scholarly journals Dyslipoproteinemia and Impairment of Renal Function in Diabetic Kidney Disease: An Analysis of Animal Studies, Observational Studies, and Clinical Trials

2013 ◽  
Vol 10 (2-3) ◽  
pp. 110-120 ◽  
Author(s):  
Chi-Chih Hung ◽  
Jer-Chia Tsai ◽  
Hung-Tien Kuo ◽  
Jer-Ming Chang ◽  
Shang-Jyh Hwang ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Renal Function ◽  
Kidney Disease ◽  
Observational Studies ◽  
Animal Studies ◽  
Diabetic Kidney Disease ◽  
Diabetic Kidney

scholarly journals Effect of Pentoxifylline on Renal Function and Urinary Albumin Excretion in Patients with Diabetic Kidney Disease: The PREDIAN Trial

2014 ◽  
Vol 26 (1) ◽  
pp. 220-229 ◽  
Author(s):  
Juan F. Navarro-González ◽  
Carmen Mora-Fernández ◽  
Mercedes Muros de Fuentes ◽  
Jesús Chahin ◽  
María L. Méndez ◽  
...  
Keyword(s):  
Renal Function ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Urinary Albumin Excretion ◽  
Urinary Albumin ◽  
Diabetic Kidney ◽  
Albumin Excretion

scholarly journals Metformin Protects against Podocyte Injury in Diabetic Kidney Disease

2020 ◽  
Vol 13 (12) ◽  
pp. 452
Author(s):  
Sanna Lehtonen
Keyword(s):  
Kidney Disease ◽  
Animal Studies ◽  
Diabetic Kidney Disease ◽  
Clinical Settings ◽  
Low Grade ◽  
Diabetic Kidney ◽  
Cellular Targets ◽  
Glomerular Epithelial Cells ◽  
Low Grade Inflammation

Metformin is the most commonly prescribed drug for treating type 2 diabetes mellitus (T2D). Its mechanisms of action have been under extensive investigation, revealing that it has multiple cellular targets, either direct or indirect ones, via which it regulates numerous cellular pathways. Diabetic kidney disease (DKD), the serious complication of T2D, develops in up to 50% of the individuals with T2D. Various mechanisms contribute to the development of DKD, including hyperglycaemia, dyslipidemia, oxidative stress, chronic low-grade inflammation, altered autophagic activity and insulin resistance, among others. Metformin has been shown to affect these pathways, and thus, it could slow down or prevent the progression of DKD. Despite several animal studies demonstrating the renoprotective effects of metformin, there is no concrete evidence in clinical settings. This review summarizes the renoprotective effects of metformin in experimental settings. Special emphasis is on the effects of metformin on podocytes, the glomerular epithelial cells that are central in maintaining the glomerular ultrafiltration function.

scholarly journals SO004IDENTIFICATION OF HUB GENES, FOCUSED ON CHEMOKINES AND CHEMOKINE RECEPTORS, ASSOCIATED WITH THE DECLINE OF RENAL FUCTION OF DIABETIC KIDNEY DISEASE BY WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Songtao Feng ◽  
Bicheng Liu ◽  
Linli Lv ◽  
Gao Yueming ◽  
Di Yin ◽  
...  
Keyword(s):  
Renal Function ◽  
Network Analysis ◽  
Kidney Disease ◽  
T Cell Activation ◽  
Chemokine Receptors ◽  
Diabetic Kidney Disease ◽  
Expression Level ◽  
Hub Genes ◽  
Diabetic Kidney ◽  
Gene Modules

Abstract Background and Aims The fact that activation of the innate immune system and chronic inflammation are closely involved in the pathogenesis of diabetic Kidney disease (DKD). Recent studies have suggested the inflammatory process plays a crucial role in the progression of DKD. Identifying novel inflammatory molecules closely related to the decline of renal function is of significance in diagnosing and predicting the progression of DKD. The weighted gene co-expression network analysis (WGCNA) algorithm represents a novel systems biology method that provide the approach of association between gene modules and clinical traits to find the genes involvement into the certain phenotypic trait. The goal of this study was to identify hub genes and their roles in DKD from the gene sets associated with the decline of renal function by WGCNA. Method The Gene Expression Omnibus (GEO) database and “Nephroseq” website were searched and transcriptome study from DN biopsies with well-established clinical phenotypic data were selected for analysis. Next, we constructed a weighted gene co-expression network and identified modules negatively correlated with eGFR by WGCNA in the data of glomerular tissue. Functional annotations of the genes in modules negatively correlated with eGFR were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Through protein-protein interaction (PPI) analysis and hub gene screening, the hub genes were obtained. Furthermore, we compared the expression level of hub genes between DKD and normal control and drew ROC curves to determine the diagnosis value to DKD of these genes. Results The microarray-based expression datasets GSE30528 were screened out for analysis, which included glomeruli tissue of 9 cases of DKD and 13 cases of control. This microarray platform represented the transcriptome profile of 12411 well-characterized genes. Using WGCNA, a total of 19 gene modules were identified. Then module eigengene were analyzed for correlation with clinical traits of age, sex, ethnicity and eGFR and the “MEhoneydew1” module showed negative associated with eGFR (r=-0.58). GO functional annotation showed that these 551 genes in the “MEhoneydew1” module mainly enriched in the T cell activation. KEGG annotation showed mainly enriched in chemokine signaling pathway. Except for C3, top 10 hub genes, CCR5, CXCR4, CCR7, CCL5, CXCL8, CCR2, CCR1, CX3CR1, C3AR1 and C3, are all members of chemokines or chemokine receptors. Furthermore, we compared the expression level of these 9 genes between DKD and control, and found that all of these 9 genes increased in the DKD group, and the differences of 6 genes, CCR5, CCR7, CCL5, CCR2, CCR1, C3AR1, were of statistical significance. Linear correlation analysis showed that the expression of these 6 genes was negatively correlated with eGFR, and the ROC curve showed that the area under the curve could reach 0.812∼1.0. Conclusion We identified a panel of 6 hub genes focused on chemokines and chemokine receptors critical for decline of renal function of DKD using WGCNA. These genes may serve as biomarkers for diagnosis/prognosis and as putative novel therapeutic targets for DKD.

scholarly journals Determining the Optimal Protocol for Measuring an Albuminuria Class Transition in Clinical Trials in Diabetic Kidney Disease

2016 ◽  
Vol 27 (11) ◽  
pp. 3405-3412 ◽  
Author(s):  
Tobias F. Kröpelin ◽  
Dick de Zeeuw ◽  
Giuseppe Remuzzi ◽  
Rudy Bilous ◽  
Hans-Henrik Parving ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Diabetic Kidney ◽  
Optimal Protocol

scholarly journals Prevalence of and risk factors for chronic kidney disease and diabetic kidney disease in a central Chinese urban population: a cross-sectional survey

2019 ◽  
Author(s):  
Jiayu Duan ◽  
Duan Guang-Cai ◽  
Wang Chong-Jian ◽  
Liu Dong-Wei ◽  
Qiao Ying-Jin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Chronic Kidney Disease ◽  
Logistic Regression ◽  
Renal Function ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Density Lipoprotein ◽  
Ordinal Logistic Regression ◽  
Central China ◽  
Diabetic Kidney

Abstract Background This study was conducted to evaluate and update the current prevalence of and risk factors for chronic kidney disease (CKD) and diabetic kidney disease (DKD) in a China. Methods A total of 5231 participants were randomly recruited for this study. CKD and DKD were defined according to the combination of estimated glomerular filtration rate (eGFR), presence of albuminuria and diabetes. Participants completed a questionnaire assessing lifestyle and relevant medical history, and blood and urinary specimens were taken. Serum creatinine, uric acid, total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein and urinary albumin were assessed. The age- and gender-adjusted prevalences of CKD and DKD were calculated, and risk factors associated with the presence of reduced eGFR, albuminuria, DKD, severity of albuminuria and progression of reduce renal function were analyzed by binary and ordinal logistic regression. Results The overall adjusted prevalence of CKD was 16.8% (15.8 – 17.8%) and that of DKD was 3.5% (3.0 – 4.0%). Decreased renal function was detected in 132 participants [2.9%, 95% confidence interval (CI): 2.5 – 3.2%], whereas albuminuria was found in 858 participants (14.9%, 95% CI: 13.9 – 15.9%). In all participants with diabetes, the prevalence of reduced eGFR was 6.3% (95% CI = 3.9 – 8.6%) and that of albuminuria was 45.3% (95% CI = 40.4 – 50.1%). The overall prevalence of CKD in participants with diabetes was 48.0% (95% CI = 43.1 – 52.9%). The results of the binary and ordinal logistic regression indicated that factors independently associated with higher risk of reduced eGFR and albuminuria were older age, gender, smoking, alcohol consumption, overweight, obesity, diabetes, hypertension, dyslipidemia and hyperuricemia. Conclusions Our study shows the current prevalences of CKD and DKD in residents of Central China. The high prevalence suggests an urgent need to implement interventions to relieve the high burden of CKD and DKD in China.

scholarly journals Kidney cytosine methylation changes improve renal function decline estimation in patients with diabetic kidney disease

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Caroline Gluck ◽  
Chengxiang Qiu ◽  
Sang Youb Han ◽  
Matthew Palmer ◽  
Jihwan Park ◽  
...  
Keyword(s):  
Renal Function ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Cytosine Methylation ◽  
Diabetic Kidney ◽  
Renal Function Decline
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