RESUMO
BACKGROUND: Epigenetic changes, especially DNA methylation have a main role in regulating cardiometabolic disorders and their risk factors. This study provides a review of the current evidence on the association between methylation of some genes (LINE1, ABCG1, SREBF1, PHOSPHO1, ADRB3, and LEP) and cardiometabolic risk factors. METHODS: A systematic literature search was conducted in electronic databases including Web of Science, PubMed, EMBASE, Google Scholar and Scopus up to end of 2020. All observational human studies (cross-sectional, case-control, and cohort) were included. Studies that assessed the effect of DNA methylation on cardiometabolic risk factors were selected. RESULTS: Among 1398 articles, eight studies and twenty-one studies were included in the meta-analysis and the systematic review, respectively. Our study showed ABCG1 and LINE1 methylation were positively associated with blood pressure (Fisher's zr = 0.07 (0.06, 0.09), 95% CI: 0.05 to 0.08). Methylation in LINE1, ABCG1, SREBF1, PHOSPHO1 and ADRB3 had no significant association with HDL levels (Fisher's zr = - 0.05 (- 0.13, 0.03), 95% CI:-0.12 to 0.02). Positive association was existed between LINE1, ABCG1 and LEP methylation and LDL levels (Fisher's zr = 0.13 (0.04, 0.23), 95% CI: 0.03 to 0.23). Moreover, positive association was found between HbA1C and ABCG1 methylation (Fisher's zr = 0.11 (0.09, 0.13), 95% CI: 0.09 to 0.12). DNA methylation of LINE1, ABCG1 and SREBF1 genes had no significant association with glucose levels (Fisher's zr = 0.01 (- 0.12, 0.14), 95% CI:-0.12 to 0.14). CONCLUSION: This meta-analysis showed that DNA methylation was associated with some cardiometabolic risk factors including LDL-C, HbA1C, and blood pressure. REGISTRATION: Registration ID of the protocol on PROSPERO is CRD42020207677 .
RESUMO
BACKGROUND: There are numerous sophisticated studies which have investigated risk factors of breast cancer (BC). The purpose of this paper is to use benefits of Bayesian modeling to involve such prior information in determining factors affecting the survival of women with BC in Yazd city. MATERIALS AND METHODS: The checklist included the characteristics of the patients and the factors studied. Then, from the records of patients referred to Radiotherapy Center of Shahid Ramezanzadeh, who had BC, from April 2005 to March 2012, the survival of 538 persons was recorded in the census. Data were analyzed by R software version 3.4.2, and 0.05 was considered the significance level. RESULTS: The mean age of BC diagnosis was 48.03 ± 11016 years. The Bayesian Cox regression showed that surgery (hazard ratio [HR] =1.631 95% PI; 1.102-2.422), ki67 (HR = 3.260. 95% PI; 1.6308-6.372), stage (HR = 5.620, 95% PI; 4.079-7.731), lymph node (HR = 1.765, 95% PI; 1.127-2.790), and ER (HR = 2. 600 95% PI; 2.023-3.354) were significantly related to survival time. CONCLUSION: The parametric and cox models were compared with standard error, and Cox model was selected as an optimal model. Accordingly, stage, ki67, lymph node, ER, and surgery variables had a positive effect on death hazard.
