Methylation Status of Transcriptional Modulatory Genes Associated with Colorectal Cancer in Northeast China

BACKGROUND/AIMS: Methylation status plays a causal role in carcinogenesis in targeted tissues. However, the relationship between the DNA methylation status of multiple genes in blood leukocytes and colorectal cancer (CRC) susceptibility as well as interactions between dietary factors and CRC risks are unclear. METHODS: We performed a case-control study with 466 CRC patients and 507 cancer-free controls to investigate the association among the methylation status of individual genes, multiple CpG site methylation (MCSM), multiple CpG site heterogeneous methylation and CRC susceptibility. Peripheral blood DNA methylation levels were detected by performing methylation-sensitive high-resolution melting. RESULTS: Total heterogeneous methylation of CA10 and WT1 conferred a significantly higher risk of CRC (adjusted odds ratio [OR(adjusted)], 5.445; 95% confidence interval [CI], 3.075 to 9.643; OR(adjusted), 1.831; 95% CI, 1.100 to 3.047; respectively). Subjects with high-level MCSM (MCSM-H) status demonstrated a higher risk of CRC (OR(adjusted), 4.318; 95% CI, 1.529 to 12.197). Additionally, interactions between the high-level intake of fruit and CRH, WT1, and MCSM on CRC were statistically significant. CONCLUSIONS: The gene methylation status of blood leukocytes may be associated with CRC risk. MCSM-H of blood leukocytes was associated with CRC, especially in younger people. Some dietary factors may affect hypermethylation status and influence susceptibility to CRC.

Pre-diabetes mellitus influenced by hyperuricemia / 中华流行病学杂志

Objective To investigate the relationship and the influence between pre-diabetes mellitus (PDM) and hyperuricemia (HUA).Methods 157 PDM patients,aged 20 to 75 years old were selected from the Second Clinical Medical College of Harbin Medical University,from 2009 February to 2010 February and were divided into HUA group (76 cases) and NUA group (81 cases).All the patients had not been on thiazide drugs.T-test and Pearson correlation analysis were used to calculate the differences and correlation between uric acid and biochemical indicators.Results In the HUA group,BMI was (27.74 ± 2.88) kg/m2,waist to height ratio (WSR) was (0.55 ± 0.41),TC was (6.61 ± 0.73) mmol/L,TG was (3.94 ± 1.97) mmol/L,LDL-C was (3.60 ± 0.45) mmol/L and homeostasis model assessment-insulin resistance index (HOMA-IR) was (3.09± 1.20).There were significant differences noticed in BMI,TG,TC,LDL-C,HOMA-IR at higher level in the HUA group than those in the NUA group.Pre-diabetes uric acid levels were positively correlated with TG,TC,LDL-C while HOMA-1R (TG:r=0.29,TC:r=0.33,LDL-C:r=0.49,HOMA-IR:r=0.51,P＜0.05)was negatively correlated (r=－0.30,P＜0.05) with the HbAlc.Conclusion The levels of PDM uric acid might both be related with TC,TG,LDL-C and HOMA-IR.The High level of uric acid status in vivo appeared closely related to HOMA-IR,which could further promote the progress of pre-diabetic patients to diabetes and causing dyslipidemia.Our findings suggested that the levels of pre-diabetes uric acid levels should be under concern.

A preliminary study on the effects of meteorological factors on intracerebral hemorrhage death using the BP neural network model / 中华流行病学杂志

Objective Using the Back Propagation (BP) Neural Network Model to discover the relationship between meteorological factors and mortality of intracerebral hemorrhage,to provide evidence for developing an intracerebral hemorrhage prevention and control program,in Harbin.Methods Based on the characteristics of BP neural network,a neural network Toolbox of MATLAB 7.0 software was used to build Meteorological data of 2007-2009 with intracerebral hemorrhage mortality to predict the effect of BP neural network model,and to compare with the traditional multivariate linear regression model. Results Datas from the multivariate linear regrcssion indicated that the cerebral hemorrhage death mortality had a negative correlation with maximum temperatureand minimum humidity while having a positive correlation with the average relative humidity and the hours of sunshine.The linear correlation coefficient of intracerebral hemorrhage mortality was 0.7854,with mean absolute percentage (MAPE) as 0.21,mean square error (MSE) as 0.22,mean absolute error(MAE) as 0.19.The accuracy of forecasting was 81.31％ with an average error rate as 0.19.The Fitting results of BP neural network model showed that non-linear correlation coefficient of intracerebral hemorrhage mortality was 0.7967,with MAPE as 0.19,MSE as 0.21,MAE as 0.18.The forecasting accuracy was 82.53％ with the average error rate as 0.17.Conclusion The BP neural network model showed a higher forecasting accuracy when compared to the multiple linear regression model on intraccrebral hemorrhage mortality,using the data of 2010' s.