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Updated: Aug 31, 2025

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of SLC30A8 gene: a
Fulan Hu1, Yanyan Zhang1, Pei Qin1
1School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
Abstract:
To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of SLC30A8 gene and T2DM risk, and the interactions among SNPs, methylation, and environmental factors on T2DM risk. We genotyped 9 SNPs and tested methylation at 46 CpG loci of SLC30A8 in the baseline DNA of 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study. A conditional logistic regression model was used to estimate the associations between SNPs and SLC30A8 methylation and T2DM risk. Multifactor Dimensionality Reduction analysis was used to estimate the effect of interactions among SNPs, methylation, and environment on T2DM risk. Probability of T2DM was decreased with rs11558471 (GG vs. AA, OR = 0.55, 95% CI 0.32, 0.96), with rs13266634 (TT vs. CC, OR = 0.55, 95% CI 0.32, 0.94), with rs3802177 (AA vs. GG, OR = 0.54, 95%CI 0.31, 0.94), and its probability was increased with rs2466293 of SLC30A8 (GA vs. AA, OR = 1.63, 95% CI 1.08-2.47). Its probability was also significantly associated with methylation of CG9 and CG45 (OR = 0.56 [95% CI 0.33-0.97] and 1.61 [95%CI 1.03--2.51]). T2DM probability was significantly associated with the interaction effect between rs2466293 and hypertension (p = 0.045). T2DM probability was also significantly associated with the combination effects of rs2466293 with BMI, hypertension, and hypertriglyceridemia, with the combination effects of hypertriglyceridemia with rs11558471, rs13266634, and methylation of CG45.
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