Matrix Metalloproteinases in Diabetic Kidney Disease

García-Fernández, Núria; Jacobs-Cachá, Conxita; Mora-Gutiérrez, José María; Vergara, Ander; Orbe, Josune

doi:10.3390/jcm9020472

Cited by 81 publications

(55 citation statements)

References 111 publications

(136 reference statements)

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“…MMP-2 degrades the components of ECM, including col-IV, bronectin, aggrecan, laminin, elastin, gelatin, and non-matrix substrates. In patients with DN, MMP-2 was increased in kidney samples and urinary MMP-2 was elevated in patients with albuminuria and established renal injury [28,29]. Elastin, encoded by ELN, was found accumulated in DN kidney samples and involved in the deposition of ECM in DN [30].…”

Section: Discussionmentioning

confidence: 99%

Identification of hub genes associated with accumulation of extracellular matrix as biomarkers of diabetic nephropathy

Feng

Gao

Yin

et al. 2020

Preprint

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Abstract Background Diabetic nephropathy (DN) remains a major cause of end stage renal disease (ESRD). The development of novel biomarkers and early diagnosis of DN are of great clinical importance. The goal of this study was to identify hub genes with diagnostic potential for DN by weighted gene co-expression network analysis (WGCNA). Methods Gene Expression Omnibus (GEO) database was searched for microarray data including distinct types of chronic kidney diseases (CKD). Gene co-expression network was constructed and modules specific for DN were identified by WGCNA. Gene Ontology (GO) analysis was performed and the hub genes were screened out within the selected gene modules. Furthermore, receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic values of hub genes. In addition, an external validation was performed in an independent dataset. Results Dataset GSE99339 was selected and a total of 179 microdissected glomeruli samples were analyzed, including DN, normal control and 7 groups of other glomerular diseases. 23 modules of the total 10947 genes were grouped by WGCNA and a module was specifically correlated with DN (r = 0.54, 9e-15). GO analysis showed that module genes were mainly enriched in the accumulation of extracellular matrix (ECM). LUM, ELN, FBLN1, MMP2, FBLN5 and FMOD were identified as hub genes. Furthermore, levels of hub genes were the highest in DN compared to other groups, which could differentially diagnose DN (AUC, 0.67 ~ 0.95). External verification showed hub genes were higher in DN group and were negatively correlated with eGFR. Conclusions By using WGCNA approach, we identified 6 hub genes, LUM, ELN, FBLN1, MMP2, FBLN5 and FMOD, related to ECM accumulation and were specific for DN. These genes may represent potential candidate diagnostic biomarkers of DN.

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Section: Discussionmentioning

confidence: 99%

Identification of hub genes associated with accumulation of extracellular matrix as biomarkers of diabetic nephropathy

Feng

Gao

Yin

et al. 2020

Preprint

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Section: Introductionmentioning

confidence: 99%

“…The matrix metalloproteinases (MMPs) family is a bundle of zinc-dependent proteases that are involved in the degradation and hydrolysis of extracellular matrix components [14]. Their activity contributes to all phases of vascular remodeling, especially in the diabetic and uremic milieu [14,15]. In T1D patients, some of MMPs were shown to be associated with arterial stiffness and pulse pressure [16], as well as cardiovascular events and all-cause mortality [17].…”

Section: Introductionmentioning

confidence: 99%

Beneficial effect of successful simultaneous pancreas-kidney transplantation on plasma profile of metalloproteinases in type 1 diabetes mellitus patients

Chudek

Kolonko

Ziaja

et al. 2020

Preprint

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Background It is virtually unknown whether the restoring of normal glucose metabolism after successful simultaneous pancreas-kidney transplantation (SPK) improves vascular wall morphology and function in type 1 diabetic (T1D) patients. This study has been aimed to compare arterial stiffness, assessed by pulse wave velocity (PWV), carotid intima-media thickness (IMT) biomarkers of arterial wall calcification, and parameters of calcium-phosphate metabolism in T1D patients after SPK or kidney transplantation alone (KTA). Methods In 39 SPK and 39 KTA adult patients of similar age, PWV and IMT were measured at a median of 83 (62–109) months post-transplantation. Additionally, carotid plaques were visualized and semi-qualitatively classified. Circulating matrix metalloproteinases (MMPs), calcification biomarkers, and calcium-phosphate metabolism parameters were measured. Results Although PWV and IMT values were similar, the occurrence of atherosclerotic plaques (51.3 vs. 70.3%, p < 0.01), turned to be lower, especially in case of calcified lesions (35.9 vs. 64.9%, p < 0.05) in patients after SPK. There were significantly lower concentrations of MMP-1, MMP-2, MMP-3 and osteocalcin (OC) in SPK subjects. Among the analyzed biomarkers, only log MMP-1, log MMP-2 and log MMP-3 concentrations were associated with log HbA1c. In addition, both log MMP-1 and log MMP-3 were inversely related to estimated glomerular filtration rate (eGFR). Multivariate stepwise backward regression analysis revealed that MMP-1 and MMP-3 variability were explained only by log HbA1c, whereas OC variability only by eGFR. Conclusion Normal glucose metabolism achieved by simultaneously transplanted pancreas in T1D renal transplant recipients is followed by the favorable profile of circulating matrix metalloproteinases, which may reflect the vasoprotective effect of SPK.

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“…Current studies suggest that Transforming Growth Factor beta (TGF-β) is involved in the progression of tubulointerstitial fi brosis in DN [10,11]. Matrix MetalloPeptidase 9 (MMP9) [12][13][14], and Adenomatous Polyposis Coli ( APC) [15] et al may also play a role in the progression of tubulointerstitial fi brosis in DN. However, these scattered studies cannot provide a global impression for DN, because of the complexity of DN`s mechanism.…”

Section: Introductionmentioning

confidence: 99%

Novel key gene tenascin C related to extracellular matrix accumulation in diabetic nephropathy kidney tubules: Results of integrative bioinformatics analysis

Zhang¹,

Wang²,

He³

et al. 2020

Glob J Obes Diabetes Metab Syndr

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Background: As the incidence of type 2 diabetes increases year by year, the number of individuals diagnosed with Diabetic Nephropathy (DN) has increased steeply. DN is characterized by glomerular sclerosis, tubulointerstitial fi brosis and atrophy. However, most of the previous studies on the pathogenesis of DN were focused on glomeruli, and now more and more evidences show that tubulointerstitial fi brosis plays an important role in the progress of DN. Bioinformatics analysis can be used in discovering disease-causing genes, biomarkers, and therapeutic targets through global analysis. In this study, we used this method to fi nd and verify novel genes in DN. Materials and methods: Microarray expression levels were downloaded from Gene Expression Omnibus datasets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted after Differentially Expressed Genes (DEGs) were identifi ed. Hub genes were fi ltered on the basis of the result of GO enrichment, and functional analysis was performed by browsing the GeneCards website and the latest literatures. The expression levels of all the hub genes in HK2 cells stimulated by high glucose were verifi ed, and TeNascin C (TNC), which is important and interesting, was verifi ed through animal experiment. Result: The relative expression levels of 54 samples were obtained, and 382 DEGs were identifi ed. 286 GO terms and 100 KEGG pathways were enriched remarkably. Nine of the key genes of interest: MMP7, TNC, LUM, LTF, IGLC1, LYZ, CXCL6, CYP27B1 and FOS were selected and verifi ed in HK2 cells stimulated by high glucose. quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) indicated that the mRNA levels of most of the hub genes were up-regulated and had an accordance rate of approximately 66.7%. In addition, the expression of TNC in renal tubular tissue of STZ-induced diabetic nephropathy rat gradually increased with time. Conclusion: Several novel key genes were discovered and verifi ed in this study, and TNC plays an important role in the renal fi brosis of DN and is expected to be a new therapeutic target. This study provides a theoretical basis and data resources for further research.

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Matrix Metalloproteinases in Diabetic Kidney Disease

Cited by 81 publications

References 111 publications

Identification of hub genes associated with accumulation of extracellular matrix as biomarkers of diabetic nephropathy

Identification of hub genes associated with accumulation of extracellular matrix as biomarkers of diabetic nephropathy

Beneficial effect of successful simultaneous pancreas-kidney transplantation on plasma profile of metalloproteinases in type 1 diabetes mellitus patients

Novel key gene tenascin C related to extracellular matrix accumulation in diabetic nephropathy kidney tubules: Results of integrative bioinformatics analysis

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