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Single cell RNA sequencing of urine sediment from early and advanced Diabetic Kidney Disease (DKD) patients

ABSTRACT: Single cell RNA sequencing of urine sediment from early and advanced Diabetic Kidney Disease (DKD) patients

PROVIDER: PRJNA1106002 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR28840322_1.fastq.gz	Fastqsanger.gz
	SRR28840322_2.fastq.gz	Fastqsanger.gz
	SRR28840323_1.fastq.gz	Fastqsanger.gz
	SRR28840323_2.fastq.gz	Fastqsanger.gz
	SRR28840324_1.fastq.gz	Fastqsanger.gz

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Single cell RNA sequencing of urine sediment from early and advanced Diabetic Kidney Disease (DKD) patients

Project description:Urine sediment collected from patients diagnosed with early and advanced DKD are subject to single cell RNA sequencing. The resulting data are used to define early tubule injury/repairing signatures.

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Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Glomeruli vs. Control Glomeruli)

Project description:We identified 1,700 differentially expressed probesets in DKD glomeruli and 1,831 in diabetic tubuli; 330 probesets were commonly differentially expressed in both compartments. 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 an additional set of DKD samples. Affymetrix expression arrays were used to identify differentially regulated transcripts in 44 microdissected human kidney samples. Stringent statistical analysis using the Benjamini_Hochberg corrected 2-tailed t-test was used to identify differentially expressed transcripts in control and diseased glomeruli and tubuli. This Series includes DKD and control glomeruli samples.

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Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Tubuli vs. Control Tubuli)

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Transcriptome Analysis of Human Diabetic Kidney Disease

Project description:This SuperSeries is composed of the following subset Series: GSE30528: Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Glomeruli vs. Control Glomeruli) GSE30529: Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Tubuli vs. Control Tubuli) GSE30566: Transcriptome Analysis of Human Diabetic Kidney Disease (Control Glomeruli vs. Control Tubuli) Refer to individual Series

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Cyclodextrin protects podocytes in diabetic kidney disease [HumanWG-6 v3.0 array]

Project description:Analysis of gene expression changes in differentiated human podocytes treated with the serum from patients with (DKD+) or without (DKD-) diabetic kidney disease when compared to normal subjects (C). The hypothesis is that the three groups can be distinghed by their differential gene expression pattern. The results obtained revealed important information regarding differences in gene expression in human podocytes treated with the serum from patients with (DKD+) or without (DKD-) diabetic kidney disease when compared to normal subjects (C). Human podocytes were contacted with the serum from patients with diabetes and kidney disease (DKD+) or without kidney disease (DKD-) and compared to normal human podocytes contacted with serum from patients without diabetes (C).

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Cyclodextrin protects podocytes in diabetic kidney disease [HumanHT-12 V4.0 array]

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Project description:Genome wide DNA methylation profiling of urine and blood samples from patients with diabetic chronic kidney disease. The Illumina Infinium MethylationEPIC BeadChip kit was used to obtain DNA methylation profiles across approximately 850,000 CpGs. Samples included two urine and four buffy coat samples from adults with diabetic chronic kidney disease.

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Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Tubuli vs. Control Tubuli)

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Serum integrative omics reveals the landscape of human diabetic kidney disease

Project description:Diabetic kidney disease (DKD) is the most common microvascular complication of type 2 diabetes mellitus (2-DM). Currently, urine and kidney biopsy specimens are the major clinical resources for DKD diagnosis. The diagnostic values of blood in monitoring the onset and progression of DKD have not been well explored. To fully describe the biological changes in human blood after DKD, we recruited 1,513 participants including healthy adults and patients diagnosed with 2-DM, early stage of DKD (DKD-E), and advanced stage of DKD (DKD-A) from 4 independent medical centers. The collected serums were subjected to pilot proteomics and large-scale metabolomics, respectively. By performing deep profiling of serum proteomes and metabolomes, several insights were revealed. First, the pilot proteomics revealed that the combination of alpha 2-Macroglobulin, Cathepsin D, and CD324 served as a surrogate protein biomarker in monitoring DKD progression. Second, metabolomics demonstrated that galactose metabolism and glycerolipid metabolism are the major disturbed metabolic pathways in DKD. Serum metabolite, glycerol-3-galactoside, is an independent marker in predicting DKD. Third, integrating proteomics and metabolomics increased the diagnostic and predictive stability and accuracy in distinguishing DKD status. Our study provides a rich and open-access data resource to shed light on optimizing the management of diabetes.

2021-05-22 | MSV000087487 | MassIVE

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