Similar Datasets
Project description:Single-cell RNAseq analysis of kidney glomerular injury in IgA nephropathy
| PRJNA701968 | ENA
Project description:Comparative analysis of the tonsillar microbiota in IgA nephropathy and other glomerular diseases
| PRJEB39311 | ENA
Project description:This SuperSeries is composed of the following subset Series: GSE35487: Expression data from human with IgA nephropathy (IgAN) [HG-U133A] GSE35488: Expression data from human with IgA nephropathy (IgAN) [HG-U133A_ENTREZG_10] Refer to individual Series
2012-02-02 | E-GEOD-35489 | biostudies-arrayexpress
Project description:IgA nephropathy (IgAN) is the most common glomerulonephritis in the world. The disease is characterized by galactose deficient IgA (gd-IgA) in the circulation forming immune complexes. The complexes are deposited in the glomerular mesangium leading to inflammation and loss of renal function, but the pathophysiology of the disease is still not fully understood. Using an integrated global transcriptomic and proteomic profiling approach we investigated the role of the mesangium in the onset and progression of IgAN. Global gene expression was investigated by microarray analysis of the glomerular compartment of renal biopsies from patients with IgAN. The influence of galactose deficient IgA (gd-IgA) on mesangial cells was investigated by proteomic profiling. By utilizing the previous published literature curated glomerular cell type-specific genes, we found that mesangial cells and their positive standard genes play a more dominant role in IgAN comparing to the podocyte standard genes. Additionally, the patient clinical parameters (serum creatinine values and estimated glomerular filtration rate - eGFR) significantly correlate with z-scores derived from expression profile of mesangial cell positive standard genes. 22 common pathways were identified both from in vivo microarray data and in vitro mesangial cell mass spectrometry data and the main part was inflammatory pathways. The correlation between clinical data and mesangial standard genes allows for a better understanding of the onset of IgAN. The genes, proteins and their corresponding pathways identified in this paper give us novel insights into the pathophysiological mechanisms leading to progression of IgAN. RNA from glomerular compartment was extracted and processed for hybridization on Affymetrix microarrays. This dataset is part of the TransQST collection.
2017-07-03 | E-GEOD-93798 | biostudies-arrayexpress
Project description:IgA nephropathy (IgAN), the most common primary glomerulonephritis worldwide, is characterized by IgA1-containing glomerular immunodeposits. These immunodeposits are thought to originate from the circulating immune complexes consisting of aberrantly glycosylated IgA1 (galactose-deficient IgA1; Gd-IgA1) bound by IgG autoantibodies. This hypothesis is supported by the findings that renal immunodeposits of IgA nephropathy patients are enriched for IgG autoantibodies specific for galactose-deficient IgA1 (Rizk et al., J. Am. Soc. Nephrol. 30(10), 2017-2026, 2019). However, experimental proof is needed. This study provides in vivo data in mice that support the pathogenic role of IgG autoantibodies in IgAN.
2021-01-31 | GSE156179 | GEO
Project description:IgA nephropathy (IgAN), the most common primary glomerulonephritis worldwide, is characterized by glomerular deposition of immune complexes (IC) consisting of IgA1 with some O-glycans deficient in galactose (Gd-IgA1) and Gd-IgA1-specific IgG autoantibodies. These IC induce kidney injury, and in the absence of disease-specific therapy, up to 40% of IgAN patients progress to kidney failure. IgA1 with its clustered O-glycans is unique to humans, which hampered development of small-animal models of IgAN. To address this issue, we developed a model wherein engineered IC (EIC) formed from human Gd-IgA1 and recombinant IgG autoantibody are injected into nude mice to induce glomerular injury mimicking human IgAN. Here, we used this animal model to assess the protective effects of sparsentan, a single-molecule dual antagonist of endothelin A receptor (ETAR) and angiotensin II type 1 receptor (AT1R) (DEARA). Oral administration of sparsentan (60 or 120 mg/kg) to mice intravenously injected with EIC attenuated the EIC-induced glomerular hypercellularity.
2024-02-29 | GSE225447 | GEO
Project description:IgA nephropathy (IgAN) is the most common glomerulonephritis in the world. The disease is characterized by galactose deficient IgA (gd-IgA) in the circulation forming immune complexes. The complexes are deposited in the glomerular mesangium leading to inflammation and loss of renal function, but the pathophysiology of the disease is still not fully understood. Using an integrated global transcriptomic and proteomic profiling approach we investigated the role of the mesangium in the onset and progression of IgAN. Global gene expression was investigated by microarray analysis of the glomerular compartment of renal biopsies from patients with IgAN. The influence of galactose deficient IgA (gd-IgA) on mesangial cells was investigated by proteomic profiling. By utilizing the previous published literature curated glomerular cell type-specific genes, we found that mesangial cells and their positive standard genes play a more dominant role in IgAN comparing to the podocyte standard genes. Additionally, the patient clinical parameters (serum creatinine values and estimated glomerular filtration rate - eGFR) significantly correlate with z-scores derived from expression profile of mesangial cell positive standard genes. 22 common pathways were identified both from in vivo microarray data and in vitro mesangial cell mass spectrometry data and the main part was inflammatory pathways. The correlation between clinical data and mesangial standard genes allows for a better understanding of the onset of IgAN. The genes, proteins and their corresponding pathways identified in this paper give us novel insights into the pathophysiological mechanisms leading to progression of IgAN.
2017-07-03 | GSE93798 | GEO
Project description:Susceptibility loci for IgA nephropathy
| PRJNA80299 | ENA
Project description:The current study makes use of NanoString targeted technology to profile urinary exosomal miRNAs from IgA nephropathy affected patients and corresponding healthy controls. Circulatory biomarkers were detected for IgA nephropathy from Indian cohort which can be made used for the diagnostic therapy. 14 miRNAs were detected to be related to the disregulation in miRNome of IgA nephropathy patients using lasso feature selection method, out of which multiple miRNAs like hsa.mir.146b.3p, hsa.mir.599 and many more was resulted with high AUROC values >=0.9 efficient in differentiating between healthy controls and IgA nephropathy condition. These markers can be use further in the diagnosis and treatment of IgAN.
2023-12-13 | GSE244625 | GEO
Project description:Background and Objective: Hypertensive nephropathy (HN) requires a kidney biopsy as gold-standard for its diagnosis but histological findings are not entirely specific and lack specific prognostic markers. We aimed at defining prognostic candidate markers based on glomerular protein signatures. Method: We included adult patients (n=17) with an eGFR >30 ml/min/1.73m2 and proteinuria <3g/d from the Norwegian Kidney Biopsy Registry: stable patients (n=9) and subjects with HN progression (n=8) leading to end-stage renal disease (ESRD) within 20 years of follow-up. Glomerular cross-sections were microdissected from archival kidney biopsy sections and processed for protein extraction. Proteomic analyses were performed using Q-exactive HF mass spectrometer and relative glomerular protein abundance were compared between progressive vs non-progressive patients. Results: Amongst 1870 quality filtered proteins, we identified 58 proteins with an absolute fold change (FC)>1.5, p<0.05, including 17 proteins with absolute FC >2, indicative of HN progression (highest FC: Cadherin 16 and UDP-glucuronosyl-transferase 2B7). Hierarchical cluster and principal component analysis (PCA) with the 17 proteins showed clear separation of samples into HN progressors and non-progressors. Supervised classifier analysis (K nearest neighbour) identified a set of five proteins which classified 16/17 samples correctly. Applying Geneset Enrichment Analysis (GSEA), in general metabolic pathways were enriched in progressors, and structural cell pathways enriched in non-progressors. Pathway analysis identified Epithelial Adherens Junction Signaling as the most affected canonical pathway. The signature of HN progression is different from the respective signature of IgA progression. Conclusion: Glomerular proteomic profiling can be used to discriminate progressors from non-progressors in HN.
2023-05-23 | PXD026709 | Pride