16 research outputs found
Tracing the footsteps of glomerular insulin signaling in diabetic kidney disease
Insufficient insulin secretion and insulin resistance are hallmarks of diabetes. Recent studies indicate that insulin plays an important role in maintaining the glomerular filtration barrier. Mima et al. report that glomeruli of diabetic and obese rats suffer from insulin resistance and altered insulin signaling. Protein kinase C inhibitors are able to overcome insulin resistance, offering new hopes for the treatment of the condition
Transgenic expression of human APOL1 risk variants in podocytes induces kidney disease in mice
Transgenic expression of human APOL1 risk variants in podocytes induces kidney disease in mice
Diet-Induced Podocyte Dysfunction in Drosophila and Mammals
Diabetic nephropathy is a major cause of end-stage kidney disease. Characterized by progressive microvascular disease, most efforts have focused on injury to the glomerular endothelium. Recent work has suggested a role for the podocyte, a highly specialized component of the glomerular filtration barrier. Here, we demonstrate that the Drosophila nephrocyte, a cell analogous to the mammalian podocyte, displays defects that phenocopy aspects of diabetic nephropathy in animals fed chronic high dietary sucrose. Through functional studies, we identify an OGT-Polycomb-Knot-Sns pathway that links dietaryĀ sucrose to loss of the Nephrin ortholog Sns. Reducing OGT through genetic or drug means is sufficient to rescue loss of Sns, leading to overall extension of lifespan. We demonstrate upregulation of theĀ Knot ortholog EBF2 in glomeruli of human diabetic nephropathy patients and a mouse ob/ob diabetes model. Furthermore, we demonstrate rescue of Nephrin expression and cell viability in ebf2ā/ā primary podocytes cultured in high glucose
Functional genomic annotation of genetic risk loci highlights inflammation and epithelial biology networks in CKD.
Genome-wide association studies (GWASs) have identified multiple loci associated with the risk of CKD. Almost all risk variants are localized to the noncoding region of the genome; therefore, the role of these variants in CKD development is largely unknown. We hypothesized that polymorphisms alter transcription factor binding, thereby influencing the expression of nearby genes. Here, we examined the regulation of transcripts in the vicinity of CKD-associated polymorphisms in control and diseased human kidney samples and used systems biology approaches to identify potentially causal genes for prioritization. We interrogated the expression and regulation of 226 transcripts in the vicinity of 44 single nucleotide polymorphisms using RNA sequencing and gene expression arrays from 95 microdissected control and diseased tubule samples and 51 glomerular samples. Gene expression analysis from 41 tubule samples served for external validation. 92 transcripts in the tubule compartment and 34 transcripts in glomeruli showed statistically significant correlation with eGFR. Many novel genes, including ACSM2A/2B, FAM47E, and PLXDC1, were identified. We observed that the expression of multiple genes in the vicinity of any single CKD risk allele correlated with renal function, potentially indicating that genetic variants influence multiple transcripts. Network analysis of GFR-correlating transcripts highlighted two major clusters; a positive correlation with epithelial and vascular functions and an inverse correlation with inflammatory gene cluster. In summary, our functional genomics analysis highlighted novel genes and critical pathways associated with kidney function for future analysis
Transcriptome Analysis of Human Diabetic Kidney Disease
OBJECTIVE: Diabetic kidney disease (DKD) is the single leading cause of kidney failure in the U.S., for which a cure has not yet been found. The aim of our study was to provide an unbiased catalog of gene-expression changes in human diabetic kidney biopsy samples. RESEARCH DESIGN AND METHODS: Affymetrix expression arrays were used to identify differentially regulated transcripts in 44 microdissected human kidney samples. DKD samples were significant for their racial diversity and decreased glomerular filtration rate (~25ā35 mL/min). Stringent statistical analysis, using the Benjamini-Hochberg corrected two-tailed t test, was used to identify differentially expressed transcripts in control and diseased glomeruli and tubuli. Two different web-based algorithms were used to define differentially regulated pathways. RESULTS: We identified 1,700 differentially expressed probesets in DKD glomeruli and 1,831 in diabetic tubuli, and 330 probesets were commonly differentially expressed in both compartments. Pathway analysis highlighted the regulation of Ras homolog gene family member A, Cdc42, integrin, integrin-linked kinase, and vascular endothelial growth factor signaling in DKD glomeruli. The tubulointerstitial compartment showed strong enrichment for inflammation-related pathways. The canonical complement signaling pathway was determined to be statistically differentially regulated in both DKD glomeruli and tubuli and was associated with increased glomerulosclerosis even in a different set of DKD samples. CONCLUSIONS: Our studies have cataloged gene-expression regulation and identified multiple novel genes and pathways that may play a role in the pathogenesis of DKD or could serve as biomarkers
Human Kidney Tubule-Specific Gene Expression Based Dissection of Chronic Kidney Disease Traits
Chronic kidney disease (CKD) has diverse phenotypic manifestations including structural (such as fibrosis) and functional (such as glomerular filtration rate and albuminuria) alterations. Gene expression profiling has recently gained popularity as an important new tool for precision medicine approaches. Here we used unbiased and directed approaches to understand how gene expression captures different CKD manifestations in patients with diabetic and hypertensive CKD.
Transcriptome data from ninety-five microdissected human kidney samples with a range of demographics, functional and structural changes were used for the primary analysis. Data obtained from 41 samples were available for validation. Using the unbiased Weighted Gene Co-Expression Network Analysis (WGCNA) we identified 16 co-expressed gene modules.
We found that modules that strongly correlated with eGFR primarily encoded genes with metabolic functions. Gene groups that mainly encoded T-cell receptor and collagen pathways, showed the strongest correlation with fibrosis level, suggesting that these two phenotypic manifestations might have different underlying mechanisms. Linear regression models were then used to identify genes whose expression showed significant correlation with either structural (fibrosis) or functional (eGFR) manifestation and mostly corroborated the WGCNA findings.
We concluded that gene expression is a very sensitive sensor of fibrosis, as the expression of 1654 genes correlated with fibrosis even after adjusting to eGFR and other clinical parameters. The association between GFR and gene expression was mostly mediated by fibrosis. In conclusion, our transcriptome-based CKD trait dissection analysis suggests that the association between gene expression and renal function is mediated by structural changes and that there may be differences in pathways that lead to decline in kidney function and the development of fibrosis, respectively