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Volume 45(2); March 2021
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Reviews
Basic Research
Application of Animal Models in Diabetic Cardiomyopathy
Wang-Soo Lee, Jaetaek Kim
Diabetes Metab J. 2021;45(2):129-145.   Published online March 25, 2021
DOI: https://doi.org/10.4093/dmj.2020.0285
  • 9,356 View
  • 335 Download
  • 10 Web of Science
  • 14 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDFPubReader   ePub   
Diabetic heart disease is a growing and important public health risk. Apart from the risk of coronary artery disease or hypertension, diabetes mellitus (DM) is a well-known risk factor for heart failure in the form of diabetic cardiomyopathy (DiaCM). Currently, DiaCM is defined as myocardial dysfunction in patients with DM in the absence of coronary artery disease and hypertension. The underlying pathomechanism of DiaCM is partially understood, but accumulating evidence suggests that metabolic derangements, oxidative stress, increased myocardial fibrosis and hypertrophy, inflammation, enhanced apoptosis, impaired intracellular calcium handling, activation of the renin-angiotensin-aldosterone system, mitochondrial dysfunction, and dysregulation of microRNAs, among other factors, are involved. Numerous animal models have been used to investigate the pathomechanisms of DiaCM. Despite some limitations, animal models for DiaCM have greatly advanced our understanding of pathomechanisms and have helped in the development of successful disease management strategies. In this review, we summarize the current pathomechanisms of DiaCM and provide animal models for DiaCM according to its pathomechanisms, which may contribute to broadening our understanding of the underlying mechanisms and facilitating the identification of possible new therapeutic targets.

Citations

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Cardiovascular Risk/Epidemiology
Epidemiology, Pathophysiology, Diagnosis and Treatment of Heart Failure in Diabetes
Jin Joo Park
Diabetes Metab J. 2021;45(2):146-157.   Published online March 25, 2021
DOI: https://doi.org/10.4093/dmj.2020.0282
Correction in: Diabetes Metab J 2021;45(5):796
  • 14,353 View
  • 1,237 Download
  • 55 Web of Science
  • 60 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
The cardiovascular disease continuum begins with risk factors such as diabetes mellitus (DM), progresses to vasculopathy and myocardial dysfunction, and finally ends with cardiovascular death. Diabetes is associated with a 2- to 4-fold increased risk for heart failure (HF). Moreover, HF patients with DM have a worse prognosis than those without DM. Diabetes can cause myocardial ischemia via micro- and macrovasculopathy and can directly exert deleterious effects on the myocardium. Hyperglycemia, hyperinsulinemia, and insulin resistance can cause alterations in vascular homeostasis. Then, reduced nitric oxide and increased reactive oxygen species levels favor inflammation leading to atherothrombotic progression and myocardial dysfunction. The classification, diagnosis, and treatment of HF for a patient with and without DM remain the same. Until now, drugs targeting neurohumoral and metabolic pathways improved mortality and morbidity in HF with reduced ejection fraction (HFrEF). Therefore, all HFrEF patients should receive guideline-directed medical therapy. By contrast, drugs modulating neurohumoral activity did not improve survival in HF with preserved ejection fraction (HFpEF) patients. Trials investigating whether sodium-glucose cotransporter-2 inhibitors are effective in HFpEF are on-going. This review will summarize the epidemiology, pathophysiology, and treatment of HF in diabetes.

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Cardiovascular Risk/Epidemiology
Diabetes Management in Patients with Heart Failure
Jia Shen, Barry H. Greenberg
Diabetes Metab J. 2021;45(2):158-172.   Published online March 25, 2021
DOI: https://doi.org/10.4093/dmj.2020.0296
  • 8,411 View
  • 510 Download
  • 7 Web of Science
  • 11 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDFPubReader   ePub   
Diabetes and heart failure (HF) are common diseases, each affecting large segments of the world population. Moreover, prevalence rates for both are expected to rise dramatically over coming decades. The high prevalence rates of both diseases and wellrecognized association of diabetes as a risk factor for HF make it inevitable that both diseases co-exist in a large number of patients, complicating their management and increasing the risk of a poor outcome. Management of diabetes has been shown to impact clinical events in patients with HF and there is emerging evidence that agents used to treat diabetes can reduce HF events, even in non-diabetic patients. In this review we summarize the clinical course and treatment of patients with type 2 diabetes mellitus (T2DM) and HF and review the efficacy and safety of pharmacological agents in patients with T2DM at risk for HF and those with established disease.

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    International Journal of Cardiology.2024; 407: 132109.     CrossRef
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    Journal of Racial and Ethnic Health Disparities.2024;[Epub]     CrossRef
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Editorial
Skeletal Muscle Should Not Be Overlooked
Ji A Seo
Diabetes Metab J. 2021;45(2):173-174.   Published online March 25, 2021
DOI: https://doi.org/10.4093/dmj.2021.0024
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Original Articles
Metabolic Risk/Epidemiology
Insulin Resistance Increases Serum Immunoglobulin E Sensitization in Premenopausal Women
Seung Eun Lee, Ji Yeon Baek, Kyungdo Han, Eun Hee Koh
Diabetes Metab J. 2021;45(2):175-182.   Published online April 14, 2020
DOI: https://doi.org/10.4093/dmj.2019.0150
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Graphical AbstractGraphical Abstract AbstractAbstract PDFPubReader   ePub   
Background

Although studies have shown that obesity is associated with aeroallergen sensitization (atopy), controversy still exists. We aimed to investigate the association between metabolic status, obesity, and atopy stratified by sex and menopausal status.

Methods

A total of 1,700 adults from the 2010 Korean National Health and Nutrition Examination Survey were classified into metabolically healthy nonobese (MHNO), metabolically unhealthy nonobese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) by body mass index and insulin resistance. Atopy was defined as a positive response to at least one aeroallergen. Multiple regression analysis was used to evaluate the risk of immunoglobulin E (IgE) elevation or atopy in relation to the degree of metabolic abnormality and obesity.

Results

In premenopausal women, total IgE was positively correlated with obesity and insulin resistance. MUNO participants had a higher risk of having elevated total IgE compared to MHNO participants (odds ratio [OR], 2.271; 95% confidence interval [CI], 1.201 to 4.294), while MHO participants did not show a significant difference (OR, 1.435; 95% CI, 0.656 to 3.137) in premenopausal women. MUNO, but not MHO was also associated with atopy (OR, 2.157; 95% CI, 1.284 to 3.625). In men and postmenopausal women, there was no significant difference between metabolic status, obesity, and atopy among groups.

Conclusion

Increased insulin resistance is associated with total IgE and atopy in premenopausal women but not in postmenopausal women or men.

Citations

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  • Association of serum total IgE and allergen-specific IgE with insulin resistance in adolescents: an analysis of the NHANES database
    Yaping Liu, Xiaoxia Wang, Yong Liu
    BMC Pediatrics.2024;[Epub]     CrossRef
  • Is There a Relationship between Insulin Resistance and Eosinophil, Inflammatory Parameters Neutrophil to lymphocyte ratio, C-Reactive Protein Values?
    Meltem YİĞİT, Özgür OLUKMAN
    Medical Records.2024; 6(1): 32.     CrossRef
Metabolic Risk/Epidemiology
Age- and Sex-Related Differential Associations between Body Composition and Diabetes Mellitus
Eun Roh, Soon Young Hwang, Jung A Kim, You-Bin Lee, So-hyeon Hong, Nam Hoon Kim, Ji A Seo, Sin Gon Kim, Nan Hee Kim, Kyung Mook Choi, Sei Hyun Baik, Hye Jin Yoo
Diabetes Metab J. 2021;45(2):183-194.   Published online June 16, 2020
DOI: https://doi.org/10.4093/dmj.2019.0171
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Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

The age- and sex-related differences on the impacts of body composition on diabetes mellitus (DM) remain uncertain.

Methods

The fourth and fifth Korea National Health and Nutrition Examination Survey included 15,586 subjects over 30 years of age who completed dual-energy X-ray absorptiometry. We conducted a cross-sectional study to investigate whether muscle mass index (MMI), defined as appendicular skeletal muscle divided by body mass index (BMI), and fat mass index (FMI), defined as trunk fat mass divided by BMI, were differently associated with DM according to age and sex.

Results

In multivariate logistic regression, the risk for DM significantly increased across quartiles of FMI in men aged ≥70. Meanwhile, MMI showed a protective association with DM in men of the same age. The odds ratios (ORs) for the highest quartile versus the lowest quartile of FMI and MMI were 3.116 (95% confidence interval [CI], 1.405 to 6.914) and 0.295 (95% CI, 0.157 to 0.554), respectively. In women, the ORs of DM was significantly different across FMI quartiles in those over age 50. The highest quartile of FMI exhibited increased ORs of DM in subjects aged 50 to 69 (OR, 1.891; 95% CI, 1.229 to 2.908) and ≥70 (OR, 2.275; 95% CI, 1.103 to 4.69) compared to lowest quartile. However, MMI was not significantly associated with DM in women of all age groups.

Conclusion

Both FMI and MMI were independent risk factors for DM in men aged 70 years or more. In women over 50 years, FMI was independently associated with DM. There was no significant association between MMI and DM in women.

Citations

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  • Research Progress on Correlation between Body Composition Changes and Disease Pro-gression of Type 2 Diabetes
    敏 张
    Advances in Clinical Medicine.2024; 14(03): 936.     CrossRef
  • Low Skeletal Muscle Mass Accompanied by Abdominal Obesity Additively Increases the Risk of Incident Type 2 Diabetes
    Ji Eun Jun, Seung-Eun Lee, You-Bin Lee, Gyuri Kim, Sang-Man Jin, Jae Hwan Jee, Jae Hyeon Kim
    The Journal of Clinical Endocrinology & Metabolism.2023; 108(5): 1173.     CrossRef
  • Is imaging-based muscle quantity associated with risk of diabetes? A meta-analysis of cohort studies
    Shanhu Qiu, Xue Cai, Yang Yuan, Bo Xie, Zilin Sun, Tongzhi Wu
    Diabetes Research and Clinical Practice.2022; 189: 109939.     CrossRef
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    Şükran Nazan Koşar, Yasemin Güzel, Mehmet Gören Köse, Ayşe Kin İşler, Tahir Hazır
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    Hye Jin Yoo
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Metabolic Risk/Epidemiology
Plasma Targeted Metabolomics Analysis for Amino Acids and Acylcarnitines in Patients with Prediabetes, Type 2 Diabetes Mellitus, and Diabetic Vascular Complications
Xin Li, Yancheng Li, Yuanhao Liang, Ruixue Hu, Wenli Xu, Yufeng Liu
Diabetes Metab J. 2021;45(2):195-208.   Published online March 9, 2021
DOI: https://doi.org/10.4093/dmj.2019.0209
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Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
We hypothesized that specific amino acids or acylcarnitines would have benefits for the differential diagnosis of diabetes. Thus, a targeted metabolomics for amino acids and acylcarnitines in patients with diabetes and its complications was carried out.
Methods
A cohort of 54 normal individuals and 156 patients with type 2 diabetes mellitus and/or diabetic complications enrolled from the First Affiliated Hospital of Jinzhou Medical University was studied. The subjects were divided into five main groups: normal individuals, impaired fasting glucose, overt diabetes, diabetic microvascular complications, and diabetic peripheral vascular disease. The technique of tandem mass spectrometry was applied to obtain the plasma metabolite profiles. Metabolomics multivariate statistics were applied for the metabolic data analysis and the differential metabolites determination.
Results
A total of 10 cross-comparisons within diabetes and its complications were designed to explore the differential metabolites. The results demonstrated that eight comparisons existed and yielded significant metabolic differences. A total number of 24 differential metabolites were determined from six selected comparisons, including up-regulated amino acids, down-regulated medium-chain and long-chain acylcarnitines. Altered differential metabolites provided six panels of biomarkers, which were helpful in distinguishing diabetic patients.
Conclusion
Our results demonstrated that the biomarker panels consisted of specific amino acids and acylcarnitines which could reflect the metabolic variations among the different stages of diabetes and might be useful for the differential diagnosis of prediabetes, overt diabetes and diabetic complications.

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  • Liquid Biopsy: A Game Changer for Type 2 Diabetes
    Gratiela Gradisteanu Pircalabioru, Madalina Musat, Viviana Elian, Ciprian Iliescu
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    Shaghayegh Hosseinkhani, Babak Arjmand, Arezou Dilmaghani-Marand, Sahar Mohammadi Fateh, Hojat Dehghanbanadaki, Niloufar Najjar, Sepideh Alavi-Moghadam, Robabeh Ghodssi-Ghassemabadi, Ensieh Nasli-Esfahani, Farshad Farzadfar, Bagher Larijani, Farideh Razi
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    Zongyi Wang, Jiyang Tang, Enzhong Jin, Yusheng Zhong, Linqi Zhang, Xinyao Han, Jia Liu, Yong Cheng, Jing Hou, Xuan Shi, Huijun Qi, Tong Qian, Li Yuan, Xianru Hou, Hong Yin, Jianhong Liang, Mingwei Zhao, Lvzhen Huang, Jinfeng Qu
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Metabolic Risk/Epidemiology
Effect of Sarcopenia and Body Shape on Cardiovascular Disease According to Obesity Phenotypes
Hyun-Woong Cho, Wankyo Chung, Shinje Moon, Ohk-Hyun Ryu, Min Kyung Kim, Jun Goo Kang
Diabetes Metab J. 2021;45(2):209-218.   Published online July 10, 2020
DOI: https://doi.org/10.4093/dmj.2019.0223
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

This study aimed to assess the effects of sarcopenia and A Body Shape Index (ABSI) on cardiovascular disease (CVD) risk according to obesity phenotypes.

Methods

We used data from the National Health and Nutrition Examination Survey 1999 to 2012. A total of 25,270 adults were included and classified into the following groups: metabolically healthy normal weight (MHNW), metabolically healthy overweight/obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy overweight/obese (MUO). Sarcopenia was defined as the appendicular skeletal mass index <7 kg/m2 in men and <5.5kg/m2 in women. A multivariate logistic regression analysis was performed to evaluate the odds ratio (OR) of sarcopenia and ABSI for CVD events according to the obesity phenotype.

Results

The MHNW participants with sarcopenia had higher risk for CVD than those without sarcopenia (OR, 2.69; 95% confidence interval [CI], 1.56 to 4.64). In the analysis with MHNW participants without sarcopenia as a reference, the participants with sarcopenia showed a higher OR for CVD than those without sarcopenia in both MHO (OR in participants without sarcopenia, 3.31; 95% CI, 1.94 to 5.64) (OR in participants with sarcopenia, 8.59; 95% CI, 2.63 to 28.04) and MUO participants (OR in participants without sarcopenia, 5.11; 95% CI, 3.21 to 8.15) (OR in participants with sarcopenia, 8.12; 95% CI, 4.04 to 16.32). Participants within the second and third tertiles of ABSI had higher ORs for CVDs than the counterpart of obesity phenotypes within the first tertile.

Conclusion

These results suggest that clinical approaches that consider muscle and body shape are required.

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    Ji A Seo
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Cardiovascular Risk/Epidemiology
Clinical Significance of Body Fat Distribution in Coronary Artery Calcification Progression in Korean Population
Heesun Lee, Hyo Eun Park, Ji Won Yoon, Su-Yeon Choi
Diabetes Metab J. 2021;45(2):219-230.   Published online October 28, 2020
DOI: https://doi.org/10.4093/dmj.2019.0161
Correction in: Diabetes Metab J 2021;45(6):974
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Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Although obesity differs according to ethnicity, it is globally established as a solid risk factor for cardiovascular disease. However, it is not fully understood how obesity parameters affect the progression of coronary artery calcification (CAC) in Korean population. We sought to evaluate the association of obesity-related parameters including visceral adipose tissue (VAT) measurement and CAC progression.
Methods
This retrospective observational cohort study investigated 1,015 asymptomatic Korean subjects who underwent serial CAC scoring by computed tomography (CT) with at least 1-year interval and adipose tissue measurement using non-contrast CT at baseline for a routine checkup between 2003 and 2015. CAC progression, the main outcome, was defined as a difference of ≥2.5 between the square roots of the baseline and follow-up CAC scores using Agatston units.
Results
During follow-up (median 39 months), 37.5% of subjects showed CAC progression of a total population (56.4 years, 80.6% male). Body mass index (BMI) ≥25 kg/m2, increasing waist circumferences (WC), and higher VAT/subcutaneous adipose tissue (SAT) area ratio were independently associated with CAC progression. Particularly, predominance of VAT over SAT at ≥30% showed the strongest prediction for CAC progression (adjusted hazard ratio, 2.20; P<0.001) and remained of prognostic value regardless of BMI or WC status. Further, it provided improved risk stratification of CAC progression beyond known prognosticators.
Conclusion
Predominant VAT area on CT is the strongest predictor of CAC progression regardless of BMI or WC in apparently healthy Korean population. Assessment of body fat distribution may be helpful to identify subjects at higher risk.

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Genetics
Exome Chip Analysis of 14,026 Koreans Reveals Known and Newly Discovered Genetic Loci Associated with Type 2 Diabetes Mellitus
Seong Beom Cho, Jin Hwa Jang, Myung Guen Chung, Sang Cheol Kim
Diabetes Metab J. 2021;45(2):231-240.   Published online July 28, 2020
DOI: https://doi.org/10.4093/dmj.2019.0163
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Background

Most loci associated with type 2 diabetes mellitus (T2DM) discovered to date are within noncoding regions of unknown functional significance. By contrast, exonic regions have advantages for biological interpretation.

Methods

We analyzed the association of exome array data from 14,026 Koreans to identify susceptible exonic loci for T2DM. We used genotype information of 50,543 variants using the Illumina exome array platform.

Results

In total, 7 loci were significant with a Bonferroni adjusted P=1.03×10−6. rs2233580 in paired box gene 4 (PAX4) showed the highest odds ratio of 1.48 (P=1.60×10−10). rs11960799 in membrane associated ring-CH-type finger 3 (MARCH3) and rs75680863 in transcobalamin 2 (TCN2) were newly identified loci. When we built a model to predict the incidence of diabetes with the 7 loci and clinical variables, area under the curve (AUC) of the model improved significantly (AUC=0.72, P<0.05), but marginally in its magnitude, compared with the model using clinical variables (AUC=0.71, P<0.05). When we divided the entire population into three groups—normal body mass index (BMI; <25 kg/m2), overweight (25≤ BMI <30 kg/m2), and obese (BMI ≥30 kg/m2) individuals—the predictive performance of the 7 loci was greatest in the group of obese individuals, where the net reclassification improvement was highly significant (0.51; P=8.00×10−5).

Conclusion

We found exonic loci having a susceptibility for T2DM. We found that such genetic information is advantageous for predicting T2DM in a subgroup of obese individuals.

Citations

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  • Polygenic Risk Score, Lifestyles, and Type 2 Diabetes Risk: A Prospective Chinese Cohort Study
    Jia Liu, Lu Wang, Xuan Cui, Qian Shen, Dun Wu, Man Yang, Yunqiu Dong, Yongchao Liu, Hai Chen, Zhijie Yang, Yaqi Liu, Meng Zhu, Hongxia Ma, Guangfu Jin, Yun Qian
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    Hye-Ah Lee, Hyesook Park
    Nutrients.2022; 14(3): 654.     CrossRef
  • Ethnic-Specific Type 2 Diabetes Risk Factor PAX4 R192H Is Associated with Attention-Specific Cognitive Impairment in Chinese with Type 2 Diabetes
    Su Fen Ang, Serena Low, Tze Pin Ng, Clara S.H. Tan, Keven Ang, Ziliang Lim, Wern Ee Tang, Tavintharan Subramaniam, Chee Fang Sum, Su Chi Lim, Nagaendran Kandiah
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  • TrustGWAS: A full-process workflow for encrypted GWAS using multi-key homomorphic encryption and pseudorandom number perturbation
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Genetics
Enhancer-Gene Interaction Analyses Identified the Epidermal Growth Factor Receptor as a Susceptibility Gene for Type 2 Diabetes Mellitus
Yang Yang, Shi Yao, Jing-Miao Ding, Wei Chen, Yan Guo
Diabetes Metab J. 2021;45(2):241-250.   Published online June 10, 2020
DOI: https://doi.org/10.4093/dmj.2019.0204
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

Genetic interactions are known to play an important role in the missing heritability problem for type 2 diabetes mellitus (T2DM). Interactions between enhancers and their target genes play important roles in gene regulation and disease pathogenesis. In the present study, we aimed to identify genetic interactions between enhancers and their target genes associated with T2DM.

Methods

We performed genetic interaction analyses of enhancers and protein-coding genes for T2DM in 2,696 T2DM patients and 3,548 controls of European ancestry. A linear regression model was used to identify single nucleotide polymorphism (SNP) pairs that could affect the expression of the protein-coding genes. Differential expression analyses were used to identify differentially expressed susceptibility genes in diabetic and nondiabetic subjects.

Results

We identified one SNP pair, rs4947941×rs7785013, significantly associated with T2DM (combined P=4.84×10−10). The SNP rs4947941 was annotated as an enhancer, and rs7785013 was located in the epidermal growth factor receptor (EGFR) gene. This SNP pair was significantly associated with EGFR expression in the pancreas (P=0.033), and the minor allele “A” of rs7785013 decreased EGFR gene expression and the risk of T2DM with an increase in the dosage of “T” of rs4947941. EGFR expression was significantly upregulated in T2DM patients, which was consistent with the effect of rs4947941×rs7785013 on T2DM and EGFR expression. A functional validation study using the Mouse Genome Informatics (MGI) database showed that EGFR was associated with diabetes-relevant phenotypes.

Conclusion

Genetic interaction analyses of enhancers and protein-coding genes suggested that EGFR may be a novel susceptibility gene for T2DM.

Citations

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    Raymond C. Harris
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  • Co-expression Network Revealed Roles of RNA m6A Methylation in Human β-Cell of Type 2 Diabetes Mellitus
    Cong Chen, Qing Xiang, Weilin Liu, Shengxiang Liang, Minguang Yang, Jing Tao
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COVID-19
Effects of a DPP-4 Inhibitor and RAS Blockade on Clinical Outcomes of Patients with Diabetes and COVID-19
Sang Youl Rhee, Jeongwoo Lee, Hyewon Nam, Dae-Sung Kyoung, Dong Wook Shin, Dae Jung Kim
Diabetes Metab J. 2021;45(2):251-259.   Published online March 5, 2021
DOI: https://doi.org/10.4093/dmj.2020.0206
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Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Dipeptidyl peptidase-4 inhibitor (DPP-4i) and renin-angiotensin system (RAS) blockade are reported to affect the clinical course of coronavirus disease 2019 (COVID-19) in patients with diabetes mellitus (DM).
Methods
As of May 2020, analysis was conducted on all subjects who could confirm their history of claims related to COVID-19 in the National Health Insurance Review and Assessment Service (HIRA) database in Korea. Using this dataset, we compared the short-term prognosis of COVID-19 infection according to the use of DPP-4i and RAS blockade. Additionally, we validated the results using the National Health Insurance Service (NHIS) of Korea dataset.
Results
Totally, data of 67,850 subjects were accessible in the HIRA dataset. Of these, 5,080 were confirmed COVID-19. Among these, 832 subjects with DM were selected for analysis in this study. Among the subjects, 263 (31.6%) and 327 (39.3%) were DPP4i and RAS blockade users, respectively. Thirty-four subjects (4.09%) received intensive care or died. The adjusted odds ratio for severe treatment among DPP-4i users was 0.362 (95% confidence interval [CI], 0.135 to 0.971), and that for RAS blockade users was 0.599 (95% CI, 0.251 to 1.431). These findings were consistent with the analysis based on the NHIS data using 704 final subjects. The adjusted odds ratio for severe treatment among DPP-4i users was 0.303 (95% CI, 0.135 to 0.682), and that for RAS blockade users was 0.811 (95% CI, 0.391 to 1.682).
Conclusion
This study suggests that DPP-4i is significantly associated with a better clinical outcome of patients with COVID-19.

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Basic Research
Umbilical Cord-Mesenchymal Stem Cell-Conditioned Medium Improves Insulin Resistance in C2C12 Cell
Kyung-Soo Kim, Yeon Kyung Choi, Mi Jin Kim, Jung Wook Hwang, Kyunghoon Min, Sang Youn Jung, Soo-Kyung Kim, Yong-Soo Choi, Yong-Wook Cho
Diabetes Metab J. 2021;45(2):260-269.   Published online July 10, 2020
DOI: https://doi.org/10.4093/dmj.2019.0191
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Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

Umbilical cord-mesenchymal stem cell-conditioned medium (UC-MSC-CM) has emerged as a promising cell-free therapy. The aim of this study was to explore the therapeutic effects of UC-MSC-CM on insulin resistance in C2C12 cell.

Methods

Insulin resistance was induced by palmitate. Effects of UC-MSC-CM on insulin resistance were evaluated using glucose uptake, glucose transporter type 4 (GLUT4) translocation, the insulin-signaling pathway, and mitochondrial contents and functions in C2C12 cell.

Results

Glucose uptake was improved by UC-MSC-CM. UC-MSC-CM treatment increased only in membranous GLUT4 expression, not in cytosolic GLUT4 expression. It restored the insulin-signaling pathway in insulin receptor substrate 1 and protein kinase B. Mitochondrial contents evaluated by mitochondrial transcription factor A, mitochondrial DNA copy number, and peroxisome proliferator-activated receptor gamma coactivator 1-alpha were increased by UC-MSC-CM. In addition, UC-MSC-CM significantly decreased mitochondrial reactive oxygen species and increased fatty acid oxidation and mitochondrial membrane potential. There was no improvement in adenosine triphosphate (ATP) contents, but ATP synthesis was improved by UC-MSC-CM. Cytokine and active factor analysis of UC-MSC-CM showed that it contained many regulators inhibiting insulin resistance.

Conclusion

UC-MSC-CM improves insulin resistance with multiple mechanisms in C2C12 cell.

Citations

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    Human Cell.2023; 37(1): 54.     CrossRef
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    Francesca Paris, Valeria Pizzuti, Pasquale Marrazzo, Andrea Pession, Francesco Alviano, Laura Bonsi
    International Journal of Molecular Sciences.2022; 23(23): 14597.     CrossRef
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    Huixue Tang, Huikun Luo, Zihan Zhang, Di Yang
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    Andreia Gomes, Pedro Coelho, Raquel Soares, Raquel Costa
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Brief Report
Cardiovascular risk/Epidemiology
Clinical Impact of Dysglycemia in Patients with an Acute Myocardial Infarction
Jae-Wook Chung, Yeong-Seon Park, Jeong-Eon Seo, Yeseul Son, Cheol-Woo Oh, Chan-Hee Lee, Jong-Ho Nam, Jung-Hee Lee, Jang-Won Son, Ung Kim, Jong-Seon Park, Kyu-Chang Won, Dong-Gu Shin
Diabetes Metab J. 2021;45(2):270-274.   Published online April 16, 2020
DOI: https://doi.org/10.4093/dmj.2019.0164
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Graphical AbstractGraphical Abstract AbstractAbstract PDFPubReader   ePub   

This study aimed to determine the impact of dysglycemia on myocardial injury and cardiac dysfunction in acute myocardial infarctions (AMIs). From 2005 to 2016, a total of 1,593 patients with AMIs who underwent percutaneous coronary intervention were enrolled. The patients were classified into five groups according to the admission glucose level: ≤80, 81 to 140, 141 to 200, 201 to 260, and ≥261 mg/dL. The clinical and echocardiographic parameters and 30-day mortality were analyzed. The peak troponin I and white blood cell levels had a positive linear relationship to the admission glucose level. The left ventricular ejection fraction had an inverted U-shape trend, and the E/E' ratio was U-shaped based on euglycemia. The 30-day mortality also increased as the admission glucose increased, and the cut-off value for predicting the mortality was 202.5 mg/dL. Dysglycemia, especially hyperglycemia, appears to be associated with myocardial injury and could be another adjunctive parameter for predicting mortality in patients with AMIs.

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DOI: https://doi.org/10.4093/dmj.2020.0288
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Citations

Citations to this article as recorded by  
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    Frontiers in Endocrinology.2022;[Epub]     CrossRef

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