TXNIP DNA methylation is associated with glycemic control over 28 years in type 1 diabetes: findings from the Pittsburgh Epidemiology of Diabetes Complications (EDC) study

Update: the role of epigenetics in the metabolic memory of diabetic complications

Diabetes, a chronic disease characterized by hyperglycemia, is associated with significantly accelerated complications, including diabetic kidney disease (DKD), which increases morbidity and mortality. Hyperglycemia and other diabetes-related environmental factors such as overnutrition, sedentary lifestyles, and hyperlipidemia can induce epigenetic changes. Working alone or with genetic factors, these epigenetic changes that occur without alterations in the underlying DNA sequence, can alter the expression of pathophysiological genes and impair functions of associated target cells/organs, leading to diabetic complications like DKD. Notably, some hyperglycemia-induced epigenetic changes persist in target cells/tissues even after glucose normalization, leading to sustained complications despite glycemic control, so-called metabolic memory. Emerging evidence from in vitro and in vivo animal models and clinical trials with subjects with diabetes identified clear associations between metabolic memory and epigenetic changes including DNA methylation, histone modifications, chromatin structure, and noncoding RNAs at key loci. Targeting such persistent epigenetic changes and/or molecules regulated by them can serve as valuable opportunities to attenuate, or erase metabolic memory, which is crucial to prevent complication progression. Here, we review these cell/tissue-specific epigenetic changes identified to-date as related to diabetic complications, especially DKD, and the current status on targeting epigenetics to tackle metabolic memory. We also discuss limitations in current studies, including the need for more (epi)genome-wide studies, integrative analysis using multiple epigenetic marks and Omics datasets, and mechanistic evaluation of metabolic memory. Considering the tremendous technological advances in epigenomics, genetics, sequencing, and availability of genomic datasets from clinical cohorts, this field is likely to see considerable progress in the upcoming years.

Genome- and epigenome-wide association studies identify susceptibility of CpG sites and regions for metabolic syndrome in a Korean population

BACKGROUND

While multiple studies have investigated the relationship between metabolic syndrome (MetS) and its related traits (fasting glucose, triglyceride, HDL cholesterol, blood pressure, waist circumference) and DNA methylation, our understanding of the epigenetic mechanisms in MetS remains limited. Therefore, we performed an epigenome-wide meta-analysis of blood DNA methylation to identify differentially methylated probes (DMPs) and differentially methylated regions (DMRs) associated with MetS and its components using two independent cohorts comprising a total of 2,334 participants. We also investigated the specific genetic effects on DNA methylation, identified methylation quantitative trait loci (meQTLs) through genome-wide association studies and further utilized Mendelian randomization (MR) to assess how these meQTLs subsequently influence MetS status.

RESULTS

We identified 40 DMPs and 27 DMRs that are significantly associated with MetS. In addition, we identified many novel DMPs and DMRs underlying inflammatory and steroid hormonal processes. The most significant associations were observed in 3 DMPs (cg19693031, cg26974062, cg02988288) and a DMR (chr1:145440444-145441553) at the TXNIP, which are involved in lipid metabolism. These CpG sites were identified as coregulators of DNA methylation in MetS, TG and FAG levels. We identified a total of 144 cis-meQTLs, out of which only 13 were found to be associated with DMPs for MetS. Among these, we confirmed the identified causal mediators of genetic effects at CpG sites cg01881899 at ABCG1 and cg00021659 at the TANK genes for MetS.

CONCLUSIONS

This study observed whether specific CpGs and methylated regions act independently or are influenced by genetic effects for MetS and its components in the Korean population. These associations between the identified DNA methylation and MetS, along with its individual components, may serve as promising targets for the development of preventive interventions for MetS.

Alu Methylation Patterns in Type 1 Diabetes: A Case-Control Study

Evidence suggests that genome-wide hypomethylation may promote genomic instability and cellular senescence, leading to chronic complications in people with diabetes mellitus. Limited data are however available on the Alu methylation status in patients with type 1 diabetes (T1D). Methods: We investigated DNA methylation levels and patterns of Alu methylation in the peripheral blood of 36 patients with T1D and 29 healthy controls, matched for age and sex, by using the COmbined Bisulfite Restriction Analysis method (COBRA). Results: Total Alu methylation rate (mC) was similar between patients with T1D and controls (67.3% (64.4-70.9%) vs. 68.0% (62.0-71.1%), p = 0.874). However, patients with T1D had significantly higher levels of the partial Alu methylation pattern (mCuC + uCmC) (41.9% (35.8-45.8%) vs. 36.0% (31.7-40.55%), p = 0.004) compared to healthy controls. In addition, a positive correlation between levels of glycated hemoglobin (HbA1c) and the partially methylated loci (mCuC + uCmC) was observed (Spearman's rho = 0.293, p = 0.018). Furthermore, significant differences were observed between patients with T1D diagnosed before and after the age of 15 years regarding the total methylation mC, the methylated pattern mCmC and the unmethylated pattern uCuC (p = 0.040, p = 0.044 and p = 0.040, respectively). Conclusions: In conclusion, total Alu methylation rates were similar, but the partial Alu methylation pattern (mCuC + uCmC) was significantly higher in patients with T1D compared to healthy controls. Furthermore, this pattern was associated positively with the levels of HbA1c and negatively with the age at diagnosis.

Metabolite profiles and DNA methylation in metabolic syndrome: a two-sample, bidirectional Mendelian randomization

Introduction: Metabolic syndrome (MetS) increases the risk of cardiovascular disease and death. Previous '-omics' studies have identified dysregulated serum metabolites and aberrant DNA methylation in the setting of MetS. However, the relationship between the metabolome and epigenome have not been elucidated. In this study, we identified serum metabolites associated with MetS and DNA methylation, and we conducted bidirectional Mendelian randomization (MR) to assess causal relationships between metabolites and methylation. Methods: We leveraged metabolomic and genomic data from a national United States cohort of older adults (REGARDS), as well as metabolomic, epigenomic, and genomic data from a family-based study of hypertension (HyperGEN). We conducted metabolite profiling for MetS in REGARDS using weighted logistic regression models and validated them in HyperGEN. Validated metabolites were selected for methylation studies which fit linear mixed models between metabolites and six CpG sites previously linked to MetS. Statistically significant metabolite-CpG pairs were selected for two-sample, bidirectional MR. Results: Forward MR indicated that glucose and serine metabolites were causal on CpG methylation near CPT1A [B(SE): -0.003 (0.002), p = 0.028 and B(SE): 0.029 (0.011), p = 0.030, respectively] and that serine metabolites were causal on ABCG1 [B(SE): -0.008(0.003), p = 0.006] and SREBF1 [B(SE): -0.009(0.004), p = 0.018] methylation, which suggested a protective effect of serine. Reverse MR showed a bidirectional relationship between cg06500161 (ABCG1) and serine [B(SE): -1.534 (0.668), p = 0.023]. Discussion: The metabolome may contribute to the relationship between MetS and epigenetic modifications.

DNA methylation and 28-year cardiovascular disease risk in type 1 diabetes: the Epidemiology of Diabetes Complications (EDC) cohort study

BACKGROUND

The potential for DNA methylation (DNAm) as an early marker for cardiovascular disease (CVD) and how such an association might differ by glycemic exposure has not been examined in type 1 diabetes, a population at increased CVD risk. We thus performed a prospective epigenome-wide association study of blood leukocyte DNAm (EPIC array) and time to CVD incidence over 28 years in a childhood-onset (< 17 years) type 1 diabetes cohort, the Pittsburgh Epidemiology of Diabetes Complications (EDC) study (n = 368 with DNA and no CVD at baseline), both overall and separately by glycemic exposure, as measured by HbA1c at baseline (split at the median: < 8.9% and ≥ 8.9%). We also assessed whether DNAm-CVD associations were independent of established cardiometabolic risk factors, including body mass index, estimated glucose disposal rate, cholesterol, triglycerides, blood pressure, pulse rate, albumin excretion rate, and estimated glomerular filtration rate.

RESULTS

CVD (first instance of CVD death, myocardial infarction, coronary revascularization, ischemic ECG, angina, or stroke) developed in 172 participants (46.7%) over 28 years. Overall, in Cox regression models for time to CVD, none of the 683,597 CpGs examined reached significance at a false discovery rate (FDR) ≤ 0.05. In participants with HbA1c < 8.9% (n = 180), again none reached FDR ≤ 0.05, but three were associated at the a priori nominal significance level FDR ≤ 0.10: cg07147033 in MIB2, cg12324048 (intergenic, chromosome 3), and cg15883830 (intergenic, chromosome 1). In participants with HbA1c ≥ 8.9% (n = 188), two CpGs in loci involved in calcium channel activity were significantly associated with CVD (FDR ≤ 0.05): cg21823999 in GPM6A and cg23621817 in CHRNA9; four additional CpGs were nominally associated (FDR ≤ 0.10). In participants with HbA1c ≥ 8.9%, DNAm-CVD associations were only modestly attenuated after cardiometabolic risk factor adjustment, while attenuation was greater in those with HbA1c < 8.9%. No pathways were enriched in those with HbA1c < 8.9%, while pathways for calcium channel activity and integral component of synaptic membrane were significantly enriched in those with HbA1c ≥ 8.9%.

CONCLUSIONS

These results provide novel evidence that DNAm at loci involved in calcium channel activity and development may contribute to long-term CVD risk beyond known risk factors in type 1 diabetes, particularly in individuals with greater glycemic exposure, warranting further study.

Genetic and epigenetic background of diabetic kidney disease

Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.