Identification of DNA methylation change in TCF7L2 gene in the blood of type 2 diabetes mellitus as a predictive biomarker in Iraq Kurdistan region by using methylation-specific PCR.
{"title":"Identification of DNA methylation change in TCF7L2 gene in the blood of type 2 diabetes mellitus as a predictive biomarker in Iraq Kurdistan region by using methylation-specific PCR.","authors":"Harem Othman Smail, Dlnya Asaad Mohamad","doi":"10.2478/enr-2023-0007","DOIUrl":null,"url":null,"abstract":"<p><p><b>Objective.</b> Nowadays, type 2 diabetes mellitus (T2D) is the most common chronic endocrine disorder affecting an estimated 5-10% of adults worldwide, and this disease also rapidly increased among the population in the Kurdistan region. This research aims to identify DNA methylation change in the TCF7L2 gene as a possible predictive T2D biomarker. <b>Methods.</b> One hundred and thirteen participants were divided into three groups: diabetic (47), prediabetic (36), and control (30). The study was carried out in patients who visited the private clinical sector between August and December 2021 in Koya city (Iraq Kurdistan region) to determine DNA methylation status using a methylation-specific PCR (MSP) with paired primers for each methylated and non-methylated region. In addition, the X2 Kruskal-Wallis statistical and Wilcoxon signed-rank tests were used, p<0.05 was considered significant. <b>Results.</b> The results showed hypermethylation of DNA in the promoter region in diabetic and prediabetic groups compared to the healthy controls. Different factors affected the DNA methylation level, including body max index, alcohol consumption, family history, and physical activity with the positive Coronavirus. <b>Conclusion.</b> The results obtained indicate that DNA methylation changes in the TCF7L2 promoter region may be used as a potential predictive biomarker of the T2D diagnosis. However, the findings obtained in this study should be supported by additional data.</p>","PeriodicalId":11650,"journal":{"name":"Endocrine regulations","volume":"57 1","pages":"53-60"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine regulations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/enr-2023-0007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Objective. Nowadays, type 2 diabetes mellitus (T2D) is the most common chronic endocrine disorder affecting an estimated 5-10% of adults worldwide, and this disease also rapidly increased among the population in the Kurdistan region. This research aims to identify DNA methylation change in the TCF7L2 gene as a possible predictive T2D biomarker. Methods. One hundred and thirteen participants were divided into three groups: diabetic (47), prediabetic (36), and control (30). The study was carried out in patients who visited the private clinical sector between August and December 2021 in Koya city (Iraq Kurdistan region) to determine DNA methylation status using a methylation-specific PCR (MSP) with paired primers for each methylated and non-methylated region. In addition, the X2 Kruskal-Wallis statistical and Wilcoxon signed-rank tests were used, p<0.05 was considered significant. Results. The results showed hypermethylation of DNA in the promoter region in diabetic and prediabetic groups compared to the healthy controls. Different factors affected the DNA methylation level, including body max index, alcohol consumption, family history, and physical activity with the positive Coronavirus. Conclusion. The results obtained indicate that DNA methylation changes in the TCF7L2 promoter region may be used as a potential predictive biomarker of the T2D diagnosis. However, the findings obtained in this study should be supported by additional data.