Cardiovascular diseases (CVDs) and metabolic disorders stand as formidable challenges that significantly impact the clinical outcomes and living quality for afflicted individuals. An intricate comprehension of the underlying mechanisms is paramount for the development of efficacious therapeutic strategies. Protein arginine methyltransferases (PRMTs), a class of enzymes responsible for the precise regulation of protein methylation, have ascended to pivotal roles and emerged as crucial regulators within the intrinsic pathophysiology of these diseases. Herein, we review recent advancements in research elucidating on the multifaceted involvements of PRMTs in cardiovascular system and metabolic diseases, contributing significantly to deepen our understanding of the pathogenesis and progression of these maladies. In addition, this review provides a comprehensive analysis to unveil the distinctive roles of PRMTs across diverse cell types implicated in cardiovascular and metabolic disorders, which holds great potential to reveal novel therapeutic interventions targeting PRMTs, thus presenting promising perspectives to effectively address the substantial global burden imposed by CVDs and metabolic disorders.
Several mitochondrial dysfunctions in obesity and diabetes include impaired mitochondrial membrane potential, excessive mitochondrial reactive oxygen species generation, reduced mitochondrial DNA, increased mitochondrial Ca2+ flux, and mitochondrial dynamics disorders. Mitophagy, specialized autophagy, is responsible for clearing dysfunctional mitochondria in physiological and pathological conditions. As a paradox, inhibition and activation of mitophagy have been observed in obesity and diabetes-related heart disorders, with both exerting bidirectional effects. Suppressed mitophagy is beneficial to mitochondrial homeostasis, also known as benign mitophagy. On the contrary, in most cases, excessive mitophagy is harmful to dysfunctional mitochondria elimination and thus is defined as detrimental mitophagy. In obesity and diabetes, two classical pathways appear to regulate mitophagy, including PTEN-induced putative kinase 1 (PINK1)/Parkin-dependent mitophagy and receptors/adapters-dependent mitophagy. After the pharmacologic interventions of mitophagy, mitochondrial morphology and function have been restored, and cell viability has been further improved. Herein, we summarize the mitochondrial dysfunction and mitophagy alterations in obesity and diabetes, as well as the underlying upstream mechanisms, in order to provide novel therapeutic strategies for the obesity and diabetes-related heart disorders.
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Background Diabetes-induced cardiac fibrosis is one of the main mechanisms of diabetic cardiomyopathy. As a common histone methyltransferase, enhancer of zeste homolog 2 (EZH2) has been implicated in fibrosis progression in multiple organs. However, the mechanism of EZH2 in diabetic myocardial fibrosis has not been clarified.
Methods In the current study, rat and mouse diabetic model were established, the left ventricular function of rat and mouse were evaluated by echocardiography and the fibrosis of rat ventricle was evaluated by Masson staining. Primary rat ventricular fibroblasts were cultured and stimulated with high glucose (HG) in vitro. The expression of histone H3 lysine 27 (H3K27) trimethylation, EZH2, and myocardial fibrosis proteins were assayed.
Results In STZ-induced diabetic ventricular tissues and HG-induced primary ventricular fibroblasts in vitro, H3K27 trimethylation was increased and the phosphorylation of EZH2 was reduced. Inhibition of EZH2 with GSK126 suppressed the activation, differentiation, and migration of cardiac fibroblasts as well as the overexpression of the fibrotic proteins induced by HG. Mechanical study demonstrated that HG reduced phosphorylation of EZH2 on Thr311 by inactivating AMP-activated protein kinase (AMPK), which transcriptionally inhibited peroxisome proliferator-activated receptor γ (PPAR-γ) expression to promote the fibroblasts activation and differentiation.
Conclusion Our data revealed an AMPK/EZH2/PPAR-γ signal pathway is involved in HG-induced cardiac fibrosis.
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Background It is well known that a large number of patients with diabetes also have dyslipidemia, which significantly increases the risk of cardiovascular disease (CVD). This study aimed to evaluate the efficacy and safety of combination drugs consisting of metformin and atorvastatin, widely used as therapeutic agents for diabetes and dyslipidemia.
Methods This randomized, double-blind, placebo-controlled, parallel-group and phase III multicenter study included adults with glycosylated hemoglobin (HbA1c) levels >7.0% and <10.0%, low-density lipoprotein cholesterol (LDL-C) >100 and <250 mg/dL. One hundred eighty-five eligible subjects were randomized to the combination group (metformin+atorvastatin), metformin group (metformin+atorvastatin placebo), and atorvastatin group (atorvastatin+metformin placebo). The primary efficacy endpoints were the percent changes in HbA1c and LDL-C levels from baseline at the end of the treatment.
Results After 16 weeks of treatment compared to baseline, HbA1c showed a significant difference of 0.94% compared to the atorvastatin group in the combination group (0.35% vs. −0.58%, respectively; P<0.0001), whereas the proportion of patients with increased HbA1c was also 62% and 15%, respectively, showing a significant difference (P<0.001). The combination group also showed a significant decrease in LDL-C levels compared to the metformin group (−55.20% vs. −7.69%, P<0.001) without previously unknown adverse drug events.
Conclusion The addition of atorvastatin to metformin improved HbA1c and LDL-C levels to a significant extent compared to metformin or atorvastatin alone in diabetes and dyslipidemia patients. This study also suggested metformin’s preventive effect on the glucose-elevating potential of atorvastatin in patients with type 2 diabetes mellitus and dyslipidemia, insufficiently controlled with exercise and diet. Metformin and atorvastatin combination might be an effective treatment in reducing the CVD risk in patients with both diabetes and dyslipidemia because of its lowering effect on LDL-C and glucose.
Background We aimed to evaluate whether composite blood biomarkers including aldo-keto reductase family 1 member B10 (AKR1B10) and cytokeratin 18 (CK-18; a nonalcoholic steatohepatitis [NASH] marker) have clinically applicable performance for the diagnosis of NASH, advanced liver fibrosis, and high-risk NASH (NASH+significant fibrosis).
Methods A total of 116 subjects including healthy control subjects and patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD) were analyzed to assess composite blood-based and imaging-based biomarkers either singly or in combination.
Results A composite blood biomarker comprised of AKR1B10, CK-18, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) showed excellent performance for the diagnosis of, NASH, advanced fibrosis, and high-risk NASH, with area under the receiver operating characteristic curve values of 0.934 (95% confidence interval [CI], 0.888 to 0.981), 0.902 (95% CI, 0.832 to 0.971), and 0.918 (95% CI, 0.862 to 0.974), respectively. However, the performance of this blood composite biomarker was inferior to that various magnetic resonance (MR)-based composite biomarkers, such as proton density fat fraction/MR elastography- liver stiffness measurement (MRE-LSM)/ALT/AST for NASH, MRE-LSM+fibrosis-4 index for advanced fibrosis, and the known MR imaging-AST (MAST) score for high-risk NASH.
Conclusion Our blood composite biomarker can be useful to distinguish progressive forms of NAFLD as an initial noninvasive test when MR-based tools are not available.
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Aldo-keto reductase (AKR) superfamily website and database: An update Andrea Andress Huacachino, Jaehyun Joo, Nisha Narayanan, Anisha Tehim, Blanca E. Himes, Trevor M. Penning Chemico-Biological Interactions.2024; 398: 111111. CrossRef
Background To investigate the association between the time-varying resting heart rate (RHR) and change in RHR (∆RHR) over time and the risk of diabetes mellitus (DM) by sex.
Methods We assessed 8,392 participants without DM or atrial fibrillation/flutter from the Korean Genome and Epidemiology Study, a community-based prospective cohort study that was initiated in 2001 to 2002. The participants were followed up until December 31, 2018. Updating RHR with biennial in-study re-examinations, the time-varying ∆RHR was calculated by assessing the ∆RHR at the next follow-up visit.
Results Over a median follow-up of 12.3 years, 1,345 participants (16.2%) had DM. As compared with RHR of 60 to 69 bpm, for RHR of ≥80 bpm, the incidence of DM was significantly increased for both male and female. A drop of ≥5 bpm in ∆RHR when compared with the stable ∆RHR group (–5< ∆RHR <5 bpm) was associated significantly with lower risk of DM in both male and female. However, an increase of ≥5 bpm in ∆RHR was significantly associated with higher risk of DM only in female, not in male (hazard ratio for male, 1.057 [95% confidence interval, 0.869 to 1.285]; and for female, 1.218 [95% confidence interval, 1.008 to 1.471]).
Conclusion In this community-based longitudinal cohort study, a reduction in ∆RHR was associated with a decreased risk of DM, while an increase in ∆RHR was associated with an increased risk of DM only in female.
Background We evaluated changes in glycemic status, over 1 year, of coronavirus disease 2019 (COVID-19) survivors with dysglycemia in acute COVID-19.
Methods COVID-19 survivors who had dysglycemia (defined by glycosylated hemoglobin [HbA1c] 5.7% to 6.4% or random glucose ≥10.0 mmol/L) in acute COVID-19 were recruited from a major COVID-19 treatment center from September to October 2020. Matched non-COVID controls were recruited from community. The 75-g oral glucose tolerance test (OGTT) were performed at baseline (6 weeks after acute COVID-19) and 1 year after acute COVID-19, with HbA1c, insulin and C-peptide measurements. Progression in glycemic status was defined by progression from normoglycemia to prediabetes/diabetes, or prediabetes to diabetes.
Results Fifty-two COVID-19 survivors were recruited. Compared with non-COVID controls, they had higher C-peptide (P< 0.001) and trend towards higher homeostasis model assessment of insulin resistance (P=0.065). Forty-three COVID-19 survivors attended 1-year reassessment. HbA1c increased from 5.5%±0.3% to 5.7%±0.2% (P<0.001), with increases in glucose on OGTT at fasting (P=0.089), 30-minute (P=0.126), 1-hour (P=0.014), and 2-hour (P=0.165). At baseline, 19 subjects had normoglycemia, 23 had prediabetes, and one had diabetes. Over 1 year, 10 subjects (23.8%; of 42 non-diabetes subjects at baseline) had progression in glycemic status. C-peptide levels remained unchanged (P=0.835). Matsuda index decreased (P=0.007) and there was a trend of body mass index increase from 24.4±2.7 kg/m2 to 25.6±5.2 (P=0.083). Subjects with progression in glycemic status had more severe COVID-19 illness than non-progressors (P=0.030). Reassessment was not performed in the control group.
Conclusion Subjects who had dysglycemia in acute COVID-19 were characterized by insulin resistance. Over 1 year, a quarter had progression in glycemic status, especially those with more severe COVID-19. Importantly, there was no significant deterioration in insulin secretory capacity.
Background This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve.
Methods The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance.
Results The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05).
Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.
Background The effects of excessive ultra-processed food (UPF) consumption on body composition measures or sociodemographic disparities are understudied in Korea. We aimed to investigate the association of UPF intake with percent body fat (PBF) and percent appendicular skeletal muscle mass (PASM) by sociodemographic status in adults.
Methods This study used data from the Korea National Health and Nutrition Examination Survey 2008–2011 (n=11,123 aged ≥40 years). We used a NOVA system to classify all foods reported in a 24-hour dietary recall, and the percentage of energy intake (%kcal) from UPFs was estimated. PBF and PASM were measured by dual-energy X-ray absorptiometry. Tertile (T) 3 of PBF indicated adiposity and T1 of PASM indicated low skeletal muscle mass, respectively. Multinomial logistic regression models were used to estimate odds ratios (OR) with 95% confidence interval (CI) after adjusting covariates.
Results UPF intake was positively associated with PBF-defined adiposity (ORper 10% increase, 1.04; 95% CI, 1.002 to 1.08) and low PASM (ORper 10% increase, 1.05; 95% CI, 1.01 to 1.09). These associations were stronger in rural residents (PBF: ORper 10% increase, 1.14; 95% CI, 1.06 to 1.23; PASM: ORper 10% increase, 1.15; 95% CI, 1.07 to 1.23) and not college graduates (PBF: ORper 10% increase, 1.06; 95% CI, 1.02 to 1.11; PASM: ORper 10% increase, 1.07; 95% CI, 1.03 to 1.12) than their counterparts.
Conclusion A higher UPF intake was associated with higher adiposity and lower skeletal muscle mass among Korean adults aged 40 years and older, particularly in those from rural areas and with lower education levels.
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Background This study examines integrating physical and mental healthcare for disadvantaged persons with type 2 diabetes mellitus and mild-to-moderate depression in the community, using a mobile application within a public-private-academic partnership.
Methods The Korean Diabetes Association has developed a mobile application combining behavioral activation for psychological well-being and diabetes self-management, with conventional medical therapy. Participants were randomly assigned to receive the application with usual care or only usual care. Primary outcomes measured changes in psychological status and diabetes selfmanagement through questionnaires at week 12 from the baseline. Secondary outcomes assessed glycemic and lipid control, with psychological assessments at week 16.
Results Thirty-nine of 73 participants completed the study (20 and 19 in the intervention and control groups, respectively) and were included in the analysis. At week 12, the intervention group showed significant reductions in depression severity and perceived stress compared to the control group. Additionally, they reported increased perceived social support and demonstrated improved diabetes self-care behavior. These positive effects persisted through week 16, with the added benefit of reduced anxiety. While fasting glucose levels in the intervention group tended to improve, no other significant differences were observed in laboratory assessments between the groups.
Conclusion This study provides compelling evidence for the potential efficacy of a mobile application that integrates physical and mental health components to address depressive symptoms and enhance diabetes self-management in disadvantaged individuals with type 2 diabetes mellitus and depression. Further research involving larger and more diverse populations is warranted to validate these findings and solidify their implications.