OBJECTIVE: To investigate the whole-genome differential methylation profile of patients with high-altitude polycythemia (HAPC). METHODS: In this study, a total of 20 adult male patients with HAPC were included, including 10 Tibetan and 10 Han patients. The control group consisted of 20 healthy adult males, including 10 Tibetan and 10 Han patients. Peripheral blood was collected from each group for DNA extraction and quality inspection, and DNA libraries were constructed. The differential methylation regions (DMRs) between groups were detected using reduced representation bisulfite sequencing, with enriched regions compared to those of the control group. The differential enrichment regions were selected, and the intersection of the enriched regions was associated with genes. The methylation enrichment regions that differed significantly between groups were filtered based on the number of enriched samples in the enriched regions between the groups. GO, KEGG functional, and pathway analysis were performed on the differentially associated gene sets to reveal significant differences between the patients and control groups at the functional and pathway levels. RESULTS: In comparison with the control group, 17 152 sites with more than 25% difference and 15 558 sites with less than -25% difference were identified in Tibetan patients. The top 5 genes with the largest methylation differences between the two groups were MCCC2, RP3-399L15.3, ZNF621, RP11-394A14.2 and SLC39A10. The top significantly different pathways annotated in the differentially expressed genes pathway was serotonergic synapse. In comparison with the control group, 2 687 CpG sites with a greater than 25% difference and 2 602 CpG sites with a less than -25% difference were identified in Han patients. The top 5 genes with the largest methylation differences between the two groups were NAA25, CORO2B, PDC, ZNF853, and MLLT10. The top significantly different pathways annotated in the differentially expressed genes pathway were glutamatergic synapse, retrograde endocannabinoid signaling, Rap1 signaling pathway and cholinergic synapse. In comparison with the control group, 3 895 CpG sites with a greater than 25% difference and 3 969 CpG sites with a less than -25% difference were identified in HAPC patients. The maximum methylation difference between the two groups could reach 78.1%, while the minimum was -42.6%. The top 5 genes with the largest methylation differences between the two groups were MCCC2, ARSJ, CTNNA3, SLC39A10, and SWAP70. The top significantly different pathways annotated in the differentially expressed genes pathway was signaling pathways regulating pluripotency of stem cells. CONCLUSION The occurrence of HAPC may be related to abnormal changes in DNA methylation, and methylation sites may be helpful for the early diagnosis of HAPC.
Humans ; DNA Methylation ; Altitude ; Polycythemia/genetics* ; Male ; Adult ; CpG Islands

OBJECTIVES: To investigate the association between methylation levels of tumor suppressing subtransferable candidate 1 (TSSC1) and melanophilin (MLPH) genes in peripheral blood and coronary heart disease (CHD) in Chinese population. METHODS: This case-control study was conducted in 86 CHD patients and 95 healthy individuals, whose methylation levels of TSSC1 and MLPH genes in peripheral blood were determined using mass spectrometry. Mann-Whitney U test was used to compare the methylation levels in different subgroups. The correlation of TSSC1 and MLPH gene methylation levels with age and gender were evaluated using Spearman correlation coefficient and contingency coefficient, respectively. RESULTS: Compared with the healthy individuals, the CHD patients showed a significant correlation between MLPH hypermethylation and myocardial infarction (MI) (MLPH_CpG_2.7: P=0.045; MLPH_CpG_3/cg06639874: P=0.049; MLPH_CpG_5: P=0.019), and this correlation was even stronger in individuals below 65 years of age (MLPH_CpG_2.7: P=0.014; MLPH_CpG_4: P=0.001) and in male subjects (MLPH_CpG_2.7: P=0.004; MLPH_CpG_3/cg06639874: P=0.044). The methylation level of TSSC1 gene in peripheral blood was not found to correlate with CHD or its subtypes. CONCLUSIONS Our findings suggest a correlation of MLPH hypermethylation in peripheral blood with CHD and MI in Chinese population, especially in individuals below 65 years and in male individuals.
Humans ; DNA Methylation ; Male ; Female ; Middle Aged ; Case-Control Studies ; Aged ; Coronary Disease/blood* ; Adult ; CpG Islands

OBJECTIVES: To evaluate the forensic application value of an age estimation model based on DNA methylation in eastern Chinese Han population, and to provide a theoretical basis for exploring age estimation models suitable for different detection platforms. METHODS: According to the 6 age-related methylation sites in the published blood DNA methylation age estimation models of Chinese Han population, the DNA methylation level of 48 samples was detected by pyrosequencing and next-generation sequencing (NGS). After submitting DNA methylation levels to the age estimation model, the DNA methylation ages were predicted and compared with their real ages. RESULTS: The 6 DNA methylation sites in both detection techniques were age-related, with an R² of 0.85 and a median absolute deviation (MAD) of 4.81 years when using pyrosequencing；with an R² of 0.84 and MAD of 4.41 years when using NGS. CONCLUSIONS The blood DNA methylation age estimation model can be used under pyrosequencing and multi-purpose regional methylation enrichment sequencing technology based on NGS and it can accurately estimate the age.
Humans ; Aging/genetics* ; CpG Islands ; DNA Methylation ; East Asian People ; Forensic Genetics/methods*

Age estimation based on tissues or body fluids is an important task in forensic science. The changes of DNA methylation status with age have certain rules, which can be used to estimate the age of the individuals. Therefore, it is of great significance to discover specific DNA methylation sites and develop new age estimation models. At present, statistical models for age estimation have been developed based on the rule that DNA methylation status changes with age. The commonly used models include multiple linear regression model, multiple quantile regression model, support vector machine model, artificial neural network model, random forest model, etc. In addition, there are many factors that affect the level of DNA methylation, such as the tissue specificity of methylation. This paper reviews these modeling methods and influencing factors for age estimation based on DNA methylation, with a view to provide reference for the establishment of age estimation models.
Humans ; DNA Methylation ; CpG Islands ; Forensic Genetics ; Neural Networks, Computer ; Linear Models ; Aging/genetics*

With the improvement of DNA methylation detection techniques, studies on age-related methylation sites have found more age-specific ones across tissues, which improves the sensitivity and accuracy of age estimation. In addition, the establishment of various statistical models also provides a new direction for the age estimation of tissues from different sources. This review summarizes the related studies of age estimation based on DNA methylation from the aspects of detection technology, age-related cytosine phosphate guanine site and model selection in recent years.
DNA Methylation ; Forensic Genetics/methods* ; CpG Islands ; Forensic Medicine

Objective: To investigate the type, length, and CG loci of HBV DNA CpG islands in HBsAg positive maternal C genotype and its relationship with intrauterine HBV transmission, so as to provide a new perspective for the study of intrauterine transmission of HBV. Methods: From June 2011 to July 2013, HBsAg-positive mothers and their newborns who delivered in the obstetrics and gynecology department of the Third People's Hospital of Taiyuan were collected. Epidemiological data were collected through face-to-face questionnaires and electronic medical records. Serum HBV markers and serum HBV DNA were detected by electrochemiluminescence and quantitative fluorescence PCR, respectively. Intrauterine transmission of HBV was determined by positive HBsAg and/or HBV DNA in femoral venous blood before injection of HBV vaccine/Hepatitis B immunoglobulin within 24 h of birth. A total of 22 mothers and their newborns with HBV DNA load ≥10⁶ IU/ml in intrauterine transmission were selected as the intrauterine transmission group, and 22 mothers with HBV DNA load ≥10⁶ IU/ml without intrauterine transmission were chosen as the control group by random seed method. The distribution prediction of CpG islands of HBV DNA in 39 mothers with genotype C by HBV DNA sequencing was analyzed. Results: Among 39 mothers with HBV C genotype, 19 were in the intrauterine transmission group, and 20 were in the control group. The HBV DNA of 39 patients with genotype C traditional CpG island Ⅱ and Ⅲ, while the control group had traditional CpG island Ⅰ and novel CpG island Ⅳ and Ⅴ. The length of CpG island Ⅱ and Ⅲ and the number of CG loci of CpG island Ⅱ in the intrauterine transmission group differed from those in the control group (P<0.05). The CpG island Ⅱ length ≥518 bp and the number of CG loci ≥40 in the intrauterine transmission group (11/19) were significantly higher than those in the control group (2/20) (P<0.05). The length of CpG island Ⅱ and the number of CG loci in the X gene promoter region (Xp region) were higher than those in the control group (P<0.05). In the HBV intrauterine transmission group, most of maternal (12/19) HBV DNA CpG island Ⅱ completely covered the Xp region, which was significantly higher than that in the control group (5/20), and the number of HBV DNA Xp region CG loci was higher than that in the control group (P<0.05). Conclusions: The distribution of maternal C genotype HBV DNA CpG islands is related to intrauterine transmission. The length of CpG island Ⅱ and the number of CG sites may increase the risk of intrauterine transmission of HBV.
Biomarkers ; CpG Islands ; DNA, Viral/genetics* ; Female ; Hepatitis B ; Hepatitis B Surface Antigens ; Hepatitis B virus/genetics* ; Humans ; Infant, Newborn ; Infectious Disease Transmission, Vertical ; Mothers ; Pregnancy ; Pregnancy Complications, Infectious

OBJECTIVES: To explore the correlation between cytosine-phosphoric-guanylic (CpG) site of Septin 9 gene and colorectal cancer, and to develop a real-time PCR detection system in plasma in patients with colorectal cancer. METHODS: The methylation of training samples was detected by high-throughput sequencing technology, and the sites highly consistent with the clinical information of colorectal cancer were identified. Then the detection system of real-time PCR was designed to analyze the consistency of plasma and tissue based on methylationa sensitive enzyme digestion. Finally, 100 clinical trials were conducted to evaluate the performance of the detection system with the methylation sensitive enzyme digestion-real-time PCR. RESULTS: The highly consistent sites, which were selected by high-throughput sequencing from 71 training set samples, was the 38th CpG. Based on the detection region, the screened methylation sensitive enzymes were CONCLUSIONS The 38th CpG site of Septin 9 detected by the detection system of methylation sensitive enzyme digestion-real-time PCR can highly predict the occurrence of colorectal cancer with great clinical application value.
Colorectal Neoplasms/genetics* ; CpG Islands/genetics* ; DNA ; DNA Methylation ; Humans ; Plasma/metabolism* ; Septins/metabolism*

The effect of altering the promoter region of ubiquitous chromatin-opening element (UCOE) and matrix attachment region (MAR) on stable and efficient expression of genes was investigated. Four different promoters were tested, namely, oct4 containing an enhancer region, sox2 having a CpG island, nanog having no regulatory elements, and CMV containing a CpG island and an enhancer region. Eight reporter plasmids were constructed: pOCT4-UCOE, pOCT4-MAR, pSOX2-UCOE, pSOX2-MAR, pNANOG-UCOE, pNANOG-MAR, pCMV-UCOE, and pCMV-MAR. Stable and efficient expression was observed when UCOE combined with the oct4 promoter, whereas the sox2 was the best promoter suited for MAR. Comparison of the stable clones of oct4-UCOE and sox2-MAR showed that UCOE-regulated expression is more stable and efficient than MAR-regulated expression. When CpG island-containing promoter is linked with UCOE, stable and efficient expression could be observed. These data suggest that an enhancer region in the promoter leads to high, yet unstable expression when combined with UCOE, whereas CpG islands stabilize expression. In conclusion, UCOE and MAR interact with regulatory elements on the promoter by altering the chromatin open state and chromatin loop to regulate gene expression.
Chromatin/genetics* ; CpG Islands/genetics* ; Gene Expression ; Gene Expression Regulation ; Promoter Regions, Genetic/genetics*

OBJECTIVE: To study the difference in age estimation based on quantitative analysis of DNA methylation by MassARRAY and pyrosequencing techniques. METHODS: The methylation levels of 9 CpG sites from two independent whole blood sample sets (containing 65 and 62 samples) were detected using MassARRAY and pyrosequencing techniques. Z-score transformation was used to remove the batch effects of different techniques, and a linear regression model was used for age prediction. RESULTS: For age prediction using the MassARRAY system, the 65 samples showed a mean absolute difference (MAD) of 2.49 years before Z-score transformation of the data and 2.44 years after the transformation, similar to the results in the 62 samples (MAD of 3.36 years before and 3.42 years after Z-score transformation). For data typed from pyrosequencing, the 65 samples showed a MAD of 4.20 years before and 2.76 years after data Z-score transformation, also similar to the results in the 62 samples (MAD of 3.92 years before and 3.63 years after data transformation). CONCLUSIONS Z-score transformation can effectively reduce the system batch effect between MassARRAY and pyrosequencing. Data from the MassARRAY system allows direct age estimation without further data processing, while the pyrosequencing data may increase the error in age estimation, which can be corrected by Z-score transformation of the data.
CpG Islands/genetics* ; DNA Methylation ; High-Throughput Nucleotide Sequencing ; Linear Models ; Sequence Analysis, DNA

BACKGROUND: Various treatments for hepatocellular carcinoma (HCC) are utilized in clinical practice; however, the prognosis is still poor on account of high recurrence rates. DNA methylation levels of CpG islands around promoters (promoter CpGis) inversely regulate gene expression and closely involved in carcinogenesis. As a new strategy, several chemicals globally inhibiting DNA methylation have been developed aiming at reducing DNA methylation levels and maintaining the expression of tumor suppressor genes. On the other hand, since these drugs nonspecifically modify DNA methylation, they can cause serious adverse effects. In order to ameliorate the methods by targeting specific CpGs, information of cancer-related genes that are regulated by DNA methylation is required. METHODS: We searched candidate genes whose expressions were regulated by DNA methylation of promoter CpGi and which are involved in HCC cases. To do so, we first identified genes whose expression were changed in HCC by comparing gene expressions of 371 HCC tissues and 41 non-tumor tissues using the Cancer Genome Atlas (TCGA) database. The genes were further selected for poor prognosis by log-rank test of Kaplan-Meier plot and for cancer relevance by Pubmed search. Expression profiles of upregulated genes in HCC tissues were assessed by Gene Ontology (GO) analysis. Finally, using DNA methylation data of TCGA database, we selected genes whose promoter DNA methylation levels were inversely correlated with gene expression. RESULTS: We found 115 genes which were significantly up- or downregulated in HCC tissues and were associated with poor prognosis and cancer relevance. The upregulated genes were significantly enriched in cell division, cell cycle, and cell proliferation. Among the upregulated genes in HCC, we identified hypomethylation of CpGis around promoters of FANCB, KIF15, KIF4A, ERCC6L, and UBE2C. In addition, TCGA data showed that the tumor suppressor gene P16 is unexpectedly overexpressed in many types of cancers. CONCLUSIONS We identified five candidate genes whose expressions were regulated by DNA methylation of promoter CpGi and associate with cancer cases and poor prognosis in HCC. Modification of site-specific DNA methylation of these genes enables a different approach for HCC treatment with higher selectivity and lower adverse effects.
Carcinoma, Hepatocellular ; genetics ; metabolism ; Cell Proliferation ; CpG Islands ; genetics ; DNA Methylation ; Databases as Topic ; Gene Expression Regulation, Neoplastic ; Humans ; Liver Neoplasms ; genetics ; metabolism ; Promoter Regions, Genetic