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 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 Circulating Expression Level of LncRNA Malat1 in Diabetic Kidney Disease Patients and Its Clinical Significance

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Lian-ji Zhou ◽  
Da-wei Yang ◽  
Li-Na Ou ◽  
Xing-Rong Guo ◽  
Biao-liang Wu
Keyword(s):  
Diabetes Mellitus ◽  
Diabetic Nephropathy ◽  
Kidney Disease ◽  
Clinical Significance ◽  
Diabetic Kidney Disease ◽  
Glycosylated Hemoglobin ◽  
Expression Level ◽  
Diabetic Kidney ◽  
Lncrna Malat1 ◽  
Prediction Probability

Background. Long noncoding RNA MALAT1 is closely related to diabetes and kidney diseases and is expected to be a new target for the diagnosis and treatment of diabetic nephropathy. Objective. This study aimed to explore the circulating expression level and significance of lncRNA Malat1 in patients with type 2 diabetes mellitus (T2DM) and diabetic kidney disease (DKD). Methods. Quantitative real-time PCR (qPCR) was conducted to assess the expression of lncRNA Malat1 in 20 T2DM patients, 27 DKD patients, and 14 healthy controls, and then, the clinical significance was analyzed. Results. LncRNA MALAT1 expression in peripheral blood mononuclear cells (PBMC) was significantly upregulated in T2DM and DKD groups when compared to control. Pearson’s correlation analysis showed correlation of lncRNA MALAT1 levels with ACR, urine β2-microglobulin (β2-MG), urine α1-microglobulin (α1-MG), creatinine (Cr), and glycosylated hemoglobin (HbA1c), while negative with superoxide dismutase (SOD) (r=−0.388, P<0.05). Binary regression analysis showed that ACR, creatinine, α1-MG, and LncRNA Malat1 were the risk factors for diabetic nephropathy with OR value of 1.166, 1.031, 1.031, and 2.019 (P<0.05). The area under ROC curve (AUC) of DKD identified by the above indicators was 0.914, 0.643, 0.807, and 0.797, respectively. The AUC of Joint prediction probability of DKD recognition was 0.914, and the sensitivity and specificity of DKD diagnosis were 1.0 and 0.806, respectively. (Take ≥0.251 as the diagnostic cutoff point). Conclusion. LncRNA Malat1 is highly expressed in DKD patients, and the combined detection of ACR, creatinine, α1-MG, and LncRNA Malat1 with diabetes mellitus may be the best way to diagnose diabetic nephropathy.

scholarly journals Weighted gene co-expression network analysis identifies FCER1G as a key gene associated with diabetic kidney disease

2020 ◽  
Vol 8 (21) ◽  
pp. 1427-1427
Author(s):  
Shanshan Liu ◽  
Cuili Wang ◽  
Huiying Yang ◽  
Tingting Zhu ◽  
Hong Jiang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Diabetic Kidney

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

P0971IDENTIFICATION OF HUB GENES ASSOCIATED WITH THE DEPOSITION OF EXTRACELLULAR MATRIX AND SPECIFIC FOR DIABETIC NEPHROPATHY BY WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Songtao Feng ◽  
Linli Lv ◽  
Gao Yueming ◽  
Cao Jingyuan ◽  
Di Yin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Extracellular Matrix ◽  
Diabetic Nephropathy ◽  
Network Analysis ◽  
Expression Level ◽  
Hub Genes ◽  
Hub Gene ◽  
Gene Screening ◽  
Gene Modules ◽  
Geo Database

Abstract Background and Aims Diabetic nephropathy (DN) and its most severe manifestation, end-stage renal disease (ESRD), remains one of the leading causes of reduced lifespan in people with diabetes. Identifying novel molecules that are involved in the pathogenesis of DN has both diagnostic and therapeutic implications. The gene co-expression network analysis (WGCNA) algorithm represents a novel systems biology approach that provide the approach of association between gene modules and clinical traits to find the module involvement into the certain phenotypic trait. The goal of this study was to identify hub genes and their roles in DN from the aspect of whole gene transcripts analysis. Method Various types of chronic kidney diseases (CKD), including DN, microarray-based mRNA gene expression data, listed in the Gene Expression Omnibus (GEO) database, were analyzed. Next, we constructed a weighted gene co-expression network and identified modules distinguishing DN from normal or other types of CKD by WGCNA. Functional annotations of the genes in modules specialized for DN were analyzed by Gene Ontology (GO) enrichment analysis. Through protein-protein interaction (PPI) analysis and hub gene screening, the hub genes specific for DN were obtained. Furthermore, we drew ROC curves to determine the diagnosis and differential diagnosis value to DN of hub genes. Finally, another study of microarray in the GEO database was selected to verify the expression level of hub genes and in the “Nephroseq” database, the correlation between the gene expression level and eGFR was analyzed. Results “GSE99339”, glomerular tissue microarray in 187 patients with a total of 10947 genes, was selected for analysis. After excluding the inappropriate cases, a total of 179 specimens were analyzed, including 14 cases of DN, 22 cases of focal segmental glomerulosclerosis (FSGS), 15 cases of hypertensive nephropathy (HT), 26 cases of IgA nephropathy (IgAN), 13 cases of minimal change disease (MCD), 21 cases of membranous nephropathy (MGN), 23 cases of rapidly progressive glomerulonephritis (RPGN), 30 cases of lupus nephritis (LN) and 14 cases of kidney tissue adjacent to tumor. Co-expression network analysis by WGCNA identified 23 distinct gene modules of the total 10947 genes and revealed “MEsaddlegreen” module was strongly correlated with DN (r=0,54), but not with other groups. GO functional annotation showed that these 64 genes in the “MEsaddlegreen” module mainly enriched in the deposition of extracellular matrix, which represents the specific and diagnostic pathophysiological process of DN. Further PPI and hub gene screening analysis revealed that LUM, ELN, FBLN1, MMP2, FBLN5 and FMOD can be served as hub genes, which had been proved to play an important role in the deposition of extracellular matrix. Furthermore, we found that the expression of hub genes was the highest in DN group and for the diagnosis value of DN by each gene, the area under the ROC curve is about 0.75∼0.95. The external verification of another study showed that compared with the normal control group, the expression of these hub genes was the highest in the DN group, and their expression level was negatively correlated with eGFR. Conclusion Using WGCNA and further bioinformatics approach, we identified six hub genes that appear to be identical to DN development. As such, they may represent potential diagnostic biomarkers as well as therapeutic targets with clinical utility.

scholarly journals A Multidisciplinary Approach for Improving Quality of Life and Self-Management in Diabetic Kidney Disease: A Crossover Study

2020 ◽  
Vol 9 (7) ◽  
pp. 2160
Author(s):  
Nancy Helou ◽  
Dominique Talhouedec ◽  
Maya Zumstein-Shaha ◽  
Anne Zanchi
Keyword(s):  
Quality Of Life ◽  
Renal Function ◽  
Kidney Disease ◽  
Glycemic Control ◽  
Usual Care ◽  
Diabetic Kidney Disease ◽  
Self Management ◽  
Diabetic Kidney ◽  
Diet Habits

Individuals with diabetic kidney disease are at high risk of complications and challenged to self-manage. Previous research suggested that multidisciplinary approaches would improve health outcomes. This study investigated the effect of a multidisciplinary self-management approach of diabetic kidney disease on quality of life, and self-management, glycemic control, and renal function. A uniform balanced crossover design was used because it attains a high level of statistical power with a lower sample size. A total of 32 participants (aged 67.8 ± 10.8) were randomized into four study arms. In differing sequences, each participant was treated twice with three months of usual care alternated with three months of multidisciplinary management. The intervention improved the present dimension of quality of life demonstrating higher mean rank as compared to usual care (52.49 vs. 41.01; p = 0.026, 95% CI) and three self-care activities, general diet habits, diabetes diet habits, and blood sugar testing (respectively: 55.43 vs. 38.31; p = 0.002, 56.84 vs. 37.02; p = 0.000, 53.84 vs. 39.77; p = 0.008; 95% CI). Antihypertensive medication engagement was high across the study period (Mean = 95.38%, Min = 69%, Max = 100%). Glycemic control and renal function indicators were similar for the intervention and the usual care. Studies are needed to determine how the new recommended therapies for diabetic kidney disease such as SGLT2 inhibitors and GLP-1 receptor agonists impact on self-management and quality of life.

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