likely to develop ATMDS if the inactivated copy of the ATRX gene ( ATRX ) became progressively re-activated throughout life. This study ruled out this hypothesis by investigating the pattern of ATRX inactivation in a cross-sectional analysis of normal females at ages ranging from newborn to 90 years.     

Identification of tissue-specific cell death using methylation patterns of circulating DNA

Minimally invasive detection of cell death could prove an invaluable resource in many physiologic and pathologic situations. Cell-free circulating DNA (cfDNA) released from dying cells is emerging as a diagnostic tool for monitoring cancer dynamics and graft failure. However, existing methods rely on differences in DNA sequences in source tissues, so that cell death cannot be identified in tissues with a normal genome. We developed a method of detecting tissue-specific cell death in humans based on tissue-specific methylation patterns in cfDNA. We interrogated tissue-specific methylome databases to identify cell type-specific DNA methylation signatures and developed a method to detect these signatures in mixed DNA samples. We isolated cfDNA from plasma or serum of donors, treated the cfDNA with bisulfite, PCR-amplified the cfDNA, and sequenced it to quantify cfDNA carrying the methylation markers of the cell type of interest. Pancreatic β-cell DNA was identified in the circulation of patients with recently diagnosed type-1 diabetes and islet-graft recipients; oligodendrocyte DNA was identified in patients with relapsing multiple sclerosis; neuronal/glial DNA was identified in patients after traumatic brain injury or cardiac arrest; and exocrine pancreas DNA was identified in patients with pancreatic cancer or pancreatitis. This proof-of-concept study demonstrates that the tissue origins of cfDNA and thus the rate of death of specific cell types can be determined in humans. The approach can be adapted to identify cfDNA derived from any cell type in the body, offering a minimally invasive window for diagnosing and monitoring a broad spectrum of human pathologies as well as providing a better understanding of normal tissue dynamics.Cell death plays a critical role in the pathogenesis and therapy of a large number of diseases affecting every organ system in the body. Examples range from pancreatic β-cell death in type 1 diabetes (T1D) to neuronal death in neurodegenerative disease and after traumatic brain injury (TBI). In most cases, cell death can be measured only by its functional consequence: hyperglycemia or cognitive dysfunction in the examples given. These measures typically lack sensitivity, represent late phases of disease, and, in the case of T1D and neurologic disease, are often measurable only after potential therapeutic windows have been closed.It has been known for decades that plasma and serum contain small fragments of cell-free circulating DNA (cfDNA) derived from dead cells (on average, 5,000 genome equivalents/mL) (1). Although the mechanisms underlying the release and rapid clearance of cfDNA (2) remain obscure, the phenomenon is currently being exploited for a variety of applications with clinical relevance. The recognition that fragments of fetal DNA travel briefly in maternal circulation has opened the way for next-generation sequencing (NGS)-based prenatal testing to identify fetal trisomies and other genetic aberrations, potentially replacing invasive and potentially dangerous procedures such as amniocentesis (3–5). In cancer biology, tumors are known to release DNA (including tumor-specific somatic mutations) into the circulation, allowing tumor dynamics and genomic evolution to be monitored by liquid biopsies (6–8). In addition, cfDNA has been used to detect graft cell death after kidney, liver, or heart transplantation, based on SNPs that distinguish the DNA of the donor from that of the recipient (9–11). In all these cases, genetic differences exist between the DNA sequence of the tissue of interest (fetus, tumor, or graft) and that of the host, providing the basis for highly specific assays.Blood levels of cfDNA increase in many conditions, such as TBI (12), cardiovascular disease (13), sepsis (14), and intensive exercise (15). However, in these cases, the cfDNA sequence is identical to that of genomic DNA, making it impossible to use sequence variation to identify the source of the elevated cfDNA and thus greatly compromising the utility of cfDNA as a diagnostic or prognostic tool. For example, the cfDNA could originate from parenchymal cells of the injured tissue but also from dying inflammatory cells.Despite having an identical nucleotide sequence, the DNA of each cell type in the body carries unique methylation marks correlating with its gene-expression profile, and these marks represent a fundamental aspect of tissue identity. Methylation patterns are unique to each cell type, are conserved among cells of the same type in the same individual and among individuals, and are highly stable under physiologic or pathologic conditions (16). Therefore, it is possible to use the DNA methylation pattern of cfDNA to determine its tissue of origin and hence to infer cell death in the source organ.DNA methylation in cfDNA has been studied extensively but usually in the context of epigenetic aberrations unique to the specific pathology, such as abnormal methylation in promoters of tumor-suppressor genes, which may lead to insights into cancer biology (17–20). By contrast, our approach seeks to identify, in plasma or serum, the normal, stable methylation signature of a specific tissue as a sensitive biomarker of cell death. Therefore the approach can be applied to pathologies that retain a stable genome and epigenome.A classic example of tissue-specific DNA methylation is provided by the insulin gene (INS) promoter, which is unmethylated in insulin-producing pancreatic β cells and is methylated elsewhere. Recent studies have identified unmethylated INS promoter DNA in the circulation of patients with recently diagnosed T1D and in islet-graft recipients, likely reflecting both autoimmune and alloimmune destruction of β cells (21–25). However, published data suggest that the analytic approaches used were not sufficiently specific to differentiate robustly between β-cell– and non–β-cell–derived cfDNA. We sought to optimize the method and generalize the approach toward proof of the concept that tissue-specific methylation patterns in cfDNA can be used to detect tissue cell death with a high level of specificity and sensitivity in multiple human pathologies. Here we demonstrate the detection of cell death in different pathologies of the pancreas and the brain.     

甲基转移酶基因甲基化在结直肠肿瘤中的作用

目的探讨6氧甲基鸟嘌呤DNA甲基转移酶(MGMT)基因启动子CpG岛高甲基化在结直肠肿瘤发生、发展中的作用。方法用甲基特异性PCR检测20例正常大肠黏膜、27例散发性结直肠腺瘤和62例散发性结直肠腺癌组织DNA中MGMT基因启动子的甲基化,同时用免疫组化方法检测MGMT蛋白的表达情况。结果正常大肠黏膜组织均未显示甲基化条带,分别有40.7%(11/27)的腺瘤组织和43.5%(27/62)的腺癌组织存在MGMT基因启动子CpG岛高甲基化。正常大肠黏膜胞核和胞质表达MGMT蛋白,22.2%(6/27)的腺瘤和45.2%(28/62)的腺癌MGMT蛋白表达缺失,其差异有显著性(P=0.041)。6例MGMT表达缺失的腺瘤中5例存在甲基化(P=0.027),28例表达缺失的腺癌中24例存在甲基化(P<0.001)。结论结直肠肿瘤中存在高频率MGMT基因启动子高甲基化和蛋白表达缺失,腺癌中蛋白表达缺失比腺瘤中更常见。MGMT蛋白表达缺失与MGMT基因启动子区域高甲基化有关。MGMT基因表型遗传性失活可能在结直肠肿瘤发生过程中起重要作用。     

TLC-based detection of methylated cytosine: application to aging epigenetics

5-Methylcytosine (m⁵C) has a plethora of functions and roles in various biological processes including human diseases and aging. A TLC-based fast and simple method for quantitative determination of total genomic levels of m⁵C in DNA is described, which can be applicable to aging research with respect to rapid and high throughput screening and comparison. Using this method, an example of the analysis of global alternations of m⁵C in serially passaged human skin fibroblasts is provided, which shows age-related global hypomethylation during cellular aging in vitro. This method can be useful for screening potential modulators of aging at the level of epigenetic alterations.     

实验性肝纤维化大鼠肝组织CTGF基因DNA甲基化的变化

目的：研究实验性肝纤维化大鼠肝组织结缔组织生长因子（CTGF）启动子DNA甲基化变化及其对CTGF基因表达的影响。方法建立大鼠四氯化碳肝纤维化模型,以HE染色和Sirius red染色评估大鼠肝组织学变化;采用RT-PCR和Western blot法分别检测肝组织CTGF mRNA和蛋白质表达;采用亚硫酸氢盐修饰后测序评估肝组织CTGF基因DNA甲基化水平变化。结果在皮下注射四氯化碳6周时模型组大鼠肝组织呈III级纤维化改变;模型组大鼠肝组织CTGF mRNA及蛋白表达分别为（1.581±0.276）和（0.875±0.102）,均显著高于正常对照组分别为（0.415±0.041）和（0.115±0.083）,（P值均＆lt;0.01）;模型组CTGF基因启动子DNA甲基化率为（1.8±1.8）%,显著低于对照组（11.6±3.8）%,（P＜0.01）。结论肝纤维化大鼠肝组织CTGF基因表达上调,其机制可能与CTGF基因DNA低甲基化改变相关。     

The CEBPA gene is down-regulated in acute promyelocytic leukemia and its upstream promoter, but not the core promoter, is highly methylated

Impairment of CCAAT Enhancer Binding Protein alpha (CEBPA) function is a common finding in acute myeloid leukemia; nevertheless, its relevance for acute promyelocytic leukemia pathogenesis is unclear. We analyzed the expression and assessed the methylation status of the core and upstream promoters of CEBPA in acute promyelocytic leukemia at diagnosis. Patients with acute promyelocytic leukemia (n = 18) presented lower levels of CEBPA expression compared to healthy controls (n = 5), but higher levels than those in acute myeloid leukemia with t(8;21) (n = 9) and with inv(16) (n = 5). Regarding the core promoter, we detected no methylation in 39 acute promyelocytic leukemia samples or in 8 samples from controls. In contrast, analysis of the upstream promoter showed methylation in 37 of 39 samples, with 17 patients showing methylation levels over 30%. Our results corroborate data obtained in animal models showing that CEBPA is down-regulated in acute promyelocytic leukemia stem cells and suggest that epigenetic mechanisms may be involved.     

Associations between changes in the maternal gut microbiome and differentially methylated regions of diabetes‐associated genes in fetuses: A pilot study from a birth cohort study

Several intrauterine environmental factors can increase the future risk of type 2 diabetes. The microbiome can influence the balance between health and disease. However, the influence of the maternal gut microbiome on the future risk of diabetes in the fetus is unknown. The present study investigated the associations between maternal gut microbiome and differentially methylated regions of diabetes‐associated genes in umbilical cord samples. The present study included 10 pregnant participants from a birth cohort study. 16S ribosomal ribonucleic acid metagenome analysis of maternal stool samples and deoxyribonucleic acid methylation assays of umbilical cord samples were carried out. The present study found that changes in the UBE2E2 and KCNQ1 methylation rates in umbilical cord samples were associated with the proportion of Firmicutes in the maternal gut, albeit with marginal correlations after adjustment for age and body mass index. These findings suggest a link between the methylation of diabetes‐associated genes in fetuses and maternal microbiota components during pregnancy.     

联合应用地西他滨和ATRA对白血病细胞p21~(CIP1)和p57~(KIP2)基因启动子区域甲基化的影响

目的:研究白血病患者和白血病细胞株中p21CIP1和p57KIP2基因启动子区域甲基化水平,应用地西他滨(DAC)或联合ATRA对白血病细胞生长抑制及甲基化水平改变的影响。方法:选取白血病细胞株HL60和Molt4及ALL患者骨髓细胞,测定p21CIP1和p57KIP2基因启动子区域甲基化,检测使用DAC或联合ATRA对白血病细胞株生存的影响、p21CIP1和p57KIP2基因甲基化改变和细胞周期改变。结果:不同浓度的DAC和ATRA培养,表现出对细胞的生长抑制作用;ALL患者p57KIP2治疗前后均为高甲基化状态,而p21CIP1治疗前后均为低甲基化。Molt4和HL60的p57KIP2为高甲基化状态,DAC处理使2种细胞p57KIP2甲基化明显降低(P<0.01或P<0.05);DAC联合ATRA处理2种细胞株,p57KIP2甲基化状态均明显减低(P<0.01)。Molt4细胞对照组的p21CIP1为低甲基化状态,以DAC或DAC加ATRA处理可以使甲基化水平降低(P<0.05);HL60细胞对照组p21CIP1为高甲基化状态,以DAC或DAC加ATRA处理使p21CIP1低甲基化(P<0.01)。联合上...     

Epigenetic-based age acceleration in a representative sample of older Americans: Associations with aging-related morbidity and mortality

Biomarkers developed from DNA methylation (DNAm) data are of growing interest as predictors of health outcomes and mortality in older populations. However, it is unknown how epigenetic aging fits within the context of known socioeconomic and behavioral associations with aging-related health outcomes in a large, population-based, and diverse sample. This study uses data from a representative, panel study of US older adults to examine the relationship between DNAm-based age acceleration measures in the prediction of cross-sectional and longitudinal health outcomes and mortality. We examine whether recent improvements to these scores, using principal component (PC)-based measures designed to remove some of the technical noise and unreliability in measurement, improve the predictive capability of these measures. We also examine how well DNAm-based measures perform against well-known predictors of health outcomes such as demographics, SES, and health behaviors. In our sample, age acceleration calculated using “second and third generation clocks,” PhenoAge, GrimAge, and DunedinPACE, is consistently a significant predictor of health outcomes including cross-sectional cognitive dysfunction, functional limitations and chronic conditions assessed 2 y after DNAm measurement, and 4-y mortality. PC-based epigenetic age acceleration measures do not significantly change the relationship of DNAm-based age acceleration measures to health outcomes or mortality compared to earlier versions of these measures. While the usefulness of DNAm-based age acceleration as a predictor of later life health outcomes is quite clear, other factors such as demographics, SES, mental health, and health behaviors remain equally, if not more robust, predictors of later life outcomes.

Cellular alterations and damage are important biological determinants of age-related health (1–3). Biomarkers based on DNA methylation (DNAm) are of growing interest as predictors of health outcomes in older populations because DNAm is thought to be influenced by external exposures, modifying the expression of genes and potentially resulting in an increased risk of morbidity and mortality (3–5).Epigenetic “clocks” are estimations of “biological” age derived from DNAm patterns associated with markers of aging (4, 6). Initially, these measures, more generally called DNAm surrogates, were developed by identifying DNAm patterns associated with chronological age, such as the Horvath and Hannum clocks (6, 7). More recent epigenetic measures, known as the “second and third generation clocks,” focus on DNAm patterns associated with aging phenotypes, health risks, mortality, or change in health indicators, including GrimAge, PhenoAge and DunedinPACE (8–10). Some have also examined methylation as a mechanism or biomarker of how social influences lead to later life health disparities (11, 12). As the number of these epigenetic clocks expands, studies have compared multiple epigenetic clocks to each other and to risk factors associated with poor health at older ages (13–16). Within the same study population, wide variations in correlation between the individual clocks and chronological aging, as well as differences in the association between individual clocks and demographic characteristics, have been observed (13) and underscore the importance of understanding how these measures compare in predicting age-related health outcomes.One potential contributor to the variation in associations between the clocks and demographic characteristics as well as health outcomes might be the underlying technical noise in the measurement of DNAm. Previous studies using technical duplicates have shown that a significant number of CpG methylation sites, regions of DNA where a cytosine nucleotide is followed by a guanine nucleotide, are not measured reliably using methylation arrays (17–20). This measurement error is largely still present after post-processing quality control and adjustment for batch effects and has been found in samples using both the Illumina 450K and EPIC arrays (21–23). This measurement error has important implications for use in research on biological aging and health prediction. Fortunately, computational methods have been developed to partially correct for this variation by extracting the age-related signal across probes using principal components (PCs) thereby minimizing noise from individual CpG sites (24).Socioeconomic and behavioral factors are major determinants of health and accelerated aging over the life course, with individuals of lower status at greater risk of morbidity and mortality (25, 26). However, the utility of epigenetic measures of aging in predicting the most important set of age-related health outcomes in conjunction with socioeconomic factors in a large, representative sample of older persons is unknown. Epigenetic age acceleration measures may provide information on the biological context associated with aging not captured by demographics or in self-reported health assessments. To address these knowledge gaps, this study had two aims; the first aim was to examine the association between five commonly used epigenetic age acceleration measures [first generation: Horvath (6), Hannum (7); second generation: PhenoAge 2018 (10), GrimAge 2019 (9); and third generation: DunedinPACE 2022 (27)] and health outcomes linked to age, some cross-sectional and some longitudinal, as well as to evaluate these same relationships using new PC-trained measures. The second aim was to determine how epigenetic aging fits within the context of known socioeconomic and behavioral associations with aging-related health outcomes in a representative panel survey of older adults in the United States. We hypothesized that the second and third generation measures, those trained on phenotypic outcomes other than age, would be better predictors of health outcomes associated with aging, including mortality, and that PC-trained measures would predict better than the original measures.     

Epigenetic regulation of Kiss1 gene expression mediating estrogen-positive feedback action in the mouse brain

This study aims to determine the epigenetic mechanism regulating Kiss1 gene expression in the anteroventral periventricular nucleus (AVPV) to understand the mechanism underlying estrogen-positive feedback action on gonadotropin-releasing hormone/gonadotropin surge. We investigated estrogen regulation of the epigenetic status of the mouse AVPV Kiss1 gene locus in comparison with the arcuate nucleus (ARC), in which Kiss1 expression is down-regulated by estrogen. Histone of AVPV Kiss1 promoter region was highly acetylated, and estrogen receptor α was highly recruited at the region by estrogen. In contrast, the histone of ARC Kiss1 promoter region was deacetylated by estrogen. Inhibition of histone deacetylation up-regulated in vitro Kiss1 expression in a hypothalamic non-Kiss1-expressing cell line. Gene conformation analysis indicated that estrogen induced formation of a chromatin loop between Kiss1 promoter and the 3' intergenic region, suggesting that the intergenic region serves to enhance estrogen-dependent Kiss1 expression in the AVPV. This notion was proved, because transgenic reporter mice with a complete Kiss1 locus sequence showed kisspeptin neuron-specific GFP expression in both the AVPV and ARC, but the deletion of the 3' region resulted in greatly reduced GFP expression only in the AVPV. Taken together, these results demonstrate that estrogen induces recruitment of estrogen receptor α and histone acetylation in the Kiss1 promoter region of the AVPV and consequently enhances chromatin loop formation of Kiss1 promoter and Kiss1 gene enhancer, resulting in an increase in AVPV-specific Kiss1 gene expression. These results indicate that epigenetic regulation of the Kiss1 gene is involved in estrogen-positive feedback to generate the gonadotropin-releasing hormone/gonadotropin surge.     

Association of AGTR1 gene methylation and its genetic variant in Chinese farmer with hypertension: A case-control study

The objective was to determine the potential associations of the angiotensin II receptor type 1 (AGTR1) gene polymorphism, methylation, and lipid metabolism in Chinese farmers with hypertension.A case-control study was conducted in Wuzhi county of Henan province in China in 2013 to 2014. A total of 1034 local residents (35–74 years, 386 hypertensive cases, and 648 normotensive subjects) were enrolled in this study. Triglyceride (TG), total cholesterol (TC), high-density lipoprotein, and low-density lipoprotein were measured using automatic chemistry analyzer. The AGTR1 gene promoter methylation level was measured using quantitative methylation-specific polymerase chain reaction method. The single nucleotide polymorphism rs275653 was genotyped with TaqMan probe assay at an applied biosystems platform.The gender, body mass index (BMI), TG, TC, and family history of hypertension in the hypertension group were significantly higher than those in control group (P < .05). No significant difference was observed in the distribution of AGTR1 rs275653 polymorphism in the hypertension and controls (P > .05). The AGTR1 gene methylation in subjects carrying different genotypes was not significantly observed (P > .05). The logistic regression analysis found the AGTR1 gene methylation level was negative correlation with hypertension in the present study (odds ratio, 0.946, 95% confidence interval, 0.896–0.999) through adjusting for age, gender, BMI, education, smoking, alcohol drinking, fruit and vegetable intake, pickles intake, and family history of hypertension.The association of AGTR1 gene hypomethylation and essential hypertension was observed in Chinese farmers; no significant difference was observed in the distribution of AGTR1 rs275653 polymorphism.