Dataset Information

The Association between Genomic DNA Methylation and Diabetic Peripheral Neuropathy in Patients with Type 2 Diabetes Mellitus.

ABSTRACT: Aim:DNA methylation is thought to be involved in regulating the expression of key genes and inducing diabetic peripheral neuropathy (DPN). However, clinically, the level of whole-genome DNA methylation and its relationship with DPN remains unclear. Methods:186 patients with type 2 diabetes mellitus (T2DM) admitted to the Second Affiliated Hospital of Soochow University since Jul. 2016 to Oct. 2017 were enrolled in the study, including 100 patients in the DPN group and 86 patients in the non-DPN group, diagnosed with Toronto Clinical Scoring System (TCSS). Clinical and biochemical characteristics between the two groups were compared, and the correlations with TCSS scores were analyzed. Furthermore, the levels of genomic DNA methylation of leukocytes, measured with high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS), were also analyzed between the two groups. Results:Age, duration, triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL-C), creatinine, uric acid (UA), blood urea nitrogen (BUN), and C-reactive protein (CRP) were significantly higher in the DPN group. Estimated glomerular filtration rate (eGFR) and the level of genomic DNA methylation were much lower in the DPN group. Spearman correlation analysis showed that TCSS was positively correlated with age, duration, UA, and CRP and was negatively correlated with body mass index (BMI), eGFR, and the level of genomic DNA methylation. Interestingly, multiple stepwise regression analysis showed that only duration, genomic DNA methylation, and eGFR had impacts on TCSS. The results also showed that the levels of genomic DNA methylation did not change significantly whether or not there was renal injury. Another multiple stepwise regression analysis showed that TCSS and BMI were the influencing factors of genomic DNA methylation. Finally, we found that genomic DNA methylation levels were decreased significantly in the DPN group compared with the non-DPN group when the duration is ?5 years or BMI ? 25?kg/m2. Conclusion:Low level of genomic DNA methylation is a relative specific risk factor of diabetic peripheral neuropathy in patients with type 2 diabetes.

SUBMITTER: Zhang HH

PROVIDER: S-EPMC6875377 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Association between Genomic DNA Methylation and Diabetic Peripheral Neuropathy in Patients with Type 2 Diabetes Mellitus.

Zhang Hong-Hong HH Han Xingfa X Wang Mengmeng M Hu Qingfang Q Li Sicheng S Wang Meng M Hu Ji J

Journal of diabetes research 20191103

<h4>Aim</h4>DNA methylation is thought to be involved in regulating the expression of key genes and inducing diabetic peripheral neuropathy (DPN). However, clinically, the level of whole-genome DNA methylation and its relationship with DPN remains unclear.<h4>Methods</h4>186 patients with type 2 diabetes mellitus (T2DM) admitted to the Second Affiliated Hospital of Soochow University since Jul. 2016 to Oct. 2017 were enrolled in the study, including 100 patients in the DPN group and 86 patients ...[more]

PMID: 31781662

Similar Datasets

Project description:BACKGROUND:Many CpGs become hyper or hypo-methylated with age. Multiple methods have been developed by Horvath et al. to estimate DNA methylation (DNAm) age including Pan-tissue, Skin & Blood, PhenoAge, and GrimAge. Pan-tissue and Skin & Blood try to estimate chronological age in the normal population whereas PhenoAge and GrimAge use surrogate markers associated with mortality to estimate biological age and its departure from chronological age. Here, we applied Horvath's four methods to calculate and compare DNAm age in 499 subjects with type 1 diabetes (T1D) from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study using DNAm data measured by Illumina EPIC array in the whole blood. Association of the four DNAm ages with development of diabetic complications including cardiovascular diseases (CVD), nephropathy, retinopathy, and neuropathy, and their risk factors were investigated. RESULTS:Pan-tissue and GrimAge were higher whereas Skin & Blood and PhenoAge were lower than chronological age (p < 0.0001). DNAm age was not associated with the risk of CVD or retinopathy over 18-20?years after DNAm measurement. However, higher PhenoAge (? = 0.023, p = 0.007) and GrimAge (? = 0.029, p = 0.002) were associated with higher albumin excretion rate (AER), an indicator of diabetic renal disease, measured over time. GrimAge was also associated with development of both diabetic peripheral neuropathy (OR = 1.07, p = 9.24E-3) and cardiovascular autonomic neuropathy (OR = 1.06, p = 0.011). Both HbA1c (? = 0.38, p = 0.026) and T1D duration (? = 0.01, p = 0.043) were associated with higher PhenoAge. Employment (? = - 1.99, p = 0.045) and leisure time (? = - 0.81, p = 0.022) physical activity were associated with lower Pan-tissue and Skin & Blood, respectively. BMI (? = 0.09, p = 0.048) and current smoking (? = 7.13, p = 9.03E-50) were positively associated with Skin & Blood and GrimAge, respectively. Blood pressure, lipid levels, pulse rate, and alcohol consumption were not associated with DNAm age regardless of the method used. CONCLUSIONS:Various methods of measuring DNAm age are sub-optimal in detecting people at higher risk of developing diabetic complications although some work better than the others.

Project description:Aims/introductionNon-alcoholic fatty liver disease and type 2 diabetes mellitus are closely related, and often occur simultaneously in patients. Type 2 diabetes increases the risk of diabetic peripheral neuropathy, resulting in intolerable pain and extremity amputation that reduces the quality of life. However, the role of non-alcoholic fatty liver disease in the pathogenesis of diabetic peripheral neuropathy remains unclear. Thus, we evaluated the correlation of liver fibrosis and steatosis, which are representative histological morphologies of non-alcoholic fatty liver disease, with diabetic peripheral neuropathy in type 2 diabetes patients.Materials and methodsFive hundred twenty individuals with type 2 diabetes were recruited. All the patients were detected nerve conduction study for diabetic peripheral neuropathy and fibro touch for liver steatosis and fibrosis. Correlation of DPN with liver steatosis and fibrosis were analysed with binary logistic analysis.ResultsAmong the 520 patients, the prevalence of liver steatosis, fibrosis and diabetic peripheral neuropathy was 63.0% (n = 328), 18.1% (n = 94) and 52.1% (n = 271), respectively. The prevalence of diabetic peripheral neuropathy was significantly elevated in patients with liver steatosis (55.7 vs 44.9%, P = 0.03) and fibrosis (61.5 vs 50%, P = 0.04), and it increased as liver stiffness measurement increased. Additionally, both hepatic steatosis (odds ratio 1.48, 95% confidence interval 1.04-2.11, P = 0.03) and fibrosis (odds ratio 1.60, 95% confidence interval 1.02-2.51, P = 0.04) were correlated with diabetic peripheral neuropathy. After adjusting for age, sex, weight, height, body mass index, waist hip ratio, duration of type 2 diabetes, blood glucose, homeostatic model assessment of insulin resistance, blood pressure, serum lipid, liver enzyme, urea, uric acid, creatinine and inflammatory factors, liver fibrosis remained associated with diabetic peripheral neuropathy (odds ratio 2.24, 95% confidence interval 1.11-4.53, P = 0.02).ConclusionsThe prevalence of diabetic peripheral neuropathy was elevated in patients with liver steatosis and fibrosis. Liver fibrosis was also independently associated with an increased risk of diabetic peripheral neuropathy.

Dataset Information

The Association between Genomic DNA Methylation and Diabetic Peripheral Neuropathy in Patients with Type 2 Diabetes Mellitus.

Publications

The Association between Genomic DNA Methylation and Diabetic Peripheral Neuropathy in Patients with Type 2 Diabetes Mellitus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets