Diabetes & Metabolism Journal

Review

Pharmacotherapy
SGLT2 Inhibitors and GLP-1 Receptor Agonists in Diabetic Kidney Disease: Evolving Evidence and Clinical Application: Jae Hyun Bae; Diabetes Metab J. 2025;49(3):386-402. Published online May 1, 2025; DOI: https://doi.org/10.4093/dmj.2025.0220

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Abstract PDF: Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease and significantly increases cardiovascular risk and mortality. Despite conventional therapies, including renin-angiotensin-aldosterone system inhibitors, substantial residual risk remains. The emergence of sodium-glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists has reshaped DKD management. Beyond glycemic control, these agents provide distinct and complementary cardiorenal benefits through mechanisms such as hemodynamic modulation, anti-inflammatory effects, and metabolic adaptations. Landmark trials, including CREDENCE, DAPA-CKD, EMPA-KIDNEY, and FLOW, have demonstrated their efficacy in preserving kidney function and reducing adverse outcomes. SGLT2 inhibitors appear more effective in mitigating glomerular hyperfiltration and lowering heart failure risk, whereas GLP-1 receptor agonists are particularly beneficial in reducing albuminuria and atherosclerotic cardiovascular events. Although indirect comparisons suggest that SGLT2 inhibitors may offer greater protection against kidney function decline, direct head-to-head trials are lacking. Combination therapy holds promise, however further studies are needed to define optimal treatment strategies. This review synthesizes current evidence, evaluates comparative effectiveness, and outlines future directions in DKD management, emphasizing precision medicine approaches to enhance clinical outcomes. The integration of these therapies represents a paradigm shift in diabetes care, expanding treatment options for people with diabetes mellitus at risk of kidney failure.

Original Articles

Basic and Translational Research
Inflammatory Milieu by Crosstalk between Glomerulus and Proximal Tubular Cells in Type 2 Diabetes Mellitus Kidney Disease: Peong Gang Park, Juhyeon Hwang, Yongjun Kim, Minki Hong, Donghwan Yun, Haein Yoon, Chaelin Kang, Sohyun Bae, Soo Heon Kwak, Yong Chul Kim, Kyung Chul Moon, Dong-Sup Lee, Yon Su Kim, Hee Gyung Kang, Hyun Je Kim, Seung Seok Han; Received September 4, 2024 Accepted December 12, 2024 Published online March 31, 2025; DOI: https://doi.org/10.4093/dmj.2024.0535 [Epub ahead of print]

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Abstract PDF Supplementary Material PubReader ePub: Background
Due to the limited availability of therapeutic agents for type 2 diabetic kidney disease (T2DKD), there is a need for further knowledge derived from experimental models and innovative techniques. In addressing this issue, single-cell RNA sequencing (scRNA-seq) has been exclusively applied to a genetically modified diabetic kidney disease model, but not to an induced model representing T2DKD. Herein, we analyzed scRNA-seq and other experiments from an induced T2DKD model and validated the results in human-derived biospecimens.
Methods
The model was induced by combining a high-fat diet with streptozotocin to simulate induced T2DKD. scRNA-seq, histological, and flow cytometric analyses were conducted, and the results were compared with control mice. The findings were then applied to human T2DKD kidneys.
Results
Biochemical and histological analyses unveiled early-stage T2DKD features, such as hyperfiltration, increased proteinuria, glomerulomegaly, and interstitial fibrosis. scRNA-seq identified that proximal tubules secreted a variety of chemokines, potentially in response to crosstalk with glomeruli. Notably, C-X-C motif chemokine 12 (CXCL12) emerged as a key player in potentially promoting T-cell recruitment. Flow cytometry substantiated T-cell infiltration into the kidney of the T2DKD model. This finding was further corroborated in human biopsied kidney tissues, showing a correlation between elevated CXCL12 levels and T2DKD progression.
Conclusion
The induced T2DKD model highlights the pivotal role of CXCL12-mediated T-cell infiltration, stemming from the crosstalk between proximal tubules and glomeruli. This data serves as a foundation for future studies, promising a therapeutic target for T2DKD.

Complications
Does 10-Year Atherosclerotic Cardiovascular Disease Risk Predict Incident Diabetic Nephropathy and Retinopathy in Patients with Type 2 Diabetes Mellitus? Results from Two Prospective Cohort Studies in Southern China: Jiaheng Chen, Yu Ting Li, Zimin Niu, Zhanpeng He, Yao Jie Xie, Jose Hernandez, Wenyong Huang, Harry H.X. Wang, on Behalf of the Guangzhou Diabetic Eye Study Group; Diabetes Metab J. 2025;49(2):298-310. Published online February 4, 2025; DOI: https://doi.org/10.4093/dmj.2024.0239

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Background
Diabetic macrovascular and microvascular complications often coexist and may share similar risk factors and pathological pathways. We aimed to investigate whether 10-year atherosclerotic cardiovascular disease (ASCVD) risk, which is commonly assessed in diabetes management, can predict incident diabetic nephropathy (DN) and retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM).
Methods
This prospective cohort study enrolled 2,891 patients with clinically diagnosed T2DM who were free of ASCVD, nephropathy, or retinopathy at baseline in the Guangzhou (2017–2022) and Shaoguan (2019–2021) Diabetic Eye Study in southern China. The 10-year ASCVD risk was calculated by the Prediction for ASCVD Risk in China (China-PAR) equations. Multivariable- adjusted Cox proportional hazard models were developed to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive capability.
Results
During follow-up, a total of 171 cases of DN and 532 cases of DR were documented. Each 1% increment in 10-year ASCVD risk was associated with increased risk of DN (pooled HR, 1.122; 95% CI, 1.094 to 1.150) but not DR (pooled HR, 0.996; 95% CI, 0.979 to 1.013). The model demonstrated acceptable performance in predicting new-onset DN (pooled AUC, 0.670; 95% CI, 0.628 to 0.715). These results were consistent across cohorts and subgroups, with the association appearing to be more pronounced in women.
Conclusion
Ten-year ASCVD risk predicts incident DN but not DR in our study population with T2DM. Regular monitoring of ASCVD risk in routine diabetes practice may add to the ability to enhance population-based prevention for both macrovascular and microvascular diseases, particularly among women.

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Investigation of the Potential Association Between Atherosclerotic Cardiovascular Disease Risk Score and Diabetic Retinopathy in Patients with Type 2 Diabetes: A Cross-Sectional Study
Chrysa Agapitou, Theodoros N. Sergentanis, Effie G. Papageorgiou, Panagiotis Theodossiadis, Ignatios Ikonomidis, Vaia Lambadiari, Irini Chatziralli
Biomedicines.2025; 13(3): 633. CrossRef

Basic and Translational Research
Revealing VCAN as a Potential Common Diagnostic Biomarker of Renal Tubules and Glomerulus in Diabetic Kidney Disease Based on Machine Learning, Single-Cell Transcriptome Analysis and Mendelian Randomization: Li Jiang, Jie Jian, Xulin Sai, Xiai Wu; Diabetes Metab J. 2025;49(3):407-420. Published online January 24, 2025; DOI: https://doi.org/10.4093/dmj.2024.0233

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Abstract PDF Supplementary Material PubReader ePub: Background
Diabetic kidney disease (DKD) is recognized as a significant complication of diabetes mellitus and categorized into glomerular DKDs and tubular DKDs, each governed by distinct pathological mechanisms and biomarkers.
Methods
Through the identification of common features observed in glomerular and tubular lesions in DKD, numerous differentially expressed gene were identified by the machine learning, single-cell transcriptome and mendelian randomization.
Results
The diagnostic markers versican (VCAN) was identified, offering supplementary options for clinical diagnosis. VCAN significantly highly expressed in glomerular parietal epithelial cell and proximal convoluted tubular cell. It was mainly involved in the up-regulation of immune genes and infiltration of immune cells like mast cell. Mendelian randomization analysis confirmed that serum VCAN protein levels were a risky factor for DKD, while there was no reverse association. It exhibited the good diagnostic potential for estimated glomerular filtration rate and proteinuria in DKD.
Conclusion
VCAN showed the prospects into DKD pathology and clinical indicator.

Complications
Association of Succinate and Adenosine Nucleotide Metabolic Pathways with Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus: Inha Jung, Seungyoon Nam, Da Young Lee, So Young Park, Ji Hee Yu, Ji A Seo, Dae Ho Lee, Nan Hee Kim; Diabetes Metab J. 2024;48(6):1126-1134. Published online July 1, 2024; DOI: https://doi.org/10.4093/dmj.2023.0377

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Background
Although the prevalence of diabetic kidney disease (DKD) is increasing, reliable biomarkers for its early detection are scarce. This study aimed to evaluate the association of adenosine and succinate levels and their related pathways, including hyaluronic acid (HA) synthesis, with DKD.
Methods
We examined 235 participants and categorized them into three groups: healthy controls; those with diabetes but without DKD; and those with DKD, which was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m². We compared the concentrations of urinary adenosine, succinate, and HA and the serum levels of cluster of differentiation 39 (CD39) and CD73, which are involved in adenosine generation, among the groups with DKD or albuminuria. In addition, we performed multiple logistic regression analysis to evaluate the independent association of DKD or albuminuria with the metabolites after adjusting for risk factors. We also showed the association of these metabolites with eGFR measured several years before enrollment. This study was registered with the Clinical Research Information Service (https://cris.nih.go.kr; Registration number: KCT0003573).
Results
Urinary succinate and serum CD39 levels were higher in the DKD group than in the control and non-DKD groups. Correlation analysis consistently linked urinary succinate and serum CD39 concentrations with eGFR, albuminuria, and ΔeGFR, which was calculated retrospectively. However, among the various metabolites studied, only urinary succinate was identified as an independent indicator of DKD and albuminuria.
Conclusion
Among several potential metabolites, only urinary succinate was independently associated with DKD. These findings hold promise for clinical application in the management of DKD.

Citations

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Trifolirhizin: A Phytochemical with Multiple Pharmacological Properties
Varun Jaiswal, Hae-Jeung Lee
Molecules.2025; 30(2): 383. CrossRef
The role of redox signaling in mitochondria and endoplasmic reticulum regulation in kidney diseases
Omar Emiliano Aparicio-Trejo, Estefani Yaquelin Hernández-Cruz, Laura María Reyes-Fermín, Zeltzin Alejandra Ceja-Galicia, José Pedraza-Chaverri
Archives of Toxicology.2025;[Epub] CrossRef

Complications
Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning: Chuan Yun, Fangli Tang, Zhenxiu Gao, Wenjun Wang, Fang Bai, Joshua D. Miller, Huanhuan Liu, Yaujiunn Lee, Qingqing Lou; Diabetes Metab J. 2024;48(4):771-779. Published online April 30, 2024; DOI: https://doi.org/10.4093/dmj.2023.0033

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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.

Citations

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Trends and analysis of risk factor differences in the global burden of chronic kidney disease due to type 2 diabetes from 1990 to 2021: A population‐based study
Yifei Wang, Ting Lin, Jiale Lu, Wenfang He, Hongbo Chen, Tiancai Wen, Juan Jin, Qiang He
Diabetes, Obesity and Metabolism.2025; 27(4): 1902. CrossRef

Metabolic Risk/Epidemiology
2023 Diabetic Kidney Disease Fact Sheet in Korea: Nam Hoon Kim, Mi-Hae Seo, Jin Hyung Jung, Kyung Do Han, Mi Kyung Kim, Nan Hee Kim, on Behalf of Diabetic Kidney Disease Research Group of the Korean Diabetes Association; Diabetes Metab J. 2024;48(3):463-472. Published online March 19, 2024; DOI: https://doi.org/10.4093/dmj.2023.0310

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Background
To investigate the prevalence, incidence, comorbidities, and management status of diabetic kidney disease (DKD) and diabetes-related end-stage kidney disease (ESKD) in South Korea.
Methods
We used the Korea National Health and Nutrition Examination Survey data (2019 to 2021, n=2,665) for the evaluation of prevalence, comorbidities, control rate of glycemia and comorbidities in DKD, and the Korean Health Insurance Service-customized database (2008 to 2019, n=3,950,857) for the evaluation of trends in the incidence and prevalence rate of diabetes-related ESKD, renin-angiotensin system (RAS) blockers and sodium glucose cotransporter 2 (SGLT2) inhibitors use for DKD, and the risk of atherosclerotic cardiovascular disease (ASCVD) and mortality according to DKD stages. DKD was defined as albuminuria or low estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m² in patients with diabetes mellitus.
Results
The prevalence of DKD was 25.4% (albuminuria, 22.0%; low eGFR, 6.73%) in patients with diabetes mellitus aged ≥30 years. Patients with DKD had a higher rate of comorbidities, including hypertension, dyslipidemia, and central obesity; however, their control rates were lower than those without DKD. Prescription rate of SGLT2 inhibitors with reduced eGFR increased steadily, reaching 5.94% in 2019. Approximately 70% of DKD patients were treated with RAS blockers. The prevalence rate of diabetesrelated ESKD has been steadily increasing, with a higher rate in older adults. ASCVD and mortality were significantly associated with an in increase in DKD stage.
Conclusion
DKD is prevalent among Korean patients with diabetes and is an independent risk factor for cardiovascular morbidity and mortality, which requiring intensive management of diabetes and comorbidities. The prevalence of diabetes-related ESKD has been increasing, especially in the older adults, during past decade.

Citations

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Glycemia Risk Index is Associated With Risk of Albuminuria Among Individuals With Type 1 Diabetes
Ji Yoon Kim, Jee Hee Yoo, Nam Hoon Kim, Jae Hyeon Kim
Journal of Diabetes Science and Technology.2025;[Epub] CrossRef
Big Data Research for Diabetes-Related Diseases Using the Korean National Health Information Database
Kyung-Soo Kim, Bongseong Kim, Kyungdo Han
Diabetes & Metabolism Journal.2025; 49(1): 13. CrossRef
Effect of Glomerular Hyperfiltration on Incident Cardiovascular Disease in Patients with Type 2 Diabetes Mellitus
Seung Min Chung, Inha Jung, Da Young Lee, So Young Park, Ji Hee Yu, Jun Sung Moon, Ji A. Seo, Kyung-Do Han, Nan Hee Kim
Clinical Journal of the American Society of Nephrology.2025; 20(3): 410. CrossRef
Impact of Muscle Quality on Muscle Strength and Physical Performance Beyond Muscle Mass or Diabetes Status
Jung A Kim, Chol Shin, Inha Jung, So Young Park, Da Young Lee, Ji Hee Yu, Hyunjoo Cho, Seung Ku Lee, Kyoung Jin Kim, Eyun Song, Kyeong Jin Kim, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Kyung Mook Choi, Nan Hee Kim, Ji A Seo
Journal of Cachexia, Sarcopenia and Muscle.2025;[Epub] CrossRef
A Machine Learning-Based Prediction Model for Diabetic Kidney Disease in Korean Patients with Type 2 Diabetes Mellitus
Kyung Ae Lee, Jong Seung Kim, Yu Ji Kim, In Sun Goak, Heung Yong Jin, Seungyong Park, Hyejin Kang, Tae Sun Park
Journal of Clinical Medicine.2025; 14(6): 2065. CrossRef
Optimal Management of Diabetic Kidney Disease
Jae-Han Jeon
The Journal of Korean Diabetes.2025; 26(1): 1. CrossRef
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Minsang Kim, Jung Hun Koh, Jeong Min Cho, Semin Cho, Soojin Lee, Hyuk Huh, Seong Geun Kim, Sehyun Jung, Eunjeong Kang, Sehoon Park, Jin Hyuk Paek, Woo Yeong Park, Kyubok Jin, Seungyeup Han, Kwon Wook Joo, Kyungdo Han, Dong Ki Kim, Yaerim Kim
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Karin A. M. Jandeleit-Dahm, Haritha R. Kankanamalage, Aozhi Dai, Jaroslawna Meister, Sara Lopez-Trevino, Mark E. Cooper, Rhian M. Touyz, Christopher R. J. Kennedy, Jay C. Jha
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Hyung Eun Son
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Cardiovascular Risk/Epidemiology
Two-Year Changes in Diabetic Kidney Disease Phenotype and the Risk of Heart Failure: A Nationwide Population-Based Study in Korea: Seung Eun Lee, Juhwan Yoo, Han Seok Choi, Kyungdo Han, Kyoung-Ah Kim; Diabetes Metab J. 2023;47(4):523-534. Published online April 25, 2023; DOI: https://doi.org/10.4093/dmj.2022.0096

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Background
Diabetic kidney disease (DKD) is a risk factor for hospitalization for heart failure (HHF). DKD could be classified into four phenotypes by estimated glomerular filtration rate (eGFR, normal vs. low) and proteinuria (PU, negative vs. positive). Also, the phenotype often changes dynamically. This study examined HHF risk according to the DKD phenotype changes across 2-year assessments.
Methods
The study included 1,343,116 patients with type 2 diabetes mellitus (T2DM) from the Korean National Health Insurance Service database after excluding a very high-risk phenotype (eGFR <30 mL/min/1.73 m2) at baseline, who underwent two cycles of medical checkups between 2009 and 2014. From the baseline and 2-year eGFR and PU results, participants were divided into 10 DKD phenotypic change categories.
Results
During an average of 6.5 years of follow-up, 7,874 subjects developed HHF. The cumulative incidence of HHF from index date was highest in the eGFR^lowPU– phenotype, followed by eGFR^norPU⁺ and eGFR^norPU^–. Changes in DKD phenotype differently affect HHF risk. When the persistent eGFR^norPU^– category was the reference, hazard ratios for HHF were 3.10 (95% confidence interval [CI], 2.73 to 3.52) in persistent eGFR^norPU⁺ and 1.86 (95% CI, 1.73 to 1.99) in persistent eGFR^lowPU^–. Among altered phenotypes, the category converted to eGFR^lowPU⁺ showed the highest risk. In the normal eGFR category at the second examination, those who converted from PU^– to PU⁺ showed a higher risk of HHF than those who converted from PU⁺ to PU^–.
Conclusion
Changes in DKD phenotype, particularly with the presence of PU, are more likely to reflect the risk of HHF, compared with DKD phenotype based on a single time point in patients with T2DM.

Citations

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Different Associations between Lipid Levels and Risk for Heart Failure according to Diabetes Progression
Seung-Hwan Lee, Kyu Na Lee, Jong-Chan Youn, Hun Sung Kim, Kyungdo Han, Mee Kyoung Kim
Diabetes & Metabolism Journal.2025; 49(1): 105. CrossRef
Persistent proteinuria is associated with the occurrence of cardiovascular disease: a nationwide population-based cohort study
Ho Geol Woo, Moo-Seok Park, Tae-Jin Song
Scientific Reports.2024;[Epub] CrossRef

Review

Complications
Pathophysiologic Mechanisms and Potential Biomarkers in Diabetic Kidney Disease: Chan-Young Jung, Tae-Hyun Yoo; Diabetes Metab J. 2022;46(2):181-197. Published online March 24, 2022; DOI: https://doi.org/10.4093/dmj.2021.0329

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Although diabetic kidney disease (DKD) remains the leading cause of end-stage kidney disease eventually requiring chronic kidney replacement therapy, the prevalence of DKD has failed to decline over the past 30 years. In order to reduce disease prevalence, extensive research has been ongoing to improve prediction of DKD onset and progression. Although the most commonly used markers of DKD are albuminuria and estimated glomerular filtration rate, their limitations have encouraged researchers to search for novel biomarkers that could improve risk stratification. Considering that DKD is a complex disease process that involves several pathophysiologic mechanisms such as hyperglycemia induced inflammation, oxidative stress, tubular damage, eventually leading to kidney damage and fibrosis, many novel biomarkers that capture one specific mechanism of the disease have been developed. Moreover, the increasing use of high-throughput omic approaches to analyze biological samples that include proteomics, metabolomics, and transcriptomics has emerged as a strong tool in biomarker discovery. This review will first describe recent advances in the understanding of the pathophysiology of DKD, and second, describe the current clinical biomarkers for DKD, as well as the current status of multiple potential novel biomarkers with respect to protein biomarkers, proteomics, metabolomics, and transcriptomics.

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Original Articles

Type 1 Diabetes
Association between Metabolic Syndrome and Microvascular Complications in Chinese Adults with Type 1 Diabetes Mellitus: Qianwen Huang, Daizhi Yang, Hongrong Deng, Hua Liang, Xueying Zheng, Jinhua Yan, Wen Xu, Xiangwen Liu, Bin Yao, Sihui Luo, Jianping Weng; Diabetes Metab J. 2022;46(1):93-103. Published online August 31, 2021; DOI: https://doi.org/10.4093/dmj.2020.0240

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Background
Both type 1 diabetes mellitus (T1DM) and metabolic syndrome (MetS) are associated with an elevated risk of morbidity and mortality yet with increasing heterogeneity. This study primarily aimed to evaluate the prevalence of MetS among adult patients with T1DM in China and investigate its associated risk factors, and relationship with microvascular complications.
Methods
We included adult patients who had been enrolled in the Guangdong T1DM Translational Medicine Study conducted from June 2010 to June 2015. MetS was defined according to the updated National Cholesterol Education Program criterion. Logistic regression models were used to estimate the odds ratio (OR) for the association between MetS and the risk of diabetic kidney disease (DKD) and diabetic retinopathy (DR).
Results
Among the 569 eligible patients enrolled, the prevalence of MetS was 15.1%. While female gender, longer diabetes duration, higher body mass index, and glycosylated hemoglobin A1c (HbA1c) were risk factors associated with MetS (OR, 2.86, 1.04, 1.14, and 1.23, respectively), received nutrition therapy education was a protective factor (OR, 0.46). After adjustment for gender, age, diabetes duration, HbA1c, socioeconomic and lifestyle variables, MetS status was associated with an increased risk of DKD and DR (OR, 2.14 and 3.72, respectively; both P<0.05).
Conclusion
Although the prevalence of MetS in adult patients with T1DM in China was relatively low, patients with MetS were more likely to have DKD and DR. A comprehensive management including lifestyle modification might reduce their risk of microvascular complications in adults with T1DM.

Citations

Citations to this article as recorded by

Link Between Metabolic Syndrome, Inflammation, and Eye Diseases
Kamila Pieńczykowska, Anna Bryl, Małgorzata Mrugacz
International Journal of Molecular Sciences.2025; 26(5): 2174. CrossRef
Metabolic syndrome in type 1 diabetes: higher time above range and glycemic variability revealed by continuous glucose monitoring (CGM)
Yayu Fang, Wei Liu, Xiaoling Cai, Yu Zhu, Mingxia Zhang, Siqian Gong, Xiangqing Wang, Chu Lin, Rui Zhang, Sai Yin, Juan Li, Yongran Huo, Xiaodan Hu, Xiaoqi Xie, Linong Ji
Diabetology & Metabolic Syndrome.2025;[Epub] CrossRef
Current status, trend changes, and future predictions of the disease burden of type 1 diabetes kidney disease in global and China
Qinghua Yang, Li Jin, Mingwei Luo, Shiwei Xie
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Dynamic Changes in Metabolic Status Are Associated With Risk of Ocular Motor Cranial Nerve Palsies
Daye Diana Choi, Kyung-Ah Park, Kyungdo Han, Sei Yeul Oh
Journal of Neuro-Ophthalmology.2024; 44(3): 386. CrossRef
Prevalence of Metabolic Syndrome and Its Risk Factors Influence on Microvascular Complications in Patients With Type 1 and Type 2 Diabetes Mellitus
Asad Riaz, Shoaib Asghar, Salman Shahid, Haider Tanvir, Muhammad Hamza Ejaz, Mamuna Akram
Cureus.2024;[Epub] CrossRef
Simplified integration of optimal self-management behaviors is associated with improved HbA1c in patients with type 1 diabetes
C. Deng, Y. Xie, F. Liu, X. Tang, L. Fan, X. Yang, Y. Chen, Z. Zhou, X. Li
Journal of Endocrinological Investigation.2024; 47(11): 2691. CrossRef
Correlation between triglyceride-glucose index and diabetic kidney disease risk in adults with type 1 diabetes mellitus
Mengyun Lei, Ping Ling, Yongwen Zhou, Jing Lv, Ying Ni, Hongrong Deng, Chaofan Wang, Daizhi Yang, Xubin Yang, Wen Xu, Jinhua Yan
Diabetology & Metabolic Syndrome.2024;[Epub] CrossRef
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Association of Endotoxemia with Low-Grade Inflammation, Metabolic Syndrome and Distinct Response to Lipopolysaccharide in Type 1 Diabetes
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Biomedicines.2023; 11(12): 3269. CrossRef
Association between Metabolic Syndrome and Microvascular Complications in Chinese Adults with Type 1 Diabetes Mellitus (Diabetes Metab J 2022;46:93-103)
Qianwen Huang, Sihui Luo
Diabetes & Metabolism Journal.2022; 46(3): 515. CrossRef
Association between Metabolic Syndrome and Microvascular Complications in Chinese Adults with Type 1 Diabetes Mellitus (Diabetes Metab J 2022;46:93-103)
Gyuri Kim
Diabetes & Metabolism Journal.2022; 46(3): 512. CrossRef
Metabolic syndrome associated with higher glycemic variability in type 1 diabetes: A multicenter cross-sectional study in china
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Frontiers in Endocrinology.2022;[Epub] CrossRef

Basic Research
Sulforaphane Ameliorates Diabetes-Induced Renal Fibrosis through Epigenetic Up-Regulation of BMP-7: Lili Kong, Hongyue Wang, Chenhao Li, Huiyan Cheng, Yan Cui, Li Liu, Ying Zhao; Diabetes Metab J. 2021;45(6):909-920. Published online June 4, 2021; DOI: https://doi.org/10.4093/dmj.2020.0168

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Background
The dietary agent sulforaphane (SFN) has been reported to reduce diabetes-induced renal fibrosis, as well as inhibit histone deacetylase (HDAC) activity. Bone morphologic protein 7 (BMP-7) has been shown to reduce renal fibrosis induced by transforming growth factor-beta1. The aim of this study was to investigate the epigenetic effect of SFN on BMP-7 expression in diabetes-induced renal fibrosis.
Methods
Streptozotocin (STZ)-induced diabetic mice and age-matched controls were subcutaneously injected with SFN or vehicle for 4 months to measure the in vivo effects of SFN on the kidneys. The human renal proximal tubular (HK11) cell line was used to mimic diabetic conditions in vitro. HK11 cells were transfected to over-express HDAC2 and treated with high glucose/palmitate (HG/Pal) to explore the epigenetic modulation of BMP-7 in SFN-mediated protection against HG/Pal-induced renal fibrosis.
Results
SFN significantly attenuated diabetes-induced renal fibrosis in vivo. Among all of the HDACs we detected, HDAC2 activity was markedly elevated in the STZ-induced diabetic kidneys and HG/Pal-treated HK11 cells. SFN inhibited the diabetes-induced increase in HDAC2 activity which was associated with histone acetylation and transcriptional activation of the BMP-7 promoter. HDAC2 over-expression reduced BMP-7 expression and abolished the SFN-mediated protection against HG/Pal-induced fibrosis in vitro.
Conclusion
Our study demonstrates that the HDAC inhibitor SFN protects against diabetes-induced renal fibrosis through epigenetic up-regulation of BMP-7.

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Complications
Screening Tools Based on Nomogram for Diabetic Kidney Diseases in Chinese Type 2 Diabetes Mellitus Patients: Ganyi Wang, Biyao Wang, Gaoxing Qiao, Hao Lou, Fei Xu, Zhan Chen, Shiwei Chen; Diabetes Metab J. 2021;45(5):708-718. Published online April 13, 2021; DOI: https://doi.org/10.4093/dmj.2020.0117

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Background
The influencing factors of diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus (T2DM) were explored to develop and validate a DKD diagnostic tool based on nomogram approach for patients with T2DM.
Methods
A total of 2,163 in-hospital patients with diabetes diagnosed from March 2015 to March 2017 were enrolled. Specified logistic regression models were used to screen the factors and establish four different diagnostic tools based on nomogram according to the final included variables. Discrimination and calibration were used to assess the performance of screening tools.
Results
Among the 2,163 participants with diabetes (1,227 men and 949 women), 313 patients (194 men and 120 women) were diagnosed with DKD. Four different screening equations (full model, laboratory-based model 1 [LBM1], laboratory-based model 2 [LBM2], and simplified model) showed good discriminations and calibrations. The C-indexes were 0.8450 (95% confidence interval [CI], 0.8202 to 0.8690) for full model, 0.8149 (95% CI, 0.7892 to 0.8405) for LBM1, 0.8171 (95% CI, 0.7912 to 0.8430) for LBM2, and 0.8083 (95% CI, 0.7824 to 0.8342) for simplified model. According to Hosmer-Lemeshow goodness-of-fit test, good agreement between the predicted and observed DKD events in patients with diabetes was observed for full model (χ²=3.2756, P=0.9159), LBM1 (χ²=7.749, P=0.4584), LBM2 (χ²=10.023, P=0.2634), and simplified model (χ²=12.294, P=0.1387).
Conclusion
LBM1, LBM2, and simplified model exhibited excellent predictive performance and availability and could be recommended for screening DKD cases among Chinese patients with diabetes.

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Machine learning-based risk predictive models for diabetic kidney disease in type 2 diabetes mellitus patients: a systematic review and meta-analysis
Yihan Li, Nan Jin, Qiuzhong Zhan, Yue Huang, Aochuan Sun, Fen Yin, Zhuangzhuang Li, Jiayu Hu, Zhengtang Liu
Frontiers in Endocrinology.2025;[Epub] CrossRef
Deep learning for early detection of chronic kidney disease stages in diabetes patients: A TabNet approach
Md Nakib Hayat Chowdhury, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali, María Liz Crespo, Shamim Ahmad, Ghassan Maan Salim, Fahmida Haque, Luis Guillermo García Ordóñez, Md. Johirul Islam, Taher Muhammad Mahdee, Kh Shahriya Zaman, Md Shahriar Khan Hemel, Moham
Artificial Intelligence in Medicine.2025; 166: 103153. CrossRef
Developing screening tools to estimate the risk of diabetic kidney disease in patients with type 2 diabetes mellitus
Xu Cao, Xiaomei Pei
Technology and Health Care.2024; 32(3): 1807. CrossRef
Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients
Chunxia Jiang, Xiumei Ma, Jiao Chen, Yan Zeng, Man Guo, Xiaozhen Tan, Yuping Wang, Peng Wang, Pijun Yan, Yi Lei, Yang Long, Betty Yuen Kwan Law, Yong Xu
Diabetes, Metabolic Syndrome and Obesity.2024; Volume 17: 1051. CrossRef
Two-Dimensional Ultrasound-Based Radiomics Nomogram for Diabetic Kidney Disease: A Pilot Study
Xingyue Huang, Yugang Hu, Yao Zhang, Qing Zhou
International Journal of General Medicine.2024; Volume 17: 1877. CrossRef
Risk prediction models for diabetic nephropathy among type 2 diabetes patients in China: a systematic review and meta-analysis
Wenbin Xu, Yanfei Zhou, Qian Jiang, Yiqian Fang, Qian Yang
Frontiers in Endocrinology.2024;[Epub] CrossRef
Changes in urinary exosomal protein CALM1 may serve as an early noninvasive biomarker for diagnosing diabetic kidney disease
Tao Li, Tian ci Liu, Na Liu, Man Zhang
Clinica Chimica Acta.2023; 547: 117466. CrossRef
Development and validation of a novel nomogram to predict diabetic kidney disease in patients with type 2 diabetic mellitus and proteinuric kidney disease
Hui Zhuan Tan, Jason Chon Jun Choo, Stephanie Fook-Chong, Yok Mooi Chin, Choong Meng Chan, Chieh Suai Tan, Keng Thye Woo, Jia Liang Kwek
International Urology and Nephrology.2022; 55(1): 191. CrossRef
Nomogram-Based Chronic Kidney Disease Prediction Model for Type 1 Diabetes Mellitus Patients Using Routine Pathological Data
Nakib Hayat Chowdhury, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali, Shamim Ahmad, María Liz Crespo, Andrés Cicuttin, Fahmida Haque, Ahmad Ashrif A. Bakar, Mohammad Arif Sobhan Bhuiyan
Journal of Personalized Medicine.2022; 12(9): 1507. CrossRef
Development and assessment of diabetic nephropathy prediction model using hub genes identified by weighted correlation network analysis
Xuelian Zhang, Yao Wang, Zhaojun Yang, Xiaoping Chen, Jinping Zhang, Xin Wang, Xian Jin, Lili Wu, Xiaoyan Xing, Wenying Yang, Bo Zhang
Aging.2022; 14(19): 8095. CrossRef

Complications
Associations of Plasma Glucagon Levels with Estimated Glomerular Filtration Rate, Albuminuria and Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus: Hua-Xing Huang, Liang-Lan Shen, Hai-Yan Huang, Li-Hua Zhao, Feng Xu, Dong-Mei Zhang, Xiu-Lin Zhang, Tong Chen, Xue-Qin Wang, Yan Xie, Jian-Bin Su; Diabetes Metab J. 2021;45(6):868-879. Published online March 23, 2021; DOI: https://doi.org/10.4093/dmj.2020.0149

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Background
Type 2 diabetes mellitus (T2DM) is characterized by elevated fasting glucagon and impaired suppression of postprandial glucagon secretion, which may participate in diabetic complications. Therefore, we investigated the associations of plasma glucagon with estimated glomerular filtration rate (eGFR), albuminuria and diabetic kidney disease (DKD) in T2DM patients.
Methods
Fasting glucagon and postchallenge glucagon (assessed by area under the glucagon curve [AUC_gla]) levels were determined during oral glucose tolerance tests. Patients with an eGFR <60 mL/min/1.73 m² and/or a urinary albumin-to-creatinine ratio (UACR) ≥30 mg/g who presented with diabetic retinopathy were identified as having DKD.
Results
Of the 2,436 recruited patients, fasting glucagon was correlated with eGFR and UACR (r=–0.112 and r=0.157, respectively; P<0.001), and AUC_gla was also correlated with eGFR and UACR (r=–0.267 and r=0.234, respectively; P<0.001). Moreover, 31.7% (n=771) presented with DKD; the prevalence of DKD was 27.3%, 27.6%, 32.5%, and 39.2% in the first (Q1), second (Q2), third (Q3), and fourth quartile (Q4) of fasting glucagon, respectively; and the corresponding prevalence for AUC_gla was 25.9%, 22.7%, 33.7%, and 44.4%, respectively. Furthermore, after adjusting for other clinical covariates, the adjusted odds ratios (ORs; 95% confidence intervals) for DKD in Q2, Q3, and Q4 versus Q1 of fasting glucagon were 0.946 (0.697 to 1.284), 1.209 (0.895 to 1.634), and 1.521 (1.129 to 2.049), respectively; the corresponding ORs of AUC_gla were 0.825 (0.611 to 1.114), 1.323 (0.989 to 1.769), and 2.066 (1.546 to 2.760), respectively. Additionally, when we restricted our analysis in patients with glycosylated hemoglobin <7.0% (n=471), we found fasting glucagon and AUC_gla were still independently associated with DKD.
Conclusion
Both increased fasting and postchallenge glucagon levels were independently associated with DKD in T2DM patients.

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Bu Zhao, Vy Kim Nguyen, Ming Xu, Justin A. Colacino, Olivier Jolliet
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Maja Mizdrak, Bozo Smajic, Ivan Mizdrak, Tina Ticinovic Kurir, Marko Kumric, Ivan Paladin, Darko Batistic, Josko Bozic
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Glucagon in type 2 diabetes: Friend or foe?
Irene Caruso, Nicola Marrano, Giuseppina Biondi, Valentina Annamaria Genchi, Rossella D'Oria, Gian Pio Sorice, Sebastio Perrini, Angelo Cignarelli, Annalisa Natalicchio, Luigi Laviola, Francesco Giorgino
Diabetes/Metabolism Research and Reviews.2023;[Epub] CrossRef

Complications
Association of Urinary N-Acetyl-β-D-Glucosaminidase with Cardiovascular Autonomic Neuropathy in Type 1 Diabetes Mellitus without Nephropathy: Min Sun Choi, Ji Eun Jun, Sung Woon Park, Jee Hee Yoo, Jiyeon Ahn, Gyuri Kim, Sang-Man Jin, Kyu Yeon Hur, Moon-Kyu Lee, Jae Hyeon Kim; Diabetes Metab J. 2021;45(3):349-357. Published online February 2, 2021; DOI: https://doi.org/10.4093/dmj.2019.0211

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Background
Cardiovascular autonomic neuropathy (CAN) is a common microvascular complication of diabetes and related to albuminuria in diabetic nephropathy (DN). Urinary N-acetyl-β-D-glucosaminidase (uNAG) is a renal tubular injury marker which has been reported as an early marker of DN even in patients with normoalbuminuria. This study evaluated whether uNAG is associated with the presence and severity of CAN in patients with type 1 diabetes mellitus (T1DM) without nephropathy.
Methods
This cross-sectional study comprised 247 subjects with T1DM without chronic kidney disease and albuminuria who had results for both uNAG and autonomic function tests within 3 months. The presence of CAN was assessed by age-dependent reference values for four autonomic function tests. Total CAN score was assessed as the sum of the partial points of five cardiovascular reflex tests and was used to estimatethe severity of CAN. The correlations between uNAG and heart rate variability (HRV) parameters were analyzed.
Results
The association between log-uNAG and presence of CAN was significant in a multivariate logistic regression model (adjusted odds ratio, 2.39; 95% confidence interval [CI], 1.08 to 5.28; P=0.031). Total CAN score was positively associated with loguNAG (β=0.261, P=0.026) in the multivariate linear regression model. Log-uNAG was inversely correlated with frequency-domain and time-domain indices of HRV.
Conclusion
This study verified the association of uNAG with presence and severity of CAN and changes in HRV in T1DM patients without nephropathy. The potential role of uNAG should be further assessed for high-risk patients for CAN in T1DM patients without nephropathy.

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Determination of Diabetes-associated Cardiovascular Autonomic Neuropathy Risk Factors among Insulin and Non-insulin Dependent Diabetics
Ibrahim Abdulsada, Zain Alabdeen Obaid, Farah Almerza, Mays Alwaeli, Anmar Al-Elayawi, Taha Al-Dayyeni, Harir Al-Tuhafy
The Journal of Medical Research.2023; 9(6): 141. CrossRef
Association between carotid atherosclerosis and presence of intracranial atherosclerosis using three-dimensional high-resolution vessel wall magnetic resonance imaging in asymptomatic patients with type 2 diabetes
Ji Eun Jun, You-Cheol Hwang, Kyu Jeong Ahn, Ho Yeon Chung, Geon-Ho Jahng, Soonchan Park, In-Kyung Jeong, Chang-Woo Ryu
Diabetes Research and Clinical Practice.2022; 191: 110067. CrossRef

Review

Complications
Treatment of Diabetic Kidney Disease: Current and Future: Tomotaka Yamazaki, Imari Mimura, Tetsuhiro Tanaka, Masaomi Nangaku; Diabetes Metab J. 2021;45(1):11-26. Published online January 22, 2021; DOI: https://doi.org/10.4093/dmj.2020.0217

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Diabetic kidney disease (DKD) is the major cause of end-stage kidney disease. However, only renin-angiotensin system inhibitor with multidisciplinary treatments is effective for DKD. In 2019, sodium-glucose cotransporter 2 (SGLT2) inhibitor showed efficacy against DKD in Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial, adding a new treatment option. However, the progression of DKD has not been completely controlled. The patients with transient exposure to hyperglycemia develop diabetic complications, including DKD, even after normalization of their blood glucose. Temporary hyperglycemia causes advanced glycation end product (AGE) accumulations and epigenetic changes as metabolic memory. The drugs that improve metabolic memory are awaited, and AGE inhibitors and histone modification inhibitors are the focus of clinical and basic research. In addition, incretin-related drugs showed a renoprotective ability in many clinical trials, and these trials with renal outcome as their primary endpoint are currently ongoing. Hypoxia-inducible factor prolyl hydroxylase inhibitors recently approved for renal anemia may be renoprotective since they improve tubulointerstitial hypoxia. Furthermore, NF-E2–related factor 2 activators improved the glomerular filtration rate of DKD patients in Bardoxolone Methyl Treatment: Renal Function in chronic kidney disease/Type 2 Diabetes (BEAM) trial and Phase II Study of Bardoxolone Methyl in Patients with Chronic Kidney Disease and Type 2 Diabetes (TSUBAKI) trial. Thus, following SGLT2 inhibitor, numerous novel drugs could be utilized in treating DKD. Future studies are expected to provide new insights.

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DIGITAL HEALTH.2024;[Epub] CrossRef
Network Pharmacology, Molecular Docking, and Experimental Verification to Reveal the Mitophagy-Associated Mechanism of Tangshen Formula in the Treatment of Diabetic Nephropathy
Yinfeng Chen, Xiaying Wang, Jie Min, Jie Zheng, Xuanli Tang, Xiaoling Zhu, Dongrong Yu, De Jin
Diabetes, Metabolic Syndrome and Obesity.2024; Volume 17: 739. CrossRef
Senolytic combination of dasatinib and quercetin protects against diabetic kidney disease by activating autophagy to alleviate podocyte dedifferentiation via the Notch pathway
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International Journal of Molecular Medicine.2024;[Epub] CrossRef
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System biology approaches for systemic diseases: Emphasis on type II diabetes mellitus and allied metabolism
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Two-Dimensional Ultrasound-Based Radiomics Nomogram for Diabetic Kidney Disease: A Pilot Study
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International Journal of General Medicine.2024; Volume 17: 1877. CrossRef
Autocatalytic, Brain Tumor‐Targeting Delivery of Bardoxolone Methyl Self‐Assembled Nanoparticles for Glioblastoma Treatment
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Low molecular weight heparin promotes the PPAR pathway by protecting the glycocalyx of cells to delay the progression of diabetic nephropathy
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In Silico Investigation against Inhibitors of Alpha-Amylase Using Structure-based Screening, Molecular Docking, and Molecular Simulations Studies
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Real-World Clinical Effectiveness of Glucagon-Like Peptide-1 Receptor Agonist on Mild-to-Moderate Diabetic Kidney Disease in Patients with Type 2 Diabetes: A Retrospective, Single-Arm Clinical Trial
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Single-cell RNA sequencing in diabetic kidney disease: a literature review
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Fufang Zhenzhu Tiaozhi (FTZ) capsule ameliorates diabetic kidney disease in mice via inhibiting the SGLT2/glycolysis pathway
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Astragaloside IV attenuates fatty acid-induced renal tubular injury in diabetic kidney disease by inhibiting fatty acid transport protein-2
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Deciphering interleukin‐18 in diabetes and its complications: Biological features, mechanisms, and therapeutic perspectives
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Diabetes, Metabolic Syndrome and Obesity.2023; Volume 16: 1085. CrossRef
Medial Arterial Calcification and the Risk of Amputation of Diabetic Foot Ulcer in Patients With Diabetic Kidney Disease
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Heparanase-2 protein and peptides have a protective effect on experimental glomerulonephritis and diabetic nephropathy
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Oral Chinese patent medicines for diabetic kidney disease: An overview of systematic reviews
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A Systematic Review and Meta-Analysis on the Efficacy and Safety of Finerenone Therapy in Patients with Cardiovascular and Chronic Kidney Diseases in Type 2 Diabetes Mellitus
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SGLT2 Inhibitors in the Treatment of Diabetic Kidney Disease: More than Just Glucose Regulation
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CUL3 induces mitochondrial dysfunction via MRPL12 ubiquitination in renal tubular epithelial cells
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HP1 induces ferroptosis of renal tubular epithelial cells through NRF2 pathway in diabetic nephropathy
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A Review of the Potential of Nuclear Factor [Erythroid-Derived 2]-like 2 Activation in Autoimmune Diseases
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Astragalus membranaceus and Salvia miltiorrhiza ameliorate diabetic kidney disease via the “gut-kidney axis”
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The relevance of the non-invasive biomarkers lncRNA GAS5/miR-21 ceRNA regulatory network in the early identification of diabetes and diabetic nephropathy
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Activation of acetyl-CoA synthetase 2 mediates kidney injury in diabetic nephropathy
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SET7, a lysine-specific methyl transferase: An intriguing epigenetic target to combat diabetic nephropathy
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Dznep, a histone modification inhibitor, inhibits HIF1α binding to TIMP2 gene and suppresses TIMP2 expression under hypoxia
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From normal population to prediabetes and diabetes: study of influencing factors and prediction models
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Diabetes Monitoring through Urine Analysis Using ATR-FTIR Spectroscopy and Machine Learning
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Cardiovascular autonomic neuropathy and incident diabetic kidney disease in patients with type 2 diabetes
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Lipidomic Analysis Reveals the Protection Mechanism of GLP-1 Analogue Dulaglutide on High-Fat Diet-Induced Chronic Kidney Disease in Mice
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Evolving Type 2 diabetes management focuses on clinical outcomes
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Critical shear stress of red blood cells as a novel integrated biomarker for screening chronic kidney diseases in cases of type 2 diabetes
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Inhibition of ChREBP ubiquitination via the ROS/Akt-dependent downregulation of Smurf2 contributes to lysophosphatidic acid-induced fibrosis in renal mesangial cells
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Repurposing drugs for highly prevalent diseases: pentoxifylline, an old drug and a new opportunity for diabetic kidney disease
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Oxidative Stress and NRF2/KEAP1/ARE Pathway in Diabetic Kidney Disease (DKD): New Perspectives
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Serum isthmin-1 levels are positively and independently correlated with albuminuria in patients with type 2 diabetes mellitus
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REDD1 Ablation Attenuates the Development of Renal Complications in Diabetic Mice
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Resistant Starch as a Dietary Intervention to Limit the Progression of Diabetic Kidney Disease
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Aggravated renal fibrosis is positively associated with the activation of HMGB1-TLR2/4 signaling in STZ-induced diabetic mice
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Single-cell multiomics reveals the complexity of TGFβ signalling to chromatin in iPSC-derived kidney organoids
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Whether Renal Pathology Is an Independent Predictor for End-Stage Renal Disease in Diabetic Kidney Disease Patients with Nephrotic Range Proteinuria: A Biopsy-Based Study
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What’s New in the Molecular Mechanisms of Diabetic Kidney Disease: Recent Advances
Kimio Watanabe, Emiko Sato, Eikan Mishima, Mariko Miyazaki, Tetsuhiro Tanaka
International Journal of Molecular Sciences.2022; 24(1): 570. CrossRef
Clinical efficacy and safety of astragalus injection combined with ACEI/ARB in the treatment of diabetic kidney disease: Protocol for a systematic review and meta-analysis
Zhiyue Zhu, Qi Zhang, Le Liu, Pengjie Bao, Shilin Liu, Chaoqun Song, Wenbo Yang, Zheng Nan
Medicine.2022; 101(49): e31490. CrossRef
Cudrania tricuspidata Root Extract Prevents Methylglyoxal‐Induced Inflammation and Oxidative Stress via Regulation of the PKC‐NOX4 Pathway in Human Kidney Cells
Donghee Kim, Jayeon Cheon, Haelim Yoon, Hee-Sook Jun, Evangelia Dounousi
Oxidative Medicine and Cellular Longevity.2021;[Epub] CrossRef
Pleiotropic Effects of Sodium-Glucose Cotransporter-2 Inhibitors: Renoprotective Mechanisms beyond Glycemic Control
Tomoaki Takata, Hajime Isomoto
International Journal of Molecular Sciences.2021; 22(9): 4374. CrossRef
HIF-α Prolyl Hydroxylase Inhibitors and Their Implications for Biomedicine: A Comprehensive Review
Kiichi Hirota
Biomedicines.2021; 9(5): 468. CrossRef
Nephropathie bei Diabetes
Roland E. Schmieder
CardioVasc.2021; 21(3): 31. CrossRef
Clinical Predictors of Nondiabetic Kidney Disease in Patients with Diabetes: A Single-Center Study
Francesco Fontana, Rossella Perrone, Francesco Giaroni, Gaetano Alfano, Silvia Giovanella, Giulia Ligabue, Riccardo Magistroni, Gianni Cappelli, Udeme Ekrikpo
International Journal of Nephrology.2021; 2021: 1. CrossRef
Activated Histone Acetyltransferase p300/CBP-Related Signalling Pathways Mediate Up-Regulation of NADPH Oxidase, Inflammation, and Fibrosis in Diabetic Kidney
Alexandra-Gela Lazar, Mihaela-Loredana Vlad, Adrian Manea, Maya Simionescu, Simona-Adriana Manea
Antioxidants.2021; 10(9): 1356. CrossRef
Plasma and urine biomarkers in chronic kidney disease: closer to clinical application
Azadeh Zabetian, Steven G. Coca
Current Opinion in Nephrology & Hypertension.2021; 30(6): 531. CrossRef
Therapeutic effect and mechanism of combined use of FGF21 and insulin on diabetic nephropathy
Fanrui Meng, Yukai Cao, Mir Hassan Khoso, Kai Kang, Guiping Ren, Wei Xiao, Deshan Li
Archives of Biochemistry and Biophysics.2021; 713: 109063. CrossRef
Mineralocorticoid Receptor Antagonists in Diabetic Kidney Disease
Daiji Kawanami, Yuichi Takashi, Yoshimi Muta, Naoki Oda, Dai Nagata, Hiroyuki Takahashi, Makito Tanabe
Frontiers in Pharmacology.2021;[Epub] CrossRef
Transcription Factor ChREBP Mediates High Glucose-Evoked Increase in HIF-1α Content in Epithelial Cells of Renal Proximal Tubules
Aleksandra Owczarek, Katarzyna B. Gieczewska, Robert Jarzyna, Zuzanna Frydzinska, Katarzyna Winiarska
International Journal of Molecular Sciences.2021; 22(24): 13299. CrossRef
The effect of modern hypoglycemic therapy on the course of chronic kidney disease in patients with type 2 diabetes mellitus
V.I. Katerenchuk
INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine).2021; 17(8): 624. CrossRef

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