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

Objective: To estimate the epidemic threshold and graded intensity thresholds of influenza in Zhejiang Province from 2012 to 2023 using the moving epidemic method (MEM), and evaluate the intensity of influenza epidemics, so as to provide the reference for influenza prevention and control in Zhejiang Province. Methods: The positive rates of influenza virus per week during the influenza epidemic seasons (from 40th week to 20th week of the following year) in Zhejiang Province from 2012 to 2022 were collected through the Chinese Influenza Surveillance Information System. A MEM model was established and optimized using cross-validation. The maximum accumulated rates percentage was used to divide the epidemic into pre-epidemic, epidemic, and post-epidemic periods, and to estimate the epidemic thresholds and graded intensity thresholds. The intensity of influenza epidemics in Zhejiang Province during the 2022-2023 epidemic season were assessed. Results: The positive rates of influenza virus in five epidemic seasons from 2012 to 2022 were included in the model. The MEM model performed best when the parameter δ was set to 1.5, with a sensitivity of 0.971, a specificity of 0.745, and a Youden's index of 0.716. According to the model analysis, the epidemic beginning and ending thresholds of influenza in Zhejiang Province during the 2022-2023 epidemic season were 19.32% and 10.92%, respectively, and the medium, high, and extremely high intensity thresholds were 48.65%, 63.49%, and 68.47%, respectively. During 2022-2023, the influenza epidemic was in the pre-epidemic period from the 40th week in 2022 to the 7th week in 2023; the epidemic period was from the 8th to the 18th week, the epidemic intensity was low in the 8th week and increased to a high level in the 9th week, and reached to a extremely high level from the 10th to the 13th week, then fell to the high and the medium level in the 14th week and 15th week, respectively, and fell to a low level from the 16th to the 18th week; the influenza epidemic entered the post-epidemic period since the 19th week. Conclusion MEM could be applied for evaluation of influenza epidemic intensity, providing the reference for early identification and taking graded preventive and control measures.