Data from: DNA methylation changes associated with type 2 diabetes and diabetic kidney disease in an East Asian population
Kim, Hakyung et al. (2021), Data from: DNA methylation changes associated with type 2 diabetes and diabetic kidney disease in an East Asian population, Dryad, Dataset, https://doi.org/10.5061/dryad.866t1g1pt
Objective: There is growing body of evidence that epigenetic changes including DNA methylation influence the risk of type 2 diabetes and its microvascular complications. We conducted a methylome-wide association study (MWAS) to identify differentially methylated regions (DMRs) of type 2 diabetes and diabetic kidney disease (DKD) in Korean population.
Methods: We performed an initial MWAS in 232 participants in a case-control study design with type 2 diabetes and 197 non-diabetic controls with Illumina EPIC bead chip using peripheral blood leukocytes. Type 2 diabetes group was subdivided to 87 DKD cases and 80 non-DKD controls. Additional 819 individuals from two population-based cohorts were used to investigate the association of the identified DMRs with quantitative metabolic traits. We developed a DNA methylation score using identified DMRs to predict the occurrence of type 2 diabetes. To examine the causal relationship between the metabolic traits and differentially methylated status, we performed Mendelian randomization (MR) analyses.
Results: We identified eight DMRs (each at BMP8A, NBPF20, STX18, ZNF365, CPT1A, and TRIM37, and two at TXNIP) which were significantly associated with risk of type 2 diabetes (P < 9.0×10-8), including three that were previously known (DMRs in TXNIP and CPT1A), in 429 type 2 diabetes cases and controls. DNA methylation score consisted of these DMRs differentiated the risk of developing type 2 diabetes in an independent prospective cohort with a relative risk of 2.44 (95% confidence interval 1.39–4.28) between the lowest and highest deciles of DNA methylation score. DMRs in CPT1A and TXNIP were associated with quantitative metabolic traits, including fasting glucose, HbA1c, and body mass index. We also identified three DMRs (on COMMD1, TMOD1, and FHOD1) associated with DKD in 167 DKD cases and controls. The DMRs of DKD did not show meaningful overlap with those of type 2 diabetes. In MR analysis, the estimated glomerular filtration rate was causally associated with DNA methylation of these three DMRs.
Conclusions: In an East Asian population, we identified eight DMRs, including five novel ones, associated with type 2 diabetes and three DMRs associated with DKD at methylome-wide statistical significance. Our findings suggest that epigenetics of DKD may share little with those responsible for the development of type 2 diabetes.
Ministry of Health and Welfare, Award: HI15C3131
Seoul National University Hospital, Award: 2520160050
The Ministry of Science, ICT & Future Planning, Award: NRF-2017R1A2B2002136