The roles of collagen in chronic kidney disease and vascular calcification

Huang, Aoran; Guo, Guangying; Yu, Yanqiu; Li, Yao

doi:10.1007/s00109-020-02014-6

Cited by 10 publications

(8 citation statements)

References 120 publications

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“…Collagen is one of the major ECM components in urological organs and is also correlated with urological disease progression. In kidney, the interstitial matrix of the kidney is also mainly comprised with collagen type I and III [ 81 ], and the up-regulation of collagen was found to be correlated with renal fibrosis and has been recognized as the biomarker to delineate the pathological alterations to the ECM during chronic kidney disease progression [ [81] , [82] , [83] , [84] ]. Human embryonic kidney cells in agarose-collagen bioink were reported to proliferate within the printed structures, and could be potentially used for kidney regeneration [ 85 ].…”

Section: Commonly Used 3d Bioprinting Technologies In Urological Dise...mentioning

confidence: 99%

The application of 3D bioprinting in urological diseases

Han

Huang

et al. 2022

Materials Today Bio

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Section: Commonly Used 3d Bioprinting Technologies In Urological Dise...mentioning

confidence: 99%

The application of 3D bioprinting in urological diseases

Han

Huang

et al. 2022

Materials Today Bio

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“…The mesangial matrix consists mainly of collagen IV and fibronectin. The tubular interstitial matrix is composed mainly of collagens I [ 33 ]. TRPC6 was found to be distributed in kidney tubules and glomeruli by immunofluorescence [ 34 ].…”

Section: Discussionmentioning

confidence: 99%

Transient receptor potential canonical 6 knockdown ameliorated diabetic kidney disease by inhibiting nuclear factor of activated T cells 2 expression in glomerular mesangial cells

et al. 2022

Renal Failure

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Purpose Glomerular mesangial cell (GMC) dysfunction plays a vital role in the pathogenesis of diabetic kidney disease (DKD). Transient receptor potential canonical 6 (TRPC6) has been demonstrated to be involved in the development of DKD. However, the underlying mechanism remains unclear. The present study investigated the role of TRPC6 in GMC dysfunction and the related mechanism. Methods Diabetic rats and cultured GMCs were used in the experiment. The diabetic rat model was created by intraperitoneal injection of streptozotocin. Protein and mRNA levels were assessed by Western blotting and quantitative RT–PCR, respectively. Histological changes in the kidneys were observed by immunochemistry and hematoxylin and eosin. TRPC6 knockdown was achieved by adenovirus-mediated TRPC6 shRNA delivery in vivo and TRPC6 siRNA transfection in vitro . Results TRPC6 expression was increased in diabetic rat kidneys. Knockdown of TRPC6 attenuated diabetes-induced kidney functional deterioration. In addition, the increases in extracellular matrix components, including collagen IV, collagen I, and fibronectin production, as well as NFAT2 expression were also suppressed. In cultured GMCs, high glucose (25 mM, HG) treatment increased the expression of TRPC6. Knockdown of TRPC6 alleviated HG-induced increases in collagen IV, fibronectin, and NFAT2 expression. Knockdown of NFAT2 also inhibited the upregulation of proteins, including collagen IV and fibronectin, in HG-treated GMCs. Conclusion These results demonstrate that inhibition of TRPC6/NFAT2 signaling attenuates GMC dysfunction and the development of DKD and suggest that pharmacological targeting of TRPC6/NFAT2 in GMCs may provide beneficial effects for DKD.

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“…Renal ECM is a complex network of collagens, elastin, and several glycoproteins and proteoglycans, forming basal membranes and interstitial space, and it is functionally determined by each histological compartment of the kidney [18]. Therefore, increased synthesis and secretion and decreased degradation of collagen are the main causes or important factors involved in the development of renal diseases, ECM accumulation, and even glomerulosclerosis and interstitial brosis [19][20][21]. In some studies, diabetic kidney disease progression has been reported to be correlated with urinary collagen level, and urinary collagen level may be a greater predictor of renal failure than albuminuria [22,23].…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of two hub genes involved in membranous nephropathy based on machine learning

Pan

Jiang

et al. 2022

Preprint

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Background: Membranous nephropathy (MN) is an autoimmune disease. It is an important cause of end-stage renal disease in primary glomerulonephritis. Significant breakthroughs in its diagnosis have been made in previous studies, however, the pathogenesis of MN has still remained elusive. In recent years, bioinformatics has provided new research strategies to investigate the mechanisms of kidney disease. This study aimed to explore potential biomarkers of MN through bioinformatics analysis. Methods: Differentially expressed genes (DEGs) were identified by performing a differential expression analysis with the "limma" R package, and then, the weighted gene co-expression network analysis (WGCNA) was applied to obtain the most MN-related genes. After intersecting these genes, the least absolute shrinkage and selection operator (LASSO) and the support vector machine-recursive feature elimination (SVM-RFE) algorithms were utilized to identify hub genes. To assess the diagnostic value of hub genes, the receiver operating characteristic (ROC) curve analysis was performed. Finally, the relationship between hub genes and the immune microenvironment (IME) was analyzed. Results: The differential expression analysis yielded 1,466 DEGs, and using the WGCNA, 442 genes, which were the most MN-related genes, were obtained. From the intersection of these genes, 130 genes were identified. Subsequently, two hub genes (ECM1 and ATP8B1) were detected by the LASSO and SVM-REF algorithms. It was found that they were associated with components of the IME (natural killer T cells, gamma delta T cells, macrophages, etc.). Conclusion: Two hub genes (ECM1 and ATP8B1) were identified by machine learning, and their diagnostic value was evaluated. It was revealed that these two genes were associated with the components of the IME. Our findings may provide new ideas for developing new biomarkers for MN.

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The roles of collagen in chronic kidney disease and vascular calcification

Cited by 10 publications

References 120 publications

The application of 3D bioprinting in urological diseases

The application of 3D bioprinting in urological diseases

Transient receptor potential canonical 6 knockdown ameliorated diabetic kidney disease by inhibiting nuclear factor of activated T cells 2 expression in glomerular mesangial cells

Identification and validation of two hub genes involved in membranous nephropathy based on machine learning

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