Recent studies have identified DNA methylation signatures in the white blood cells as potential biomarkers for breast cancer (BC) in the European population. Here, we investigated the association between BC and blood-based methylation of cluster of differentiation 160 (CD160), inositol-3-phosphate synthase 1 (ISYNA1) and RAD51 paralog B (RAD51B) genes in the Chinese population. Peripheral blood samples were collected from two independent case-control studies with a total of 272 sporadic early-stage BC cases (76.5% at stage I&II) and 272 cancer-free female controls. Mass spectrometry was applied to quantitatively measure the levels of DNA methylation. The logistic regression and non-parametric tests were used for the statistical analyses. In contrast to the protective effects reported in European women, we reported the blood-based hypomethylation in CD160, ISYNA1 and RAD51B as risk factors for BC in the Chinese population (CD160_CpG_3, CD160_CpG_4/cg20975414, ISYNA1_CpG_2, RAD51B_CpG_3 and RAD51B_CpG_4; odds ratios (ORs) per -10% methylation ranging from 1.08 to 1.67, p < 0.05 for all). Moreover, hypomethylation of CD160, ISYNA1 and RAD51B was significantly correlated with age, BC subtypes including estrogen receptor (ER)-negative BC tumors, triple negative tumors, BC cases with larger size, advanced stages and more lymph node involvement. Our results supported the report in European women that BC is associated with altered methylation of CD160, ISYNA1 and RAD51B in the peripheral blood, although the effects are opposite in the Chinese population. The difference between the two populations may be due to variant genetic background or life styles, implicating that the validations of epigenetic biomarkers in variant ethnic groups are warranted.
BackgroundCoronary heart disease (CHD) brings a heavy burden to society worldwide. Novel and minimally invasive biomarkers for the risk evaluation of CHD are urgently needed. Previous study has revealed that blood-based hypomethylation of β-actin (ACTB) was associated with increased risk of stroke, but not reported in CHD yet.ObjectivesWe aimed to explore the association between blood-based ACTB methylation and the risk of CHD in a case-control study in the Chinese population.MethodsThe methylation level of ACTB was quantitatively determined by mass spectrometry in 281 CHD patients and 272 controls. The association between ACTB methylation and CHD risk was estimated by logistic regression analyses adjusted for possible confounding effects.ResultsWe found a significant association between hypermethylation of ACTB in peripheral blood and increased risk of CHD (odds ratios (ORs) per +10% methylation: 1.19–1.45, p < 0.013 for nine out of thirteen CpG sites), especially in male subjects and heart failure (HF) patients (ORs per +10% methylation: 1.20–1.43, 1.38–1.46; p < 0.030, 1.52 × 10−4, respectively). Hypermethylation of ACTB_CpG_2.3, ACTB_CpG_7.8, and ACTB_CpG_9.10 was observed in the CHD patients with minor to medium cardiac function impairment (NYHA I&II CHD cases) (ORs per +10% methylation: 1.38–1.44; p < 0.001). The combination of ACTB_CpG_2.3, ACTB_CpG_7.8, and ACTB_CpG_9.10 methylation levels could efficiently discriminate CHD cases, male CHD patients, HF and NYHA I&II CHD patients from controls (area under curve (AUC) = 0.75, 0.74, 0.73, and 0.77, respectively).ConclusionsOur study reveals a strong association between blood-based ACTB hypermethylation and CHD risk. The combination of ACTB methylation and conventional risk factors might provide a novel strategy to improve risk assessment of CHD.
Background Novel molecular biomarkers for the risk assessment and early detection of coronary heart disease (CHD) are urgently needed for disease prevention. Altered methylation of ATP-binding cassette subfamily G member 1 (ABCG1) has been implicated in CHD but was mostly studied in Caucasians. Exploring the potential relationship between ABCG1 methylation in blood and CHD among the Chinese population would yield valuable insights. Methods Peripheral blood samples were obtained from a case–control study (287 CHD patients vs. 277 controls) and a prospective nested case–control study (171 CHD patients and 197 matched controls). DNA extraction and bisulfite-specific PCR amplification techniques were employed for sample processing. Quantitative assessment of methylation levels was conducted using mass spectrometry. Statistical analyses involved the utilization of logistic regression and nonparametric tests. Results We found hypomethylation of ABCG1 in whole blood was associated with the risk of CHD in both studies, which was enhanced in heart failure (HF) patients, female and younger subjects. When combined with baseline characteristics, altered ABCG1 methylation showed improved predictive effect for differentiating CHD cases, ischemic cardiomyopathy (ICM) cases, younger than 60 years CHD cases, and female CHD cases from healthy controls (area under the curve (AUC) = 0.68, 0.71, 0.74, and 0.73, respectively). Conclusions We demonstrated a robust link between ABCG1 hypomethylation in whole blood and CHD risk in the Chinese population and provided novel evidence indicating that aberrant ABCG1 methylation in peripheral blood can serve as an early detection biomarker for CHD patients.
e20551 Background: Early detection of lung cancer (LC) is vital for reducing of LC-related mortality. Although the screening of persons at high risk for LC by low-dose computed tomographic (LDCT) has showed an inspiring 20.0% decrease in mortality, it also comes along with a dramatically high false positive rate for distinguishing the malignant nodules from the benign nodules. Thus, it is necessary to develop a diagnostic tool with high discriminant ability for identifying malignant nodules. Methods: The methylation levels of five candidate genes were quantitatively measured via mass spectrometry. A diagnostic model was developed by blood-based methylation levels in training cohort (650 LC cases vs. 114 benign lung nodules), and further validated the performance in validation cohort (195 LC cases vs. 39 benign lung nodules) by binary logistic regression. Notably, 91.8% LC cases were collected at Stage I. Results: The methylation model of 35 CpG sites was developed and validated for LC diagnosis. This model achieved a sensitivity of 85.4% and a specificity of 92.5% in training cohort [Area Under the Curve (AUC): 0.945], and a sensitivity of 84.1% and a specificity of 97.2% in validation cohort (AUC: 0.932). The performance was well maintained in (a) Stage I subgroup (n = 447), with a sensitivity of 82.6% and a specificity of 81.6%; (b) nodule diameter ≤ 1 cm (n = 113), with a sensitivity of 80.6% and a specificity of 81.6% in validation cohort. Conclusions: This study suggests that the blood-based DNA methylation panel may provide the potential utility for early diagnosis of LC cases, which would promote early diagnosis and benefit more LC patients.
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