DNA Methylation Changes Associated with Type 2 Diabetes and Diabetic Kidney Disease in an East Asian Population

2021 ◽  
Author(s):  
Hakyung Kim ◽  
Jae Hyun Bae ◽  
Kyong Soo Park ◽  
Joohon Sung ◽  
Soo Heon Kwak
Keyword(s):  
Type 2 Diabetes ◽  
Dna Methylation ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Fasting Glucose ◽  
East Asian ◽  
Asian Population ◽  
Diabetic Kidney ◽  
Metabolic Phenotypes

Abstract Background There is a growing body of evidence that epigenetic changes including DNA methylation influence the risk of type 2 diabetes (T2D) and its microvascular complications. We conducted a methylome-wide association study (MWAS) to identify differentially methylated sites (DMSs) of T2D and diabetic kidney disease (DKD) in a Korean population. Methods We performed an MWAS in 232 participants with T2D and 197 non-diabetic controls with Illumina EPIC bead chip using peripheral blood leukocytes. T2D group was subdivided into 87 DKD cases and 80 non-DKD controls. Additional 819 individuals from two population-based cohorts were used to investigate the association of identified DMSs with quantitative metabolic phenotypes. Mendelian randomization (MR) approach was applied to evaluate the causal effect of metabolic phenotypes on identified DMSs. Results We identified eight DMSs (each at BMP8A, NBPF20, STX18, ZNF365, CPT1A, and TRIM37, and two at TXNIP) which were significantly associated with the risk of T2D (P < 9.0×10 -8), including three that were previously known (DMSs in TXNIP and CPT1A). We also identified three DMSs (in COMMD1, TMOD1, and FHOD1) associated with DKD. With our limited sample size, we were not able to observe a significant overlap between DMSs of T2D and DKD. DMSs in TXNIP and CTP1A were associated with fasting glucose and HbA1c. In MR analysis, fasting glucose was causally associated with DMS in CPT1A. Conclusions In an East Asian population, we identified eight DMSs, including five novel CpG loci, associated with T2D and three DMSs associated with DKD at methylome-wide statistical significance.

Albuminuria Is More Closely Associated with Vascular Endothelial Function than eGFR in Type 2 Diabetes with Diabetic Kidney Disease

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 443-P
Author(s):  
YOSHINORI KAKUTANI ◽  
MASANORI EMOTO ◽  
YUKO YAMAZAKI ◽  
KOKA MOTOYAMA ◽  
TOMOAKI MORIOKA ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Kidney Disease ◽  
Endothelial Function ◽  
Diabetic Kidney Disease ◽  
Vascular Endothelial ◽  
Vascular Endothelial Function ◽  
Diabetic Kidney

Progression of diabetic kidney disease and trajectory of kidney function decline in Chinese patients with Type 2 diabetes

2019 ◽  
Vol 95 (1) ◽  
pp. 178-187 ◽  
Author(s):  
Guozhi Jiang ◽  
Andrea On Yan Luk ◽  
Claudia Ha Ting Tam ◽  
Fangying Xie ◽  
Bendix Carstensen ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Kidney Disease ◽  
Kidney Function ◽  
Diabetic Kidney Disease ◽  
Chinese Patients ◽  
Diabetic Kidney ◽  
Kidney Function Decline

scholarly journals Association Between Classical and Emerging Risk Factors for Diabetic Kidney Disease and Albuminuria in a Cohort of Type 2 Diabetes Mellitus Patients

2021 ◽  
Vol 18 (3) ◽  
pp. 17-25
Author(s):  
Stoiţă Marcel ◽  
Popa Amorin Remus
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Significant Positive Association ◽  
Diabetic Kidney

Abstract The presence of albuminuria in patients with type 2 diabetes mellitus is a marker of endothelial dysfunction and also one of the criteria for diagnosing diabetic kidney disease. The present study aimed to identify associations between cardiovascular risk factors and renal albumin excretion in a group of 218 patients with type 2 diabetes mellitus. HbA1c values, systolic blood pressure, diastolic blood pressure were statistically significantly higher in patients with microalbuinuria or macroalbuminuria compared to patients with normoalbuminuria (p <0.01). We identified a statistically significant positive association between uric acid values and albuminuria, respectively 25- (OH)2 vitamin D3 deficiency and microalbuminuria (p <0.01).

scholarly journals Diabetic kidney disease: Act now or pay later

2008 ◽  
Vol 11 (4) ◽  
pp. 988-991
Author(s):  
Robert C Atkins ◽  
Paul Zimmet
Keyword(s):  
Type 2 Diabetes ◽  
Kidney Disease ◽  
International Society ◽  
Diabetic Kidney Disease ◽  
International Diabetes Federation ◽  
Diabetic Kidney ◽  
Global Pandemic

In 2003, the International Society of Nephrology and the International Diabetes Federation launched a booklet called “Diabetes in the Kidney: Time to act” [1] to highlight the global pandemic of type 2 diabetes and diabetic kidney disease. ration (PZ)

AI-based prediction model for the risk of diabetic kidney disease in patients with type 2 diabetes mellitus

2021 ◽  
Author(s):  
Ning Zhang ◽  
Rui Fan ◽  
Jing Ke ◽  
Qinghua Cui ◽  
Dong ZHAO
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Kidney Disease ◽  
Prediction Model ◽  
Diabetic Kidney Disease ◽  
Feature Selection Method ◽  
Training Set ◽  
Test Set ◽  
Diabetic Kidney

Abstract BackgroundMicroalbuminuria is the main characteristic of Diabetic kidney disease (DKD), but it fluctuates greatly under the influence of blood glucose. Our aim was to establish some common clinical variables which could be easily collected to predict the risk of DKD in patients with type 2 diabetes. Methods and resultsWe build an artificial intelligence (AI) model to quantitively predict the risk of DKD based on the biomedical parameters from 1239 patients. An information entropy-based feature selection method was applied to screen out the risk factors of DKD. The dataset was divided with 4/5 into the training set and 1/5 into the test set. By using the selected risk factors, 5-fold cross-validation is applied to train the prediction model and it finally got AUC of 0.72 and 0.71 in the training set and test set respectively. In addition, we provide a method of calculating risk factors’ contribution for individuals to provide personalized guidance for treatment. We set up web-based application available on http://www.cuilab.cn/dkd for self-check and early warning. ConclusionsWe establish a feasible prediction model for DKD and suggest the degree of risk contribution of each indicator for each individual, which has certain clinical significance for early intervention and prevention.

scholarly journals Cholesteryl Ester Transfer Protein Genetic Variants Associated with Risk for Type 2 Diabetes and Diabetic Kidney Disease in Taiwanese Population

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 782 ◽  
Author(s):  
Huang ◽  
Chen ◽  
Liu ◽  
Lin ◽  
Lin ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Kidney Disease ◽  
Cholesteryl Ester ◽  
Cholesteryl Ester Transfer Protein ◽  
Diabetic Kidney Disease ◽  
Density Lipoprotein ◽  
Diabetic Kidney ◽  
Transfer Protein ◽  
Low Levels

Cholesteryl ester transfer protein (CETP) plays an important role in lipid metabolism. Low levels of high-density lipoprotein cholesterol (HDL-C) increase the risk of type 2 diabetes (T2D). This study investigated CETP gene variants to assess the risk of T2D and specific complications of diabetic kidney disease (DKD) and diabetic retinopathy. Towards this, a total of 3023 Taiwanese individuals (1383 without T2D, 1640 with T2D) were enrolled in this study. T2D mice (+Leprdb/+Leprdb, db/db) were used to determine CETP expression in tissues. The A-alleles of rs3764261, rs4783961, and rs1800775 variants were found to be independently associated with 2.86, 1.71, and 0.91 mg/dL increase in HDL-C per allele, respectively. In addition, the A-allele of rs4783961 was significantly associated with a reduced T2D risk (odds ratio (OR), 0.82; 95% confidence interval (CI), 0.71‒0.96)), and the A-allele of rs1800775 was significantly related to a lowered DKD risk (OR, 0.78; 95% CI, 0.64‒0.96). CETP expression was significantly decreased in the T2D mice kidney compared to that in the control mice (T2D mice, 0.16 0.01 vs. control mice, 0.21 0.02; p = 0.02). These collective findings indicate that CETP variants in the promoter region may affect HDL-C levels. Taiwanese individuals possessing an allele associated with higher HDL-C levels had a lower risk of T2D and DKD.

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