Gene expression profiles of diabetic kidney disease and neuropathy in eNOS knockout mice: Predictors of pathology and RAS blockade effects

2021 ◽  
Vol 35 (5) ◽  
Author(s):  
Stephanie A. Eid ◽  
Lucy M. Hinder ◽  
Hongyu Zhang ◽  
Ridvan Eksi ◽  
Viji Nair ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Knockout Mice ◽  
Diabetic Kidney Disease ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Diabetic Kidney

scholarly journals Identification of VCAN as Hub Gene for Diabetic Kidney Disease Immune Injury Using Integrated Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Qiannan Xu ◽  
Binjue Li ◽  
Yucheng Wang ◽  
Cuili Wang ◽  
Shi Feng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Expression Profiles ◽  
Kidney Tissue ◽  
Gene Expression Profiles ◽  
Online Database ◽  
Hub Gene ◽  
Diabetic Kidney ◽  
Immune Injury

Background: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease in China. Tubular injury contributes to the progression of DKD. Our study was conducted to explore the differential gene expression profiles between kidneys from patients with DKD and kidney living donors (LDs).Methods: In total, seven DKD and eighteen LD gene expression profiles from the GSE104954 dataset were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were analyzed in R with the limma package. DEGs were uploaded to the g:Profiler online database to explore the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Ingenuity pathway analysis (IPA) was carried out using online IPA software. Weighted gene co-expression network analysis (WGCNA) was performed using the WGCNA R package. By integrating DEGs and genes from the top 1 phenotype-gene associated module, we determined the hub gene. We next tested the hub gene, VCAN, in the GSE30122 dataset. We also validated the versican levels in human kidney tissues, explored immune cell type enrichment using an online database xCell, and investigated the correlation between cell types and VCAN expression.Results: A total of 563 DEGs was identified. A large number of pathways were involved in the immune response process according to the results of GO, KEGG, and IPA. Using WGCNA, we selected the lightcyan module in which genes showed the strongest correlation with the phenotype and smallest P-value. We also identified VCAN as a hub gene by integrating DEG analysis and WGCNA. Versican expression was upregulated in human diabetic kidney tissue. Moreover, versican was speculated to play a role in immune injury according to the enrichment of functions and signaling pathways. VCAN transcript levels correlate with the assembly of immune cells in the kidney.Conclusion: Immune processes played an essential role in DKD tubulointerstitium injury. The hub gene VCAN contributed to this process.

scholarly journals Identification of Key Candidate Genes and Chemical Perturbagens in Diabetic Kidney Disease Using Integrated Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuo Gao ◽  
Aishwarya S ◽  
Xiao-mei Li ◽  
Xin-lun Li ◽  
Li-na Sui
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Kinase Inhibitor ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Diabetic Patients ◽  
Diabetic Kidney

Globally, nearly 40 percent of all diabetic patients develop serious diabetic kidney disease (DKD). The identification of the potential early-stage biomarkers and elucidation of their underlying molecular mechanisms in DKD are required. In this study, we performed integrated bioinformatics analysis on the expression profiles GSE111154, GSE30528 and GSE30529 associated with early diabetic nephropathy (EDN), glomerular DKD (GDKD) and tubular DKD (TDKD), respectively. A total of 1,241, 318 and 280 differentially expressed genes (DEGs) were identified for GSE30258, GSE30529, and GSE111154 respectively. Subsequently, 280 upregulated and 27 downregulated DEGs shared between the three GSE datasets were identified. Further analysis of the gene expression levels conducted on the hub genes revealed SPARC (Secreted Protein Acidic And Cysteine Rich), POSTN (periostin), LUM (Lumican), KNG1 (Kininogen 1), FN1 (Fibronectin 1), VCAN (Versican) and PTPRO (Protein Tyrosine Phosphatase Receptor Type O) having potential roles in DKD progression. FN1, LUM and VCAN were identified as upregulated genes for GDKD whereas the downregulation of PTPRO was associated with all three diseases. Both POSTN and SPARC were identified as the overexpressed putative biomarkers whereas KNG1 was found as downregulated in TDKD. Additionally, we also identified two drugs, namely pidorubicine, a topoisomerase inhibitor (LINCS ID- BRD-K04548931) and Polo-like kinase inhibitor (LINCS ID- BRD-K41652870) having the validated role in reversing the differential gene expression patterns observed in the three GSE datasets used. Collectively, this study aids in the understanding of the molecular drivers, critical genes and pathways that underlie DKD initiation and progression.

scholarly journals Integrative transcriptomic profiling of a mouse model of hypertension-accelerated diabetic kidney disease

2021 ◽  
Author(s):  
Frederikke E. Sembach ◽  
Helene M. Ægidius ◽  
Lisbeth N. Fink ◽  
Thomas Secher ◽  
Annemarie Aarup ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Expression Profiles ◽  
Complex Structure ◽  
Gene Expression Profiles ◽  
Signalling Pathways ◽  
Diabetic Kidney ◽  
Single Nucleus

The current understanding of molecular mechanisms driving diabetic kidney disease (DKD) is limited, partly due to the complex structure of the kidney. To identify genes and signalling pathways involved in the progression of DKD, we compared kidney cortical vs. glomerular transcriptome profiles in uninephrectomized (UNx) db/db mouse models of early-stage (UNx only) and advanced (UNx plus AAV-mediated renin overexpression, UNx-Renin) DKD using RNA sequencing (RNAseq). Compared to normoglycemic db/m mice, db/db UNx and db/db UNx-Renin mice showed marked changes in kidney cortical and glomerular gene expression profiles. UNx-Renin mice displayed more marked perturbations in gene components associated with activation of the immune system and enhanced extracellular matrix remodelling, supporting histological hallmarks of progressive DKD in this model. Single-nucleus RNAseq enabled linking transcriptome profiles to specific kidney cell types. In conclusion, integration of RNAseq at the cortical, glomerular and single-nucleus level provides enhanced resolution of molecular signalling pathways associated with disease progression in preclinical models of DKD, and may thus be advantageous for identifying novel therapeutic targets in DKD.

scholarly journals Targeted Disruption of Mapk14 (p38MAPKα) in Granulosa Cells and Cumulus Cells Causes Cell-Specific Changes in Gene Expression Profiles that Rescue COC Expansion and Maintain Fertility

2010 ◽  
Vol 24 (9) ◽  
pp. 1794-1804 ◽  
Author(s):  
Zhilin Liu ◽  
Heng-Yu Fan ◽  
Yibin Wang ◽  
JoAnne S. Richards
Keyword(s):  
Gene Expression ◽  
Granulosa Cells ◽  
Knockout Mice ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Cumulus Cells ◽  
Mutant Mice ◽  
Prostaglandin E

Abstract MAPK14 (p38MAPKα) is critical for FSH and prostaglandin E (PGE)2 signaling cascades in granulosa cells (GCs) and cumulus cell-oocyte complexes (COCs) in culture, indicating that this kinase might impact follicular development and COC expansion in vivo. Because Mapk14 knockout mice are embryonic lethal, we generated GC specific Mapk14 knockout mice (Mapk14gc−/−) by mating Mapk14fl/fl and Cyp19-Cre mice. Unexpectedly, the Mapk14gc−/− female mice were fertile. Analyses of gene expression patterns showed that amphiregulin (Areg) and epiregulin (Ereg), two key regulators of ovulation and COC expansion, were up-regulated in the GCs but down-regulated in cumulus cells of the mutant mice in vivo. COCs from the mutant mice expanded and expressed matrix-related genes, if cultured with AREG, but not when cultured with forskolin or PGE2, the latter being a key factor regulating MAPK14 activity in cumulus cells. Conversely, when GCs from the Mapk14gc−/− mice were cultured with forskolin, they produced more Areg and Ereg mRNA than did wild-type GCs. These results indicate that disruption of Mapk14 selectively alters the expression of Areg and other genes in each cell type. Greater AREG and EREG produced by the GCs appears to by-pass and compensate for the critical need for MAPK14 signaling and induction of Areg/Ereg (and hence matrix genes) by PGE2 in cumulus cells of the mutant mice. In conclusion, although MAPK14 is not overtly essential for preovulatory follicle development or events associated with ovulation and luteinization in vivo, it does impact gene expression profiles.

scholarly journals Gene Expression Profiles of Main Olfactory Epithelium in Adenylyl Cyclase 3 Knockout Mice

2015 ◽  
Vol 16 (12) ◽  
pp. 28320-28333 ◽  
Author(s):  
Zhenshan Wang ◽  
Yanfen Zhou ◽  
Yingtao Luo ◽  
Jing Zhang ◽  
Yunpeng Zhai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Adenylyl Cyclase ◽  
Olfactory Epithelium ◽  
Knockout Mice ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Main Olfactory Epithelium

scholarly journals Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

Database ◽  
2014 ◽  
Vol 2014 (0) ◽  
pp. bau092-bau092 ◽  
Author(s):  
Q. Zhang ◽  
B. Yang ◽  
X. Chen ◽  
J. Xu ◽  
C. Mei ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Relational Database ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Database

scholarly journals Amelioration of Albuminuria in ROCK1 Knockout Mice with Streptozotocin-Induced Diabetic Kidney Disease

2011 ◽  
Vol 34 (5) ◽  
pp. 468-475 ◽  
Author(s):  
Li Zhou ◽  
Fei Liu ◽  
Xiao R. Huang ◽  
Fang Liu ◽  
Haiyong Chen ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Knockout Mice ◽  
Diabetic Kidney Disease ◽  
Diabetic Kidney

scholarly journals Systematic integrated analysis of genetic and epigenetic variation in diabetic kidney disease

2020 ◽  
Vol 117 (46) ◽  
pp. 29013-29024
Author(s):  
Xin Sheng ◽  
Chengxiang Qiu ◽  
Hongbo Liu ◽  
Caroline Gluck ◽  
Jesse Y. Hsu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Kidney Function ◽  
Diabetic Kidney Disease ◽  
Genetic Variations ◽  
Integrated Analysis ◽  
Disease Development ◽  
Diabetic Kidney ◽  
Genotype Effect

Poor metabolic control and host genetic predisposition are critical for diabetic kidney disease (DKD) development. The epigenome integrates information from sequence variations and metabolic alterations. Here, we performed a genome-wide methylome association analysis in 500 subjects with DKD from the Chronic Renal Insufficiency Cohort for DKD phenotypes, including glycemic control, albuminuria, kidney function, and kidney function decline. We show distinct methylation patterns associated with each phenotype. We define methylation variations that are associated with underlying nucleotide variations (methylation quantitative trait loci) and show that underlying genetic variations are important drivers of methylation changes. We implemented Bayesian multitrait colocalization analysis (moloc) and summary data-based Mendelian randomization to systematically annotate genomic regions that show association with kidney function, methylation, and gene expression. We prioritized 40 loci, where methylation and gene-expression changes likely mediate the genotype effect on kidney disease development. Functional annotation suggested the role of inflammation, specifically, apoptotic cell clearance and complement activation in kidney disease development. Our study defines methylation changes associated with DKD phenotypes, the key role of underlying genetic variations driving methylation variations, and prioritizes methylome and gene-expression changes that likely mediate the genotype effect on kidney disease pathogenesis.

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